
==== Front
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Front Pharmacol
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Frontiers in Pharmacology
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1445328
10.3389/fphar.2024.1445328
Pharmacology
Systematic Review
Genetic polymorphisms and platinum-induced hematological toxicity: a systematic review
Zheng et al.
10.3389/fphar.2024.1445328
Zheng Yi 1

Tang Mimi 2

Deng Zheng 3 4 * †

Cai Pei 1 * †

1 Hunan Provincial Maternal and Child Health Care Hospital, Changsha, China
2 Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, China
3 Hunan Institute for Tuberculosis Control and Hunan Chest Hospital, Changsha, China
4 Hunan Chest Hospital, Changsha, China
Edited by: Roberto Rodríguez-Labrada, Cuban Neuroscience Center, Cuba

Reviewed by: Md. Siddiqul Islam, Southeast University, Bangladesh

Mukerrem Betul Yerer Aycan, Erciyes University, Türkiye

*Correspondence: Pei Cai, caipei19850104@126.com; Zheng Deng, zrsuiyue@sina.com
† These authors have contributed equally to this work

21 8 2024
2024
15 144532807 6 2024
05 8 2024
Copyright © 2024 Zheng, Tang, Deng and Cai.
2024
Zheng, Tang, Deng and Cai
https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Background

Platinum-based chemotherapy bring severe hematological toxicity that can lead to dose reduction or discontinuation of therapy. Genetic variations have been reported to influence the risk and extent of hematological toxicity; however, the results are controversial and a comprehensive overview is lacking. This systematic review aimed to identify genetic biomarkers of platinum-induced hematological toxicity.

Method

Pubmed, Embase and Web of science database were systematically reviewed for studies that evaluated the association of genetic variants and platinum-related hematological toxicity in tumor patients with no prior history of chemotherapy or radiation, published from inception to the 28th of January 2022. The studies should have specific toxicity scoring system as well as defined toxicity end-point. The quality of reporting was assessed using the Strengthening the Reporting of Genetic Association Studies (STREGA) checklist. Results were summarized using narrative synthesis.

Results

83 studies were eligible with over 682 single-nucleotide polymorphisms across 110 genes. The results are inconsistent and diverse with methodological issues including insufficient sample size, population stratification, various treatment schedule and toxicity end-point, and inappropriate statistics. 11 SNPs from 10 genes (ABCB1 rs1128503, GSTP1 rs1695, GSTM1 gene deletion, ERCC1 rs11615, ERCC1 rs3212986, ERCC2 rs238406, XPC rs2228001, XPCC1 rs25487, MTHFR rs1801133, MDM2 rs2279744, TP53 rs1042522) had consistent results in more than two independent populations. Among them, GSTP1 rs1695, ERCC1 rs11615, ERCC1 rs3212986, and XRCC1 rs25487 present the most promising results.

Conclusion

Even though the results are inconsistent and several methodological concerns exist, this systematic review identified several genetic variations that deserve validation in well-defined studies with larger sample size and robust methodology.

Systematic Review Registration

https://www.crd.york.ac.uk/, identifier CRD42021234164.

platinum
chemotherapy
hematological toxicity
polymorphisms
pharmacogenomics
The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by Health Research Project of Hunan Provincial Health Commission (D202302046032, W20243057), National Key Clinical Specialty Scientific Research Project (Z2023110), as well as National Natural Science Foundation of China (81903111).section-at-acceptancePharmacogenetics and Pharmacogenomics
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pmc1 Introduction

Platinum agents, including cisplatin, carboplatin and oxaliplatin, are used effectively against various tumor diseases either as monotherapy or in combination with other chemotherapeutics, radiation therapy and/or surgery. However, they display a range of severe side effects due to their poor selectivity for cancerous tissue over normal tissue. Hematological toxicity caused by platinum drugs are those that affect bone marrow function and blood cell production, characterized by leukopenia, neutropenia, thrombocytopenia, and anemia (Oun et al., 2018). Leukopenia or neutropenia, can leave patients susceptible to infections. Platinum-induced anemia is persisting erythropoietin deficiency state correlated with renal tubular dysfunction (Wood and Hrushesky, 1995). Acute myelosuppression occurs shortly after chemotherapy, while residual bone marrow injury manifested by a decrease in hematopoietic stem cell reserves or a myelodysplastic syndrome (Wang et al., 2006).

All three platinum drugs can cause some form of hematological toxicity, and myelosuppression is the dose-limiting toxicity of carboplatin. In the majority of cases, neither cisplatin nor oxaliplatin is associated with severe myelosuppression (Rabik and Dolan, 2007). Carboplatin induced myelosuppression resulted in neutropenia and thrombocytopenia. Severe (grade 3 or 4) neutropenia occurs in approximately 18% of carboplatin-treated patients, whereas severe thrombocytopenia occurs in approximately 25% of cases (Go and Adjei, 1999). Cisplatin-induced hematological toxicity is usually mild at intermittent doses of 50–60 mg/m2 and myelosuppression presents in 25%–30% of patients (Prestayko et al., 1979). Myelosuppression caused by oxaliplatin is generally mild. Grade 3/4 anemia, neutropenia and thrombocytopenia are observed in only 2%–3% of patients (Hartmann and Lipp, 2003). Hematological toxicity aggravates when platinum agents were combined with other cytotoxic drugs. The degree of hematological toxicity varies upon different chemotherapy regimen. For example, hematological toxicity was more profound in lung cancer patients treated with platinum agents plus gemcitabine (Fisher and D’Orazio, 2000; Schiller et al., 2002).

Inhibition of cell proliferation is one of the major causes of platinum-induced myelosuppression and related complications. The cytotoxicity of platinum on hematopoietic stem cells is attributed to its highly reactive hydrated platinum complex that binds to DNA and form intra- and inter-strand crosslinks; thereby produce subsequent interference with DNA transcription and/or DNA replication (Das et al., 2008). The generation in oxidative stress is also responsible for platinum-induced bone marrow toxicity (Basu et al., 2015). Increased platinum influx, decreased platinum efflux, impaired cell detoxification, low or absent DNA damage repair and activated cell death signaling may be the reasons of platinum-induced hematological toxicity (Shaloam and Paul, 2014) (Figure 1).

FIGURE 1 Mechanism of platinum-induced hematological toxicity. (The figure was made by Figdraw) Abbreviations: BER, base excision repair; DSB, double strand break repair; FA, fanconi anemia pathway; MMR, mismatch repair; NER, nucleotide excision repair; TLS, translesion DNA synthesis.

Identifying patients at greatest risk for these complications would be clinically useful for selecting patients for chemotherapy and planning the frequency of monitor and clinical treatment with colony-stimulating factor. Risk factors for hematological toxicities include kidney function, age, drug doses, combination chemotherapy, a poor performance status and prior chemotherapy exposure (Hartmann and Lipp, 2003; Ouyang et al., 2013). Furthermore, genetic variations in genes encoding proteins involved in pharmacokinetic and pharmacodynamic processes influence the occurrence and extent of adverse reactions (Zheng et al., 2020). Although several genetic polymorphisms have been identified to influence platinum-induced hematological toxicity, a comprehensive overview is lacking. We here provide an overview to identify which genetic variants consistently associated with hematological toxicity and discuss limitations of current pharmacogenetic analyses and formulate directions for further research.

2 Methods

2.1 Study eligibility

The systematic review was reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) checklist (Page et al., 2021) (Supplementary Table S1). The protocol was registered in the international prospective register of systematic reviews (PROSPERO; Registered number: CRD42021234164). The inclusion criteria were (Oun et al., 2018): studies that focus on the association between hematological toxicity and genetic polymorphisms (Wood and Hrushesky, 1995); studies including cancer patients using platinum-containing chemotherapy (Wang et al., 2006); studies that have specific toxicity scoring system and defined toxicity end-point. The exclusion criteria include the followings (Oun et al., 2018): preclinical studies (animal experiment or in vitro studies) (Wood and Hrushesky, 1995); studies in which patients were treated with concurrent radiotherapy (Wang et al., 2006); studies that were non-English, case report, review or meta-analysis (Rabik and Dolan, 2007); studies in which patients have prior history of chemotherapy and/or radiation.

2.2 Search strategy

PubMed/MEDLINE, EMBASE and Web of Science were searched for publications from inception to the 28th of January 2022. The literature search was conducted using Medical Subject Headings and combinations of relevant keywords. The detailed search strategy can be found in Supplementary Table S2. Additional research papers were identified by screening the reference sections of included articles. Two authors (YZ and MT) independently performed the data screening. Disagreements were consulted with a third arbiter (ZD).

2.3 Quality assessment

The quality of the studies will be assessed using a scoring system modified from a previously published study (Leusink et al., 2016) based on STREGA recommendations (Little et al., 2009) Supplementary Table S3. The scoring system contains ten items on five domains: clinical information, genotyping, study population origin, sample size and statistical correction for multiple testing, and study analysis. Each study included in this review was assessed for quality as good (overall quality score:7-10), moderate (overall quality score:4-6), or poor (overall quality score≤3) based on scores. Two reviewers (YZ and MT) will assess the quality independently and a third reviewer (PC) will be consulted in case of disagreement.

2.4 Data collection and analysis

The following data were extracted from each publication by two authors (YZ and MT): author, year, source of study (reference), sample size, ethnicity, type of cancer, number of treatment cycles, treatment schedule, toxicity scoring system, defined toxicity end-point, genetic polymorphisms involved and main study results.

Due to the heterogeneity in the patient population, treatment schedule, outcome definitions, meta-analysis was not appropriate. Studies were analyzed using a narrative synthesis approach.

3 Results

3.1 Study selection

The initial search delivered 2057 articles; after removal of duplicates, 1156 abstracts were primarily screened of which 207 full-text articles remained. After reading the full-text, 83 studies were eventually included in the present systematic review. The article selection process is shown in Figure 2.

FIGURE 2 Flow diagram for study selection.

3.2 Study characteristics and quality assessment

The study characteristics of the 83 included articles are shown in Table 1, Supplementary Tables S4, S5. 75 studies were candidate gene studies. Three studies were genome-wide association studies (GWAS) (Low et al., 2013; Huang et al., 2015; Cao et al., 2016), three studies were whole-exome sequencing (Gréen et al., 2016; Svedberg et al., 2020; Björn et al., 2020a). 1 study was whole-genome sequencing (WGS) (Björn et al., 2020b). 1 study used targeted resequencing of 100 pharmacokinetics-related genes (Yoshihama et al., 2018).

TABLE 1 Overview of pharmacogenetic studies on platinum-induced hematological toxicity.

Authors, Year	Sample size cancer	Treatment	Gene	Toxicity endpoint	SNPs with significant association)	Total score	
Isla et al. (2004)	62 NSCLC	DDP + TXT	ERCC1, XPD, RRM1, MDR1	Grade 2-4 anemia, leukopenia, neutropenia and thrombocytopenia	ERCC2/XPD rs13181 (Lys751Gln), RRM1 rs12806698(-37C/A)	2	
Han et al. (2007)	107 NSCLC	DDP + CPT-11	ABCB1, ABCC2, ABCG2	Grade 4 neutropenia	ABCB1/MDR1 rs2032582 (G2677TA)	2	
Kimcurran et al. (2011)	300 NSCLC	DDP/CBP + GEM/NVB/PTX	ERCC1	Grade 1-3 hematologic toxicity	No significant association	4	
Marsh et al. (2007)	914 (Discovery cohort and validation cohort in ratio 2:1)
Ovarian cancer	CBP + PTX/TXT	ERCC1, XPD, XRCC1, ABCB1(MDR1), ABCC1, ABCC2, ABCG2, GSTP1, MAPT, MPO, TP53	Grade 4 neutropenic toxicity	No significant association	4	
Tibaldi et al. (2008)	65 NSCLC	DDP + GEM	ERCC1, XPD	Grade 3-4 neutropenia, thrombocytopenia and anemia	No significant association	3	
Wang et al. (2008)	139 NSCLC + SCLC	DDP + NVB/PTX/TXT/GEM/VP-16	XPCC1	Grade 3-4 hematologic toxicity	No significant association	4	
Kim et al. (2009)	118 Epithelial ovarian cancer	DDP/CBP + PTX CBP + TXT	ERCC1, ERCC2, XRCC1, ABCB1, GSTP1, GSTM1, GSTT1	Grade 3-4 hematological toxicity	GSTP1 rs1695 (A313G, Ile105Val)	5	
Seo et al. (2009)	75 Gastric cancer	L-OHP + 5-FU + LV	ERCC1, GSTT1, GSTM1, GSTP1	Grade 3-4 neutropenia	No significant association	3	
(Wu et al. 2009)	209 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	XPD	Grade 3-4 hematologic toxicity, leukocytopenia, anemia and thrombocytopenia	XPD rs238406 (C22541A, Arg156Arg)	7	
Chen et al. (2010)	95 NSCLC	DDP + GEM/NVB/TXT	ERCC1, ABCB1(MDR1)	Grade≥1 hematologic toxicity	No significant association	3	
Giovannetti et al. (2011)	122 Pancreatic cancer	PEXG, PDXG, EC-GemCap	ERCC1, XPD, XRCC1	Grade 1-4 hematological toxicity, Grade 3-4 hematological toxicity	No significant association	5	
Han et al. (2011)	445 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOther DDP/CBP combinations	ABCC2(MRP2)	Grade 3-4 hematologic toxicity, anemia, agranulocytosis, leukocytopenia and thrombocytopenia	ABCC2/MRP2 rs3740066 (C3972T)	7	
Ludovini et al. (2011)	189 NSCLC	DDP + GEM/PTX/NVB	ERCC1, XRCC3, XPD, P53	Grade 3-4 hematologic toxicity	No significant association	6	
Zhao et al. (2012)	663 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	MMP-2	Grade 3-4 hematologic toxicity, neutropenia, anemia and thrombocytopenia	MMP-2 rs1477017, MMP-2 rs17301608, MMP-2 rs12934241, MMP-2 rs243847, MMP-2 rs243844, MMP-2 rs11639960, MMP-2 rs199211	8	
Erčulj et al. (2012)	94 Malignant mesothelioma	DDP/CBP + GEM/PEM
DDP + MMC + VCR	XPD, ERCC1, GSTP1, GSTM1, GSTT1	Grade 1-4 thrombocytopenia, Grade 2-4 leukopenia, anemia and neutropenia	ERCC2/XPD rs1799793 (Asp312Asn), ERCC1 rs3212986 (C8092A), GSTM1 gene deletion	6	
Gu et al. (2012)	445 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOther DDP/CBP combinations	BCL2, BAX, CASP3, CASP8, CASP10, TNFa, MIF	Grade 3-4 hematologic toxicity	CASP3 rs6948 (1296A>C, 3′-UTR)	8	
Iwata et al. (2012)	53 Advanced carcinomas	DDP + 5-FU/GEM/TXT/VP-16/PEM/CPT-11	OCT2, MATE1	Grade 2-4 leukopenia and thrombocytopenia	No significant association	2	
Khrunin et al. (2010)	104 Ovarian cancer	DDP + CTX	GSTA1, GSTM1, GSTM3, GSTP1, GSTT1, ERCC1, XPD, XPCC1, TP53, CYP2E1	Grade 3-4 neutropenia, Grade 2-4 anemia, Grade 1-4 thrombocitopenia	XPCC1 rs25487 (Arg399Gln), TP53 rs1042522 (C>G, Pro72Arg), ERCC2/XPD rs1799793 (Asp312Asn), GSTM1 gene deletion, GSTM3 AGG deletion	4	
Qian et al. (2012)	279 (in a discovery set) and 384 (in a validation set)
NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOther DDP/CBP combination	CASP8, CASP10	Grade 3-4 hematologic toxicity, leukocytopenia, agranulocytosis, anemia, thrombocytopenia	CASP8 rs12990906(A>G)	8	
Xu et al. (2012)	204 NSCLC	DDP + GEM/VP-16/TXT/VDS	CTR1	Grade 3-4 neutropenia, anemia and thrombocytopenia	No significant association	5	
Zhan et al. (2012)	445 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	Hsa-miR-196a2	Grade 3-4 hematologic toxicity, leukocytopenia, neutropenia, thrombocytopenia and anemia	No significant association	6	
Cortejoso et al. (2013)	106 Colorectal cancer	L-OHP + 5-FU + LV
L-OHP + CAP	ABCB1, XRCC1, ERCC1, ERCC2, GSTP1, GSTT1	Grade 3-4 hematological toxicity, anemia, neutropenia, neutropenia febrile, leucopenia and thrombocytopenia	ERCC1 rs11615 (C118T, Asn118Asn)	6	
Goričar et al. (2014)	139 Malignant mesothelioma	DDP + GEM/PEM
Other DDP doublets	REV1, REV3L	Grade 2-4 neutropenia, leukopenia, anemia and thrombocytopenia	REV1 rs3087403(C>T), REV1 rs3087386(A>G)	5	
Lee et al. (2013)	292 Colon cancer	L-OHP + LV + 5-FU	MTHFR, ERCC1, XPD, XRCC1, ABCC2, AGXT, GSTP1, GSTT1, GSTM1	Grade 3-4 neutropenia, anemia, thrombocytopenia and febrile neutropenia	MTHFR rs1801133(C677T), ERCC1 rs11615 (C118T, Asn118Asn), ABCC2/MRP2 rs717620 (C-24T)	6	
Li et al. (2014)	1004 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOther DDP/CBP combinations	MTHFR	Grade 3-4 hematologic toxicity, neutropenia, leucopenia, anemia and thrombocytopenia	MTHFR rs1537514(G>C), MTHFR rs1801133(C677T)	8	
Low et al. (2013)	1171 Carcinomas	DDP/CBP-based chemotherapy	GWAS	Grade 3-4 neutropenia/leucopenia	rs4886670 near RPL36AP45; rs10253216 near AGR2, rs11071200 on PRTG	5	
Peng et al. (2013)	663 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOther DDP/CBP combinations	VCP	Grade 3-4 hematologic toxicity, neutropenia, anemia and thrombocytopenia	VCP rs2074549	7	
Corrigan et al. (2014)	136 NSCLC
Malignant mesothelioma	DDP/CBP + PEM	MTHFR, ERCC2	Grade 3-4 hematologic toxicity and neutropaenia	No significant association	8	
Cai et al. (2014)	663 NSCLC	DDP/CBP + NVB/GEM/PTX/VP-16/BEV	CDC25A, CDC25B, CDC25C	Grade 3-4 hematology toxicity	CDC25B rs3761218	6	
Chen et al. (2014)	412 NSCLC + SCLC	DDP/CBP + GEM/PTX/NVB/VP-16/CPT-11	WISP1	Grade 3-4 hematologic toxicity	WISP1 rs16904853, WISP1 rs2929970, WISP1 rs2977549, WISP1 rs2977551	6	
Kanazawa et al. (2014)	41 Non-squamous non-small cell lung cancer	CBP + PEM	MTHFR	Grade 3-4 leukopenia, neutropenia, anemia and thrombocytopenia	No significant association	4	
Peng et al. (2014)	235 NSCLC	DDP + PTX/GEM/NVB/PEM	OGG1, APE1, XPCC1	Grade 3-4 hematologic toxicity	XPCC1 rs25487	7	
Ruzzo et al. (2014)	517 Colorectal cancer	L-OHP + 5-FU + LV
L-OHP + CAP	MTHFR, ERCC1, XRCC1, XPD, XRCC3, GST-PI, GST-T1, GST-M1, ABCC1, ABCC2	Grade 3-4 neutropenia	No significant association	7	
Shao et al. (2014)	663 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOther DDP/CBP combinations	POLK	Grade 3-4 hematological toxicity, anemia, agranulocytosis, leukocytopenia and thrombocytopenia	POLK rs3756558	6	
Tan et al. (2014)	1004 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	MIF, JAB1, SKP1, CUL1, RBX1, NEDD8, CAND1, CD74	Grade 3-4 hematologic toxicity, neutropenia, leucopenia, anemia and thrombocytopenia	MIF rs482244 (G>A), MIF rs4822446(A>G), MIF rs12485068(A>G), CD74 rs2748249(C>A), CD74 rs1560661(G>A)	7	
Wang et al. (2014)	119 SCLC	DDP + VP-16	MDM2, TP53	Grade 3-4 neutropenia	MDM2 rs2279744, TP53 rs1042522	6	
Zhao et al. (2015)	1004 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	TERT	Grade 3-4 hematologic toxicity, neutropenia, anemia and thrombocytopenia	No significant association	8	
Zheng et al. (2014)	444 NSCLC	DDP/CBP + GEM/VP-16/PTX/PEM
Other	TP53, MDM2	Grade 3-4 hematologic toxicity	MDM2 rs937282	7	
Cao et al. (2016)	333 (in discovery cohort) and 876 (in validation cohort) NSCLC	DDP/CBP + GEM/PTX/TXT	GWAS	Grade 3-4 myelosuppression	rs13014982 at 2q24.3, rs9909179 at 17p12	7	
Chen et al. (2016)	317 NSCLC + SCLC	DDP/CBP + GEM/PTX/NVB/VP-16/CPT-11	ABCB1, ABCG2, AQP2, AQP9, MVP, OCT2, SIRT1, SLC2A1, TMEM205, HMGB2, RPA1, SSRP1, XPA, XRCC5	Grade 3-4 hematologic toxicity	XRCC5 rs1051685, XRCC5 rs6941, AQP2 rs10875989	6	
Deng et al. (2015)	97 NSCLC	DDP + GEM/NVB/PTX/TXT	XPCC1, GSTP1, ATP7A	Grade 1-4 lymphopenia, leukopenia, neutropenia, thrombocytopenia and anemia	XRCC1 rs25487(G23885A, Arg399Gln)	5	
Gréen et al. (2016)	32(in discovery cohort) and 291(in validation cohort) NSCLC	CBP + GEM	Whole-Exome Sequencing	Grade 3-4 neutropenia, thrombocytopenia	rs1453542 in OR4D6, rs5925720 in DDX53	7	
Huang et al. (2015)	286 Cervical cancer	DDP/CBP + taxanes/CPT-11	GWAS	Grade 2-4 neutropenia	32 variants	6	
Kalikaki et al. (2015)	107 NSCLC	DDP/CBP + PTX/GEMDDP + TXT/NVB	ERCC1, XPD, XRCC1	Grade 3-4 hematologic toxicity	No significant association	4	
Lambrechts et al. (2015)	290 Ovarian cancer	CBP + PTX
CBP mono-therapy	ABCB1, ABCC1, ABCC2, ABCG2, TP53, GSTP1, ERCC1, ERCC2	Grade 3-4 anemia, thrombocytopenia and febrile neutropenia, Grade 4 neutropenia	ABCB1/MDR1 rs1128503 (C1236T), ABCC2/MRP2 rs12762549 (*+9383C>G), ERCC1 rs11615 (C118T, Asn118Asn)	8	
Qian et al. (2015)	663 NSCLC	DDP/CBP + NVB/GEM/PTX/TXT
Other combinations	MDM2	Grade 3-4 hematologic toxicity	MDM2 rs1470383(G>A)	7	
Ye et al. (2015)	663 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	REV3, REV7	Grade 3-4 hematological toxicity, anemia, agranulocytosis, leukocytopenia and thrombocytopenia	REV3 rs240966, REV3 rs4945880(G>A), REV3 rs465646(G>A), REV7 rs2233025(G>A)	7	
Yin et al. (2015)	325 NSCLC	DDP/CBP + GEM/VP-16/PTX/PEM
Other	eIF3a	Grade 1-4 neutropenia, anemia and thrombocytopenia	eIF3a rs1409314, eIF3a rs4752219, eIF3a rs4752220, eIF3a rs7091672	5	
Chu et al. (2016)	1021 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOther DDP/CBP combinations	Rad18	Grade 3-4 hematological toxicity, anemia, agranulocytosis, leukocytopenia and thrombocytopenia	No association in the whole population. Significant association in subgroup: RAD18 rs586014(A>G), RAD18 rs654448(G>A), RAD18 rs9880051(G>A), RAD18 rs6763823(G>A)	6	
Fang et al. (2017)	408 NSCLC + SCLC	DDP/CBP + NVB/GEM/TXT/VP-16	miR-605, miR-146a, miR-149, miR-196a-2, miR-27a, miR-499, miR-30c-1, miR-5197	Grade 3-4 haematologic toxicity	No association in the whole population. Significant association in subgroup: miR-5197 rs2042253	7	
Guo et al. (2016)	292 Lung adenocarcinoma	DDP/CBP combinations	p53, MDM2	Grade 3-4 hematologic toxicity	MDM2 rs2279744 (309T>G)	5	
Hu et al. (2016)	467 NSCLC + SCLC	DDP/CBP + GEM/VP-16/PEM/TXT/PTX/CPT-11/NVB	CASC8	Grade 3-4 hematologic toxicity	No significant association in overall subjects.
Significant association in subgroup: CASC8 rs10505477	6	
Jia et al. (2016)	345 (in discovery group) and 344 (in replication group) NSCLC	DDP/CBP + PEM/TXT/PTX/GEM	GADD45A, GADD45B, GADD45G, MAP2K7, MAP2K4, MAP3K4, MAPK8, MAPK9, MAPK14	Grade 2-4 leukopenia, neutropenia, thrombocytopenia and anemia	GADD45B rs2024144(C>T), GADD45B rs2024144(C>T), GADD45B rs2024144(C>T)	6	
Kumpiro et al. (2016)	32 NSCLC	CBP + GEM	CTR1	Grade 1-4 anemia, thrombocytopenia and neutropenia	No significant association	3	
Qian et al. (2016)	403 NSCLC	DDP/CBP + GEM/PEM/PTX/TXT/NVB	OCT2, ABCB1, ABCC2(MRP2), MATE1	Grade 3-4 hematologic toxicity	OCT2 rs316019 (808G/T, p.270Ala > Ser), MATE1 rs2289669	6	
Song et al. (2017)	1004 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	XPC, RAD23B, ERCC2, GTF2H1, XPA, ERCC5, ERCC1, ERCC4, ERCC8, ERCC, DDB2, LIG1, CDK7, CCNH, MNAT1, RPA1, RPA2, RFC1, RFC2, POLD1, POLD2, POLD3, POLD4, POLE, POLE2, GTF2H3, GTF2H4	Grade 3-4 anemia, neutropenia and trombocytopenia	No SNPs satisfied the significant level of bonferroni correction
GTF2H1 rs4150558, POLD3 rs10857, POLD3 rs6592576, RPA1 rs12727, POLD1 rs3219281, POLD1 rs3219341, POLD1 rs1726801	5	
Wang et al. (2016)	1004 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	RICTOR	Grade 3-4 hematologic toxicity, anemia, neutropenia and thrombocytopenia	RICTOR rs7703002, RICTOR rs4321771	8	
Xu et al. (2016)	272 female patients NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	CHEK2	Grade 3-4 hematological toxicity and leukotoxicity	No significant association	6	
Yin et al. (2016)	190 (in Derivation cohort) and 200 (in Derivation cohort) NSCLC	DDP/CBP + GEM/PEM/PTX/TXT/NVB/VP-16	416 SNPs in 185 genes	Grade 3-4 hematological toxicity	The hematological toxicity prediction model achieved a sensitivity of 0.89 and a specificity of 0.39 with the ROC AUC of 0.76	5	
Zou et al. (2016)	317 NSCLC + SCLC	DDP/CBP + GEM/PTX/NVB/VP-16/CPT-11	HSPA4, HSPB1, HSPE1, RAC1, RhoA	Grade 3-4 hematologic toxicity	RAC1 rs836554, RAC1 rs4720672	6	
Gong et al. (2017)	467 NSCLC + SCLC	DDP/CBP + PEM/GEM/PTX/TXT/VP-16Other DDP/CBP-based chemotherapy (CPT-11 + DDP/CBP, NVB + DDP/CBP)	HOTTIP, HOTAIR, H19, ANRIL, CCAT2, MALAT1, MEG3, POLR2E	Grade 3-4 hematological toxicity	No association in the whole population significant association in subgroup	6	
Liu et al. (2017a)	555 Lung adenocarcinoma	DDP/CBP + PTX/TXT/NVB/VP-16/BEV	CASP8	Grade 3-4 neutropenia, thrombocytopenia and anemia	CASP8 rs7608692(G>A)	6	
Liu et al. (2017b)	220 NSCLC + SCLC	DDP/CBP + GEM/PEM/PTX/TXT/NVB	MLH1, MSH2, MSH3, MSH4, MSH5, MSH6	Grade 3-4 hematologic toxicity	MSH3 rs6151627, MSH3 rs6151670, MSH3 rs7709909, MSH5 rs805304	6	
Zheng et al. (2017)	437 (in the discovery cohort) and 781 (in the validation cohort) NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	54 gene	Grade 3-4 hematologic toxicity, leukocytopenia, neutropenia, thrombocytopenia and anemia	ERCC1 rs3212986, ERCC1 rs11615, RRM1 rs12806698, XPC rs2228001, XPC rs2228000, XPF rs1799801, XPG rs1047768, XPG rs17655, APE1 rs1130409, XRCC1 rs25487, MDM2 rs2279744, RAD51 rs1801320, RAD51 rs12593359	8	
Björn et al. (2020a)	215 in the discovery cohort) and validated in an independent genome-wide association study NSCLC	CBP + GEM	whole-exome sequence	Grade 3-4 thrombocytopenia	These analyses identified 130 SNVs/INDELs and 25 genes associated with thrombocytopenia (p-value <0.002). Twenty-three SNVs were validated in an independent genome-wide association study (GWAS)	7	
De Troia et al. (2019)	82 NSCLC + SCLC	DDP/CBP + VP-16/NVBDDP + GEM/PEM/TXT
DDP monotherapy	ABCB1, ABCC2, GSTP1	Grade 3-4 hematological toxicity	ABCB1/MDR1 rs1045642 (C3435T): decreased risk of grade 3-4 hematological toxicity	5	
Li et al. (2018)	427 NSCLC	DDP/CBP + GEM/PEM/TXT/NVB/PTX	ATP7A, ATP7B	Grade 3-4 hematological toxicity	No significant association	6	
Sun et al. (2018)	1004 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	SCL31A1	Grade 3-4 hematological toxicity, anemia, neutropenia, leukocytopenia and thrombocytopenia	SLC31A1 rs4979223, SLC31A1 rs4978536, SLC31A1 rs10817464, SLC31A1 rs10759637	8	
Yoshihama et al. (2018)	320 Ovarian fallopian tube, peritoneal, uterine, or cervical cancer	CBP + PTX	37 transporters, 30 cytochrome P450 (CYP) enzymes, 10 uridine diphosphate UDPglucuronosyltransferases (UGT), five flavin-containing monooxygenases (FMO), four glutathione S-transferases (GST), four sulfotransferases (SULT), and 10 additional genes	Severe hematotoxicity (including neutropenia G4, thrombocytopenia ≥ G3, and anemia ≥ G3)	GSTP1 rs1695	5	
Gong et al. (2019)	467 NSCLC + SCLC	DDP/CBP + PEM/GEM/PTX/TXT/VP-16Other DDP/CBP-based chemotherapy (CPT-11 + DDP/CBP, NVB + DDP/CBP)	STAT3	Grade 3-4 hematological toxicity	STAT3 rs4796793	6	
Lavanderos et al. (2019)	119 Testicular cancer	DDP + BLM + VP-16	GSTM1, GSTP1, GSTT1, UGT1A1, BLMH, ERCC1, ERCC2, MDR1	Grade 3-4 anemia, neutropenia, leukopenia, thrombocytopenia, lymphocytopenia and febrile neutropenia	ERCC2/XPD rs238406 (C22541A, Arg156Arg), ERCC1 rs11615 (C118T, Asn118Asn)	5	
Liblab et al. (2020)	52 Ovarian cancer (Epithelial ovarian cancer)	CBP + PTX
CBP mono-therapy	ERCC1, XRCC1, GSTP1	Grade 2-4 anemia	GSTP1 rs1695 (A313G, Ile105Val)	2	
Senk et al. (2019)	194 Malignant mesothelioma	DDP + GEM/PEM	AQP1	Grade 2-4 anemia, leukopenia and neutropenia, Grade 1-4 thrombocytopenia	AQP1 rs28362731(G>A), AQP1 rs1049305(G>C)	5	
Björn et al. (2020b)	96 (split up into 80% training and 20% validation) NSCLC	CBP + GEM	Whole-genome sequencing	Grade 3-4 neutropenia, leukopenia and thrombocytopenia	4594, 5019, and 5066 autosomal SNVs/INDELs	6	
Bushra et al. (2020)	285 NSCLC	DDP/CBP + GEM/NVB/PTX/TXT	GSTP1, XRCC1, XPC, ERCC1	Grade 3-4 anemia, neutropenia, leukopenia and thrombocytopenia	GSTP1 rs1695 (A313G, Ile105Val), XRCC1 rs25487(G23885A, Arg399Gln), XPC rs2228001(A>C, Lys939Gln)	5	
Ferracini et al. (2021)	112 Ovarian cancer (Epithelial ovarian cancer)	CBP + PTX
CBP mono-therapy	GSTP1, ABCB1	Grade 3-4 anemia, neutropenia, Grade 1-4 thrombocytopenia	GSTP1 rs1695 (A313G, Ile105Val), ABCB1/MDR1 rs1128503 (C1236T)	7	
Nomura et al. (2020)	158 Esophageal cancer	DDP + TXT + 5-FU	ABCB1, ABCC2, ABCG2, GSTM1, GSTT1, GSTP1	Grade 3-4 neutropenia	ABCB1/MDR1 rs1045642 (C3435T), ABCC2/MRP2 rs12762549 (*+9383C>G)	6	
Svedberg et al. (2020)	215 (in discovery cohort) and 144 (in validation cohort) NSCLC	CBP + GEM	whole-exome sequencing	Grade 3-4 neutropenia and leucopenia	50 and 111 SNVs, and 12 and 20 genes
This study created wGRS models for predicting the risk of chemotherapy-induced hematological toxicity	7	
Nairuz et al. (2021)	180 Lung cancer	DDP/CBP + VP-16/PTX/TXTCBP + GEM/ADM	XPD, TP53	Grade 3-4 neutropenia, leucopenia, anemia and thrombocytopenia	No significant association	2	
Walia et al. (2021)	317 NSCLC + SCLC	DDP/CBP + PEM/CPT-11/TXT/PTX/GEM	GSTP1	Grade 3-4 anemia, Grade 1-4 anemia, Grade 2-4 anemia, Grade 1-4 leukopenia, Grade 2-4 leukopenia	GSTP1 rs1695	7	
Walia et al. (2022)	123 Lung adenocarcinoma cancer	DDP/CBP + PEM	MTHFR	Grade 1-3 neutropenia, Grade 2-3 neutropenia	MTHFR rs1801133	7	
Wang et al. (2021)	1004 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	ABCG2	Grade 3-4 hematologic toxicity, anemia, neutropenia and thrombocytopenia	ABCG2 rs12505410, ABCG2 rs1871744, ABCG2 rs2231138	7	
Zheng et al. (2021)	437 NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	EPO	Grade 3-4 hematologic toxicity, leukocytopenia, neutropenia, thrombocytopenia and anemia	EPO rs1617640	6	
Abbreviations: ADM, doxorubicin; BEV, bevacizumab; BLM, bleomycin; CAP, capecitabine; CBP, carboplatin; CI, confidence interval; CPT-11, irinotecan; CTCAE, common terminology criteria for adverse events; CTX, cyclophosphamide; DDP, cisplatin; EC-GemCap, epirubicin cisplatin (intra-arterial infusion)-gemcitabine capecitabine; GEM, gemcitabine; L-OHP, oxaliplatin; LV, leucovorin; MMC, mitomycin C; NSCLC, non-small cell lung cancer; NVB, navelbine; OR, odds ratios; PDXG, cisplatin, docetaxel capecitabine, gemcitabine; PEM, pemetrexed; PEXG, cisplatin, epirubicin, capecitabine, gemcitabine; PTX, paclitaxel; SCLC, small cell lung cancer; TXT, docetaxel; VCR, vincristine; VDS, vindesine; VP-16, etoposide; 5-FU, fluorouracil.

59 studies involved a single ethnic group [42 Chinese or Han Chinese, 5 Caucasian (Marsh et al., 2007; Tibaldi et al., 2008; Giovannetti et al., 2011; Ludovini et al., 2011; Lambrechts et al., 2015), 4 Japanese (Iwata et al., 2012; Low et al., 2013; Yoshihama et al., 2018; Nomura et al., 2020), 3 Indian (Ruzzo et al., 2014; Walia et al., 2021; Walia et al., 2022), 2 Korean (Kim et al., 2009; Lee et al., 2013), 1 Thai (Kumpiro et al., 2016), 1 Bangladeshi (Nairuz et al., 2021) and 1 eastern Slavonic origin (Khrunin et al., 2010)]. Three studies are mixed ancestry (Corrigan et al., 2014; Lambrechts et al., 2015; Ferracini et al., 2021). 21 studies did not explain how ancestry was determined.

Individual study sizes ranged from 32 to 1171 patients. 12 studies had fewer than 100 subjects. 10 studies involved discovery and replication sets (Marsh et al., 2007; Qian et al., 2012; Cao et al., 2016; Gréen et al., 2016; Jia et al., 2016; Yin et al., 2016; Zheng et al., 2017).

The studied cancer types were: lung cancer (n = 63), ovarian cancer (n = 6) (Marsh et al., 2007; Kim et al., 2009; Khrunin et al., 2010; Lambrechts et al., 2015; Liblab et al., 2020; Ferracini et al., 2021), malignant mesothelioma (n = 3) (Erčulj et al., 2012; Goričar et al., 2014; Senk et al., 2019), colorectal cancer (n = 3) (Cortejoso et al., 2013; Ruzzo et al., 2014), one study each evaluated colon cancer (Lee et al., 2013), gastric cancer (Seo et al., 2009), testicular cancer (Lee et al., 2013), esophageal cancer (Nomura et al., 2020), cervical cancer (Huang et al., 2015), pancreatic cancer (Giovannetti et al., 2011), four studies included various cancer types (Corrigan et al., 2014; Yoshihama et al., 2018) or did not mention the cancer type (Low et al., 2013).

64 studies used mixed combination chemotherapy: cisplatin/carboplatin-based chemotherapy (n = 51), cisplatin-based chemotherapy (n = 10), carboplatin-based chemotherapy (n = 3), 19 study uses single platinum-based chemotherapy. Platinum dosage and cycles varied according the tumor type: mostly cisplatin 75 mg/m2 or carboplatin AUC 5, both administered on day 1 every 3 weeks. The dose of oxaliplatin was 85 mg/m2 or 130 mg/m2 29 studies did not mention the dose of platinum agents.

47 studies analyzed the whole hematological toxicities. 56 studies analyzed detailed hematologic toxicity (leukopenia, neutropenia, thrombocytopenia or anemia). 20 studies analyzed both of them. Most studies (n = 80) use National Cancer Institute-Common Terminology Criteria for Adverse Events (NCI-CTCAE), three studies use WHO criteria (Isla et al., 2004; Chen et al., 2010; Huang et al., 2015).

The most used end-point of toxicity was the occurrence of grade ≥3 toxicity (n = 66). Other studies used a cut-off value of grade ≥1 (n = 12), grade ≥2 (n = 11), or grade 4 (n = 2) (Han et al., 2007; Marsh et al., 2007). One study described severe hematological toxicity including neutropenia G4, thrombocytopenia ≥ G3, and anemia ≥ G3 (Yoshihama et al., 2018). Eight studies analyzed more than one end-point of grading (Khrunin et al., 2010; Giovannetti et al., 2011; Erčulj et al., 2012; Lambrechts et al., 2015; Senk et al., 2019; Ferracini et al., 2021; Walia et al., 2021; Walia et al., 2022).

Among the 83 included studies, 28 (44.4%) were considered high quality, 46 (55.4%) moderate quality, and 9 (10.8%) were of low quality (Supplementary Table S6), the main reason for low study quality was the absence of calculation of sample size (n = 82), no consideration of population stratification (n = 80) and lack of statistical correction for multiple testing (n = 53).

3.3 Genetic associations investigated in platinum-induced hematological toxicity

51 variants were analyzed in more than one study (Tables 2, 3; Supplementary Table S7).

TABLE 2 Genetic polymorphisms investigated more than twice for association with platinum-induced hematological toxicity.

Pathway	Gene	SNP/deletion	Total (n)	With association	Without association	
Increased risk	Decreased risk	
Transporter	SCL31A1 (CTR1)	rs10981699 (C>T)	2	0	0	2 (Han et al., 2007; Giuliano, 2012)	
Transporter	SCL31A1 (CTR1)	rs10817465 (C>G)	2	0	0	2 (Han et al., 2007; Giuliano, 2012)	
Transporter	SCL31A1 (CTR1)	rs12686377 (C>A)	2	0	0	2 (Giuliano, 2012; Lee et al., 2013)	
Transporter	ABCC2(MRP2)	rs717620 (C-24T)	6	0	1 (Kim et al., 2009)	5 (Isla et al., 2004; Cara and M Eileen, 2006; Ludovini et al., 2011; Xu et al., 2012; Sun et al., 2018)	
Transporter	ABCC2(MRP2)	rs3740066 (C3972T, Ile1324Ile)	5	1 (Sun et al., 2018)	0	4 (Isla et al., 2004; Kim et al., 2009; Xu et al., 2012; Nomura et al., 2020)	
Transporter	ABCC2(MRP2)	rs2273697 (G1249A, Val417Ile)	4	0	0	4 (Isla et al., 2004; Ludovini et al., 2011; Xu et al., 2012; Sun et al., 2018)	
Transporter	ABCC2(MRP2)	rs12762549 (*+9383C>G)	2	1 (Iwata et al., 2012)	1 (Giovannetti et al., 2011)	0	
Transporter	ABCC2(MRP2)	rs2073337 (c.1668 + 148A>G)	2	0	0	2 (Giovannetti et al., 2011; Ludovini et al., 2011)	
Transporter	ABCB1(MDR1)	rs1045642(C3435T, Ile1145Ile)	12	1 (Iwata et al., 2012)	1 (Cara and M Eileen, 2006)	10 (Isla et al., 2004; Seo et al., 2009; Chen et al., 2010; Khrunin et al., 2010; Giovannetti et al., 2011; Han et al., 2011; Ludovini et al., 2011; Xu et al., 2012; Senk et al., 2019; Walia et al., 2022)	
Transporter	ABCB1(MDR1)	rs2032582(G2677T/A, Ala893Ser)	7	1 (Isla et al., 2004)	0	6 (Seo et al., 2009; Khrunin et al., 2010; Ludovini et al., 2011; Iwata et al., 2012; Senk et al., 2019; Walia et al., 2022)	
Transporter	ABCB1(MDR1)	rs1128503(C1236T, Gly412Gly)	6	2 (Khrunin et al., 2010; Giovannetti et al., 2011)	0	4 (Isla et al., 2004; Ludovini et al., 2011; Iwata et al., 2012; Senk et al., 2019)	
Transporter	ABCG2	rs2231142 (421C>A, Gln141Lys)	5	0	0	5 (Isla et al., 2004; Meyer zu Schwabedissen et al., 2005; Giovannetti et al., 2011; Ludovini et al., 2011; Iwata et al., 2012)	
Transporter	ABCG2	rs2231137 (34G>A, Val12Met)	3	0	0	3 (Isla et al., 2004; Meyer zu Schwabedissen et al., 2005; Iwata et al., 2012)	
Transporter	OCT2	rs316019 (808G/T, p.270Ala > Ser)	2	0	1 (Xu et al., 2012)	1 (Tibaldi et al., 2008)	
Transporter	MATE1	rs2289669 (G/A)	2	1 (Xu et al., 2012)	0	1 (Tibaldi et al., 2008)	
Metabolism	GSTP1	rs1695 (A313G, Ile105Val)	18	2 (Ruzzo et al., 2014; Zheng et al., 2017)	4 (Moriya et al., 2002; Khrunin et al., 2010; Björn et al., 2020b; Walia et al., 2022)	12 (Kim et al., 2001; Cara and M Eileen, 2006; Kim et al., 2009; Giovannetti et al., 2011; Han et al., 2011; Ludovini et al., 2011; Iwata et al., 2012; Cortejoso et al., 2013; Senk et al., 2019; Liblab et al., 2020; Nomura et al., 2020; Nairuz et al., 2021)	
Metabolism	GSTP1	rs1138272 (c.341 C>T, Ala114Val)	4	0	0	4 (Giovannetti et al., 2011; Ludovini et al., 2011; Liblab et al., 2020; Nairuz et al., 2021)	
Metabolism	GSTT1	gene deletion	9	0	0	9 (Kim et al., 2009; Han et al., 2011; Iwata et al., 2012; Cortejoso et al., 2013; Senk et al., 2019; Liblab et al., 2020; Nomura et al., 2020; Nairuz et al., 2021; Walia et al., 2022)	
Metabolism	GSTM1	gene deletion	8	0	2 (Liblab et al., 2020; Nairuz et al., 2021)	6 (Kim et al., 2009; Han et al., 2011; Iwata et al., 2012; Cortejoso et al., 2013; Nomura et al., 2020; Walia et al., 2022)	
NER	ERCC1	rs11615 (C118T, Asn118Asn)	19	4 (Kim et al., 2009; Giovannetti et al., 2011; Han et al., 2011; Yin et al., 2016)	1 (Senk et al., 2019)	14 (Moriya et al., 2002; Marsh et al., 2007; Seo et al., 2009; Chen et al., 2010; Ludovini et al., 2011; Cortejoso et al., 2013; Zheng et al., 2014; Lambrechts et al., 2015; Qian et al., 2016; Yoshihama et al., 2018; Liblab et al., 2020; Nomura et al., 2020; Nairuz et al., 2021; Walia et al., 2022)	
NER	ERCC1	rs3212986 (C8092A)	12	0	2 (Yin et al., 2016; Liblab et al., 2020)	10 (Kim et al., 2009; Han et al., 2011; Ludovini et al., 2011; Cortejoso et al., 2013; Zheng et al., 2014; Qian et al., 2015; Qian et al., 2016; Zheng et al., 2017; Nairuz et al., 2021; Walia et al., 2022)	
NER	ERCC1	rs3212961(17677G>T)	3	0	0	3 (Giovannetti et al., 2011; Ludovini et al., 2011; Qian et al., 2016)	
NER	ERCC2/XPD	rs13181(A>C, Lys751Gln)	17	0	1 (Chen et al., 2010)	16 (Marsh et al., 2007; Kim et al., 2009; Han et al., 2011; Ludovini et al., 2011; Zheng et al., 2014; Lambrechts et al., 2015; Kumpiro et al., 2016; Qian et al., 2016; Yin et al., 2016; Yoshihama et al., 2018; Senk et al., 2019; Liblab et al., 2020; Nomura et al., 2020; Ferracini et al., 2021; Nairuz et al., 2021; Walia et al., 2022)	
NER	ERCC2/XPD	rs1799793 (G23591A, Asp312Asn)	13	1 (Nairuz et al., 2021)	1 (Liblab et al., 2020)	11 (Hoffmeyer et al., 2000; Marsh et al., 2007; Kim et al., 2009; Chen et al., 2010; Giovannetti et al., 2011; Han et al., 2011; Zheng et al., 2014; Qian et al., 2016; Yin et al., 2016; Yoshihama et al., 2018; Nomura et al., 2020)	
NER	ERCC2/XPD	rs238406 (C22541A, Arg156Arg)	5	2 (Hoffmeyer et al., 2000; Han et al., 2011)	0	3 (Kim et al., 2009; Qian et al., 2016; Yin et al., 2016)	
NER	ERCC2/XPD	rs1052555 (G>A, Asp711Asp)	3	0	0	3 (Hoffmeyer et al., 2000; Qian et al., 2016; Yin et al., 2016)	
NER	ERCC4 (XPF)	rs1799801(T>C, Ser835Ser)	2	1 (Yin et al., 2016)	0	1 (Qian et al., 2016)	
NER	XPC	rs2228001(A>C, Lys939Gln)	3	2 (Moriya et al., 2002; Yin et al., 2016)	0	1 (Qian et al., 2016)	
NER	XPG/ERCC5	rs1047768 (T>C, His46His)	2	1 (Yin et al., 2016)	0	1 (Qian et al., 2016)	
NER	XPG/ERCC5	rs17655 (G>C, His1104Asp)	2	0 (Yin et al., 2016)	0	2 (Qian et al., 2016)	
NER	CCNH	rs2230641 (A>G, Val270Ala)	2	0	0	2 (Qian et al., 2016; Yin et al., 2016)	
NER	XPA	rs1800975 (T>C)	2	0	0	2 (Qian et al., 2016; Yin et al., 2016)	
NER	RPA1	rs12727 (G>C)	2	0	0	2 (Xu et al., 1998; Qian et al., 2016)	
NER	RPA1	rs17734 (C>T)	2	0	0	2 (Xu et al., 1998; Qian et al., 2016)	
BER	XPCC1	rs25487 (G23885A, Arg399Gln)	14	3 (Moriya et al., 2002; Yin et al., 2016; De Troia et al., 2019)	2 (Kim et al., 2001; Nairuz et al., 2021)	9 (Bosch et al., 2006; Kim et al., 2009; Ludovini et al., 2011; Zheng et al., 2014; Zheng et al., 2017; Yoshihama et al., 2018; Senk et al., 2019; Nomura et al., 2020; Walia et al., 2022)	
BER	XPCC1	rs25489 (G23098A, Arg280His)	3	0	0	3 (Kim et al., 2009; Yin et al., 2016; Nairuz et al., 2021)	
BER	XPCC1	rs1799782 (C21935T, Arg194Trp)	4	0	0	4 (Bosch et al., 2006; Kim et al., 2009; Nairuz et al., 2021; Walia et al., 2022)	
BER	APE1	rs1130409 (T>G, Asp148Glu)	2	0	1 (Yin et al., 2016)	1 (De Troia et al., 2019)	
BER	OGG1	rs1052133 (C>G, Ser326Cys)	2	0	0	2 (Yin et al., 2016; De Troia et al., 2019)	
DSB	XRCC3	rs861539 (C>T, Thr241Met)	3	0	0	3 (Lambrechts et al., 2015; Yin et al., 2016; Nomura et al., 2020)	
TLS	REV3L	rs462779 (G>A, Thr1224Ile)	2	0	0	2 (Erčulj et al., 2012; Yin et al., 2016)	
TLS	REV3L	rs465646 (G>A)	3	1	0	2 (Erčulj et al., 2012; Yin et al., 2016)	
TLS	REV7	rs746218 (G>A)	2	0	0	2 (Ding-Wu et al., 2012; Yin et al., 2016)	
TLS	REV7	rs2233006 (T>A)	2	0	0	2 (Ding-Wu et al., 2012; Yin et al., 2016)	
TLS	REV1	rs3087386 (A>G, Phe257Ser)	2	0	1 (Erčulj et al., 2012)	1 (Yin et al., 2016)	
TLS	Rad18	rs373572 (C>T, Arg302Gln)	2	0	0	2 (Yin et al., 2016; Wang et al., 2021)	
DNA synthesis	MTHFR	rs1801131 (A1298C, Glu429Ala)	6	0	0	6 (Kim et al., 2009; Zolk et al., 2009; Zolk, 2012; Nomura et al., 2020; Ferracini et al., 2021; Walia et al., 2021)	
DNA synthesis	MTHFR	rs1801133 (C677T, Ala222Val)	6	2 (Kim et al., 2009; Walia et al., 2021)	1 (Zolk, 2012)	3 (Zolk et al., 2009; Nomura et al., 2020; Ferracini et al., 2021)	
DNA synthesis	RRM1	rs12806698 (−37C/A)	2	1 (Yin et al., 2016)	1 (Chen et al., 2010)	0	
Apoptosis	MDM2	rs2279744 (309T>G)	4	1 (Moyer et al., 2008)	2 (Yin et al., 2016; R et al., 2000)	1 (Clarissa Ribeiro Reily et al., 2018)	
Apoptosis	TP53	rs1042522 (C>G, Pro72Arg)	9	2 (Nairuz et al., 2021; R et al., 2000)	0	7 (Moyer et al., 2008; Giovannetti et al., 2011; Ludovini et al., 2011; Lambrechts et al., 2015; Kumpiro et al., 2016; Yin et al., 2016; Clarissa Ribeiro Reily et al., 2018)	
Abbreviations: BER, base excision repair; DSB, double-strand break repair; MMR, mismatch repair; NER, nucleotide excision repair; TLS, translesion DNA, synthesis.

TABLE 3 Summary of positive associations in genetic polymorphisms that investigated more than twice.

Study	Sample size, cancer	Treatment	Association	Trend	
ABCC2(MRP2) rs717620 (C-24T)	
Lee et al. (2013)	292 Colon cancer	L-OHP + LV + 5-FU	Lower incident rate of grade 3-4 thrombocytopenia [5.6% (9 out of 160 patients with CC) vs. 0.8% (1 out of 124 with CT or TT), p = 0.047]	Decrease	
ABCC2(MRP2) rs3740066 (C3972T, Ile1324Ile)	
Han et al. (2011)	445 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOther DDP/CBP combinations	Increased risk of grade 3-4 thrombocytopenia (CT + TT vs. CC OR = 2.43; 95% CI: 1.06–5.56; p = 0.034)	Increase	
ABCC2(MRP2) rs12762549 (*+9383C>G)	
Nomura et al. (2020)	158 Esophageal cancer	DDP + TXT + 5-FU	Increased risk of grade 3-4 neutropenia (GG vs. GC + CC OR = 2.342; 95% CI: 1.108–4.948; p = 0.026)	Increase	
Lambrechts et al. (2015)	290 Ovarian cancer	CBP + PTX
CBP mono-therapy	Decreased risk of grade 3-4 anemia in additive model (OR = 0.51; 95% CI: 0.33–0.81; p = 0.004)	Decrease	
ABCB1(MDR1) rs1045642(C3435T, Ile1145Ile)	
Nomura et al. (2020)	158 Esophageal cancer	DDP + TXT + 5-FU	Increased risk of grade 3-4 neutropenia (CT + TT vs. CC OR = 2.191; 95% CI: 1.087–4.417; p = 0.028)	Increase	
De Troia et al. (2019)	82 Lung cancer	DDP/CBP + VP-16/NVBDDP + GEM/PEM/TXT
DDP monotherapy	Decreased risk of grade 3-4 hematological toxicity (CT vs. CC OR = 0.18; 95% CI: 0.05–0.65; p = 0.01, CT + TT vs. CC OR = 0.24; 95% CI: 0.07–0.75; p = 0.01)	Decrease	
ABCB1(MDR1) rs2032582(G2677T/A, Ala893Ser)	
Han et al. (2007)	107 NSCLC	DDP + CPT-11	Associated with grade 4 neutropenia (the incident rate of grade 4 neutropenia for GG, GT/GA and TT/TA/AA were 34.6%, 53.8%, and 11.5%, p = 0.030)	Increase	
ABCB1(MDR1) rs1128503(C1236T, Gly412Gly)	
Lambrechts et al. (2015)	290 Ovarian cancer	CBP + PTX
CBP mono-therapy	Increased risk of grade 3-4 anemia in additive model (OR = 1.71; 95% CI: 1.07–2.71; p = 0.023)	Increase	
Ferracini et al. (2021)	112 Ovarian cancer (Epithelial ovarian cancer)	CBP + PTX
CBP mono-therapy	Increased risk of grade 1-4 thrombocytopenia (TT vs. CC OR = 3.63; 95% CI: 0.98–13.47; p = 0.05, TT vs. CT + CC OR = 3.50; 95% CI: 1.12–10.97; p = 0.03)	Increase	
OCT2 rs316019 (808G/T, p.270Ala > Ser)	
Qian et al. (2016)	403 NSCLC	DDP/CBP + GEM/PEM/PTX/TXT/NVB	Decreased risk of grade 3-4 hematological toxicity in additive model (OR = 0.58; 95% CI: 0.34–0.97; p = 0.039)	Decrease	
MATE1 rs2289669 (G/A)	
Qian et al. (2016)	403 NSCLC	DDP/CBP + GEM/PEM/PTX/TXT/NVB	Increased risk of grade 3-4 hematological toxicity in recessive model (OR = 1.92; 95% CI: 1.13–3.25; p = 0.016)	Increase	
GSTP1 rs1695 (A313G, Ile105Val)	
Ferracini et al. (2021)	112 Ovarian cancer (Epithelial ovarian cancer)	CBP + PTX
CBP mono-therapy	Decreased risk of grade 3-4 anemia (AG vs. AA OR = 0.16; 95% CI: 0.03–0.84; p = 0.03, AG + GG vs. AA OR = 0.17; 95% CI: 0.04–0.69; p = 0.01), grade 3-4 thrombocytopenia (AG vs. AA OR = 0.32; 95% CI: 0.12–0.82; p = 0.01, GG vs. AA OR = 0.11; 95% CI: 0.02–0.59; p < 0.01, AG + GG vs. AA OR = 0.27; 95% CI: 0.12–0.64; p < 0.01, GG vs. AA+ AG OR = 0.18; 95% CI: 0.03–0.85; p = 0.03)	Decrease	
Kim et al. (2009)	118 Ovarian cancer (Epithelial ovarian cancer)	DDP/CBP + PTX
CBP + TXT	Associated with grade 3-4 hematological toxicity (the incident rate of grade 3-4 hematology toxicity for AG/GG and AA were 54.2% and 78.7%, p = 0.015)	Decrease	
Bushra et al. (2020)	285 NSCLC	DDP/CBP + GEM/NVB/PTX/TXT	Decreased risk of grade 3-4 anemia (GG vs. AA OR = 0.29; 95% CI: 0.10–0.87; p = 0.027) and grade 3-4 neutropenia (GG vs. AA OR = 0.31; 95% CI: 0.10–0.96; p = 0.043)	Decrease	
Yoshihama et al. (2018)	320 Ovarian fallopian tube, peritoneal, uterine, or cervical cancer	CBP + PTX	Decreased risk of severe hematotoxicity (including neutropenia G4, thrombocytopenia ≥ G3,and anemia ≥ G3) (A allele vs. G allele OR = 5.71; 95% CI: 1.77–18.44; p = 0.00034)	Decrease	
Walia et al. (2021)	317 Lung cancer	DDP/CBP + PEM/CPT-11/TXT/PTX/GEM	Increased risk of grade 3-4 anemia (AG vs. AA OR = 2.12; 95% CI: 0.97–4.62; p = 0.04) and grade 2-4 leukopenia (GG vs. AA OR = 2.41; 95% CI: 1.39–4.18; p = 0.001)	Increase	
Liblab et al. (2020)	52 Ovarian cancer (Epithelial ovarian cancer)	CBP + PTX
CBP mono-therapy	Higher incident rate of grade 2-4 anemia [46.34% (AA) vs. 81.82% (AG), p = 0.036]	Increase	
GSTM1 gene deletion	
Erčulj et al. (2012)	94 Malignant mesothelioma	DDP/CBP + GEM/PEM
DDP + MMC + VCR	Decreased risk of grade 2-4 leukopenia (0/0 vs. 1/1 + 1/0 OR = 0.43; 95% CI: 0.18–0.99; p = 0.048)	Decrease	
Khrunin et al. (2010)	104 Ovarian cancer	DDP + CTX	Decreased risk of grade 1-4 thrombocytopenia (0/0 vs. 1/0 OR = 0.13; 95% CI: 0.03–0.62; p = 0.005), grade 2-4 anemia (0/0 vs. 1/0 OR = 0.29; 95% CI: 0.13–0.66; p = 0.003)	Decrease	
ERCC1 rs11615 (C118T, Asn118Asn)	
Lee et al. (2013)	292 Colon cancer	L-OHP + LV + 5-FU	Increased risk of grade 3-4 neutropenia (TT vs. TC + CC OR = 4.58, 95% CI: 1.20–17.40, p = 0.026)	Increase	
Lavanderos et al. (2019)	119 Testicular cancer	DDP + BLM + VP-16	Increased risk of grade 3-4 febrile neutropenia (TT vs. CC + CT OR = 4.89; 95% CI: 1.06–22.56; p = 0.042)	Increase	
Lambrechts et al. (2015)	290 Ovarian cancer	CBP + PTX
CBP mono-therapy	Increased risk of grade 3-4 anemia in additive model (OR = 1.61; 95% CI: 1.04–2.50; p = 0.031)	Increase	
Zheng et al. (2017)	437 in the in a discovery cohort and 781 in the validation cohort NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	Increased risk of grade 3-4 anemia in dominant model in discovery cohort (OR = 2.230; 95% CI: 1.041–4.775; p = 0.039)	Increase	
Cortejoso et al. (2013)	106 Colorectal cancer	L-OHP + 5-FU + LV
L-OHP + CAP	Decreased risk of grade 3-4 neutropenia (CT + TT vs. CC OR = 0.205; 95% CI: 0.061–0.690; p = 0.010)	Decrease	
ERCC1 rs3212986 (C8092A)	
Zheng et al. (2017)	437 in the in a discovery cohort and 781 in the validation cohort NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	Decreased risk of grade 3-4 hematologic toxicity in recessive model in discovery cohort (OR = 0.326; 95% CI: 0.123–0.861; p = 0.024)	Decrease	
Erčulj et al. (2012)	94 Malignant mesothelioma	DDP/CBP + GEM/PEM
DDP + MMC + VCR	Decreased risk of grade 2-4 leukopenia (CA + AA vs. CC OR = 0.18; 95% CI: 0.04–0.86; p = 0.032)	Decrease	
ERCC2/XPD rs13181(A>C, Lys751Gln)	
Isla et al. (2004)	62 NSCLC	DDP + TXT	Associated with grade 2-4 neutropenia (the incident rate of grade 2-4 neutropenia for Lys/Lys, Lys/Gln and Gln/Gln were 48%, 19%, and 14%, p = 0.04)	Decrease	
ERCC2/XPD rs1799793 (G23591A, Asp312Asn)	
Erčulj et al. (2012)	94 Malignant mesothelioma	DDP/CBP + GEM/PEM
DDP + MMC + VCR	Decreased risk of grade 1-4 thrombocytopenia (Asp/Asn + Asn/Asn vs. Asp/Asp OR = 0.15; 95% CI: 0.04–0.61; p = 0.008)	Decrease	
Khrunin et al. (2010)	104 Ovarian cancer	DDP + CTX	Associated with grade 1-4 thrombocytopenia (Asp/Asn vs. Asp/Asp + Asn/Asn OR = 4.05; 95% CI: 1.21–13.58; p = 0.027), grade 2-4 anemia (Asp/Asn vs. Asp/Asp + Asn/Asn OR = 2.32; 95% CI: 1.05–5.13; p = 0.048)	Increase	
ERCC2/XPD rs238406 (C22541A, Arg156Arg)	
(Wu et al. 2009)	209 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	Increased risk of grade 3-4 hematologic toxicity (AA vs. CC OR = 3.24; 95% CI: 1.35–7.78; p = 0.009), grade 3-4 leukopenia toxicity (AA vs. CC OR = 4.88; 95% CI: 1.67–14.26; p = 0.005)	Increase	
Lavanderos et al. (2019)	119 Testicular cancer	DDP + BLM + VP-16	Increased risk of grade 3-4 leukopenia (CA + AA vs. CC OR = 4.09; 95% CI: 1.04–15.99; p = 0.043)	Increase	
ERCC4 (XPF) rs1799801(T>C, Ser835Ser)	
Zheng et al. (2017)	437 in the in a discovery cohort and 781 in the validation cohort NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	Increased risk of grade 3-4 hematologic toxicity in additive model (OR = 1.555; 95% CI: 1.041–2.323; p = 0.031) and grade 3-4 thrombocytopenia in dominant model (OR = 3.562; 95% CI: 1.513–8.390; p = 0.004) in discovery cohort	Increase	
XPC rs2228001(A>C, Lys939Gln)	
Bushra et al. (2020)	285 NSCLC	DDP/CBP + GEM/NVB/PTX/TXT	Decreased risk of grade 3-4 anemia (CC vs. AA OR = 0.18; 95% CI: 0.04–0.82; p = 0.027) and Increased risk of grade 3-4 neutropenia (AC vs. AA OR = 3.31; 95% CI: 1.74–6.31; p = 0.0003, AC + CC vs. AA OR = 2.63; 95% CI: 1.41–4.90; p = 0.002)	Increase	
Zheng et al. (2017)	437 in the in a discovery cohort and 781 in the validation cohort NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	Increased risk of grade 3-4 leukocytopenia in dominant model in discovery cohort (OR = 2.217; 95% CI: 1.054–4.665; p = 0.036)	Increase	
XPG/ERCC5 rs1047768 (T>C, His46His)	
Zheng et al. (2017)	437 in the in a discovery cohort and 781 in the validation cohort NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	Increased risk of grade 3-4 leukocytopenia in additive model in discovery cohort (OR = 1.701; 95% CI: 1.021–2.835; p = 0.041)	Increase	
XPG/ERCC5 rs17655 (G>C, His1104Asp)	
Zheng et al. (2017)	437 in the in a discovery cohort and 781 in the validation cohort NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	Increased risk of grade 3-4 thrombocytopenia in additive model in discovery cohort (OR = 2.165; 95% CI: 1.191–3.938; p = 0.011)	Increase	
XPCC1 rs25487 (G23885A, Arg399Gln)	
Bushra et al. (2020)	285 NSCLC	DDP/CBP + GEM/NVB/PTX/TXT	Increased risk of grade 3-4 anemia (AA+ AG vs. GG OR = 2.0; 95% CI: 1.19–3.35; p = 0.008, AG vs. GG OR = 2.27; 95% CI: 1.32–3.91; p = 0.003), grade 3-4 neutropenia (AG vs. GG OR = 2.37; 95% CI: 1.37–4.07; p = 0.002, AA+ AG vs. GG OR = 1.98; 95% CI: 1.18–3.33; p = 0.010), grade 3-4 leukopenia (AG vs. GG OR = 1.79; 95% CI: 1.0–3.18; p = 0.049) and grade 3-4 thrombocytopenia (AG vs. GG OR = 2.14; 95% CI: 1.09–4.20; p = 0.027, AA+ AG vs. GG OR = 2.11; 95% CI: 1.10–4.06; p = 0.025)	Increase	
Peng et al. (2014)	235 NSCLC	DDP + PTX/GEM/NVB/PEM	Increased risk of grade 3-4 hematologic toxicity (AG vs. GG OR = 1.929; 95% CI: 1.069-3.481  p = 0.029, AA vs. GG OR = 4.885; 95% CI: 1.147–20.197; p = 0.032, AG + AA vs. GG OR = 2.135; 95% CI: 1.207–3.777; p = 0.009)	Increase	
Zheng et al. (2017)	437 in the in a discovery cohort and 781 in the validation cohort NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	Increased risk of grade 3-4 leukocytopenia in recessive model (OR = 2.841; 95% CI: 1.051–7.681; p = 0.040) and grade 3-4 thrombocytopenia in additive model (OR = 2.033; 95% CI: 1.113–3.715; p = 0.021) in discovery cohort	Increase	
Deng et al. (2015)	97 NSCLC	DDP + GEM/NVB/PTX/TXT	Decreased risk of grade 1-4 lymphopenia (AG + AA vs. GG OR = 0.323; 95% CI: 0.121–0.862; p = 0.024)	Decrease	
Khrunin et al. (2010)	104 Ovarian cancer	DDP + CTX	Decreased risk of grade 3-4 neutropenia (GG vs. AG + AA OR = 3.02; 95% CI: 1.33–6.88; p = 0.009)	Decrease	
APE1 rs1130409 (T>G, Asp148Glu)	
Zheng et al. (2017)	437 in the in a discovery cohort and 781 in the validation cohort NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	Decreased risk of grade 3-4 leukocytopenia in dominant model (OR = 0.460; 95% CI: 0.241–0.879; p = 0.019), grade 3-4 neutropenia in dominant model (OR = 0.557; 95% CI: 0.321–0.967; p = 0.038) in discovery cohort	Decrease	
REV3 rs465646 (G>A)	
Ye et al. (2015)	663 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOthers DDP/CBP combinations	Increased risk of grade 3-4 hematologic toxicity (A/G + A/A vs. G/G OR = 2.54; 95% CI: 1.17–5.42; p = 0.016)	Increase	
REV1 rs3087386 (A>G, Phe257Ser)	
Goričar et al. (2014)	139 Malignant mesothelioma	DDP + GEM/PEM
Other DDP doublets	Decreased risk of grade 2-4 neutropenia (GA + AA vs. GG OR = 0.38; 95% CI: 0.17–0.84; p = 0.017)	Decrease	
MTHFR rs1801133 (C677T, Ala222Val)	
Walia et al. (2022)	123 Lung adenocarcinoma cancer	DDP/CBP + PEM	Increased risk of grade 1-3 neutropenia (CT vs. CC OR = 5.34; 95% CI: 1.49–19.06; p = 0.009, CT + TT vs. CC OR = 4.45; 95% CI: 1.28–15.43; p = 0.019)	Increase	
Lee et al. (2013)	292 Colon cancer	L-OHP + LV + 5-FU	Increased risk of grade 3-4 neutropenia (TT vs. CC + CT OR = 2.32, 95% CI: 1.19–4.55, p = 0.014)	Increase	
Li et al. (2014)	1004 NSCLC	DDP/CBP + NVB/GEM/PTX/TXTOther DDP/CBP combinations	Decreased risk of grade 3-4 thrombocytopenia (CT vs. CC OR = 0.40; 95% CI: 0.19–0.85; p = 0.016)	Decrease	
RRM1 rs12806698(-37C/A)	
Isla et al. (2004)	62 NSCLC	DDP + TXT	Associated with grade 2-4 leukopenia (the incident rate of grade 2-4 leukopenia for CC and CA were 31% and 10%, p = 0.05)	Decrease	
Zheng et al. (2017)	437 in the in a discovery cohort and 781 in the validation cohort NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	Increased risk of grade 3-4 leukocytopenia in recessive model (OR = 5.095; 95% CI: 2.132–12.170; p = 0.0002), grade 3-4 neutropenia in recessive model (OR = 2.561; 95% CI: 1.075–6.099; p = 0.034) in discovery cohort	Increase	
MDM2 rs2279744 (309T>G)	
Zheng et al. (2017)	437 in the in a discovery cohort and 781 in the validation cohort NSCLC	DDP/CBP + NVB/GEM/PTX/TXT/PEM	Decreased risk of grade 3-4 thrombocytopenia in additive model (OR = 0.472; 95% CI: 0.257–0.866; p = 0.015) in discovery cohort	Decrease	
Wang et al. (2014)	119 SCLC	DDP + VP-16	Decreased risk of grade 3-4 neutropenia in additive model (OR = 0.48; 95% CI: 0.2652–0.8709; p = 0.015) and in recessive model (OR = 0.27; 95% CI: 0.08763–0.8859; p = 0.030)	Decrease	
Guo et al. (2016)	292 Lung adenocarcinoma	DDP/CBP combinations	Increased risk of grade 3-4 hematologic toxicity in recessive model (OR = 2.128; 95% CI: 1.198–3.777; p = 0.010)	Increase	
TP53 rs1042522 (C>G, Pro72Arg)	
Khrunin et al. (2010)	104 Ovarian cancer	DDP + CTX	Increased risk of grade 3-4 neutropenia (GG vs. CC + CG OR = 8.57; 95% CI: 1.05–69.8; p = 0.023)	Increase	
Wang et al. (2014)	119 SCLC	DDP + VP-16	Increased risk of grade 3-4 neutropenia in recessive model (OR = 3.44; 95% CI: 1.302–9.111; p = 0.012)	Increase	
Abbreviations: BLM, bleomycin; CAP, capecitabine; CBP, carboplatin; CI, confidence interval; CPT-11, irinotecan; CTX, cyclophosphamide; DDP, cisplatin; GEM, gemcitabine; L-OHP, oxaliplatin; LV, leucovorin; MMC, mitomycin C; NSCLC, non-small cell lung cancer; NVB, navelbine; OR, odds ratios; PEM, pemetrexed; PTX, paclitaxel; SCLC, small cell lung cancer; TXT, docetaxel; VCR, vincristine; VP-16, etoposide; 5-FU, fluorouracil.

3.3.1 Transportation for influx

3.3.1.1 SLC31A1 (CTR1)

The main route of platinum agents entering the cell is through the copper transporter CTR1 (SLC31A1) (Giuliano, 2012). Because of the lack of candidate SNPs, studies were limited. SLC31A1(CTR1) rs10981699 (Xu et al., 2012; Sun et al., 2018), rs10817465 (Xu et al., 2012; Sun et al., 2018), rs12686377 (Xu et al., 2012; Kumpiro et al., 2016) were analyzed in two studies respectively. No association has been found.

3.3.2 Transportation for efflux

3.3.2.1 ABCC2 (MRP2)

The multi-drug resistance protein (MRP2), encoded for by ABCC2, involved in pumping cisplatin out of the cell (Cara and M Eileen, 2006). The frequently investigated genetic polymorphisms in ABCC2 were rs717620 (C-24T) (n = 6), rs3740066 (C3972T, Ile1324Ile) (n = 5), rs2273697 (G1249A) (n = 4), rs12762549(*+9383C>G) (n = 2), and rs2073337 (c.1668 + 148A>G) (n = 2). ABCC2 rs717620 (C-24 T) and ABCC2 rs3740066 (C3972T, Ile1324Ile) may not affect the expression of MRP2 mRNA or protein (Moriya et al., 2002; Meyer zu Schwabedissen et al., 2005), while ABCC2 rs2273697 (G1249A) resulted in a significantly reduced expression of mRNA in human preterm placenta (Meyer zu Schwabedissen et al., 2005).

Positive association were reported in only few studies. ABCC2 rs717620 (C-24T) CC genotype present increased rate of grade 3-4 thrombocytopenia in contrast to CT and TT genotypes in 292 colon cancer patients treated with FOLFOX chemotherapy (5.6% vs. 0.8%, p = 0.047) (Lee et al., 2013). ABCC2 rs3740066(C3972T, Ile1324Ile) T allele was suggested as a risk factor for grade 3-4 thrombocytopenia in 445 NSCLC patients receiving platinum-based chemotherapy (OR = 2.43; 95% CI: 1.06–5.56; p = 0.034) (Han et al., 2011). As for ABCC2 rs12762549(G1249A), two studies show inconsistent results. Nomura et al. found a higher risk of grade 3-4 neutropenia in GG genotype in 158 esophageal cancer patients treated with docetaxel, cisplatin, and 5-fluorouracil chemotherapy (OR = 2.342; 95% CI: 1.108–4.948; p = 0.026) (Nomura et al., 2020). In contrast, ABCC2 rs12762549 is associated with decreased risk of grade 3-4 anemia in additive model (OR = 0.51; 95% CI: 0.33–0.81; p = 0.004) among 290 ovarian cancer patients upon treatment with paclitaxel and carboplatin (Lambrechts et al., 2015). No association has been found with the ABCC2 rs2073337 (Marsh et al., 2007; Lambrechts et al., 2015) and rs2273697 (Han et al., 2007; Marsh et al., 2007; Han et al., 2011; Qian et al., 2016).

3.3.2.2 ABCB1 (MDR1)

ABCB1 (MDR1 or p-glycoprotein) is thought to play a role in platinum efflux, although to a much lesser extent than the copper transporters or MRP2 (Cara and M Eileen, 2006). As to ABCB1 rs1045642(C3435T), the homozygous T-allele is associated with significantly lower duodenal MDR-1 expression and the highest digoxin plasma levels (Hoffmeyer et al., 2000). 12 studies were available for ABCB1 rs1045642(C3435T) but the results have not been consistent. De Troia B et al. reported that patients carrying 3435T allele had a lower risk of grade 3-4 neutropenia in 82 lung cancer patients treated with platinum-based chemotherapy (OR = 0.24; 95% CI: 0.07–0.75; p = 0.01) (De Troia et al., 2019). In contrast to these results, Nomura, H. et al. found T allele carriers were more likely to develop grade 3-4 neutropenia (OR = 2.191; 95% CI: 1.087–4.417; p = 0.028) in 158 esophageal cancer patients receiving docetaxel, cisplatin, and 5-fluorouracil therapy (Nomura et al., 2020).

Studies have also focused on ABCB1 rs2032582 (G2677TA, Ala893Ser) (n = 7) and ABCB1 rs1128503(C1236T) (n = 6). The two SNPs are associated with altered P-glycoprotein function, in which the Ser893 variant transporter resulted in a 47% lower intracellular digoxin concentration (p < .002) than did the Ala893 variant in vitro (Kim et al., 2001) and homozygous carriers of ABCB1 rs1128503(C1236T) polymorphism was significantly correlated with a decreased docetaxel clearance (Bosch et al., 2006). ABCB1 rs2032582 (G2677TA, Ala893Ser) displayed differential genotypic distribution between groups with grade 4 neutropenia and grade 1-3 neutropenia in 107 NSCLC patients (p = 0.030) (Han et al., 2007). ABCB1 rs1128503 (C1236T) were significantly associated with grade 3-4 anemia in additive model (OR = 1.71; 95% CI: 1.07–2.71; p = 0.023) in 290 ovarian cancer patients (Lambrechts et al., 2015). Similarly, another study in 112 ovarian cancer patients found that carriers of TT genotype were more frequently experienced grade 1-4 thrombocytopenia compared to those CC or CT genotype (OR = 3.50; 95% CI: 1.12–10.97; p = 0.03) (Ferracini et al., 2021).

3.3.2.3 ABCG2 (BCRP)

ABCG2 (breast cancer resistance protein or BCRP) is efflux transporter proteins that play a role in the development of chemoresistance to platinum agents (Ding-Wu et al., 2012). No association has been shown with the ABCG2 rs2231142 (Han et al., 2007; Marsh et al., 2007; Lambrechts et al., 2015; Nomura et al., 2020; Wang et al., 2021) and ABCG2 rs2231137 (Han et al., 2007; Nomura et al., 2020; Wang et al., 2021).

3.3.2.4 OCT2 (SLC22A2) and MATE1 (SLC47A1)

OCT2 is considered the predominant transporter mediating active accumulation of cisplatin in the kidney. MATE1 is thought to mediate the final step of renal tubular secretion of cisplatin (Giuliano, 2012). The OCT2 rs316019 (808G/T, p.270Ala > Ser) variant significantly impaired uptake kinetics of endogenous compounds and drugs (Zolk et al., 2009; Zolk, 2012). OCT2 rs316019 (808G/T, p.270Ala > Ser) and MATE1 rs2289669 (G/A) were analyzed in two studies (Iwata et al., 2012; Qian et al., 2016). Qian et al. found significant correlations with grade 3-4 hematological toxicity in these two SNPs among 403 NSCLC patients (Qian et al., 2016).

3.3.3 Metabolism

Platinum compounds can be detoxified by conjugation with glutathione through the aid of glutathione S-transferases (GSTs) (R et al., 2000). GSTP1, GSTM1, and GSTT1 belongs to Human GSTs and were mostly analyzed for the functional polymorphisms in gene regions.

3.3.3.1 GSTP1

Two common nonsynonymous polymorphisms in GSTP1, rs1695 (Ile105Val, A313G) and rs1138272 (Ala114Val), were shown to decrease GSTP1 enzyme activity (Moyer et al., 2008). GSTP1 rs1695 (Ile105Val, A313G) was the most common studied variant with 18 studies available. Four studies show a protective effect for hematological toxicity. One study in Brazil reported AG or GG genotype was associated with decreased risk of grade 3-4 anemia and grade 3-4 thrombocytopenia in 112 epithelial ovarian cancer patients (Ferracini et al., 2021). Another study in Korean showed that patients with A/G or G/G genotype showed lower rate of hematological toxicity (13/24, 54.2%) than those with A/A genotype (74/94, 78.7%) among 118 epithelial ovarian cancer patients (p = 0.015) (Kim et al., 2009). Bushra et al. found that GG genotype is associated with decreased risk of grade 3-4 anemia (OR = 0.29; 95% CI: 0.10–0.87; p = 0.027) and grade 3-4 neutropenia (OR = 0.31; 95% CI: 0.10–0.96; p = 0.043) in 285 NSCLC patients in Bangladesh (Bushra et al., 2020). Perhaps worth to mention is a comprehensive pharmacogenomic analysis in 320 gynecological cancers patients, of which GSTP1 rs1695 showed the lowest p-value against severe hematological toxicity (p = 0.00034) (Yoshihama et al., 2018). In contrast, Walia et al. found a significantly increased risk of grade 3-4 anemia with the AG genotype (OR = 2.12; 95% CI: 0.97–4.62; p = 0.04) and increased risk of grade 2-4 leukopenia with the GG genotype (OR = 2.41; 95% CI: 1.39–4.18; p = 0.001) in 317 North Indian lung cancer patients (Walia et al., 2021). Liblab et al. (2020) found that carriers of AG genotype were more frequently experienced grade 2-4 anemia than AA genotype in 52 ovarian cancer patients (81.82% vs. 46.34%, p = 0.036). Five studies demonstrated no significant association of GSTP1 rs1138272 (Ala114Val) polymorphism.

3.3.3.2 GSTT1 and GSTM1

Gene deletion in GSTT1 and GSTM1 can lead to an absence of enzymatic activity (Pemble et al., 1994; Xu et al., 1998). Nine studies showed no effect of GSTT1 gene deletion on the risk of hematological toxicity. Eight studies analyzed GSTM1 gene deletion, in which two studies showed a protective effect (Khrunin et al., 2010; Erčulj et al., 2012). In 94 malignant mesothelioma patients treated with platinum-based chemotherapy, Patients with homozygous GSTM1 gene deletion have a significantly decreased risk of grade 2-4 leukopenia compared with those of at least one functional allele (OR = 0.43; 95% CI: 0.18–0.99; p = 0.048) (Erčulj et al., 2012). Another study in 104 ovarian cancer patients that received paclitaxel and carboplatin found carriers of a homozygous GSTM1 gene deletion were less likely to develop grade 1-4 thrombocytopenia (OR = 0.13; 95% CI: 0.03–0.62; p = 0.005) and grade 2-4 anemia (OR = 0.29; 95% CI: 0.13–0.66; p = 0.003) than those of functional GSTM1 variants (Khrunin et al., 2010).

3.3.4 NER pathway

The bulky DNA intra-strand adducts generated by platinum are mainly repaired by the nucleotide-excision repair (NER) pathway (Clarissa Ribeiro Reily et al., 2018).

3.3.4.1 ERCC1

ERCC1 interact with XPF to make an incision at the damaged DNA lesion in NER pathway. ERCC1 rs11615 (C118T, Asn118Asn) (n = 19) and ERCC1 rs3212986 (C8092A) (n = 12) have been wildly studied. ERCC1 rs11615 reduces the transcription and mRNA levels of ERCC1, resulting in lower ERCC1 expression (Yu et al., 2000). ERCC1 rs3212986 resides in the 30-untranslated region that might affect mRNA stability (Chen et al., 2000). Four studies reported a significantly increased risk with ERCC1 rs11615 (C118T, Asn118Asn). In a study of 292 colon cancer patients receiving adjuvant oxaliplatin plus leucovorin plus 5-fluorouracil (FOLFOX) chemotherapy, TT genotype was more prone to develop grade 3-4 neutropenia (OR = 4.58, 95% CI: 1.20–17.40, p = 0.026) (Lee et al., 2013). Another study in 119 testicular cancer patients also reported an increased risk of grade 3-4 febrile neutropenia caused by bleomycin, etoposide, and cisplatin (BEP) chemotherapy in TT genotype (OR = 4.89; 95% CI: 1.06–22.56; p = 0.042) (Lavanderos et al., 2019). ERCC1 rs11615 was associated with an increased risk of grade 3-4 anemia in 290 ovarian cancer patients (OR = 1.61; 95% CI: 1.04–2.50; p = 0.031) (Lambrechts et al., 2015) and 437 NSCLC patients (OR = 2.230; 95% CI: 1.041–4.775; p = 0.039) (Zheng et al., 2017). On the contrary, Cortejoso et al. (2013) found individuals carrying T allele had a reduced risk of grade 3-4 neutropenia in 106 colon cancer patients (OR = 0.205; 95% CI: 0.061–0.690; p = 0.010). As for ERCC1 rs3212986(C8092A), two studies reported a decreased risk. Zheng et al. found that ERCC1 rs3212986 was significantly associated with a reduced risk of grade 3-4 hematologic toxicity in recessive model in 437 NSCLC patients (OR = 0.326; 95% CI: 0.123–0.861; p = 0.024) (Zheng et al., 2017). Erčulj et al. (2012) reported that patients carrying A allele had a lower risk of grade 2-4 leukopenia in 94 malignant mesothelioma patients (OR = 0.18; 95% CI: 0.04–0.86; p = 0.032). No association has been established between ERCC1 rs3212961 (17677G>T) and the development of hematologic toxicity (Marsh et al., 2007; Lambrechts et al., 2015; Song et al., 2017).

3.3.4.2 ERCC2/XPD

ERCC2 (XPD) is a helicase that can unwind the DNA strands to facilitate the binding of other NER proteins. ERCC2 rs13181 (Lys751Gln), rs1799793(Asp312Asn), rs238406 (C22541A, Arg156Arg), rs1052555 (Asp711Asp) have been evaluated in 17 studies, 13 studies, five studies and three studies respectively. ERCC2 rs13181(Lys751Gln) can alter mRNA transcription levels, leading to reduced levels of ERCC2 mRNA(82). For ERCC2 rs13181 (Lys751Gln), grade 2-4 neutropenia was more frequent among individual with 751 Lys/Lys genotype in 62 NSCLC patients treated with cisplatin and docetaxel (p = 0.04) (Isla et al., 2004).

ERCC2 rs1799793 (Asp312Asn) is associated with significantly decreased constitutive XPD mRNA levels in lymphocytes of healthy subjects (Wolfe et al., 2007). Results on rs1799793 (Asp312Asn) have not been consistent. Erčulj et al. found patients carrying 312Asp/Asn and 312Asn/Asn genotype had a lower risk of grade 1-4 thrombocytopenia in 94 malignant mesothelioma patients (OR = 0.15; 95% CI: 0.04–0.61; p = 0.008) (Erčulj et al., 2012). Whereas, Khrunin et al. (2010) found patients carrying Asp/Asn genotype were more prone to grade 1-4 thrombocytopenia (OR = 4.05; 95% CI: 1.21–13.58; p = 0.027) and grade 2-4 anemia (OR = 2.32; 95% CI: 1.05–5.13; p = 0.048) in 104 ovarian cancer patients. ERCC2 rs238406(C22541A, Arg156Arg) can reduce the levels of mRNA and ultimately affect XPD activity and function (Wolfe et al., 2007). The incidence of grade 3-4 hematologic toxicity (OR = 3.24; 95% CI: 1.35–7.78; p = 0.009) and grade 3-4 leukopenia (OR = 4.88; 95% CI: 1.67–14.26; p = 0.005) was significantly higher in variant homozygotes AA genotype, when compared with CC genotype in 209 NSCLC patients (Wu et al., 2009). Likewise, another study in 119 testicular cancer patients showed the increased risk of grade 3-4 leukopenia with the AA or CA genotype (OR = 4.09; 95% CI: 1.04–15.99; p = 0.043) (Lavanderos et al., 2019). Studies on ERCC2 rs1052555 (Asp711Asp) (n = 3) showed no significant difference (Wu et al., 2009; Song et al., 2017; Zheng et al., 2017).

3.3.4.3 ERCC4/XPF

ERCC4/XPF participates in the removal of damaged DNA strands by acting as an endonuclease with ERCC1. Of two studies in ERCC4 rs1799801 (T>C, Ser835Ser) (Song et al., 2017; Zheng et al., 2017), one study in 437 NSCLC patients demonstrated an association of the ERCC4 rs1799801 with grade 3-4 hematologic toxicity in additive model (OR = 1.555; 95% CI: 1.041–2.323; p = 0.031) and grade 3-4 thrombocytopenia in dominant model (OR = 3.562; 95% CI: 1.513–8.390; p = 0.004) (Zheng et al., 2017).

3.3.4.4 XPC

XPC cooperates with RAD23B to recognize DNA lesions and start the initial step of damage recognition. Three studies concentrate on XPC rs2228001(A>C, Lys939Gln) (Song et al., 2017; Zheng et al., 2017; Bushra et al., 2020). XPC rs2228001(A>C, Lys939Gln) was associated with lower DNA repair capacity (Zhu et al., 2008). In 285 Bangladesh NSCLC patients, carriers of XPC rs2228001 AC or CC genotypes showed significant suffering from grade 3-4 neutropenia (OR = 2.63; 95% CI: 1.41–4.90; p = 0.002), while those harboring CC genotypes are less likely to develop grade 3-4 anemia, compared with AA genotype carriers (OR = 0.18; 95% CI: 0.04–0.82; p = 0.027) (Bushra et al., 2020). Another study conducted in 437 Chinese NSCLC patients show XPC rs2228001 is associated with an increased risk of grade 3-4 leukocytopenia in dominant model (OR = 2.217; 95% CI: 1.054–4.665; p = 0.036) (Zheng et al., 2017).

3.3.4.5 ERCC5/XPG

ERCC5 (XPG) encodes a structure-specific endonuclease that can cleave the 3ʹ-end of damaged DNA lesions. Two studies focus on XPG rs1047768(A>C, Lys939Gln) and rs17655(A>C, Lys939Gln). Zheng et al. found a significant association of XPG rs1047768 with grade 3-4 leukocytopenia in additive model (OR = 1.701; 95% CI: 1.021–2.835; p = 0.041) and XPG rs17655 with grade 3-4 thrombocytopenia in additive model (OR = 2.165; 95% CI: 1.191–3.938; p = 0.011) (Zheng et al., 2017). The other study reported no association with these two investigated SNPs (Song et al., 2017).

3.3.4.6 Other NER genes

XPA rs1800975, RPA1 rs17734, RPA1 rs12727 and CCNH rs2230641 (Song et al., 2017; Zheng et al., 2017) were examined twice and showed no significant associations.

3.3.5 BER pathway

The base excision repair (BER) pathway is mainly responsible for removing the oxidative DNA lesions generated by platinum drug exposure (Jana et al., 2018).

3.3.5.1 XRCC1

XRCC1 acts as a central scaffolding protein to finish the final steps of BER. XPCC1 rs25487 (G>A, Arg399Gln) can cause missense mutation in the coding region, leading to decreased damage DNA repair activity (Wang et al., 2003; Vodicka et al., 2004). 14 studies investigated a link of XPCC1 rs25487 (G>A, Arg399Gln) with hematological toxicity and results have not been consistent. In a study of 285 NSCLC patients, XRCC1 rs25487 polymorphism showed significant associations with increased risk of grade 3-4 anemia, grade 3-4 neutropenia, grade 3-4 leukopenia and grade 3-4 thrombocytopenia (Bushra et al., 2020). A higher risk of grade 3-4 hematologic toxicity was also observed in AG and GG carriers in a cohort of 235 NSCLC patients (OR = 2.135; 95% CI: 1.207–3.777; p = 0.009) (Peng et al., 2014). In keeping with this, XRCC1 rs25487 was identified as risk factors for grade 3-4 leukocytopenia in recessive model (OR = 2.841; 95% CI: 1.051–7.681; p = 0.040), grade 3-4 thrombocytopenia in additive model (OR = 2.033; 95% CI: 1.113–3.715; p = 0.021) in discovery cohort of 437 NSCLC patients (Zheng et al., 2017). In contrast, AA or AG carriers had a decreased risk of grade 1-4 lymphopenia as observed in 94 NSCLC patients (OR = 0.323; 95% CI: 0.121–0.862; p = 0.024) (Deng et al., 2015). In 104 ovarian cancer that received cisplatin and cyclophosphamide, an increased risk of grade 3-4 neutropenia was found in GG wildtype carriers (OR = 3.02; 95% CI: 1.33–6.88; p = 0.009) (Khrunin et al., 2010). Other studies failed to reveal a positive association.

XPCC1 rs1799782 (Arg194Trp) can leading to decreased DNA repair activity (Wang et al., 2003). XPCC1 rs1799782 (Arg194Trp) (n = 4) (Wang et al., 2008; Kim et al., 2009; Khrunin et al., 2010; Lee et al., 2013) and XPCC1 rs25489 (Arg280His) (n = 3) (Khrunin et al., 2010; Lee et al., 2013; Zheng et al., 2017) showed no significant difference with hematological toxicity.

3.3.5.2 APE1 and OGG1

APE1 and OGG1 are key component in the BER pathway. Two studies examined APE1 rs1130409 (Asp148Glu) and OGG1 rs1052133 (Ser326Cys) (Peng et al., 2014; Zheng et al., 2017). APE1 rs1130409(Asp148Glu) variant exhibiting normal in vitro nuclease capacity (Daviet et al., 2007; Wilson et al., 2011) and OGG1 rs1052133(Ser326Cys) polymorphism negatively impacts OGG1 function (Wilson et al., 2011). APE1 rs1130409 was associated with a decreased risk of grade 3-4 leukocytopenia (OR = 0.460; 95% CI: 0.241–0.879; p = 0.019) and grade 3-4 neutropenia (OR = 0.557; 95% CI: 0.321–0.967; p = 0.038) in dominant model (Zheng et al., 2017). OGG1 rs1052133 failed to show significant association with hematological toxicity (Peng et al., 2014; Zheng et al., 2017).

3.3.6 DSB pathway

Homologous recombination (HR) and non-homologous and joining pathways are responsible for repairing the DSBs generated by platinum-induced ICLs which are the most hazardous type of DNA damage. XRCC3 are one of the crucial proteins involved in mediating the HR pathway (Giovanna and Massimo, 2019). XRCC3 rs861539(C>T, Thr241Met) was show to reduce DNA damage repair capacity (Matullo et al., 2001). However, no association was detected in three analyses on XRCC3 rs861539 (Thr241Met) (Ludovini et al., 2011; Ruzzo et al., 2014; Zheng et al., 2017).

3.3.7 TLS

TLS is performed by a series of low-fidelity polymerases to tolerate platinum-induced DNA lesions (The Vinh and Orlando, 2010). REV3L rs462779 (Goričar et al., 2014; Zheng et al., 2017), REV3L rs465646 (Goričar et al., 2014; Ye et al., 2015; Zheng et al., 2017), REV7 rs746218 (Ye et al., 2015; Zheng et al., 2017), REV7 rs2233006 (Ye et al., 2015; Zheng et al., 2017), REV1 rs3087386 (Goričar et al., 2014; Zheng et al., 2017) and Rad18 rs373572 (Chu et al., 2016; Zheng et al., 2017) were analyzed in more than one study. REV3 rs465646 were associated with grade 3-4 hematologic toxicity in 663 NSCLC patients (OR = 2.54; 95% CI: 1.17–5.42; p = 0.016) (Ye et al., 2015). In a study of 139 malignant mesothelioma patients receiving cisplatin-based chemotherapy, carriers of the REV1 rs3087386 A allele were less prone to develop grade 2-4 neutropenia (OR = 0.38; 95% CI: 0.17–0.84; p = 0.017) (Goričar et al., 2014). Other studies show no significant associations.

3.3.8 DNA synthesis

3.3.8.1 MTHFR

MTHFR is involved in folate metabolism, essential for the synthesis of nucleic acids and amino acids. Two common nonsynonymous polymorphisms in MTHFR, rs1801133 (C677T, Ala222Val) and rs1801131 (A1298C, Glu429Ala) were shown to decrease MTHFR enzyme activity in vitro (van der Put et al., 1998). These two SNPs were analyzed in six studies (Lee et al., 2013; Corrigan et al., 2014; Kanazawa et al., 2014; Li et al., 2014; Ruzzo et al., 2014; Walia et al., 2022). The results for MTHFR rs1801133 (C677T, Ala222Val) were inconsistent. An increased risk of grade 1-3 neutropenia was detected in carriers of the T allele (OR = 4.45; 95% CI: 1.28–15.43; p = 0.019) among 123 lung adenocarcinoma patients treated with platinum and pemetrexed chemotherapy (Walia et al., 2022). Likewise, carriers of the TT genotype were more likely to develop grade 3-4 neutropenia compared with those carrying CC and CT genotype in 292 colon cancer patients (OR = 2.32, 95% CI: 1.19–4.55, p = 0.014) (Lee et al., 2013). While, the heterozygote CT genotype show a protective effect for grade 3-4 thrombocytopenia in Li et al.’s study of 1004 NSCLC patients (OR = 0.40; 95% CI: 0.19–0.85; p = 0.016) (Li et al., 2014). MTHFR rs1801131 (A1298C, Glu429Ala) showed no effect on risk of hematological toxicity.

3.3.8.2 RRM1

RRM1 encodes the regulatory subunit of ribonucleotide reductase and is involved in the production of deoxyribonucleotides during DNA synthesis. RRM1 – 37A allele impacted promoter activity with increased RRM1 mRNA expression in vitro (Bepler et al., 2005; Rodriguez et al., 2011). RRM1 rs12806698 (−37C/A) was suggested as a candidate risk factor for grade 3-4 leukocytopenia (OR = 5.095; 95% CI: 2.132–12.170; p = 0.0002) and grade 3-4 neutropenia (OR = 2.561; 95% CI: 1.075–6.099; p = 0.034) in recessive model in 437 NSCLC patients (Zheng et al., 2017), while in another study of 63 NSCLC patients, grade 2-4 leukopenia was more frequent among patients with wild-type RRM1 rs12806698 CC genotype than carriers of CA genotype (37% versus 10%, p = 0.05) (Isla et al., 2004).

3.3.9 Apoptosis

3.3.9.1 MDM2

MDM2 rs2279744 (309T>G) resulted in higher levels of MDM2 RNA and protein and the subsequent attenuation of the p53 DNA damage response (Bond et al., 2004). For MDM2 rs2279744 (309T>G) (n = 4), two studies in lung cancer patients observed a protective effect for grade 3-4 thrombocytopenia (OR = 0.472; 95% CI: 0.257–0.866; p = 0.015) (Zheng et al., 2017) and grade 3-4 neutropenia (OR = 0.27; 95% CI: 0.08763–0.8859; p = 0.030) respectively (Wang et al., 2014). Another study in 292 lung adenocarcinoma patients show opposite results that MDM2 rs2279744 was associated with an increased risk of grade 3-4 hematologic toxicity in recessive model (OR = 2.128; 95% CI: 1.198–3.777; p = 0.010) (Guo et al., 2016).

3.3.9.2 TP 53

TP53 (p53) is a key regulator of cell cycle control and DNA damage response as well as apoptosis initiation. TP53 rs1042522 (Arg72Pro) Arg72 variant is more efficient than the Pro72 variant in inducing apoptosis (Dumont et al., 2003). TP53 rs1042522 (Arg72Pro) was associated with an increased risk of grade 3-4 neutropenia in recessive model (OR = 3.44; 95% CI: 1.302–9.111; p = 0.012) in 119 SCLC patients treated with cisplatin and etoposide (Wang et al., 2014). Another study in 104 ovarian cancer patients showed similar result that patients carrying GG genotype were prone to experience grade 3-4 neutropenia, compared with CC + CG genotype (OR = 8.57; 95% CI: 1.05–69.8; p = 0.023) (Khrunin et al., 2010). The remaining studies (n = 7) showed no significant difference.

3.4 Significant associations in other less commonly investigated variants

The array of SNPs that investigated only once are listed in Supplementary Table S8. Lots of studies analyzed those less commonly investigated variants in main candidate genes such as SLC31A1 (CTR1) (Xu et al., 2012; Sun et al., 2018), ATP7A (Deng et al., 2015; Li et al., 2018), ATP7B (Li et al., 2018), ABCC2 (Ruzzo et al., 2014), ABCB1 (Chen et al., 2010; Chen et al., 2016), ABCG2 (Chen et al., 2016; Wang et al., 2021), OCT2 (Chen et al., 2016; Qian et al., 2016), MDM2 (Zheng et al., 2014; Qian et al., 2015), TP53 (Khrunin et al., 2010) or tagSNPs on genes that are not directly affect the influx, efflux and metabolism of platinum agent or play as mediators or modulators of center cellular activities. Those genes and the functions were listed in Supplementary Table S8, including the transport genes (SLCs, AQP2, AQP9, TMEM205, SIRT1, ABCC1, MVP, AQP1) (Chen et al., 2016; Senk et al., 2019), Metabolism gene (CYP2E1, GSTA1, GSTM3, AGXT, MAPT, MPO) (Marsh et al., 2007; Khrunin et al., 2010; Lee et al., 2013), MicroRNAs (Zhan et al., 2012; Fang et al., 2017), Long Non-Coding RNA (Hu et al., 2016; Gong et al., 2017). Apoptosis-related genes (BCL2, BAX, CASP3, CASP8, CASP10, TNFα and MIF) (Gu et al., 2012; Qian et al., 2012; Liu D. et al., 2017a), EPO (Zheng et al., 2021), VCP (Peng et al., 2013), STAT3 (Gong et al., 2019), WISP1 (Chen et al., 2014), TERT (Zhao et al., 2015), CHEK2 (Xu et al., 2016), MMP-2 (Zhao et al., 2012), RICTOR (Wang et al., 2016), eIF3 a (Yin et al., 2015), HSP genes and Rho family genes (Zou et al., 2016), CDC25 family genes (Cai et al., 2014), The JNK and P38 MAPK pathways genes (Jia et al., 2016), MIF signaling pathway (Tan et al., 2014). As to DNA repair pathway, there were studies focus on tagSNPs in less investigated NER genes (Chen et al., 2016; Song et al., 2017; Zheng et al., 2017) and BER genes (Peng et al., 2014; Zheng et al., 2017). DNA repair pathway that not directly involved in repairing platinum-induced DNA lesions like MMR (Liu JY. et al., 2017b; Zheng et al., 2017), DSB (Zheng et al., 2017), TLS (Goričar et al., 2014; Shao et al., 2014; Ye et al., 2015; Chu et al., 2016; Zheng et al., 2017), FA pathway (Zheng et al., 2017), have received more attention recently. Some significant association was found, while these SNPs were not previously analyzed and should be validated in future studies.

3.5 High throughput researches

Four studies are derived from the same cohort in Sweden population of 215 NSCLC patients treated with gemcitabine/carboplatin chemotherapy (Gréen et al., 2016; Svedberg et al., 2020; Björn et al., 2020a; Björn et al., 2020b). Three of them were whole-exome sequence studies concentrating of gemcitabine/carboplatin-induced grade 3-4 thrombocytopenia (Gréen et al., 2016; Björn et al., 2020a), leukopenia (Svedberg et al., 2020) and neutropenia (Gréen et al., 2016; Svedberg et al., 2020). The fourth study performed a GWAS in a subset of 96 patients (Björn et al., 2020b). These studies identified and validated several genetic variations, genes and hematopoiesis-related pathways to be potential significance and created weighted genetic risk score (wGRS) prediction models for predicting the risk of chemotherapy-induced hematological toxicity. There were GWAS concentrating on NSCLC (Cao et al., 2016), cervical cancer (Huang et al., 2015), and unclassified carcinomas (Low et al., 2013). A list of novel genetic variants such as rs13014982 at 2q24.3 and rs9909179 at 17p12 were identified (Cao et al., 2016) and the artificial neural networks model based on the multiple risk factors were constructed (Huang et al., 2015). Yin et al. developed a strategy to establish a predicted model of toxicity integrating both genetic and clinical factors using DM techniques (Yin et al., 2016).

4 Discussion

4.1 Main findings

This systematic review has reported and evaluated the findings of published studies that investigated the genetic associations with hematological toxicities in the cancer patients receiving platinum-based chemotherapy. We found that ABCC2 rs12762549, ABCB1 rs1045642, ABCB1 rs1128503, GSTP1 rs1695, GSTM1 gene deletion, ERCC1 rs11615, ERCC1 rs3212986, ERCC2 rs238406, ERCC2 rs1799793, XPC rs2228001, XPCC1 rs25487, MTHFR rs1801133, MDM2 rs2279744, RRM1 rs12806698, TP53 rs1042522 show positive associations in more than two studies, but most associations were not consistently replicated across the reviewed studies. Among them, ABCB1 rs1128503, GSTP1 rs1695, GSTM1 gene deletion, ERCC1 rs11615, ERCC1 rs3212986, ERCC2 rs238406, XPC rs2228001, XPCC1 rs25487, MTHFR rs1801133, MDM2 rs2279744, TP53 rs1042522 had consistent results across at least two independent populations. These genetic variants may provide insights into the molecular mechanisms towards platinum-induced hematological toxicities (Qihai et al., 2023).

It's also worth mentioning that GSTP1 rs1695 (A313G, Ile105Val) show significant association in six studies. Among them, four studies show protective role of GSTP1 rs1695 against platinum-induced hematological toxicities, including a comprehensive analysis that targeted resequencing of 100 notable pharmacokinetics-related genes in which GSTP1 rs1695 showed the smallest p-value (p = 0.00034) (Yoshihama et al., 2018). Positive associations of GSTP1 rs1695 with increased risk of platinum-induced hematological toxicity was found in two meta-analysis (Lv et al., 2018; Kim et al., 2022), while these two meta-analysis studies face the limitations of insufficient data availability. Alteration of DNA repair ability might play an important role in the development of platinum-induced hematological toxicity. Genetic variants in the candidate NER genes may affect the repair function and are most promising in predicting platinum-related hematological toxicity, since it is the main pathway responsible of repairing the bulky DNA intra-strand adducts generated by platinum agents (Hilary et al., 2024). ERCC1 rs11615 (C118T, Asn118Asn) and ERCC1 rs3212986 (C8092A) are two common variant that affect ERCC1 (key enzyme in NER pathway) mRNA expression or mRNA stability (Chen et al., 2000; Yu et al., 2000). ERCC1 rs11615 present consistent results with increased risk of grade 3-4 neutropenia or anemia in four studies, and ERCC1 rs3212986 show decreased risk of grade 3-4 hematologic toxicity in two studies. These two SNPs may be important molecular biomarkers for predicting platinum-induced hematological toxicities. XRCC1 rs25487 (G23885A, Arg399Gln) show positive association in six studies, emphasizing the potential contribution of BER pathway in oxidative stress in platinum-induced hematological toxicity, since cisplatin can exert cytotoxic effects through the generation of ROS (Zheng et al., 2020).

Apart from that, lots of genetic variants located in genes not directly linked to drug exposure are investigated. The GWAS have identified a handful of candidate genetic variants associated with platinum-based hematological toxicities and novel biologic pathways of potential impact. But these studies still face the challenge of statistically underpowered and stringent threshold of multiple testing. Additional validation in multiple independent sample sets or functional analyses are required to further elucidate the gene-phenotype relationship (Low et al., 2014).

4.2 Quality and inconsistency among studies

Genetic association studies require a large number of patients to provide adequate power, as a rare variant with large effect, or common variant with modest effect is more probable in genetic epidemiology (Campbell et al., 1995). While the majority of the studies in our systematic review did not indicate the sample size calculation in their statistical analysis, and the sample size in most studies in our systematic review are much smaller than that would be implied, which may be underpowered to detect a statistically significant relationship (Jorgensen and Williamson, 2008).

One of the challenges in pharmacogenomics is the ethnic background of the study population. The prevalence of toxicity varies according to the ethnic background (O’Donnell and Dolan, 2009; Li and Meyre, 2013). For example, higher rates of toxicities have been observed in east Asian populations compared to European and North American populations (Watanabe et al., 2003). In addition, allele frequency of genetic variants vary depending on the ethnic background or even the geographical location. When cases and controls are drawn from multiple ethnic or geographic groups, population stratification exists, which may put the study at risk of confounding and can lead to false positive associations (Jorgensen and Williamson, 2008). Population stratification was seldom assessed in most genetic association studies, which has been cited as a major reason for lack of replication.

Different treatment protocols are recommended according to cancer types. The composition, proportion and cycles of chemotherapy regimen can influence the incidence and degree of hematological toxicity. Furthermore, treatment protocols may also differ with regard to the use of concomitant supportive treatments. The time and dose of granulocyte colony-stimulating factor administered may be various across institutions, which are seldom mentioned in the method part and may bring confounds in genetic association studies. Moreover, there are overlap in metabolic pathway between platinum and other antineoplastic drugs, which can alter the pharmacogenetic effects of polymorphisms. For example, The ABC transporter ABCB1 and ABCC2 is responsible for the efflux of many commonly used antineoplastic drugs that usually used in combination with platinum agents, including taxanes (Marsh, 2006; Lambrechts et al., 2015). If Pt-DNA lesions are not repaired, the DNA lesion triggers activation of the apoptosis pathway, an essential step for the effectiveness of platinum-based chemotherapeutics for killing tumor cells, which is also the apoptosis pathway of many other cytotoxic drugs (Fulda and Debatin, 2006). Apart from the role of participating in DNA synthesis, MTHFR encode key enzymes for the metabolism of 5-FU (Lee et al., 2013) and RRM1 was also the primary target for gemcitabine (Yuan et al., 2015).

Genetic association studies are heavily reliant on the phenotype, but it may be difficult to establish the true phenotype. Although myelosuppression is quantitative, the degree of myelosuppression could be missed based on the frequency of measurement. Apart from that, differences in the toxicity assessment criterion and endpoints may hamper reproducibility of previous findings. Some studies analyzed the total hematological toxicity (Wang et al., 2008; Kim et al., 2009; Gu et al., 2012), while other studies analyzed the detail hematological toxicity (leukopenia, neutropenia, thrombocytopenia or anemia) (Isla et al., 2004; Tibaldi et al., 2008; Xu et al., 2012). The detail hematological toxicity may be more accurate and clinically relevant, but its low incidence requires cohort study with large sample size, which are unattainable in the current researches. Furthermore, methodological flaws were observed in the imprecise dichotomization of patients with mild toxicity and severe toxicity. The majority use the occurrence of grade 3-4 as endpoints, other studies use grade 2-4 (Isla et al., 2004; Erčulj et al., 2012; Huang et al., 2015; Jia et al., 2016; Liblab et al., 2020) or grade 1-4 (Chen et al., 2010; Erčulj et al., 2012; Deng et al., 2015; Walia et al., 2022). Medical interventions of dose reduction and/or treatment discontinuation were taken when grade 3-4 hematological toxicity arises. Therefore, the toxicity endpoints of grade 2-4 or grade 1-4 may not be clinically relevant (Supplementary Table S4).

There is statistical heterogeneity in the data analysis (Supplementary Table S5). Some studies just used chi-square test or fisher’s exact test to estimate the difference of genotype distribution in cases and controls (Kimcurran et al., 2011; Kalikaki et al., 2015). Others use logistic regression to make comparisons between groups and generate odds ratios and 95% confidence intervals. Logistic regression is more appropriate as it can provide a quantitative measure of the relationship between the groups, allow adjustment for confounding factors, and detect gene-gene or gene-environment interactions. Some studies made a clear statement about mode of inheritance assumed for analysis, and used more than one assumption (Peng et al., 2014; Bushra et al., 2020; Ferracini et al., 2021; Walia et al., 2022), while other studies only compared the three categories of genotype frequencies (homozygous wild type, heterozygous, homozygous variant) between cases and controls (Isla et al., 2004; Han et al., 2007; Kim et al., 2009; Lee et al., 2013; Liblab et al., 2020). 30 of the included studies performed the correction for multiple comparisons and only 10 studies performed validation of the results or by splitting the cohort for a primary and an exploratory analysis (Marsh et al., 2007; Qian et al., 2012; Cao et al., 2016; Gréen et al., 2016; Jia et al., 2016; Yin et al., 2016; Zheng et al., 2017; Björn et al., 2020a; Björn et al., 2020b; Svedberg et al., 2020).

4.3 Limitations

This review has several limitations, which mainly reflects the status of current genetic association studies. In the search process, many studies had to be excluded because hematological toxicity was not clearly described or there is no toxicity grading criterion. What’s more, we observed that the most studies did not provide toxicity statistics data (no p-value) or just provide insufficient toxicity data (for example, some studies only mentioned correlation in the results section without providing the original statistical data), which may raise some doubts of data authenticity. Also, some studies did not control exclusion criteria of prior history of chemotherapy and/or radiation or a considerable proportion of the patients receive chemotherapy combined with radiation or other non-platinum chemotherapy regimens, which may increase the likelihood of cumulative hematological toxicity. There is much heterogeneity between incorporated studies, thus we were unable to perform a quantitative comparison and meta-analysis.

4.4 Implications for clinical practice and research

Future studies should focus on the following aspects. Firstly, genetic association study inevitably faces the concerns of bias and confounding, and are susceptible to inappropriate conclusions, therefore it calls for careful planning of study design to improving quality of methodology (Saito et al., 2006). Secondly, the majority genetic polymorphisms identified in the eligible publications were repeated in only one or two studies (Hilary et al., 2024). SNPs screened out as potential factors in susceptibility to hematological toxicity in our systematic review require well-planned, methodologically robust studies to validate them. Thirdly, functional predictions of significant genetic variants needed to be confirmed and validated in vitro or in vivo work (Felipe Antonio de Oliveira et al., 2022). Fourthly, more studies should emphasize on the hematopoiesis-related pathways identified in a whole-exome sequenced study of 215 NSCLC patients treated with a single treatment (Björn et al., 2020a). Moreover, clinical trial with large sample size to perform subgroup analysis should be conducted to allow proper stratified analysis. Finally, owing to the complexity of mechanisms of platinum action, a single SNP alone may have low effect to platinum response, thus supporting a polygenetic effect in platinum‐induced hematological toxicity (Daniel et al., 2023). Future direction should be establishing appropriate statistical methods with capacity to integrate multiple genetic, phenotypic, epidemiological and clinical variables effects.

5 Conclusion

To summarize, this systematic review has successfully reported and evaluated studies on genetic associations of platinum-based hematological toxicities. Review of these studies identified several genetic variants that potentially affect the risk of platinum-induced hematological toxicity. Many methodological issues exist that may affect reproducibility of results and lead to inconsistency, including insufficient sample size, population stratification, various treatment schedule, heterogeneity in the assessment of hematological toxicity and statistics. Well-designed studies with sufficient samples sizes and standardization of phenotypes are warranted to address the limitations of the current studies and to ensure the robust findings that can be more effective to be used in personalized therapeutics.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.

Author contributions

YZ: Conceptualization, Formal Analysis, Methodology, Supervision, Writing–original draft. MT: Conceptualization, Formal Analysis, Methodology, Writing–review and editing. ZD: Conceptualization, Formal Analysis, Methodology, Writing–review and editing. PC: Conceptualization, Formal Analysis, Writing–review and editing.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fphar.2024.1445328/full#supplementary-material

Abbreviations

AUC, area under curve; BER, base excision repair; CI, confidence interval; DSB, double-strand break repair; FA, fanconi anemia; FOLFOX, oxaliplatin, leucovorin and 5-fluorouracil; FR, flanking region; GWAS, genome-wide association studies; HR, homologous recombination; ICL, interstrand crosslink; MMR, mismatch repair; NCI-CTCAE, National Cancer Institute-Common Terminology Criteria for Adverse Events; NSCLC, non-small cell lung cancer; NER, nucleotide excision repair; OR, odds ratios; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; ROS, reactive oxygen species; SNP, single nucleotide polymorphism; TLS, translesion DNA synthesis; UTR, untranslated region; WHO, World Health Organization.
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References

Basu A. Ghosh P. Bhattacharjee A. Patra A. R. Bhattacharya S. (2015). Prevention of myelosuppression and genotoxicity induced by cisplatin in murine bone marrow cells: effect of an organovanadium compound vanadium(III)-l-cysteine. Mutagenesis 30 (4 ), 509–517. 10.1093/mutage/gev011 25778689
Bepler G. Zheng Z. Gautam A. Sharma S. Cantor A. Sharma A. (2005). Ribonucleotide reductase M1 gene promoter activity, polymorphisms, population frequencies, and clinical relevance. Lung Cancer 47 (2 ), 183–192. 10.1016/j.lungcan.2004.07.043 15639717
Björn N. Badam T. V. S. Spalinskas R. Brandén E. Koyi H. Lewensohn R. (2020b). Whole-genome sequencing and gene network modules predict gemcitabine/carboplatin-induced myelosuppression in non-small cell lung cancer patients. NPJ Syst. Biol. Appl. 6 (1 ), 25. 10.1038/s41540-020-00146-6 32839457
Björn N. Sigurgeirsson B. Svedberg A. Pradhananga S. Brandén E. Koyi H. (2020a). Genes and variants in hematopoiesis-related pathways are associated with gemcitabine/carboplatin-induced thrombocytopenia. Pharmacogenomics J. 20 (2 ), 179–191. 10.1038/s41397-019-0099-8 31616045
Bond G. L. Hu W. Bond E. E. Robins H. Lutzker S. G. Arva N. C. (2004). A single nucleotide polymorphism in the MDM2 promoter attenuates the p53 tumor suppressor pathway and accelerates tumor formation in humans. Cell 119 (5 ), 591–602. 10.1016/j.cell.2004.11.022 15550242
Bosch T. M. Huitema A. D. Doodeman V. D. Jansen R. Witteveen E. Smit W. M. (2006). Pharmacogenetic screening of CYP3A and ABCB1 in relation to population pharmacokinetics of docetaxel. Clin. cancer Res. official J. Am. Assoc. Cancer Res. 12 (19 ), 5786–5793. 10.1158/1078-0432.CCR-05-2649
Bushra M. U. Rivu S. F. Sifat A. E. Nahid N. A. Ahmed M. U. Al-Mamun M. M. A. (2020). Genetic polymorphisms of GSTP1, XRCC1, XPC and ERCC1: prediction of clinical outcome of platinum-based chemotherapy in advanced non-small cell lung cancer patients of Bangladesh. Mol. Biol. Rep. 47 (9 ), 7073–7082. 10.1007/s11033-020-05771-2 32880833
Cai W. Chen C. Li X. Shi J. Sun Q. Liu D. (2014). Association of CDC25 phosphatase family polymorphisms with the efficacy/toxicity of platinum-based chemotherapy in Chinese advanced NSCLC patients. Future Oncol. 10 (7 ), 1175–1185. 10.2217/fon.14.25 24947259
Campbell M. J. Julious S. A. Altman D. G. (1995). Estimating sample sizes for binary, ordered categorical, and continuous outcomes in two group comparisons. BMJ 311 (7013 ), 1145–1148. 10.1136/bmj.311.7013.1145 7580713
Cao S. Wang S. Ma H. Tang S. Sun C. Dai J. (2016). Genome-wide association study of myelosuppression in non-small-cell lung cancer patients with platinum-based chemotherapy. Pharmacogenomics J. 16 (1 ), 41–46. 10.1038/tpj.2015.22 25823687
Cara A. R. M Eileen D. (2006). Molecular mechanisms of resistance and toxicity associated with platinating agents. Cancer Treat. Rev. 33 (1 ), 9–23. 10.1016/j.ctrv.2006.09.006 17084534
Chen J. Wu L. Wang Y. Yin J. Li X. Wang Z. (2016). Effect of transporter and DNA repair gene polymorphisms to lung cancer chemotherapy toxicity. Tumor Biol. 37 (2 ), 2275–2284. 10.1007/s13277-015-4048-0
Chen J. Yin J. Li X. Wang Y. Zheng Y. Qian C. (2014). WISP1 polymorphisms contribute to platinum-based chemotherapy toxicity in lung cancer patients. Int. J. Mol. Sci. 15 (11 ), 21011–21027. 10.3390/ijms151121011 25405734
Chen P. Wiencke J. Aldape K. Kesler-Diaz A. Miike R. Kelsey K. (2000). Association of an ERCC1 polymorphism with adult-onset glioma. Cancer Epidemiol. biomarkers and Prev. a Publ. Am. Assoc. Cancer Res. cosponsored by Am. Soc. Prev. Oncol. 9 (8 ), 843–847.
Chen S. Huo X. Lin Y. Ban H. Lin Y. Li W. (2010). Association of MDR1 and ERCC1 polymorphisms with response and toxicity to cisplatin-based chemotherapy in non-small-cell lung cancer patients. Int. J. Hyg. Environ. Health 213 (2 ), 140–145. 10.1016/j.ijheh.2010.01.004 20189873
Chu T. Q. Li R. Shao M. H. Ye J. Y. Han B. H. (2016). RAD18 polymorphisms are associated with platinum-based chemotherapy toxicity in Chinese patients with non-small cell lung cancer. Acta Pharmacol. Sin. 37 (11 ), 1490–1498. 10.1038/aps.2016.100 27665847
Clarissa Ribeiro Reily R. Matheus Molina S. Annabel Q. Januario Bispo C.-N. Carlos Frederico Martins M. (2018). DNA repair pathways and cisplatin resistance: an intimate relationship. Clin. (Sao Paulo) 73 (Suppl. 1 ), e478s. 10.6061/clinics/2018/e478s
Corrigan A. Walker J. L. Wickramasinghe S. Hernandez M. A. Newhouse S. J. Folarin A. A. (2014). Pharmacogenetics of pemetrexed combination therapy in lung cancer: pathway analysis reveals novel toxicity associations. pharmacogenomics J. 14 (5 ), 411–417. 10.1038/tpj.2014.13 24732178
Cortejoso L. García M. I. García-Alfonso P. González-Haba E. Escolar F. Sanjurjo M. (2013). Differential toxicity biomarkers for irinotecan- and oxaliplatin-containing chemotherapy in colorectal cancer. Cancer Chemother. Pharmacol. 71 (6 ), 1463–1472. 10.1007/s00280-013-2145-6 23543295
Daniel Z. H. Thaned C. C. O. Dhayan P. T. Hui T. A. T. Eunice D. K. Wan Q. C. (2023). Systematic review and meta-analysis of the influence of genetic variation on ototoxicity in platinum-based chemotherapy. Otolaryngol. Head. Neck Surg. 168 (6 ), 1324–1337. 10.1002/ohn.222 36802061
Das B. Antoon R. Tsuchida R. Lotfi S. Morozova O. Farhat W. (2008). Squalene selectively protects mouse bone marrow progenitors against cisplatin and carboplatin-induced cytotoxicity in vivo without protecting tumor growth. Neoplasia (New York, NY) 10 (10 ), 1105–1119. 10.1593/neo.08466
Daviet S. Couvé-Privat S. Gros L. Shinozuka K. Ide H. Saparbaev M. (2007). Major oxidative products of cytosine are substrates for the nucleotide incision repair pathway. DNA repair 6 (1 ), 8–18. 10.1016/j.dnarep.2006.08.001 16978929
Deng J. H. Deng J. Shi D. H. Ouyang X. N. Niu P. G. (2015). Clinical outcome of cisplatin-based chemotherapy is associated with the polymorphisms of GSTP1 and XRCC1 in advanced non-small cell lung cancer patients. Clin. Transl. Oncol. 17 (9 ), 720–726. 10.1007/s12094-015-1299-6 26033426
De Troia B. Dalu D. Filipazzi V. Isabella L. Tosca N. Ferrario S. (2019). ABCB1 c.3435C>T polymorphism is associated with platinum toxicity: a preliminary study. Cancer Chemother. Pharmacol. 83 (4 ), 803–808. 10.1007/s00280-019-03794-6 30796464
Ding-Wu S. Lynn M. P. Matthew D. H. Michael M. G. (2012). Cisplatin resistance: a cellular self-defense mechanism resulting from multiple epigenetic and genetic changes. Pharmacol. Rev. 64 (3 ), 706–721. 10.1124/pr.111.005637 22659329
Dumont P. Leu J. I. Della Pietra A. C. 3rd George D. L. Murphy M. (2003). The codon 72 polymorphic variants of p53 have markedly different apoptotic potential. Nat. Genet. 33 (3 ), 357–365. 10.1038/ng1093 12567188
Erčulj N. Kovač V. Hmeljak J. Dolžan V. (2012). The influence of platinum pathway polymorphisms on the outcome in patients with malignant mesothelioma. Ann. Oncol. 23 (4 ), 961–967. 10.1093/annonc/mdr324 21765044
Fang C. Li X. P. Gong W. J. Wu N. Y. Tang J. Yin J. Y. (2017). Age-related common miRNA polymorphism associated with severe toxicity in lung cancer patients treated with platinum-based chemotherapy. Clin. Exp. Pharmacol. Physiology 44 , 21–29. 10.1111/1440-1681.12704
Felipe Antonio de Oliveira G. Edilene Santos dA. Edenir Inez P. (2022). Insights on variant analysis in silico tools for pathogenicity prediction. Front. Genet. 13 , 1010327. 10.3389/fgene.2022.1010327 36568376
Ferracini A. C. Lopes-Aguiar L. Lourenço G. J. Yoshida A. Lima C. S. P. Sarian L. O. (2021). GSTP1 and ABCB1 polymorphisms predicting toxicities and clinical management on carboplatin and paclitaxel-based chemotherapy in ovarian cancer. Clin. Transl. Sci. 14 (2 ), 720–728. 10.1111/cts.12937 33326171
Fisher M. D. D’Orazio A. (2000). Phase II and III trials: comparison of four chemotherapy regimens in advanced non small-cell lung cancer (ECOG 1594). Clin. Lung Cancer 2 (1 ), 21–22. 10.1016/s1525-7304(11)70620-9 14731332
Fulda S. Debatin K. M. (2006). Extrinsic versus intrinsic apoptosis pathways in anticancer chemotherapy. Oncogene 25 (34 ), 4798–4811. 10.1038/sj.onc.1209608 16892092
Giovanna D. Massimo B. (2019). Platinum resistance in ovarian cancer: role of DNA repair. Cancers (Basel) 11 (1 ), 119. 10.3390/cancers11010119 30669514
Giovannetti E. Pacetti P. Reni M. Leon L. G. Mambrini A. Vasile E. (2011). Association between DNA-repair polymorphisms and survival in pancreatic cancer patients treated with combination chemotherapy. Pharmacogenomics 12 (12 ), 1641–1652. 10.2217/pgs.11.109 22026922
Giuliano C. (2012). Membrane transporters as mediators of Cisplatin effects and side effects. Sci. (Cairo). 2012 , 473829. 10.6064/2012/473829
Go R. S. Adjei A. A. (1999). Review of the comparative pharmacology and clinical activity of cisplatin and carboplatin. J. Clin. Oncol. 17 (1 ), 409–422. 10.1200/JCO.1999.17.1.409 10458260
Gong W. J. Ma L. Y. Hu L. Lv Y. N. Huang H. Xu J. Q. (2019). STAT3 rs4796793 contributes to lung cancer risk and clinical outcomes of platinum-based chemotherapy. Int. J. Clin. Oncol. 24 (5 ), 476–484. 10.1007/s10147-018-01386-7 30689078
Gong W. J. Peng J. B. Yin J. Y. Li X. P. Zheng W. Xiao L. (2017). Association between well-characterized lung cancer lncRNA polymorphisms and platinum-based chemotherapy toxicity in Chinese patients with lung cancer. Acta Pharmacol. Sin. 38 (4 ), 581–590. 10.1038/aps.2016.164 28260796
Goričar K. Kovač V. Dolžan V. (2014). Polymorphisms in translesion polymerase genes influence treatment outcome in malignant mesothelioma. Pharmacogenomics 15 (7 ), 941–950. 10.2217/pgs.14.14 24956248
Gréen H. Hasmats J. Kupershmidt I. Edsgärd D. De Petris L. Lewensohn R. (2016). Using whole-exome sequencing to identify genetic markers for carboplatin and gemcitabine-induced toxicities. Clin. Cancer Res. 22 (2 ), 366–373. 10.1158/1078-0432.CCR-15-0964 26378035
Gu S. Wu Q. Zhao X. Wu W. Gao Z. Tan X. (2012). Association of CASP3 polymorphism with hematologic toxicity in patients with advanced non-small-cell lung carcinoma treated with platinum-based chemotherapy. Cancer Sci. 103 (8 ), 1451–1459. 10.1111/j.1349-7006.2012.02323.x 22568453
Guo D. Zhou Y. Guo Z. Gong J. Wei Y. Zhu W. (2016). Association of common polymorphisms in p53 and mdm2 with platinum-related grade iii/iv toxicities in Chinese advanced lung adenocarcinoma patients. Int. J. Clin. Exp. Med. 9 (9 ), 18410–18418.
Han B. Gao G. Wu W. Gao Z. Zhao X. Li L. (2011). Association of ABCC2 polymorphisms with platinum-based chemotherapy response and severe toxicity in non-small cell lung cancer patients. Lung Cancer 72 (2 ), 238–243. 10.1016/j.lungcan.2010.09.001 20943283
Han J. Y. Lim H. S. Yoo Y. K. Shin E. S. Park Y. H. Lee S. Y. (2007). Associations of ABCB1, ABCC2, and ABCG2 polymorphisms with irinotecan-pharmacokinetics and clinical outcome in patients with advanced non-small cell lung cancer. Cancer 110 (1 ), 138–147. 10.1002/cncr.22760 17534875
Hartmann J. T. Lipp H. P. (2003). Toxicity of platinum compounds. Expert Opin. Pharmacother. 4 (6 ), 889–901. 10.1517/14656566.4.6.889 12783586
Hilary S. Mohamad Ayub Khan S. Md Asiful I. Shing C. T. (2024). Genetic variants associated with response to platinum-based chemotherapy in non-small cell lung cancer patients: a field synopsis and meta-analysis. Br. J. Biomed. Sci. 81 , 11835. 10.3389/bjbs.2024.11835 38450253
Hoffmeyer S. Burk O. von Richter O. Arnold H. P. Brockmöller J. Johne A. (2000). Functional polymorphisms of the human multidrug-resistance gene: multiple sequence variations and correlation of one allele with P-glycoprotein expression and activity in vivo . Proc. Natl. Acad. Sci. U. S. A. 97 (7 ), 3473–3478. 10.1073/pnas.050585397 10716719
Hu L. Chen S. H. Lv Q. L. Sun B. Qu Q. Qin C. Z. (2016). Clinical significance of long non-coding RNA CASC8 rs10505477 polymorphism in lung cancer susceptibility, platinum-based chemotherapy response, and toxicity. Int. J. Environ. Res. Public Health 13 (6 ), 545. 10.3390/ijerph13060545 27249003
Huang K. Luo A. Li X. Li S. Wang S. (2015). Chemotherapy-induced neutropenia during adjuvant treatment for cervical cancer patients: development and validation of a prediction model. Int. J. Clin. Exp. Med. 8 (7 ), 10835–10844.26379877
Isla D. Sarries C. Rosell R. Alonso G. Domine M. Taron M. (2004). Single nucleotide polymorphisms and outcome in docetaxel–cisplatin-treated advanced non-small-cell lung cancer. Ann. Oncol. 15 (8 ), 1194–1203. 10.1093/annonc/mdh319 15277258
Iwata K. Aizawa K. Kamitsu S. Jingami S. Fukunaga E. Yoshida M. (2012). Effects of genetic variants in SLC22A2 organic cation transporter 2 and SLC47A1 multidrug and toxin extrusion 1 transporter on cisplatin-induced adverse events. Clin. Exp. Nephrol. 16 (6 ), 843–851. 10.1007/s10157-012-0638-y 22569819
Jana S. Mariangela S. Cristina R.-S. Colin S. Arjan F. T. Wim V. (2018). Base and nucleotide excision repair facilitate resolution of platinum drugs-induced transcription blockage. Nucleic Acids Res. 46 (18 ), 9537–9549. 10.1093/nar/gky764 30137419
Jia M. Zhu M. Wang M. Sun M. Qian J. Ding F. (2016). Genetic variants of GADD45A, GADD45B and MAPK14 predict platinum-based chemotherapy-induced toxicities in Chinese patients with non-small cell lung cancer. Oncotarget 7 (18 ), 25291–25303. 10.18632/oncotarget.8052 26993769
Jorgensen A. L. Williamson P. R. (2008). Methodological quality of pharmacogenetic studies: issues of concern. Statistics Med. 27 (30 ), 6547–6569. 10.1002/sim.3420
Kalikaki A. Voutsina A. Koutsopoulos A. Papadaki C. Sfakianaki M. Yachnakis E. (2015). ERCC1 SNPs as potential predictive biomarkers in non-small cell lung cancer patients treated with platinum-based chemotherapy. Cancer Investig. 33 (4 ), 107–113. 10.3109/07357907.2014.1001897 25647444
Kanazawa K. Yokouchi H. Wang X. Ishida T. Fujita Y. Fujiuchi S. (2014). Phase II trial of carboplatin and pemetrexed as first-line chemotherapy for non-squamous non-small cell lung cancer, and correlation between the efficacy/toxicity and genetic polymorphisms associated with pemetrexed metabolism: hokkaido Lung Cancer Clinical Study Group Trial (HOT) 0902. Cancer Chemother. Pharmacol. 74 (6 ), 1149–1157. 10.1007/s00280-014-2589-3 25294632
Khrunin A. V. Moisseev A. Gorbunova V. Limborska S. (2010). Genetic polymorphisms and the efficacy and toxicity of cisplatin-based chemotherapy in ovarian cancer patients. Pharmacogenomics J. 10 (1 ), 54–61. 10.1038/tpj.2009.45 19786980
Kim H. S. Kim M. K. Chung H. H. Kim J. W. Park N. H. Song Y. S. (2009). Genetic polymorphisms affecting clinical outcomes in epithelial ovarian cancer patients treated with taxanes and platinum compounds: a Korean population-based study. Gynecol. Oncol. 113 (2 ), 264–269. 10.1016/j.ygyno.2009.01.002 19203783
Kim R. B. Leake B. F. Choo E. F. Dresser G. K. Kubba S. V. Schwarz U. I. (2001). Identification of functionally variant MDR1 alleles among European Americans and African Americans. Clin. Pharmacol. Ther. 70 (2 ), 189–199. 10.1067/mcp.2001.117412 11503014
Kim W. Cho Y. A. Kim D. C. Lee K. E. (2022). Association between genetic polymorphism of GSTP1 and toxicities in patients receiving platinum-based chemotherapy: a systematic review and meta-analysis. Pharm. (Basel) 15 (4 ), 439. 10.3390/ph15040439
Kimcurran V. Zhou C. Schmid-Bindert G. Shengxiang R. Zhou S. Zhang L. (2011). Lack of correlation between ERCC1 (C8092A) single nucleotide polymorphism and efficacy/toxicity of platinum based chemotherapy in Chinese patients with advanced non-small cell lung cancer. Adv. Med. Sci. 56 (1 ), 30–38. 10.2478/v10039-011-0013-3 21536539
Kumpiro S. Sriuranpong V. Areepium N. (2016). Impact of the copper transporter protein 1 (CTR1) polymorphism on adverse events among advanced NonSmall cell lung cancer patients treated with a carboplatin/gemcitabine regimen. Asian Pac. J. cancer Prev. APJCP 17 (9 ), 4391–4394.27797249
Lambrechts S. Lambrechts D. Despierre E. Van Nieuwenhuysen E. Smeets D. Debruyne P. R. (2015). Genetic variability in drug transport, metabolism or DNA repair affecting toxicity of chemotherapy in ovarian cancer. Bmc Pharmacol. and Toxicol. 16 , 2. 10.1186/s40360-015-0001-5
Lavanderos M. A. Cayún J. P. Roco Á. Sandoval C. Cerpa L. Rubilar J. C. (2019). Association study among candidate genetic polymorphisms and chemotherapy-related severe toxicity in testicular cancer patients. Front. Pharmacol. 10 , 206. 10.3389/fphar.2019.00206 30914949
Lee K.-H. Chang H. J. Han S.-W. Oh D.-Y. Im S.-A. Bang Y.-J. (2013). Pharmacogenetic analysis of adjuvant FOLFOX for Korean patients with colon cancer. Cancer Chemother. Pharmacol. 71 (4 ), 843–851. 10.1007/s00280-013-2075-3 23314736
Leusink M. Onland-Moret N. C. de Bakker P. I. de Boer A. Maitland-van der Zee A. H. (2016). Seventeen years of statin pharmacogenetics: a systematic review. Pharmacogenomics 17 (2 ), 163–180. 10.2217/pgs.15.158 26670324
Li A. Meyre D. (2013). Challenges in reproducibility of genetic association studies: lessons learned from the obesity field. Int. J. Obes. 37 (4 ), 559–567. 10.1038/ijo.2012.82
Li X. Shao M. Wang S. Zhao X. Chen H. Qian J. (2014). Heterozygote advantage of methylenetetrahydrofolate reductase polymorphisms on clinical outcomes in advanced non-small cell lung cancer (NSCLC) patients treated with platinum-based chemotherapy. Tumor Biol. 35 (11 ), 11159–11170. 10.1007/s13277-014-2427-6
Li Y. Q. Zhang X. Y. Chen J. Yin J. Y. Li X. P. (2018). ATP7B rs9535826 is associated with gastrointestinal toxicity of platinum-based chemotherapy in nonsmall cell lung cancer patients. J. Cancer Res. Ther. 14 (4 ), 881–886. 10.4103/jcrt.JCRT_890_17 29970670
Liblab S. Vusuratana A. Areepium N. (2020). ERCC1, XRCC1, and GSTP1 polymorphisms and treatment outcomes of advanced epithelial ovarian cancer patients treated with platinum-based chemotherapy. Asian Pac. J. cancer Prev. APJCP 21 (7 ), 1925–1929. 10.31557/APJCP.2020.21.7.1925 32711417
Little J. Higgins J. P. Ioannidis J. P. Moher D. Gagnon F. von Elm E. (2009). STrengthening the REporting of genetic association studies (STREGA): an extension of the STROBE statement. PLoS Med. 6 (2 ), e22. 10.1371/journal.pmed.1000022 19192942
Liu D. Xu W. Ding X. Yang Y. Lu Y. Fei K. (2017a). Caspase 8 polymorphisms contribute to the prognosis of advanced lung adenocarcinoma patients after platinum-based chemotherapy. Cancer Biol. Ther. 18 (12 ), 948–957. 10.1080/15384047.2016.1276128 28278082
Liu J. Y. Qian C. Y. Gao Y. F. Chen J. Zhou H. H. Yin J. Y. (2017b). Association between DNA mismatch repair gene polymorphisms and platinum-based chemotherapy toxicity in non-small cell lung cancer patients. Chin. J. Cancer 36 (1 ), 12. 10.1186/s40880-016-0175-2 28093084
Low S. K. Chung S. Takahashi A. Zembutsu H. Mushiroda T. Kubo M. (2013). Genome-wide association study of chemotherapeutic agent-induced severe neutropenia/leucopenia for patients in Biobank Japan. Cancer Sci. 104 (8 ), 1074–1082. 10.1111/cas.12186 23648065
Low S. K. Takahashi A. Mushiroda T. Kubo M. (2014). Genome-wide association study: a useful tool to identify common genetic variants associated with drug toxicity and efficacy in cancer pharmacogenomics. Clin. cancer Res. 20 (10 ), 2541–2552. 10.1158/1078-0432.CCR-13-2755 24831277
Ludovini V. Floriani I. Pistola L. Minotti V. Meacci M. Chiari R. (2011). Association of cytidine deaminase and xeroderma pigmentosum group D polymorphisms with response, toxicity, and survival in cisplatin/gemcitabine-treated advanced non-small cell lung cancer patients. J. Thorac. Oncol. 6 (12 ), 2018–2026. 10.1097/JTO.0b013e3182307e1f 22052224
Lv F. Ma Y. Zhang Y. Li Z. (2018). Relationship between GSTP1 rs1695 gene polymorphism and myelosuppression induced by platinum-based drugs: a meta-analysis. Int. J. Biol. markers 33 (4 ), 364–371. 10.1177/1724600818792897 30238837
Marsh S. (2006). Taxane pharmacogenetics. Pers. Med. 3 (1 ), 33–43. 10.2217/17410541.3.1.33
Marsh S. Paul J. King C. R. Gifford G. McLeod H. L. Brown R. (2007). Pharmacogenetic assessment of toxicity and outcome after platinum plus taxane chemotherapy in ovarian cancer: the scottish randomised trial in ovarian cancer. J. Clin. Oncol. 25 (29 ), 4528–4535. 10.1200/JCO.2006.10.4752 17925548
Matullo G. Palli D. Peluso M. Guarrera S. Carturan S. Celentano E. (2001). XRCC1, XRCC3, XPD gene polymorphisms, smoking and (32)P-DNA adducts in a sample of healthy subjects. Carcinogenesis 22 (9 ), 1437–1445. 10.1093/carcin/22.9.1437 11532866
Meyer zu Schwabedissen H. E. Jedlitschky G. Gratz M. Haenisch S. Linnemann K. Fusch C. (2005). Variable expression of MRP2 (ABCC2) in human placenta: influence of gestational age and cellular differentiation. Drug metabolism Dispos. Biol. fate Chem. 33 (7 ), 896–904. 10.1124/dmd.104.003335
Moriya Y. Nakamura T. Horinouchi M. Sakaeda T. Tamura T. Aoyama N. (2002). Effects of polymorphisms of MDR1, MRP1, and MRP2 genes on their mRNA expression levels in duodenal enterocytes of healthy Japanese subjects. Biol. and Pharm. Bull. 25 (10 ), 1356–1359. 10.1248/bpb.25.1356 12392094
Moyer A. M. Salavaggione O. E. Wu T. Y. Moon I. Eckloff B. W. Hildebrandt M. A. (2008). Glutathione s-transferase p1: gene sequence variation and functional genomic studies. Cancer Res. 68 (12 ), 4791–4801. 10.1158/0008-5472.CAN-07-6724 18559526
Nairuz T. Bushra Y. U. Kabir Y. (2021). Effect of XPD and TP53 gene polymorphisms on the risk of platinum-based chemotherapy induced toxicity in Bangladeshi lung cancer patients. Asian Pac. J. cancer Prev. APJCP 22 (12 ), 3809–3815. 10.31557/APJCP.2021.22.12.3809 34967559
Nomura H. Tsuji D. Demachi K. Mochizuki N. Matsuzawa H. Yano T. (2020). ABCB1 and ABCC2 genetic polymorphism as risk factors for neutropenia in esophageal cancer patients treated with docetaxel, cisplatin, and 5-fluorouracil chemotherapy. Cancer Chemother. Pharmacol. 86 (2 ), 315–324. 10.1007/s00280-020-04118-9 32748110
O’Donnell P. H. Dolan M. E. (2009). Cancer pharmacoethnicity: ethnic differences in susceptibility to the effects of chemotherapy. Clin. cancer Res. 15 (15 ), 4806–4814. 10.1158/1078-0432.CCR-09-0344 19622575
Oun R. Moussa Y. E. Wheate N. J. (2018). The side effects of platinum-based chemotherapy drugs: a review for chemists. Dalton Trans. Camb. Engl. 2003 47 (19 ), 6645–6653. 10.1039/c8dt00838h
Ouyang Z. Peng D. Dhakal D. P. (2013). Risk factors for hematological toxicity of chemotherapy for bone and soft tissue sarcoma. Oncol. Lett. 5 (5 ), 1736–1740. 10.3892/ol.2013.1234 23760066
Page M. J. McKenzie J. E. Bossuyt P. M. Boutron I. Hoffmann T. C. Mulrow C. D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ Clin. Res. ed 372 , n71. 10.1136/bmj.n71
Pemble S. Schroeder K. R. Spencer S. R. Meyer D. J. Hallier E. Bolt H. M. (1994). Human glutathione S-transferase theta (GSTT1): cDNA cloning and the characterization of a genetic polymorphism. Biochem. J. 300 (Pt 1 ), 271–276. 10.1042/bj3000271 8198545
Peng J. Yang L. X. Zhao X. Y. Gao Z. Q. Yang J. Wu W. T. (2013). VCP gene variation predicts outcome of advanced non-small-cell lung cancer platinum-based chemotherapy. Tumor Biol. 34 (2 ), 953–961. 10.1007/s13277-012-0631-9
Peng Y. Li Z. Zhang S. Xiong Y. Cun Y. Qian C. (2014). Association of DNA base excision repair genes (OGG1, APE1 and XRCC1) polymorphisms with outcome to platinum-based chemotherapy in advanced nonsmall-cell lung cancer patients. Int. J. Cancer 135 (11 ), 2687–2696. 10.1002/ijc.28892 24729390
Prestayko A. W. D'Aoust J. C. Issell B. F. Crooke S. T. (1979). Cisplatin (cis-diamminedichloroplatinum II). Cancer Treat. Rev. 6 (1 ), 17–39. 10.1016/s0305-7372(79)80057-2 378370
Qian C. Y. Zheng Y. Wang Y. Chen J. Liu J. Y. Zhou H. H. (2016). Associations of genetic polymorphisms of the transporters organic cation transporter 2 (OCT2), multidrug and toxin extrusion 1 (MATE1), and ATP-binding cassette subfamily C member 2 (ABCC2) with platinum-based chemotherapy response and toxicity in non-small cell lung cancer patients. Chin. J. cancer 35 (1 ), 85. 10.1186/s40880-016-0145-8 27590272
Qian J. Liu H. Gu S. Wu Q. Zhao X. Wu W. (2015). Genetic variants of the MDM2 gene are predictive of treatment-related toxicities and overall survival in patients with advanced NSCLC. Clin. Lung Cancer 16 (5 ), e37–e53. 10.1016/j.cllc.2015.02.001 25818095
Qian J. Qu H. Q. Yang L. Yin M. Wang Q. Gu S. (2012). Association between CASP8 and CASP10 polymorphisms and toxicity outcomes with platinum-based chemotherapy in Chinese patients with non-small cell lung cancer. Oncologist 17 (12 ), 1551–1561. 10.1634/theoncologist.2011-0419 22843554
Qihai S. Zhengyang H. Xing J. Yunyi B. Jiaqi L. Huan Z. (2023). The genomic signature of resistance to platinum-containing neoadjuvant therapy based on single-cell data. Cell Biosci. 13 (1 ), 103. 10.1186/s13578-023-01061-z 37291676
R C. S. P W. J. A A. F. (2000). Glutathione S-transferase: genetics and role in toxicology. Toxicol. Lett. 112-113 , 357–363. 10.1016/s0378-4274(99)00230-1 10720752
Rabik C. A. Dolan M. E. (2007). Molecular mechanisms of resistance and toxicity associated with platinating agents. Cancer Treat. Rev. 33 (1 ), 9–23. 10.1016/j.ctrv.2006.09.006 17084534
Rodriguez J. Boni V. Hernández A. Bitarte N. Zarate R. Ponz-Sarvisé M. (2011). Association of RRM1 -37A>C polymorphism with clinical outcome in colorectal cancer patients treated with gemcitabine-based chemotherapy. Eur. J. cancer 47 (6 ), 839–847. 10.1016/j.ejca.2010.11.032 21220199
Ruzzo A. Graziano F. Galli F. Giacomini E. Floriani I. Galli F. (2014). Genetic markers for toxicity of adjuvant oxaliplatin and fluoropyrimidines in the phase III TOSCA trial in high-risk colon cancer patients. Sci. Rep. 4 , 6828. 10.1038/srep06828 25370899
Saito Y. A. Talley N. J. de Andrade M. Petersen G. M. (2006). Case-control genetic association studies in gastrointestinal disease: review and recommendations. Am. J. gastroenterology 101 (6 ), 1379–1389. 10.1111/j.1572-0241.2006.00587.x
Schiller J. H. Harrington D. Belani C. P. Langer C. Sandler A. Krook J. (2002). Comparison of four chemotherapy regimens for advanced non-small-cell lung cancer. N. Engl. J. Med. 346 (2 ), 92–98. 10.1056/NEJMoa011954 11784875
Senk B. Goricar K. Kovac V. Dolzan V. Franko A. (2019). Genetic polymorphisms in aquaporin 1 as risk factors for malignant mesothelioma and biomarkers of response to cisplatin treatment. Radiology Oncol. 53 (1 ), 96–104. 10.2478/raon-2019-0009
Seo B. G. Kwon H. C. Oh S. Y. Lee S. Kim S. G. Kim S. H. (2009). Comprehensive analysis of excision repair complementation group 1, glutathione S-transferase, thymidylate synthase and uridine diphosphate glucuronosyl transferase 1A1 polymorphisms predictive for treatment outcome in patients with advanced gastric cancer treated with FOLFOX or FOLFIRI. Oncol. Rep. 22 (1 ), 127–136. 10.3892/or_00000415 19513514
Shaloam D. Paul B. T. (2014). Cisplatin in cancer therapy: molecular mechanisms of action. Eur. J. Pharmacol. 740 , 364–378. 10.1016/j.ejphar.2014.07.025 25058905
Shao M. Jin B. Niu Y. Ye J. Lu D. Han B. (2014). Association of POLK polymorphisms with platinum-based chemotherapy response and severe toxicity in non-small cell lung cancer patients. Cell Biochem. biophysics 70 (2 ), 1227–1237. 10.1007/s12013-014-0046-x
Song X. Wang S. Hong X. Li X. Zhao X. Huai C. (2017). Single nucleotide polymorphisms of nucleotide excision repair pathway are significantly associated with outcomes of platinum-based chemotherapy in lung cancer. Sci. Rep. 7 (1 ), 11785. 10.1038/s41598-017-08257-7 28924235
Sun C. Zhang Z. Qie J. Wang Y. Qian J. Wang J. (2018). Genetic polymorphism of SLC31A1 is associated with clinical outcomes of platinum-based chemotherapy in non-small-cell lung cancer patients through modulating microRNA-mediated regulation. Oncotarget 9 (35 ), 23860–23877. 10.18632/oncotarget.24794 29844858
Svedberg A. Björn N. Sigurgeirsson B. Pradhananga S. Brandén E. Koyi H. (2020). Genetic association of gemcitabine/carboplatin-induced leukopenia and neutropenia in non-small cell lung cancer patients using whole-exome sequencing. Lung Cancer 147 , 106–114. 10.1016/j.lungcan.2020.07.005 32683206
Tan X. Wu Q. Cai Y. Zhao X. Wang S. Gao Z. (2014). Novel association between CD74 polymorphisms and hematologic toxicity in patients with nsclc after platinum-based chemotherapy. Clin. Lung Cancer 15 (1 ), 67–78. 10.1016/j.cllc.2013.08.006 24220096
The Vinh H. Orlando D. S. (2010). Translesion DNA synthesis polymerases in DNA interstrand crosslink repair. Environ. Mol. Mutagen 51 (6 ), 552–566. 10.1002/em.20573 20658647
Tibaldi C. Giovannetti E. Vasile E. Mey V. Laan A. C. Nannizzi S. (2008). Correlation of CDA, ERCC1, and XPD polymorphisms with response and survival in gemcitabine/cisplatin-treated advanced non-small cell lung cancer patients. Clin. Cancer Res. 14 (6 ), 1797–1803. 10.1158/1078-0432.CCR-07-1364 18347182
van der Put N. M. Gabreëls F. Stevens E. M. Smeitink J. A. Trijbels F. J. Eskes T. K. (1998). A second common mutation in the methylenetetrahydrofolate reductase gene: an additional risk factor for neural-tube defects? Am. J. Hum. Genet. 62 (5 ), 1044–1051. 10.1086/301825 9545395
Vodicka P. Kumar R. Stetina R. Sanyal S. Soucek P. Haufroid V. (2004). Genetic polymorphisms in DNA repair genes and possible links with DNA repair rates, chromosomal aberrations and single-strand breaks in DNA. Carcinogenesis 25 (5 ), 757–763. 10.1093/carcin/bgh064 14729591
Walia H. K. Singh N. Sharma S. (2021). GSTP1 Ile <i>105</i> Val polymorphism among North Indian lung cancer patients treated using monotherapy and poly-pharmacy. Hum. Exp. Toxicol. 40 (12_Suppl. l ), S739–S752. 10.1177/09603271211059496 34780261
Walia H. K. Singh N. Sharma S. (2022). MTHFR polymorphism as a predictive biomarker for gastrointestinal and hematological toxicity in North Indian adenocarcinoma patients. J. Chemother. 34 (5 ), 326–340. 10.1080/1120009X.2021.1997008 34730065
Wang L. Sun C. Li X. Mao C. Qian J. Wang J. (2021). A pharmacogenetics study of platinum-based chemotherapy in lung cancer: ABCG2 polymorphism and its genetic interaction with SLC31A1 are associated with response and survival. J. Cancer 12 (5 ), 1270–1283. 10.7150/jca.51621 33531973
Wang S. Song X. Li X. Zhao X. Chen H. Wang J. (2016). RICTOR polymorphisms affect efficiency of platinum-based chemotherapy in Chinese non-small-cell lung cancer patients. Pharmacogenomics 17 (15 ), 1637–1647. 10.2217/pgs-2016-0070 27676404
Wang X. Wang Y. Z. Ma K. W. Chen X. Li W. (2014). MDM2 rs2279744 and TP53 rs1042522 polymorphisms associated with etoposide- and cisplatin-induced grade III/IV neutropenia in Chinese extensive-stage small-cell lung cancer patients. Oncol. Res. Treat. 37 (4 ), 176–180. 10.1159/000360785 24732641
Wang Y. Probin V. Zhou D. (2006). Cancer therapy-induced residual bone marrow injury-Mechanisms of induction and implication for therapy. Curr. cancer Ther. Rev. 2 (3 ), 271–279. 10.2174/157339406777934717 19936034
Wang Y. Spitz M. R. Zhu Y. Dong Q. Shete S. Wu X. (2003). From genotype to phenotype: correlating XRCC1 polymorphisms with mutagen sensitivity. DNA repair 2 (8 ), 901–908. 10.1016/s1568-7864(03)00085-5 12893086
Wang Z. Xu B. Lin D. Tan W. Leaw S. Hong X. (2008). XRCC1 polymorphisms and severe toxicity in lung cancer patients treated with cisplatin-based chemotherapy in Chinese population. Lung Cancer 62 (1 ), 99–104. 10.1016/j.lungcan.2008.02.019 18400332
Watanabe A. Taniguchi M. Sasaki S. (2003). Induction chemotherapy with docetaxel, cisplatin, fluorouracil and l-leucovorin for locally advanced head and neck cancers: a modified regimen for Japanese patients. Anticancer Drugs 14 (10 ), 801–807. 10.1097/00001813-200311000-00005 14597874
Wilson D. M. 3rd Kim D. Berquist B. R. Sigurdson A. J. (2011). Variation in base excision repair capacity. Mutat. Res. 711 (1-2 ), 100–112. 10.1016/j.mrfmmm.2010.12.004 21167187
Wolfe K. J. Wickliffe J. K. Hill C. E. Paolini M. Ammenheuser M. M. Abdel-Rahman S. Z. (2007). Single nucleotide polymorphisms of the DNA repair gene XPD/ERCC2 alter mRNA expression. Pharmacogenet Genomics 17 (11 ), 897–905. 10.1097/FPC.0b013e3280115e63 18075460
Wood P. A. Hrushesky W. J. (1995). Cisplatin-associated anemia: an erythropoietin deficiency syndrome. J. Clin. investigation 95 (4 ), 1650–1659. 10.1172/JCI117840
Wu W. Zhang W. Qiao R. Chen D. Wang H. Wang Y. (2009). Association of XPD polymorphisms with severe toxicity in non-small cell lung cancer patients in a Chinese population. Clin. Cancer Res. 15 (11 ), 3889–3895. 10.1158/1078-0432.CCR-08-2715 19458053
Xu S. Wang Y. Roe B. Pearson W. R. (1998). Characterization of the human class Mu glutathione S-transferase gene cluster and the GSTM1 deletion. J. Biol. Chem. 273 (6 ), 3517–3527. 10.1074/jbc.273.6.3517 9452477
Xu W. Liu D. Yang Y. Ding X. Sun Y. Zhang B. (2016). Association of CHEK2 polymorphisms with the efficacy of platinum-based chemotherapy for advanced non-small-cell lung cancer in Chinese never-smoking women. J. Thorac. Dis. 8 (9 ), 2519–2529. 10.21037/jtd.2016.08.70 27747004
Xu X. Ren H. Zhou B. Zhao Y. Yuan R. Ma R. (2012). Prediction of copper transport protein 1 (CTR1) genotype on severe cisplatin induced toxicity in non-small cell lung cancer (NSCLC) patients. Lung Cancer 77 (2 ), 438–442. 10.1016/j.lungcan.2012.03.023 22516052
Ye J. Chu T. Li R. Niu Y. Jin B. Xia J. (2015). Pol zeta polymorphisms are associated with platinum based chemotherapy response and side effects among non-small cell lung cancer patients. Neoplasma 62 (5 ), 833–839. 10.4149/neo_2015_101 26278154
Yin J. Y. Li X. Li X. P. Xiao L. Zheng W. Chen J. (2016). Prediction models for platinum-based chemotherapy response and toxicity in advanced NSCLC patients. Cancer Lett. 377 (1 ), 65–73. 10.1016/j.canlet.2016.04.029 27126360
Yin J. Y. Meng X. G. Qian C. Y. Li X. P. Chen J. Zheng Y. (2015). Association of positively selected eIF3a polymorphisms with toxicity of platinum-based chemotherapy in NSCLC patients. Acta Pharmacol. Sin. 36 (3 ), 375–384. 10.1038/aps.2014.160 25732572
Yoshihama T. Fukunaga K. Hirasawa A. Nomura H. Akahane T. Kataoka F. (2018). GSTP1 rs1695 is associated with both hematological toxicity and prognosis of ovarian cancer treated with paclitaxel plus carboplatin combination chemotherapy: a comprehensive analysis using targeted resequencing of 100 pharmacogenes. Oncotarget 9 (51 ), 29789–29800. 10.18632/oncotarget.25712 30038720
Yu J. J. Lee K. B. Mu C. Li Q. Abernathy T. V. Bostick-Bruton F. (2000). Comparison of two human ovarian carcinoma cell lines (A2780/CP70 and MCAS) that are equally resistant to platinum, but differ at codon 118 of the ERCC1 gene. Int. J. Oncol. 16 (3 ), 555–560. 10.3892/ijo.16.3.555 10675489
Yuan Z. J. Zhou W. W. Liu W. Wu B. P. Zhao J. Wu W. (2015). Association of GSTP1 and RRM1 polymorphisms with the response and toxicity of gemcitabine-cisplatin combination chemotherapy in Chinese patients with non-small cell lung cancer. Asian Pac J. Cancer Prev. 16 (10 ), 4347–4351. 10.7314/apjcp.2015.16.10.4347 26028097
Zhan X. Wu W. Han B. Gao G. Qiao R. Lv J. (2012). Hsa-miR-196a2 functional SNP is associated with severe toxicity after platinum-based chemotherapy of advanced nonsmall cell lung cancer patients in a Chinese population. J. Clin. Laboratory Analysis 26 (6 ), 441–446. 10.1002/jcla.21544
Zhao X. Wang S. Wu J. Li X. Wang X. Gao Z. (2015). Association of TERT polymorphisms with clinical outcome of non-small cell lung cancer patients. PLoS ONE 10 (5 ), e0129232. 10.1371/journal.pone.0129232 26020272
Zhao X. Wang X. Wu W. Gao Z. Wu J. Garfield D. H. (2012). Matrix metalloproteinase-2 polymorphisms and clinical outcome of Chinese patients with nonsmall cell lung cancer treated with first-line, platinum-based chemotherapy. Cancer 118 (14 ), 3587–3598. 10.1002/cncr.26669 22072145
Zheng D. Chen Y. Gao C. Wei Y. Cao G. Lu N. (2014). Polymorphisms of p53 and MDM2 genes are associated with severe toxicities in patients with non-small cell lung cancer. Cancer Biol. Ther. 15 (11 ), 1542–1551. 10.4161/15384047.2014.956599 25482940
Zheng Y. Deng Z. Tang M. Cai P. (2021). Erythropoietin promoter polymorphism is associated with treatment efficacy and severe hematologic toxicity for platinum-based chemotherapy. Expert Opin. Drug Metabolism Toxicol. 17 (4 ), 495–502. 10.1080/17425255.2021.1879048
Zheng Y. Deng Z. Tang M. Xiao D. Cai P. (2020). Impact of genetic factors on platinum-induced gastrointestinal toxicity. Mutat. Res. Rev. Mutat. Res. 786 , 108324. 10.1016/j.mrrev.2020.108324 33339576
Zheng Y. Deng Z. Yin J. Wang S. Lu D. Wen X. (2017). The association of genetic variations in DNA repair pathways with severe toxicities in NSCLC patients undergoing platinum-based chemotherapy. Int. J. Cancer 141 (11 ), 2336–2347. 10.1002/ijc.30921 28791697
Zhu Y. Yang H. Chen Q. Lin J. Grossman H. B. Dinney C. P. (2008). Modulation of DNA damage/DNA repair capacity by XPC polymorphisms. DNA repair 7 (2 ), 141–148. 10.1016/j.dnarep.2007.08.006 17923445
Zolk O. (2012). Disposition of metformin: variability due to polymorphisms of organic cation transporters. Ann. Med. 44 (2 ), 119–129. 10.3109/07853890.2010.549144 21366511
Zolk O. Solbach T. F. König J. Fromm M. F. (2009). Functional characterization of the human organic cation transporter 2 variant p.270Ala>Ser. Drug metabolism Dispos. Biol. fate Chem. 37 (6 ), 1312–1318. 10.1124/dmd.108.023762
Zou T. Yin J. Zheng W. Xiao L. Tan L. Chen J. (2016). Rho GTPases: RAC1 polymorphisms affected platinum-based chemotherapy toxicity in lung cancer patients. Cancer Chemother. Pharmacol. 78 (2 ), 249–258. 10.1007/s00280-016-3072-0 27299748
