
==== Front
J Cancer Res Clin Oncol
J Cancer Res Clin Oncol
Journal of Cancer Research and Clinical Oncology
0171-5216
1432-1335
Springer Berlin Heidelberg Berlin/Heidelberg

5932
10.1007/s00432-024-05932-x
Research
Clinical characteristics of KRAS mutation subtypes in non-small cell lung cancer population in Xinjiang, China, and their impact on the prognosis of immunotherapy
Gu Guomin 1
Liu Chunling 1
Zhu Xiaodan 1
Yang Yan 1
Song Shuming 2
Zhao Yan 1
Sun Gang sung853219@126.com

34
1 grid.13394.3c 0000 0004 1799 3993 Department of Pulmonary Medicine, Affiliated Cancer Hospital of Xinjiang Medical University, No. 789 Suzhou East Street, Xincheng District, Urumqi, Xinjiang 830011 China
2 grid.13394.3c 0000 0004 1799 3993 Education and Research Management Office, Affiliated Cancer Hospital of Xinjiang Medical University, No. 789 Suzhou East Street, Xincheng District, Urumqi, Xinjiang 830011 China
3 grid.13394.3c 0000 0004 1799 3993 Department of Breast and Thyroid Surgery, Affiliated Cancer Hospital of Xinjiang Medical University, No. 789 Suzhou East Street, Xincheng District, Urumqi, Xinjiang 830011 China
4 Xinjiang Cancer Center/Key Laboratory of Oncology of Xinjiang Uyghur Autonomous Region, Urumqi, Xinjiang 830011 China
7 9 2024
7 9 2024
2024
150 9 4131 8 2024
25 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Purpose

Non-small cell lung cancer (NSCLC) is a highly fatal malignancy. The Kirsten rat sarcoma viral oncogene (KRAS) gene profoundly impacts patient prognosis. This study aims to explore the correlation between KRAS mutation subtypes, clinical data, and the impact of these subtypes on immunotherapy.

Materials and methods

Tumor samples from 269 NSCLC patients at the Affiliated Cancer Hospital of Xinjiang Medical University were analyzed. Patients received first- or second-line therapy without targeted therapy. Molecular and clinical data were used to analysis KRAS mutation subtypes and treatment outcomes.

Results

KRAS mutations predominantly included G12C, G12D, and G12V subtypes. TP53 had the highest mutation frequency among KRAS mutations, followed by MST1, STK11, and KMT2C. Gender differences were noted among KRAS mutation subtypes, with G12C and G12V mutations prevalent in males, while G12D mutations were less common among males. Smokers exhibited varied KRAS mutation subtypes, with G12C and G12V prevalent in smokers and G12D in nonsmokers. KRAS mutations were mainly in lung adenocarcinoma. TTF-1 and PD-L1 expression differed significantly among KRAS mutations. Patients with G12C and G12V mutations showed higher TMB levels and better immunotherapy outcomes compared to those without KRAS mutations. Conversely, patients with G12D mutations had poorer immunotherapy responses.

Conclusions

KRAS mutation subtypes exhibit distinct clinical and molecular characteristics and varying responses to immunotherapy. G12C and G12V mutations correlate with better immunotherapy outcomes, while G12D mutations are associated with poorer responses.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00432-024-05932-x.

Keywords

NSCLC
KRAS
Mutation
Immunotherapy
Prognosis
Key Laboratory of Oncology of Xinjiang Uyghur Autonomous RegionXJKLO-2023U009 Department of Science and Technology of Xinjiang Uygur Autonomous Region2022D14010 issue-copyright-statement© Springer-Verlag GmbH Germany, part of Springer Nature 2024
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pmcIntroduction

Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases, making up approximately 85% of diagnoses (Osta et al. 2019). In recent years, there have been significant advancements in the treatment of NSCLC, leading to a substantial decrease in mortality rates. This is primarily attributed to the utilization of targeted therapies based on various driver gene mutations such as EGFR, ALK, ROS1, MET, PIK3CA, RET, BRAF, as well as the approval of immune checkpoint inhibitors (either as monotherapy or in combination with chemotherapy) for patients lacking targetable driver mutations. While advancements in tumor genetic testing have revolutionized cancer diagnosis and treatment protocols, the prognosis of advanced NSCLC patients receiving second-line or subsequent treatment remains unsatisfactory. Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations have emerged as significant drivers in human cancers (Jordan et al. 2017). KRAS was one of the first human oncogenes discovered, shedding light on the molecular mechanisms underlying cancer development (Pylayeva-Gupta et al. 2011; Malumbres and Barbacid 2003). Analysis across regions reveals varying frequencies of KRAS mutations, with around 26.1% of Western lung adenocarcinoma (LUAD) patients and approximately 11.2% of Asian patients exhibiting such mutations (Dearden et al. 2013).

Located on chromosome 12p12.1, the human KRAS gene is prone to mutations, notably at the 12th position in NSCLC, including G12C, G12D, and G12V mutations. These alterations often correlate with poorer prognosis due to the molecular diversity observed in KRAS-mutated tumors, leading to differences in clinical outcomes among patients (Jancík et al. 2010; Yu et al. 2015; Scheffler et al. 2019). Despite over three decades of research, effective drugs targeting KRAS mutations have remained elusive. Consequently, standard treatment for advanced NSCLC patients with KRAS mutations typically involves chemotherapy (Ferrer et al. 2018).

However, recent developments in immunotherapy offer promising alternatives. While not all KRAS-mutant NSCLC tumors exhibit immune-resistant phenotypes, studies suggest that immune checkpoint inhibitors (ICIs) may enhance survival rates in subsets of KRAS-mutant patients compared to traditional treatments like docetaxel (Qin et al. 2024; Sun et al. 2024). Furthermore, correlations between KRAS mutation status and tumor mutational burden (TMB), PD-L1 expression, and T-cell infiltration in NSCLC highlight the potential of immunotherapy. High T-cell infiltration and TMB, often observed in smokers with KRAS mutations, suggest a favorable response to immunotherapy in KRAS-mutant NSCLC cases associated with smoking-related lung cancer (Liu et al. 2020a, b). These findings underscore the importance of exploring immunotherapeutic approaches tailored to KRAS-mutant NSCLC patients for improved clinical outcomes.

In numerous studies, patients with KRAS mutations have demonstrated positive responses to immunotherapy (Chen et al. 2024; O’Sullivan et al. 2023). For instance, in a study evaluating nivolumab in patients with KRAS-mutated NSCLC, response rates remained consistent regardless of KRAS status, indicating that KRAS might not independently influence efficacy, although KRAS-mutated cases exhibited higher PD-L1 expression levels (Passiglia et al. 2019). Similarly, a subgroup analysis of the CheckMate057 trial revealed that nivolumab monotherapy conferred greater overall survival (OS) benefits compared to docetaxel monotherapy in second-line treatment for patients with KRAS mutations (Borghaei et al. 2024). Additionally, findings from an OS analysis within the OAK study, a randomized phase III trial, suggested potential OS advantages with atezolizumab in patients with KRAS-mutated NSCLC (Christopoulos and Thomas 2017). Although overall KRAS mutations may not reliably predict patient prognosis, a nuanced examination of specific subtypes and their interactions with other genetic mutations could offer deeper insights into prognosis and guide subsequent immunotherapy strategies (Sun et al. 2024; Cao et al. 1990). Given the heterogeneous nature of NSCLC and the diverse molecular subtypes of KRAS mutations, comprehensive evaluation and classification of these subtypes are imperative in clinical management (Ye et al. 2024; Zhao et al. 2024). Presently, KRAS mutation subtypes are not regarded as independent predictors of ICI response.

Considering the variability in KRAS mutation subtypes, the predictive efficacy of immunotherapy may vary considerably. Therefore, this study meticulously categorized primary KRAS mutation subtypes and thoroughly analyzed their correlation with patients’ clinical data. The goal was to elucidate differences among mutation subtypes and uncover the underlying factors contributing to variations in immunotherapy outcomes across these subtypes.

Materials and methods

Patients and samples

In this study, from January 2017 to May 2023, we included a total of 269 patients who were tested for KRAS mutations. Among them, 140 patients had KRAS mutations, and the other 129 patients without KRAS mutations served as study controls. A retrospective review was conducted on these patients’ medical records, pathology data, molecular test results, survival status and evaluations of treatment effects. The follow-up period concluded on December 31, 2023. All participants provided informed consent, agreeing to provide their medical records and relevant data for research purposes in accordance with ethical standards. The study received approval from the committee of Affiliated Cancer Hospital of Xinjiang Medical University and adhered to the principles of the Helsinki Declaration, the approval number was K-2,022,040. The tumor stage was determined according to the 8th edition of the Tumor, Node, and Metastasis (TNM) criteria, the histological classification followed the latest standards set by the World Health Organization (WHO).

Targeted sequencing and bioinformatics analysis

In this study, we conducted high-throughput sequencing (NGS) on all samples to comprehensively understand the genomic variations in lung cancer patients. Different methods were employed to extract DNA depending on the sample type. For tissue and pleural fluid samples, we used the QIAamp DNA FFPE Tissue Kit from Qiagen, Germany, while peripheral blood samples utilized the QIAamp DNA Blood Mini Kit, also from Qiagen, Germany. cfDNA from plasma was extracted using the MagMAX™ Cell-Free DNA Isolation Kit from Life, USA. We estimated DNA concentration using the Qubit fluorometer and Qubit dsDNA High Sensitivity Assay Kit to ensure sufficient DNA yield for subsequent experiments. Subsequently, DNA library construction was performed using the MGIEasy Universal DNA Library Kit from MGI, China, followed by hybrid capture using the xGen Hybridization and Wash Kit from IDT, USA. Finally, paired-end sequencing with 2 × 100 bp reads was conducted on the MGISEQ-2000 platform, and the sequencing results were aligned to the human reference genome GRCh37/hg19 using BWA-MEM. SNVs and InDels were called using VarScan, and tumor mutation burden (TMB) was evaluated following the method described by Chalmers and colleagues to comprehensively understand the genetic variations in the samples.

Statistical analysis

Fisher’s test and Chi-squared test were employed to assess the significance of differences for categorical data, while the Kruskal-Wallis test was utilized for continuous data. P values were adjusted using the Benjamini and Hochberg (BH) procedure to control the false discovery rate (FDR). Survival curves were generated using the Kaplan-Meier method, and differences in survival curves were compared using the log-rank test. Co-mutations and mutually exclusive mutations were calculated using the Maftools R package. Statistical analysis and data visualization were performed using R software (version 4.0.1). A p-value < 0.05 was considered statistically significant.

Results

Clinical characteristics of patients with KRAS mutations

In this study, a total of 140 patients were identified with KRAS mutations. Among them, 53 patients had KRAS G12C mutations, 38 had KRAS G12D mutations, 19 had KRAS G12V mutations, and 30 had other KRAS mutation subtypes. The average age of our cohort was 65 years, with patients having a median age of 62 years at surgery, ranging from 32 to 81 years. Analysis of clinical data revealed that among all patients with available information, males exhibited a higher prevalence of KRAS mutations (63/140) compared to females (28/140). Specifically, among patients with KRAS mutation subtypes, KRAS G12C mutations were predominantly observed in males (male vs. female: 33 vs. 5), while KRAS G12D mutations were more common in females (male vs. female: 12 vs. 15). Additionally, patients with a history of smoking (51/140) were more likely to have KRAS mutations compared to those who had never smoked (39/140). Interestingly, the smoking status of patients with G12C mutations and G12D mutations showed opposing trends. Among patients with G12C mutations, there were more smokers (Ever vs. Never: 28:10), whereas among those with G12D mutations, more patients had never smoked (Ever vs. Never: 6:20). Furthermore, the majority of samples collected in this study were from patients with stage IV disease (61/140) and those receiving first-line treatment (52/140) (Table 1). Additional detailed clinical information can be found in Table 1 and Supplementary Table 1.

Table 1 Clinical characteristics of patients with KRAS mutations

characteristics	KRAS (n = 140)	G12C (N = 53)	G12D (N = 38)	G12V (N = 19)	Other (N = 30)	p	
Age (%)	< 65	46(32.9)	19 (35.8)	14 (36.8)	9 (47.4)	4 (13.3)	0.049	
>=65	45(32.1)	19 (35.8)	13 (34.2)	5 (26.3)	8 (26.7)	
NA	49(35.0)	15 (28.3)	11 (28.9)	5 (26.3)	18 (60.0)	
Gender (%)	Female	28(20.0)	5 (9.4)	15 (39.5)	4 (21.1)	4 (13.3)	< 0.001	
Male	63(45.0)	33 (62.3)	12 (31.6)	10 (52.6)	8 (26.7)	
NA	49(35.0)	15 (28.3)	11 (28.9)	5 (26.3)	18 (60.0)	
Smoking (%)	Ever	51(36.4)	28 (52.8)	6 (15.8)	9 (47.4)	8 (26.7)	< 0.001	
Never	39(27.9)	10 (18.9)	20 (52.6)	5 (26.3)	4 (13.3)	
NA	50(35.7)	15 (28.3)	12 (31.6)	5 (26.3)	18 (60.0)	
Stage (%)	I	7(5.0)	2 (3.8)	3 (7.9)	1 (5.3)	1 (3.3)	0.223	
II	5(3.6)	3 (5.7)	2 (5.3)	0 (0.0)	0 (0.0)	
III	15(10.7)	5 (9.4)	5 (13.2)	2 (10.5)	3 (10.0)	
IV	61(43.6)	28 (52.8)	16 (42.1)	10 (52.6)	7 (23.3)	
NA	52(37.1)	15 (28.3)	12 (31.6)	6 (31.6)	19 (63.3)	
Number.of.treatment.lines (%)	> 1	11(7.9)	3 (5.7)	4 (10.5)	3 (15.8)	1 (3.3)	0.013	
1	52(37.1)	27 (50.9)	14 (36.8)	7 (36.8)	4 (13.3)	
NA	77(55.0)	23 (43.4)	20 (52.6)	9 (47.4)	25 (83.3)	

Molecular characteristics of patients with KRAS mutations

In this study, all 140 samples with KRAS mutations underwent NGS testing using a cancer-related gene panel. Among them, 90 samples were analyzed using a 616-gene panel sequencing approach, while the remaining 50 patients underwent testing with a 14-gene panel targeting lung cancer-related drug genes. The predominant KRAS mutation subtype observed was G12C, constituting 38.6% (54/140) of all KRAS mutations. The distribution of other major KRAS mutation subtypes were as follows: G12D, 27.1% (38/140); G12V, 14.0% (19/140); and G12A, 6.4% (9/140) (Fig. 1A). Among the 90 samples analyzed using the 616-gene panel, TP53 exhibited the highest mutation frequency in the KRAS mutation group, followed by MST1, STK11, and KMT2C, with mutation frequencies of 56%, 13%, 12%, and 11%, respectively. Conversely, the mutation frequency of EGFR was relatively low at only 9% (Fig. 1B).

Fig. 1 The summary of the KRAS mutation. A. Landscape of somatic mutations identified in the 90 NSCLC patients with KRAS mutation, the top 30 genes with mutation frequency are shown on the graph. B. Pie charts of NSCLC patients with KRAS mutations. Pie charts showing the proportions of different KRAS mutation subtypes

Covariation analysis revealed that the most co-mutated genes with KRAS G12C were HGF, PTEN, INHBA, and PIK3CA (Fig. 2A). For KRAS G12D, the co-mutated gene was primarily STK11 (Fig. 2B), while for KRAS G12V, c11orf30 and ETV6 were the co-mutated genes (Fig. 2C). Notably, there were no mutually exclusive genes for KRAS G12C, G12D, or G12V. However, when considering the overall co-mutation status of KRAS mutations, it was observed that KRAS co-mutated with STK11 but was mutually exclusive with SETD2 and EGFR mutations (Fig. 2D).

Fig. 2 Heatmap of exclusivity and co-occurrence analysis. A. Analysis of genes with co-mutations or mutually exclusive mutations with KRAS mutation. B. Analysis of genes with co-mutations or mutually exclusive mutations with KRAS G12C mutation. C. Analysis of genes with co-mutations or mutually exclusive mutations with KRAS G12D mutations. C. Analysis of genes with co-mutations or mutually exclusive mutations with KRAS G12V mutations

Correlation analysis between KRAS mutations and clinical information

Because KRAS mutations significantly impact patient prognosis, we conducted an in-depth analysis to explore the association between KRAS mutations and patients’ clinical characteristics, aiming to identify factors predisposing certain individuals to develop KRAS mutations. Our analysis revealed that patients harboring KRAS mutations tended to be older, with a higher proportion aged ≥ 65 years compared to those without KRAS mutations, across various KRAS mutation subtypes (Fig. 3A). Furthermore, significant gender disparities were observed within each KRAS mutation subtypes. Specifically, G12C and G12V mutations predominantly occurred in male patients, whereas G12D mutations were more prevalent among female patients (Fig. 3B). Notably, the distribution of KRAS mutation subtypes varied among smokers, with G12C and G12V mutations predominantly observed in smokers, while G12D mutations were more common in non-smokers (Fig. 3C).

Additionally, we investigated the correlation between KRAS mutations and pathological indicators, including tumor antigen markers. Our analysis revealed that KRAS mutations were predominantly associated with lung adenocarcinoma, with lung adenocarcinoma representing the majority of KRAS mutation subtypes (Fig. 3D). Moreover, we observed differential behavior of TTF-1, a tumor antigen marker, across different KRAS mutation subtypes (Fig. 3E).

Fig. 3 Correlation analysis between KRAS mutations and clinical information. Analysis of correlation between KRAS mutation and age (≥ 65 years and < 65 years) (A), gender (B), smoking (C), Pathological features (D) and TTF-1 (E)

Considering the potential influence of KRAS mutations on immunotherapy efficacy, we examined the relationship between two immune-related molecular markers, PD-L1 expression and TMB, and KRAS mutation subtypes. Our findings indicated significant variations in PD-L1 expression among different KRAS mutation subtypes, G12C and G12V mutations showed a higher proportion of positive PD-L1 expression compared to G12D mutations (Fig. 4A). Similarly, TMB levels differed significantly across various KRAS mutation subtypes, with higher TMB observed in G12C and G12V patients, while patients with G12D mutations exhibited lower TMB levels (Fig. 4B).

Fig. 4 PD-L1 expression and TMB analysis in different KRAS mutation subtypes. A. Number of patients with different PD-L1 expressions between KRAS mutation and non-KRAS mutation. B. Analysis of TMB in patients with KRAS mutated subtypes and non-KRAS mutated patients

The impact of KRAS mutation subtypes on the prognosis of immunotherapy

Following our investigation, we delved into the influence of distinct KRAS mutation subtypes on immunotherapy outcomes. Our survival analysis unveiled intriguing findings, particularly regarding the response to immunotherapy among patients with different KRAS mutation subtypes. Notably, individuals harboring KRAS G12C mutations demonstrated heightened sensitivity to immunotherapy, as evidenced by significantly improved progression-free survival (PFS) and overall survival (OS) compared to those without KRAS mutations.

Kaplan-Meier analysis illustrated a pronounced discrepancy in prognosis between the KRAS G12C mutation group and the KRAS wild-type (WT) group, with KRAS G12C mutant patients exhibiting markedly prolonged PFS (Fig. 5A). Specifically, the mean PFS duration for KRAS G12C mutant patients was 10.2 months, substantially longer than the 3.6 months observed for non-KRAS-mutant patients (p = 0.009) (Fig. 5A and Supplementary Table 2). There is also a difference in OS between patients with G12C mutations and patients without G12C mutations, the mean OS duration was 18.5 months for immunotherapy-treated KRAS G12C mutated patients, surpassing the 14.1 months observed for non-KRAS-mutated patients (p = 0.367) (Fig. 5B and Supplementary Table 2). Moreover, patients with KRAS G12V mutations also exhibited favorable survival outcomes following immunotherapy, with extended PFS and OS durations compared to those without KRAS mutations (Fig. 5C and D). Although the mean PFS duration for KRAS G12V mutant patients (9.22 months) did not significantly differ from non-KRAS-mutant patients (p = 0.066), the median OS duration was notably longer at 19.3 months compared to 14.1 months for non-KRAS-mutated patients (p = 0.139) (Supplementary Table 2).

In contrast, patients with KRAS G12D mutations displayed poorer responses to immunotherapy, the PFS and OS were shorter than that in the non-KRAS-mutant patients (Fig. 5E and F). The mean PFS duration for KRAS G12D mutant patients was 1.7 months, significantly inferior to the 3.6 months observed for non-KRAS-mutant patients (p = 0.03) (Fig. 5E and Supplementary Table 2). Similarly, the mean OS was 10.8 months which was notably shorter than that 14.1 months of non-KRAS-mutated patients (p = 0.367) (Fig. 5F and Supplementary Table 2). However, patients with other KRAS mutation subtypes did not exhibit significant differences in survival outcomes compared to those without KRAS mutations following immunotherapy (Fig. 5G and H and Supplementary Table 2). These findings underscore the importance of considering specific KRAS mutation subtypes in predicting immunotherapy efficacy and tailoring treatment strategies accordingly.

Fig. 5 The Kaplan-Meier analysis for the prognostic value of KRAS mutations subtypes. A. Kaplan-Meier analyses of the PFS between the KRAS G12C mutation and WT patients who received immunotherapy. B. Kaplan-Meier analyses of the OS between the KRAS G12C mutation and WT patients who received immunotherapy. C. Kaplan-Meier analyses of the PFS between the KRAS G12CV mutation and WT patients who received immunotherapy. D. Kaplan-Meier analyses of the OS between the KRAS G12V mutation and WT patients who received immunotherapy. E. Kaplan-Meier analyses of the PFS between the KRAS G12CD mutation and WT patients who received immunotherapy. F. Kaplan-Meier analyses of the OS between the KRAS G12D mutation and WT patients who received immunotherapy. G. Kaplan-Meier analyses of the PFS between the KRAS other mutations and WT patients who received immunotherapy. H. Kaplan-Meier analyses of the OS between the KRAS other mutations and WT patients who received immunotherapy

Disscussion

Immunotherapy has made significant progress in treating cancers that are difficult to target and has become one of the important treatments for advanced non-small cell lung cancer (Landre et al. 2022). Subgroup analyses from clinical trials have highlighted that patients harboring KRAS mutations exhibit heightened sensitivity to PD-1/PD-L1 pathway inhibition therapy, leading to more favorable treatment outcomes. Compared to conventional chemotherapy alone, immunotherapy holds the potential to enhance patients’ PFS and OS (Liu et al. 2020a, b; Rekowska et al. 2024). KRAS mutation-positive patients have a relatively short OS, and further evaluation of the clinical efficacy of these treatment modalities is needed (Stratmann et al. 1990; Moldvay and Tímár 2023; Kargbo 2024). Nevertheless, current research suggests that patients with KRAS mutations face relatively poorer prognoses compared to those without such mutations (Wang et al. 2023). Our study revealed that compared with patients lacking KRAS mutations, patients with KRAS G12C and G12V mutations often show longer survival when receiving immunotherapy, which can extend patients’ PFS and OS. Of particular note is the significant effect observed in patients with KRAS G12C mutations, indicating a significant improvement in survival. This phenomenon might be linked to the elevated levels of PD-L1 expression and TMB seen in KRAS G12C and G12V mutations. Conversely, patients carrying KRAS G12D mutations tend to experience inferior outcomes with immunotherapy compared to those without KRAS mutations. Notably, in our study, KRAS G12D patients exhibited lower rates of PD-L1 positive expression and relatively lower TMB levels, potentially influencing the efficacy of immunotherapy.

While only a small subset of patients in our samples with KRAS mutations were diagnosed with stage I or II, the presence of KRAS mutations seems to initiate early stages of lung cancer development (Scheffler et al. 2019; Izar et al. 2014; Nadal et al. 2015). Moreover, the KRAS G12C mutation emerges as a promising biomarker for lung cancer immunotherapy. Recent studies have suggested that patients harboring KRAS mutations exhibit favorable responses to ICI therapy (Kaufman and Stinchcombe 2017; Skoulidis et al. 2015; Dong et al. 2017). Another critical aspect under discussion is the categorization of KRAS subtypes based on variations in mutation sites. Variability in mutation sites can influence downstream signaling pathways, thereby affecting overall survival outcomes (Cai et al. 2020). Distinct molecular subtypes of KRAS mutations yield diverse consequences, potentially impacting immune evasion mechanisms or the efficacy of immunotherapy (Ihle et al. 2012). Ongoing research into the treatment of KRAS mutations remains active. While KRAS mutations alone may not suffice as standalone predictors of immunotherapy outcomes in most studies, the identification of KRAS subtypes could still serve as valuable biomarkers aiding in prognosis prediction.

Additionally, we observed a significant association between KRAS mutation subtypes and smoking status. The majority of smokers exhibited KRAS G12C mutations (33/38), while patients with KRAS G12V mutations also had a higher proportion of smokers (9/14). Conversely, the proportion of smokers among patients with KRAS G12D mutations was relatively small (6/26). Several studies have elucidated the link between smoking exposure and KRAS mutations, suggesting that smoking contributes to a higher antigen load, potentially influencing the effect of immunotherapy on KRAS mutations (Cao et al. 1990; Amanam et al. 2020; Chapman et al. 2016). In Caucasian populations, KRAS mutations are more prevalent among females and smokers (Aredo et al. 2019). Interestingly, some studies reported that G12C mutations were more frequent in women with a smoking history (Guan et al. 2013; Liu et al. 2020a, b). However, our findings align with Guan et al., indicating that male smokers more commonly harbor KRAS mutations, including G12C mutations.

This study primarily investigates the clinical correlation between KRAS mutation subtypes in patients with NSCLC and explores their impact on immunotherapy. These results can facilitate more accurate patient classification, drug development, and offer guidance for future drug usage. Nonetheless, our study has certain limitations. Firstly, the sample is derived from a single source, limiting its generalizability. Secondly, the diverse array of KRAS mutation subtypes may exhibit distinct clinical and molecular characteristics, necessitating a larger sample size for comprehensive research. Lastly, the dataset lacks clinical data for some samples, underscoring the need for future additions to enable a more thorough investigation.

Conclusions

Our results indicate that KRAS mutation subtypes differ in their clinical and molecular characteristics. Different KRAS mutation subtypes have different immunotherapy effects. Patients with KRAS G12C and G12V mutations have better immunotherapy effects, while patients with KRAS G12D mutations have relatively poor immunotherapy effects.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Acknowledgements

No.

Author contributions

GG, CL and GS designed the research and supervised the study. GG, XH and YY collected clinical data and sample. GG and SS performed experiments. GG, CL and YZ analyzed the data and designed the figures. GG and CL wrote the paper. CL and GS revised the paper. All authors read and approved the final manuscript.

Funding

Key Laboratory of Oncology of Xinjiang Uyghur Autonomous Region, XJKLO-2023U009, Molecular mechanism of the effect of KRAS gene mutation differentiation on immunotherapy of non-small cell lung cancer. Department of Science and Technology of Xinjiang Uygur Autonomous Region, 2022D14010, Innovative team of Xinjiang Lung Cancer Immune Response Mechanism and Immunotherapy Advantageous Population Screening and Prognosis Related Research.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethical approval

This study have been approved by the Affiliated Cancer Hospital of Xinjiang Medical University, and this study was conducted in accordance with the Declaration of Helsinki. A signed written informed consent was obtained from each patient.

Consent for publication

Written informed consent for publication was obtained from each participant.

Competing interests

The authors declare no competing interests.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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