
==== Front
BMC Oral Health
BMC Oral Health
BMC Oral Health
1472-6831
BioMed Central London

39237889
4840
10.1186/s12903-024-04840-3
Research
The relationship between salivary cytokines and oral cancer and their diagnostic capability for oral cancer: a systematic review and network meta-analysis
Huang Lijun 12
Luo Fen 12
Deng Mingsi 12
Zhang Jie 305966738@qq.com

12
1 Department of Orthodontics, Changsha Stomatological Hospital, Changsha Hunan, 410006 China
2 https://ror.org/05qfq0x09 grid.488482.a 0000 0004 1765 5169 School of Stomatology, Hunan University of Traditional Chinese Medicine, Changsha Hunan, 410208 China
5 9 2024
5 9 2024
2024
24 10446 12 2023
29 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/.
Background

Oral cancer (OC) is a common malignancy in clinical practice. Saliva testing is a convenient and noninvasive early diagnostic technique for OC. Several salivary cytokines have been identified as potential biomarkers for OC, including IL-8, IL-6, TNF-α, IL-1β, and IL-10. Nonetheless, the optimal cytokine for OC diagnosis remains inconclusive and highly contentious.

Methods

PubMed, Embase, Web of Science, and Cochrane Library databases were comprehensively retrieved to collect all case–control studies on OC. A meta-analysis was performed to compare the levels of salivary IL-8, IL-6, IL-10, TNF-α, and IL-1β in OC patients and healthy controls. Network meta-analysis (NMA) was carried out to probe into the accuracy of these salivary cytokines in diagnosing OC.

Results

This analysis included 40 studies, encompassing 1280 individuals with OC and 1254 healthy controls. Significantly higher levels of salivary IL-8, IL-6, TNF-α, IL-1β, and IL-10 were observed in patients with OC in comparison to healthy controls. The results of NMA showed that TNF-α had the highest diagnostic accuracy for OC, with a sensitivity of 79% and a specificity of 92%, followed by IL-6 (sensitivity: 75%, specificity: 86%) and IL-8 (sensitivity: 80%, specificity: 80%).

Conclusion

This study suggests that IL-8, IL-6, IL-10, TNF-α, and IL-1β may be potential diagnostic biomarkers for OC. Among them, TNF-α, IL-6, and IL-8 are highly accurate in the diagnosis of OC. Nevertheless, further studies that eliminate other confounding factors are warranted, and more standardized procedures and large-scale studies are needed to support the clinical use of saliva testing.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-024-04840-3.

Keywords

Biomarkers
Cytokines
Oral cancer
Saliva
Network meta-analysis
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
==== Body
pmcIntroduction

Oral cancer (OC) is one of the most frequent aggressive malignancies worldwide. It was estimated that there were 377,713 new OC cases (approximately 2% of all cancer cases) and 177,757 deaths (1.8% of all cancer-related deaths) in 2020 around the world [1]. This cancer may locally invade the tongue, lips, lower and upper gums, hard palate, retromolar trigone, and floor of the mouth, and even metastasize to distant sites at an advanced stage [2]. Squamous cell carcinoma (OSCC) represents approximately 90% of OC cases [3], and other OC types encompass salivary gland tumors, lymphomas, and sarcomas [4]. Due to asymptomatic characteristics, around 50% of individuals with OC are diagnosed at a late stage. Accordingly, the treatment of such patients is often aggressive and mutilating, adversely affecting their quality of life [5]. The 5-year relative survival rate is about 85.1% for localized OC, and is as low as 69.1% and 39.3% for lymphatic metastasis and distant metastasis, respectively [6]. Therefore, early diagnosis of OC is essential to reduce the mortality rate and ameliorate the quality of life of OC patients.

Currently, commonly-used diagnostic approaches for OC include traditional oral visual examination (VOE), classical biopsy followed by histopathological assessment, vital staining (such as toluidine blue), and radiographic imaging [7]. Among them, biopsy and histopathological examinations are still the standard procedures for the diagnosis of OC [8]. Besides, the analysis of body fluids, especially saliva, is a promising and potential alternative to biopsy for early OC detection since it is adjacent to cancer cells, readily available, non-invasive, and inexpensive [9]. Human saliva consists of cytokines, circulating cells, DNA and RNA molecules, and derivatives of tissue and extracellular vesicles (EVs) [10]. Cytokines, as key mediators of cell communication, can control complex and dynamic cell–cell interactions and regulate various cancer-related pathways in the tumor microenvironment [11]. In histiocytology, cytokines such as IL-6 and IL-8 that are important in pro-inflammatory and pro-angiogenic responses can be detected in cell lines, tissue specimens, and serum of patients with Head and Neck squamous cell carcinoma (HNSCC includes OSCC, pharyngeal squamous cell carcinoma, laryngeal squamous cell carcinoma, nasal squamous cell carcinoma, paranasal sinuses squamous cell carcinoma etc. [12, 13]. Moreover, a large scale gene expression profiling assisted by laser capture microdissection and microarray analysis was carried out, identifying the expression of 2 cellular genes: interleukin (IL)6 and IL-8 which are uniquely associated with OSCC [14]. Besides, a direct link between oral inflammation and cancer invasion was established by showing that neutrophils increase OSCC invasion through a tumor necrosis factor (TNFα)-dependent mechanism [15]. According to many case–control studies and previous systematic reviews and meta-analyses, the average levels of salivary cytokines such as IL-6, IL-8, TNF-α, IL-1β, and IL-10 are significantly different between OSCC, oral potentially malignant disorders (OPMD), oral leukoplakia (OL) and control saliva. Previous studies also showed that IL-6 and IL-8 concentrations in saliva were associated with different stages of OSCC and the presence of cervical metastasis [6, 16, 17]. Taken together, these findings suggest that these salivary cytokines may be potential diagnostic biomarkers for OC.

Nevertheless, there is no consensus on which biomarkers have the best diagnostic value for OC. Network meta-analysis for diagnostic tests (NMA-DT) is a new analysis approach that allows simultaneously comparing multiple diagnostic tests, at multiple test thresholds [18]. This novel technique can lessen bias and enhance statistical accuracy in the comparison of the diagnostic performance of multiple tests by borrowing strength from indirect evidence [19]. Therefore, this network meta-analysis was implemented to evaluate and compare the accuracy of five common salivary cytokines (IL-8, IL-6, TNF-α, IL-1β, and IL-10) in diagnosing OC and to rank these diagnostic tests based on a superiority index.

Methods

Protocol and registration

This study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Diagnostic Test Accuracy (PRISMA-DTA) Checklist (The prisma-DTA checklist is in the Supplementary Table S5) [20]. The study protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO; registration ID: CRD42023430533).

Inclusion and exclusion criteria

The following studies were included: (1) case–control studies on human subjects; (2) patients diagnosed with OC; (3) OC was confirmed pathologically; (4) the controls were healthy subjects without systemic diseases; (5) studies that reported at least one of the diagnostic sensitivity and specificity of IL-8, IL-6, IL-10, TNF-α, or IL-1β in OC patients compared to healthy controls with no systemic disease and the concentrations of these salivary biomarkers.

The exclusion criteria were as follows: (1) duplicate publications; (2) reviews, systematic reviews, meta-analyses; (3) conference summaries/abstracts, case reports, guidelines, letters to editors, editorials, study protocols, brief correspondences, animal experiments; (4) full texts unavailable; (5) outcome data unextractable; (6) non-English articles.

Literature search

As of 10 April 2023, two independent investigators (Lijun, Huang (L, H) and Mingsi, Deng (M, D)) extensively retrieved electronic databases, including PubMed, Embase, Web of Science, and Cochrane Library. No restrictions were imposed on study type, date/time, or publication status. Search terms encompassed “cytokine”, “saliva”, and “oral cancer” in combination with “interleukin” or “interferon”. The specific search strategy is delineated in Table S1. Besides, the reference lists of related studies and reviews were manually retrieved.

Study selection

All retrieved studies were imported into EndNote 20 to eliminate duplicate records. Two investigators (L, H and Fen, Luo (F, L)) independently checked the titles and abstracts to remove irrelevant articles. A full-text review was then conducted to select eligible studies. A third reviewer (M, D) was consulted to settle any disagreements that arose throughout the literature screening process.

Data extraction and quality assessment

Relevant data were independently extracted from included articles by two investigators, encompassing title, first author, publication year, country, study design, sample size, gender, patient age, the outcomes (levels of different cytokines in saliva, sensitivity and specificity, true positives (TP), false positives (FP), true negatives (TN) and false negatives (FN) in predicting OC). Dissents, if any, were settled by consulting a third investigator.

The Newcastle–Ottawa Scale (NOS) [21] was employed to evaluate the quality of the included articles. Two researchers (L, H and M, D) independently assessed 8 items in three domains: selection of case and control groups, comparability between groups, and exposure factors. Except for comparability, which has 2 points, each item in the remaining domains has 1 point. The total score ranges from 0 to 9 points. Studies rated 8 or higher were regarded as high quality, while those rated 4 or less were deemed to be of low quality. Meanwhile, studies with a score of 5–7 were considered to have a medium quality. The Quality Assessment on Diagnostic Accuracy Studies (QUADAS) 2 tool were used to assess the risk of bias [22], too. The risk of bias was assessed in four key domains including patient selection, index test(s), reference standard, and flow and timing. Concerns regarding applicability (patient selection, index test(s), and reference standard) were determined. The degree of bias and applicability were expressed as high, low, or unclear, in accordance with the guidance documents. The quality assessment was implemented independently by two researchers. Any dissents were resolved by a third researcher (F, L).

Statistical analyses

A traditional meta-analysis was carried out to pool data from studies comparing the levels of salivary IL-8, IL-6, IL-10, TNF-α, and IL-1β in OC patients and controls (non-OC). Standardized mean difference (SMD) with 95% confidence intervals (CIs) was used as the effect size. A p < 0.05 signals statistical significance. Forest plots were generated to visually present the results. The I2 statistic was utilized to examine heterogeneity among studies. I2 > 50% indicates statistically significant heterogeneity, and therefore, a random-effects model was applied for data analysis. Potential publication bias was determined by using a funnel plot and Egger’s test.

Furthermore, a network meta-analysis for diagnostic tests (NMA-DT) was conducted to delve into which saliva cytokine is the most accurate for predicting OC. NMA-DT enables us to concurrently compare several diagnostic tests of saliv a cytokines with the gold standard, at various thresholds [23]. The relative performance, sensitivity, and specificity of the index tests were assessed in relation to standard diagnostic method for OC, and these tests were ranked utilizing the diagnostic odds ratios (DORs) and superiority index (Table S2 in the Supplementary Materials explains all statistical terms). Higher DOR and superiority values indicate higher accuracy of tests in detecting diseases. This network meta-analysis was conducted using the R package “rstan” (version 4.1.3; R Foundation for Statistical Computing, Vienna, Austria). Analysis of Variance (ANOVA) model based on the Bayesian algorithm was applied to exhibit network meta-analysis among four systems by utilizing two independent binomial distributions to describe the true positive and true negative rates between OC and non-OC patients, meantime considering the correlation between sensitivity and specificity [24]. In order to improve accuracy and compare diagnostic assays one by one, calculations were repeated 7 times (model_code = model, chains = 2, iterations = 10,000, warmup = 5000, thin = 5), and then, league tables for relative comparations were drawn. Review manager version 5.4 was employed to calculate summary receiver operating characteristic curve (SROC) values.

Results

Study selection

Initially, 3075 articles were obtained from the database search. After removing 1082 duplicates, 1993 articles remained. After screening the titles and abstracts, 58 articles were potentially eligible. Based on a full-text review, 18 studies were further excluded, including 4 studies without healthy-control group, 8 studies without required experimental group, 4 studies without cytokines of interest, 1 study with no outcome of interest, and 1 commentary. Finally, 40 articles were included in the traditional meta-analysis and 12 articles in the network meta-analysis. The study selection process is delineated in Fig. 1.Fig. 1 PRISMA flow diagram for search and selection of eligible studies included in the network meta-analysis

Study characteristics

The characteristics of the 40 included studies are presented in Table 1. These studies were published between 2004 and 2023. 19 studies were conducted in Asia [25–43], 11 studies in Europe [16, 44–53], and 10 studies in North America [54–63]. A total of 1280 patients with OC (most of the patients had OSCC) and 1254 healthy controls were included. The sample size of the included studies ranged from 9 to 100, with a mean age of 46 to 73 years. All the case–control studies enrolled both adult males and females. The enzyme-linked immunosorbent assay (ELISA) was the most often utilized detection method for determining the levels of salivary cytokines, followed by the Luminex-based immunoassay, the bead-based multiplex immunoassay, and the chemiluminescent enzyme immunoassay. For example, in the study by Piyarathne et al. [44], protein levels of ILs were quantified using a commercially available sandwich enzyme-linked immune-sorbent assay (ELISA), with pre-coated plates: E-EL-H0149, E-EL-H0102 and E-EL-H0048 kits (Elabscience; Wuhan, Hubei, China). In the study by Laliberté et al. [54], cytokines were analyzed according to the immunoassay protocol for the Millipore Human Cytokine/Chemokine Magnetic Bead Assay Panel (HCYTMAG-60K-PX30 by EMD Millipore, USA) and Luminex detection. In the study by Sato, J. et al. [42], IL-6 concentrations were measured using a highly sensitive chemiluminescent enzyme immunoassay (Fujirebio Inc., Tokyo, Japan). Table 1 General characteristics of the included studies

Author(year)	Country	Disease type	Sample Size(n)	Sex (female/fale)	Age (years)	Methods	Salivary cytokines	Outcome	NOS score	
case	control	case	control	case	control	
Nadisha (2023) [44]	UK	OSCC	37	30	31/6	24/6	60.0 ± 11.5	62.2 ± 10.2	ELISA	lL1β, IL6, IL8	①②③④	7	
Valentina (2021) [16]	Spain	OSCC	66	25	33/33	9/16	73 ± 10.9	62 ± 8.3	Multiplex Immunoassay	IL-6, IL-8, TNF-α	①②	7	
Catherine (2021) [54]	Canada	OSCC	32	24	14/18	9/15	66 ± 13	61 ± 14	a Luminex-based immunoassay	IL-1β, IL-6, IL-8, IL-10, TNF-α,	①	7	
Prerana (2020) [25]	India	OSCC	58	42	47/11	34/8	45.89 ± 12.36	43.05 ± 10.40	ELISA	IL-1β, IL-8	①②③④	6	
Karolina (2020) [45]	Poland	OSCC	14	9	6/3	5/4	49.0 ± 13.7	29.0 ± 10.1	ELISA	IL-6, IL-8,

TNF-α

	①	7	
Deepthi (2019) [27]	India	OSCC	30	30	26/4	10/20	24- 74	20–67	ELISA	TNF-α	①③④	6	
Ildikó (2019) [46]	Hungary	OSCC	95	80	60/35	30/50	61.7 ± 9.8	61.7 ± 9.2	ELISA	IL-6	①③④	7	
Jembulingam (2019) [18]	India	OSCC	10	15	ND	ND	ND	ND	biochemically estimated	TNF-α	①	6	
L. T. Lee (2018) [36]	Taiwan	OSCC	41	24	36/5	20/4	 ≥ 55(18); < 55(23)	 ≥ 55(11); < 55(13)	Luminex Bead-based Multiplex; Assay	IL-1β, IL-6, IL-8, TNF-a	①②④	6	
SUXIN (2017) [37]	China	primary oral cancer	40	20	18/22	ND	51.3 ± 10.0	ND	ELISA	IL-6	①	7	
E´ va (2017) [47]	Hungary	OSCC	26	20	6/20	12/7	58.2 ± 9.7	59.3 ± 5.6	ELISA	IL-1β, IL-6, IL-8, TNF-α	①②③④	7	
Minoo (2017) [38]	Iran	OSCC	15	15	ND	ND	ND	ND	ELISA	IL-6	①	7	
Frederico (2016) [55]	USA	OSCC	60	60	57/3	55/5	 < 39(6);40–49(21);50–59(23):60–69(7): > 70(3)	 < 39(18);40–49(11);50–59(14):60–69(10): > 70(7)	ELISA	IL-8, IL-1β	①③④	6	
Leticia (2016) [49]	Spain	OSCC	20	20	15/5	ND	65	ND	ELISA	IL-6	①	6	
Thayalan (2016) [40]	India	OSCC	100	100	68/32	65/35	21–90	21–65	ELISA	IL-6	①③④	7	
Małgorzata (2016) [48]	Poland	OSCC	78	40	71/7	35/5	40–49(12);50–69(34);70 + (32)	40–49(7);50–69(19);70 + (14)	ELISA	IL-10, TNF-α	①	7	
Niranzena (2015) [64]	India	OSCC	25	25	21/4	21/4	49	46.88	ELISA	IL-6	①	7	
Salman (2015) [43]	Pakistan	OSCC	30	33	24/6	27/6	50.33 ± 11.77	44 ± 11.48	Luminex multianalyte profifiling (xMAP) technology	IL-10	①	6	
Jun Sato (2015) [42]	Japan	OSCC	27	21	16/11	10/11	70.7 ± 8.6	68	a chemiluminescent enzyme immunoassay	IL-6	①	7	
Radu (2015) [50]	Romania	OSCC	30	14	14/16	ND	45–60	40–60	ELISA	IL-6	①	6	
Andréia (2015) [51]	Brazil	OSCC	22	23	15/7	ND	55	ND	ELISA	IL-10	①	7	
K. Rajkumar (2014) [30]	India	OSCC	100	100	68/32	65/35	21–90	21–65	ELISA	IL-8	①③	7	
Yi-Shing (2014) [56]	USA	OSCC	18	21	11/7	9/12	59.39	62.95	ELISA	IL-6, IL-8	①	7	
Rajkumar (2014) [29]	India	OSCC	100	100	68/32	65/35	21–90	21–65	ELISA	TNF-α	①③	7	
M. JURETIć (2013) [52]	Croatia	OSCC	19	19	12/7	10/9	54.2 ± 8.4	44.1 ± 4.5	ELISA	TNF-α, IL-6	①	6	
Silky (2013) [32]	India	OSCC	25	25	9/16	ND	53.2 ± 11.4	ND	ELISA	IL-8	①	6	
Jun Sato (2013) [31]	Japan	OSCC	27	21	11/16	11/10	70.7 ± 8.6	68	a chemiluminescent enzyme immunoassay	IL-6	①	8	
Vlaho (2012) [53]	Croatia	OSCC	28	31	22/6	19/12	61.9	57.8	ELISA	IL-1β, IL-6,TNF-α	①	6	
David (2012) [57]	USA	OSCC	54	36	6/30	4/50	59.9 ± 9.1	58.8 ± 13.5	ELISA	IL-8, IL-1β	①	7	
Alexis (2011) [58]	USA	TSCC (squamous cell carcinoma of the tongue)	18	14	6/12	ND	56.5 ± 13.6	45 -75	ELISA	IL-6, IL-8, TNF-α	①	6	
Ole (2011) [59]	USA	OSCC	35	51	30/5	28/23	60.94 ± 12.30	38.24 ± 12.50	ELISA	IL-1β, IL-8	①	6	
Jun Sato (2010) [33]	Japan	OSCC	29	19	18/11	9/10	69	67	a chemiluminescent enzyme immunoassay	IL-6	①	6	
Mahnaz (2008) [34]	Iran	OSCC	9	9	4/5	4/5	71.33	67.33	ELISA	TNF-α, IL-6,

IL-8

	①	6	
ME Arellano-Garcia (2008) [60]	USA	OSCC	20	20	8/12	6/14	59.1 ± 12.0	38.8 ± 14.9	Multiplexed immunobead-based assay,ELISA	IL-8, IL-1β	①	6	
Nelson (2005) [61]	USA	OSCC	13	13	10/3	3/10	59 ± 7	58 ± 12	ELISA	TNF-α, IL-6, IL-8	①	6	
Nelson (2004) [63]	USA	OSCC	13	13	10/3	ND	59.5 ± 6.7	ND	ELISA	TNF-α, IL-1, IL-6, IL-8	①	6	
Maie (2004) [62]	USA	OSCC	32	32	ND	ND	49.3 ± 7.5	48.8 ± 5.7	ELISA	IL-8, IL-6	①②③④	7	
M. Ameena (2019) [28]	India	OSCC	30	30	21/9	22/8	57.8 ± 9.4	57.2 ± 9.2	ELISA	TNF-α	①③④	7	
Iqbal (2017) [39]	Pakistan	OSCC	35	35	25/21	21/14	46.7	43.5	ELISA	IL6, IL8	①	7	
Akira (2007) [35]	Japan	Oral cancer	19	20	9/10	15/5	60.9	32	ELISA	IL-1β, IL-6, IL-8		7	
①Salivary biomarker concentration (pg/mL);②Sensitivity, Specificity;③ROC (receiver operating characteristic) curve;④AUC(area under the curve)

Ten studies reported salivary IL-1β concentrations [25, 35, 36, 44, 47, 53–55, 57, 60], 4 of which reported its sensitivity and specificity in the diagnosis of OC [25, 36, 44, 60]. 24 studies reported salivary IL-6 concentrations [16, 31, 33–42, 44–46, 49, 50, 52–54, 56, 58, 61, 63], 5 studies reported sensitivity and specificity [16, 36, 44, 46, 47]. 20 studies reported salivary IL-8 concentrations [16, 25, 29, 32, 34–36, 39, 44, 45, 47, 54–61, 63], 8 studies reported sensitivity and specificity [16, 25, 29, 36, 44, 55, 60, 62]. 15 studies reported salivary TNF-α concentrations [16, 26–29, 34, 36, 45, 48, 52–54, 58, 61, 63], 5 of which reported sensitivity and specificity [16, 27, 28, 36, 47]. 5 studies reported salivary IL-10 concentrations [36, 43, 48, 51, 54], but none of them investigated its sensitivity and specificity.

Quality assessment

The NOS scores are provided in Table 1. The quality assessment results revealed that 1 study [31] was of high quality and the other 39 studies were of medium quality. Besides, the mean score of all included studies was 6.5. Table S3 in the Supplementary Materials illustrates the thorough point-by-point evaluation. For the risk of bias and applicability of diagnostic accuracy studies, we considered the overall risk of bias to be relatively low, and all included studies generated only low concern in all aspects (details in the Supplementary Figure S1). To be specific, there was a high risk of bias in participant selection due to case–control designs and inappropriate exclusions, with unclear consecutive sample of patients enrolled in some studies. In the index test assessment, 2 [16, 44] out of 12 studies had a low risk of bias, 10 studies [25, 27–29, 36, 46, 47, 55, 60, 62] were judged to be unclear. Regarding reference standard tests, all studies had a low risk of bias. For the flow and timing aspects, all studies demonstrated a low risk of bias in statements regarding the interval time between the reference test and the index test.

Meta-analysis for comparing saliva cytokines between OC patients and healthy controls

IL-6, as the most extensively investigated cytokine, was reported in 24 studies [16, 31, 33–40, 42, 44–46, 49, 52–54, 56, 58, 61–64], including 708 OC cases and 652 controls. The meta-analysis suggested an obvious increase in salivary IL-6 levels in OC patients (SMD = 2.32, 95% CI (1.61, 3.03), p < 0.001). There was a high degree of heterogeneity (I2 = 95.8%, Fig. 2A). However, the sensitivity analysis did not find the source of heterogeneity (Supplementary Figure S2) Furthermore, subgroup analyses were conducted depending on patients’ age (> 60, ≤ 60, or not grouped), the assay kits used (ELISA, Luminex-based Multiplex immunoassay or chemiluminescent enzyme immunoassay), and the geographic locations among the included studies (Europe, north America, or Asia), and the results showed that patients’ age and the assay kits were the source of heterogeneity (> 60, I2 = 0%, ≤ 60, I2 = 90.7%; ELISA kit, I2 = 96.5%; the Luminex-based Multiplex kit and the chemiluminescent enzyme kit, I2 = 0%, details see Supplementary Table S4). Egger's test pointed to the evidence of publication bias across these 24 studies (p < 0.001).Fig. 2 Forest plot of the saliva cytokine levels in OSCC patients versus healthy controls A IL-6 levels B IL-8 levels

The second most commonly studied cytokine was IL-8, which was investigated in 20 studies [16, 25, 29, 32, 34–36, 39, 44, 45, 54–62, 65] encompassing 691 OC patients and 750 controls. According to the pooled analysis (Fig. 2B), salivary IL-8 levels were found to be markedly increased in the OC population (SMD = 1.73, 95%CI [1.20, 2.26], p < 0.001). The heterogeneity between studies was significant (I2 = 93.8%). The exclusion of individual studies did not alter the analysis results (Supplementary Figure S2). The results of subgroup analyses indicated that the assay kits were the source of heterogeneity (ELISA kit, I2 = 94.9%; the Luminex-based Multiplex kit and the chemiluminescent enzyme kit, I2 = 0%, details see Supplementary Table S4). Egger's test revealed significant publication bias (p = 0.03).

The salivary TNF-α level (Fig. 3A) was discussed in 15 studies [16, 26, 27, 29, 34, 36, 45, 48, 52–54, 58, 61, 62, 65], covering 460 cases and 435 controls. The pooled analysis showed significantly elevated TNF-α levels in OSCC patients (SMD = 2.27, 95% CI (1.27, 3.26), p < 0.001). Heterogeneity was high (I2 = 96.3%). Sensitivity analysis suggested that the exclusion of each study did not alter the pooled effect size (Supplementary Figure S2). Subgroup analyses showed that participants’ age and the assay kits were the source of heterogeneity (> 60, I2 = 0%, ≤ 60, I2 = 91.2%; ELISA kit, I2 = 96.3%; the Luminex-based Multiplex kit, I2 = 0%, Supplementary Table S4). Egger's tests (p = 0.065) revealed no publication bias.Fig. 3 Forest plot of the salivary cytokine levels in OC patients versus healthy controls A TNF-α levels B IL-1βlevels C IL-10 levels

IL-1β was evaluated in 10 studies [25, 35, 36, 44, 53–55, 57, 59, 60], including 381 OC cases and 392 controls. The meta-analysis found that OC patients exhibited a considerably higher IL-1β level in comparison to the healthy controls (SMD = 0.79, 95% CI (0.58, 1.00), p < 0.001, Fig. 3B). Heterogeneity was low (I2 = 47.1%). The funnel plot (Supplementary Figure S3) and the Egger’s test suggested no publication bias (p = 0.393).

IL-10 levels were reported in 5 included studies [36, 43, 48, 51, 54], involving 99 OC cases and 139 controls. Higher levels of IL-10 were noted in OC patients in comparison to the control group (SMD = 0.80, 95% CI (0.12, 1.48), p = 0.022, Fig. 3C). High heterogeneity was observed (I2 = 88%). The sensitivity analysis demonstrated that leaving out any one study did not have an impact on the pooled results (Supplementary Figure S2), while the assay kits and the geographic locations were the source of heterogeneity (ELISA kit, I2 = 92.0%; the Luminex-based Multiplex kit, I2 = 0%; Asia, I2 = 0%; Europe, I2 = 92.0%, Supplementary Table S4). Egger's test and the funnel plot (Supplementary Figure S3) indicated no publication bias (p = 0.231).

Diagnostic accuracy estimate

Since no studies have mentioned the sensitivity and specificity of IL-10 in the diagnosis of oral cancer only the remaining 4 kinds of saliva cytokines (i.e., IL-6, IL-8, TNF-α, and IL-1β) were included in this network meta-analysis. 12 studies [16, 25, 27–29, 36, 44, 46, 47, 55, 60, 62] provided their sensitivity and specificity, involving 1058 participants, of whom 574 (54.3%) were OC patients. Among the included studies, 5 studies [16, 36, 44, 46, 47] assessed the diagnostic accuracy of IL-6 for OC, with the sensitivity varying from 0.75 to 1.00 and specificity from 0.49 to 0.80 (Fig. 4). The pooled sensitivity and specificity of IL-6 were 0.75 (95% CI: 0.71, 0.81) and 0.86 (95%CI: 0.82, 0.90), respectively (Table 2). 8 studies [16, 25, 29, 36, 44, 55, 60, 62] assessed the diagnostic accuracy of IL-8 for OSCC, with the sensitivity varying from 0.67 to 0.97, and specificity from 0.58 to 0.97 (Fig. 4). The pooled sensitivity and specificity of IL-8 were 0.80 (95%CI: 0.77, 0.83) and 0.80 (95%CI: 0.77, 0.84), respectively (Table 2). 5 studies [16, 27, 28, 36, 47] assessed the diagnostic accuracy of TNF-α for OC, with the sensitivity varying from 0.83 to 1.00, and specificity from 0.49 to 1.00 (Fig. 4). The pooled sensitivity and specificity of TNF-α were 0.79 (95%CI: 0.76, 0.84) and 0.92 (95%CI: 0.90, 0.95) (Table 2), respectively. 4 studies [25, 36, 60, 65] assessed the diagnostic accuracy of IL-1β for OC, with the sensitivity varying from 0.61 to 0.74, and specificity from 0.76 to 0.84 (Fig. 4). The pooled sensitivity and specificity of IL-1β were 0.66 (95%CI: 0.61, 0.72) and 0.75 (95%CI: 0.70, 0.81), respectively (Table 2).Fig. 4 Forest plots for the diagnostic accuracy of saliva cytokines. TP true positive, FP false positive, FN false negative, TN true negative, CI confidence interval

Table 2 The sensitivity and specificity of saliva cytokines

	Factor	Sensitivity	Specificity	DOR	Superiority	
Value	95% CI	Value	95% CI	Value	95% CI	Value	95% CI	
1	IL6	0.75	0.71–0.81	0.86	0.82–0.90	25.13	13.48–31.77	1.93	1.00–3.00	
2	IL8	0.80	0.77–0.83	0.80	0.77–0.84	19.09	12.71–23.33	1.70	0.60–3.00	
3	TNF-α	0.79	0.76–0.84	0.92	0.90–0.95	72.42	34.00–89.45	4.77	3.00–7.00	
4	IL1β	0.66	0.61–0.72	0.75-	0.70–0.81	7.57	4.22–9.42	0.27	0.14–0.20	

The network plot for the diagnostic accuracy of salivary cytokines for OC is illustrated in Fig. 5A. The NMA suggested that TNF-α ranked first, with the highest DOR (72.42, 95%CI: 34.00, 89.45), the second highest sensitivity (0.79, 95%CI: 0.76, 0.84), highest specificity (0.97, 95%CI: 0.69, 1.00), and the highest superiority index (Table 2). IL-6 ranked second, and the pooled sensitivity, specificity and DOR of IL-6 were 0.75 (95% CI: 0.71, 0.81), 0.86 (95% CI: 0.82, 0.90) and 25.13 (95% CI:13.48, 31.77), respectively, followed by IL-8 (sensitivity: 0.80, 95% CI: 0.77,0.83; specificity: 0.80, 95% CI: 0.77, 0.84; DOR: 19.09, 95% CI: 12.71, 23.33) and IL-1β (sensitivity: 0.66, 95% CI: 0.61, 0.72; specificity: 0.75, 95% CI: 0.70, 0.81; DOR: 7.57, 95% CI: 4.22, 9.42). Summary ROC results are presented in Fig. 5B.Fig. 5 A Evidence network plot of diagnostic accuracy of saliva cytokines for OC B Summary ROC plot of saliva tests

Discussion

A traditional meta-analysis was carried out based on all available evidence from 40 case–control studies to compare the levels of salivary IL-8, IL-6, IL-10, TNF-α, and IL-1β in OC patients versus controls. Our research indicated that OC patients exhibited considerably higher levels of salivary IL-8, IL-6, TNF-α, IL-1β and IL-10 than healthy controls. To our knowledge, this is the first network meta-analysis to delve into the diagnostic accuracy of these cytokines for OC. Our NMA found that IL-8 had the highest sensitivity (0.80), followed by TNF-α (0.79) and IL6 (0.75). TNF-α had the highest specificity (0.92), followed by IL6 (0.86) and IL8 (0.80). Overall, the DOR results indicated that TNF-α had the highest accuracy for the diagnosis of OC.

In the tumor microenvironment, there are a large number of cytokines, which inhibit tumor-specific immune response and promote the proliferation of tumor cells [66, 67], thus contributing to the tumorigenesis and progression of tumors. Our results suggested that OC patients exhibited considerably higher levels of salivary IL-8, IL-6, TNF-α, IL-1β and IL-10 in comparison to healthy controls, which were consistent with previous studies [17, 68]. Specifically, Rezaei's meta-analysis implied that levels of IL-6 and IL-8 in saliva were markedly elevated in OC patients [68]. The meta-analysis by Chiamulera demonstrated significantly higher levels of salivary IL-8, IL-6, TNF-α, IL-1β and IL-10 in OC patients [17]. It has been proposed that cytokines in oral chronic/acute inflammation recruit neutrophils to form a feedback loop with OC cells, resulting in a pro-tumor phenotype [15]. Our research further supports this finding, suggesting that these cytokines can be used as potential biomarkers for OC.

The main purpose of our study was to compare common saliva cytokines so as to identify the best cytokine for diagnosing OC. According to our results, TNF-α was the most accurate and ranked first with a specificity of 0.92 and a sensitivity of 0.79, and its DOR value was much higher than others. TNF-α, a member of the enormous TNF cytokine family, plays a key role in numerous physiological and pathological cellular processes, such as cell proliferation, differentiation, and death, regulation of immune response to various cells and molecules, local and vascular invasion of tumors, and destruction of the tumor vascular system [69]. In both in vitro and in vivo models, as well as in patients with OC, the upregulation of TNF-α has been shown to enhance cell proliferation, whereas its downregulation inhibits the proliferation and migration of tumors [70, 71]. Moreover, elevated TNF-α in the OC tumor microenvironment has been reported to facilitate invasion through two mechanisms: (i) it fosters the pro-inflammatory and pro-invasive phenotype of OC cells; (ii) it acts as a paracrine mediator to promote the recruitment and activation of inflammatory cells [15, 72]. Simultaneously, TNF-α gene polymorphisms are strongly associated with an elevated risk of oral pre-cancer [73]. Based on our results, TNF-α could be a preferred biomarker for the diagnosis of OSCC.

Furthermore, our NMA implied that IL-6 and IL-8 ranked second (sensitivity: 75%; specificity: 86%) and third (sensitivity: 80%; specificity: 77%), respectively, while IL-1β ranked last (sensitivity: 66%; specificity: 75%). The diagnostic performance of IL-10 was not analyzed because the included studies did not provide the specificity and sensitivity of IL-10 for the diagnosis of OC. Previous studies and the results of the present study have shown that the IL-6 level in saliva is significantly elevated in OC patients [17], and there is a statistical difference in the concentration of IL-6 between pre-cancer state and the normal population [31, 63]. The concentration of IL-6 in saliva may be used as a biological marker for the early diagnosis of OC. For instance, an elevated IL-6 concentration indicates a higher probability of local OC recurrence [31]. Moreover, IL-6, as a member of the IL-6 cytokine family, is involved in the recruitment of neutrophils and macrophages, which is related to the pathogenesis of chronic inflammatory diseases. It not only contributes to the tumorigenesis and rapid progression of tumors, but also promotes the metastasis and spread of aggressive cancer cells [74]. Hence, IL-6 may serve as a major contributor to the occurrence and development of OC. IL-8, as a member of the CXC chemokine family, is a pro-inflammatory chemokine produced by immune cells under inflammatory conditions [75]. In the tumor microenvironment, IL-8 can not only enhance tumor cell proliferation or transformation into a migratory or stromal phenotype but also foster tumor angiogenesis or recruit additional immunosuppressive cells to the tumor, thereby promoting tumor progression [76]. In addition, cancer cells secrete IL-8, thus up-regulating the expression of matrix metalloproteinase-7 (MMP-7), which also contributes to OSCC invasion [77].

IL-1β stimulates the tyrosine phosphorylation of epidermal growth factor receptor (EGFR) through the chemokine ligand 1-receptor 2(CXCL1-CXCR2) axis, and regulates EGFR signal to promote the proliferation of dysplasia oral mucosa keratinocyte (DOK) and OSCC cells. However, a significant decrease in tyrosine phosphorylation of EGFR and a sharp decrease in DOK cell proliferation were observed by transfecting CXCL1-targeted short hairpin RNA (shRNA) with lentivirus or by using CXCR2 antagonists [78]. Lee et al. (2015) also find that IL-1β can promote the proliferation of DOK and OSCC cells, enhance the angiogenesis ability and the expression of epithelial-mesenchymal transition (EMT)-related genes Snail and Slug, and down-regulate expression of cadherin E, thereby resulting in OCC invasion and metastasis [79]. It is worth noting that IL-1β can activate the nuclear factor-κB (NF-κB) pathway and foster the expression and secretion of IL-6 and IL-8. As a powerful pro-inflammatory cytokine, IL-1β has been widely demonstrated to be upregulated in ovarian, lung, and gastrointestinal cancers, which are often associated with poor prognosis [80]. IL-10 is a representative anti-inflammatory and immunosuppressive factor that promotes immune escape of tumor cells [81]. A previous study has shown that in most OC samples, the expression of IL-10 is higher in tumor cells and stromal cells than in controls [82]. Based on our research results, IL6, IL8 and IL1β could be used as biomarkers of OC and serve as auxiliary diagnostic methods. Nonetheless, further studies are needed to explore the specific role of these cytokines in OSCC and investigate their diagnostic accuracy.

Strength, limitations, and Inspiration for future research

First of all, saliva detection provides a low-cost method for early diagnosis of oral cancer due to its advantages of non-invasive, convenient collection, processing and storage. And because saliva is in constant contact with oral lesions, it may be superior to blood or other body fluids. In our study, we found that several salivary cytokines (salivary cytokines) have strong diagnostic ability in oral cancer diagnosis. This suggests that in future studies, we can perform multiple cytokine tests on these three cytokines.

However, the study still has several limitations. The heterogeneity of the included studies was significant, similar to a previous meta-analysis [17]. As a result, the operating procedures for saliva collection, storage, and cytokine quantification should be standardized in the future. Additionally, a multicenter study with a larger sample size is warranted to rule out possible bias. Future studies should also consider some lifestyle factors, such as smoking and drinking, which may also influence IL levels (between cases and controls), although their influence may be wakened upon the occurrence of cancer [44, 65]. Few studies provided data on the sensitivity and specificity of IL-10 in diagnosing OC, so no relevant NMA was conducted. Further studies are desired to provide a more accurate evaluation of IL-10 in the diagnosis of OC. Some included studies conducted subgroup analysis by the stages of OC [16, 36, 45], but the correlation between cancer stages and cytokines was not investigated in our analysis. Since the early diagnosis of OSCC is closely related to the clinical treatment and prognosis of patients, further research in this area is necessary.

Previous studies [6] observed that IL-8 and il-6 concentrations in OC patients were significantly higher than those in OPMD patients, and also significantly increased compared with healthy subjects. This suggests that the amount of the increase may distinguish between oral cancer and precancerous states, lichen planus, periodontitis, or other inflammatory and infectious diseases. We look forward to conducting more control studies in the future to compare oral cancer with potential oral malignancies, oral inflammatory diseases, and even systemic inflammatory states to further improve its specificity in the diagnosis of oral cancer.

In addition, many studies have demonstrated the effects of cytokines in the treatment of cancers [83–86], so these cytokines provide an insight into future clinical treatment of OC.

Conclusion

This study suggests that salivary cytokines can be used as potential biomarkers for early diagnosis of OC. Given its high diagnostic specificity and sensitivity, TNF-α is recommended, followed by IL-6 and IL-8. Notably, salivary cytokine levels may be affected by other factors, such as potential malignant states, chronic local inflammation, and autoimmune diseases. Therefore, it is necessary to further distinguish the diagnostic accuracy of these cytokines in different disease states and compare them with OC and different OC stages. At the same time, more standard operating procedures and large-scale multi-center studies are needed to reduce bias and heterogeneity. It is believed that the TNF-α, IL-6, and IL-8 saliva test is an affordable technique for early clinical diagnosis of OC, which can provide novel insights into the targeted therapy of OC.

Supplementary Information

Supplementary Material 1.

Acknowledgements

Not applicable.

Author contributions

All authors contributed to the study conception and design. Lijun Huang: Conceptualization, Methodology, Software, Writing- Original draft, Data curation, Visualization were performed; Fen Luo: Investigation, Writing - Original Draft, Writing – Reviewing and Editing, Funding acquisition were performed; Mingsi Deng: Methodology, Software, Writing- Original draft were performed; Jie Zhang: Conceptualization, Supervision, Project administration, Funding acquisition were performed. All authors read and approved the final manuscript.

Funding

1. Changsha Natural Science Foundation. (No: kq2208484).

2. Research Program Project of Hunan Provincial Health and Wellness Commission. (No: 202108030155).

Availability of data and materials

All data supporting the findings of this study are available within the paper and its Supplementary Materials.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

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.
==== Refs
References

1. Sung H Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries CA Cancer J Clin 2021 71 3 209 249 10.3322/caac.21660 33538338
Sung H, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–49.33538338 10.3322/caac.21660
2. Sand L Jalouli J Viruses and oral cancer. Is there a link? Microbes Infect 2014 16 5 371 8 10.1016/j.micinf.2014.02.009 24613199
Sand L, Jalouli J. Viruses and oral cancer. Is there a link? Microbes Infect. 2014;16(5):371–8.24613199 10.1016/j.micinf.2014.02.009
3. Chamoli A Overview of oral cavity squamous cell carcinoma: Risk factors, mechanisms, and diagnostics Oral Oncol 2021 121 105451 10.1016/j.oraloncology.2021.105451 34329869
Chamoli A, et al. Overview of oral cavity squamous cell carcinoma: Risk factors, mechanisms, and diagnostics. Oral Oncol. 2021;121: 105451.34329869 10.1016/j.oraloncology.2021.105451
4. Montero PH Patel SG Cancer of the oral cavity Surg Oncol Clin N Am 2015 24 3 491 508 10.1016/j.soc.2015.03.006 25979396
Montero PH, Patel SG. Cancer of the oral cavity. Surg Oncol Clin N Am. 2015;24(3):491–508.25979396 10.1016/j.soc.2015.03.006
5. Warnakulasuriya S Global epidemiology of oral and oropharyngeal cancer Oral Oncol 2009 45 4–5 309 316 10.1016/j.oraloncology.2008.06.002 18804401
Warnakulasuriya S. Global epidemiology of oral and oropharyngeal cancer. Oral Oncol. 2009;45(4–5):309–16.18804401 10.1016/j.oraloncology.2008.06.002
6. Ferrari E Salivary Cytokines as Biomarkers for Oral Squamous Cell Carcinoma: A Systematic Review Int J Mol Sci 2021 22 13 6795 10.3390/ijms22136795 34202728
Ferrari E, et al. Salivary Cytokines as Biomarkers for Oral Squamous Cell Carcinoma: A Systematic Review. Int J Mol Sci. 2021;22(13):6795.34202728 10.3390/ijms22136795
7. Su YF Current Insights into Oral Cancer Diagnostics Diagnostics (Basel) 2021 11 7 1287 10.3390/diagnostics11071287 34359370
Su YF, et al. Current Insights into Oral Cancer Diagnostics. Diagnostics (Basel). 2021;11(7):1287.34359370 10.3390/diagnostics11071287
8. Chen XJ Nanotechnology: a promising method for oral cancer detection and diagnosis J Nanobiotechnology 2018 16 1 52 10.1186/s12951-018-0378-6 29890977
Chen XJ, et al. Nanotechnology: a promising method for oral cancer detection and diagnosis. J Nanobiotechnology. 2018;16(1):52.29890977 10.1186/s12951-018-0378-6
9. Meleti M Salivary biomarkers for diagnosis of systemic diseases and malignant tumors. A systematic review Med Oral Patol Oral Cir Bucal 2020 25 2 e299 e31 32040469
Meleti M. Salivary biomarkers for diagnosis of systemic diseases and malignant tumors. A systematic review. Med Oral Patol Oral Cir Bucal. 2020;25(2):e299–e31.32040469
10. Cristaldi M Salivary Biomarkers for Oral Squamous Cell Carcinoma Diagnosis and Follow-Up: Current Status and Perspectives Front Physiol 2019 10 1476 10.3389/fphys.2019.01476 31920689
Cristaldi M, et al. Salivary Biomarkers for Oral Squamous Cell Carcinoma Diagnosis and Follow-Up: Current Status and Perspectives. Front Physiol. 2019;10:1476.31920689 10.3389/fphys.2019.01476
11. Nisar S Chemokine-Cytokine Networks in the Head and Neck Tumor Microenvironment Int J Mol Sci 2021 22 9 4584 10.3390/ijms22094584 33925575
Nisar S. Chemokine-Cytokine Networks in the Head and Neck Tumor Microenvironment. Int J Mol Sci. 2021;22(9):4584.33925575 10.3390/ijms22094584
12. Chen Z Expression of proinflammatory and proangiogenic cytokines in patients with head and neck cancer Clin Cancer Res 1999 5 6 1369 1379 10389921
Chen Z, et al. Expression of proinflammatory and proangiogenic cytokines in patients with head and neck cancer. Clin Cancer Res. 1999;5(6):1369–79.10389921
13. Chow LQM Head and Neck Cancer N Engl J Med 2020 382 1 60 72 10.1056/NEJMra1715715 31893516
Chow LQM. Head and Neck Cancer. N Engl J Med. 2020;382(1):60–72.31893516 10.1056/NEJMra1715715
14. Alevizos I Oral cancer in vivo gene expression profiling assisted by laser capture microdissection and microarray analysis Oncogene 2001 20 43 6196 6204 10.1038/sj.onc.1204685 11593428
Alevizos I, et al. Oral cancer in vivo gene expression profiling assisted by laser capture microdissection and microarray analysis. Oncogene. 2001;20(43):6196–204.11593428 10.1038/sj.onc.1204685
15. Goertzen C Oral inflammation promotes oral squamous cell carcinoma invasion Oncotarget 2018 9 49 29047 29063 10.18632/oncotarget.25540 30018735
Goertzen C, et al. Oral inflammation promotes oral squamous cell carcinoma invasion. Oncotarget. 2018;9(49):29047–63.30018735 10.18632/oncotarget.25540
16. Dikova V Jantus-Lewintre E Bagan J Potential Non-Invasive Biomarkers for Early Diagnosis of Oral Squamous Cell Carcinoma J Clin Med 2021 10 8 1658 10.3390/jcm10081658 33924500
Dikova V, Jantus-Lewintre E, Bagan J. Potential Non-Invasive Biomarkers for Early Diagnosis of Oral Squamous Cell Carcinoma. J Clin Med. 2021;10(8):1658.33924500 10.3390/jcm10081658
17. Chiamulera MMA Salivary cytokines as biomarkers of oral cancer: a systematic review and meta-analysis BMC Cancer 2021 21 1 205 10.1186/s12885-021-07932-3 33639868
Chiamulera MMA, et al. Salivary cytokines as biomarkers of oral cancer: a systematic review and meta-analysis. BMC Cancer. 2021;21(1):205.33639868 10.1186/s12885-021-07932-3
18. O'Sullivan JW Network meta-analysis for diagnostic tests BMJ Evid Based Med 2019 24 5 192 193 10.1136/bmjebm-2019-111179 30975716
O’Sullivan JW. Network meta-analysis for diagnostic tests. BMJ Evid Based Med. 2019;24(5):192–3.30975716 10.1136/bmjebm-2019-111179
19. Veroniki AA Diagnostic test accuracy network meta-analysis methods: A scoping review and empirical assessment J Clin Epidemiol 2022 146 86 96 10.1016/j.jclinepi.2022.02.001 35181490
Veroniki AA, et al. Diagnostic test accuracy network meta-analysis methods: A scoping review and empirical assessment. J Clin Epidemiol. 2022;146:86–96.35181490 10.1016/j.jclinepi.2022.02.001
20. Moher D Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement BMJ 2009 339 b2535 10.1136/bmj.b2535 19622551
Moher D, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339: b2535.19622551 10.1136/bmj.b2535
21. Stang A Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses Eur J Epidemiol 2010 25 9 603 605 10.1007/s10654-010-9491-z 20652370
Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–5.20652370 10.1007/s10654-010-9491-z
22. Whiting PF QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies Ann Intern Med 2011 155 8 529 536 10.7326/0003-4819-155-8-201110180-00009 22007046
Whiting PF, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–36.22007046 10.7326/0003-4819-155-8-201110180-00009
23. Ma X A Bayesian hierarchical model for network meta-analysis of multiple diagnostic tests Biostatistics 2018 19 1 87 102 10.1093/biostatistics/kxx025 28586407
Ma X, et al. A Bayesian hierarchical model for network meta-analysis of multiple diagnostic tests. Biostatistics. 2018;19(1):87–102.28586407 10.1093/biostatistics/kxx025
24. Nyaga VN Aerts M Arbyn M ANOVA model for network meta-analysis of diagnostic test accuracy data Stat Methods Med Res 2018 27 6 1766 1784 10.1177/0962280216669182 27655805
Nyaga VN, Aerts M, Arbyn M. ANOVA model for network meta-analysis of diagnostic test accuracy data. Stat Methods Med Res. 2018;27(6):1766–84.27655805 10.1177/0962280216669182
25. Singh P Verma JK Singh JK Validation of Salivary Markers, IL-1β, IL-8 and Lgals3bp for Detection of Oral Squamous Cell Carcinoma in an Indian Population Sci Rep 2020 10 1 7365 10.1038/s41598-020-64494-3 32355279
Singh P, Verma JK, Singh JK. Validation of Salivary Markers, IL-1β, IL-8 and Lgals3bp for Detection of Oral Squamous Cell Carcinoma in an Indian Population. Sci Rep. 2020;10(1):7365.32355279 10.1038/s41598-020-64494-3
26. Sabarathinam J Selvaraj J Devi S Estimation of Levels of Glutathione Peroxidase (Gpx), Malondialdehyde (Mda), Tumor Necrosis Factor Alpha (Tnf Alpha) and Alpha Feto Protein (Afp) In Saliva of Potentially Malignant Disorders and Oral Squamous Cell Carcinoma Biomed Pharmacol J. 2019 12 4 1881 6 10.13005/bpj/1818
Sabarathinam J, Selvaraj J, Devi S. Estimation of Levels of Glutathione Peroxidase (Gpx), Malondialdehyde (Mda), Tumor Necrosis Factor Alpha (Tnf Alpha) and Alpha Feto Protein (Afp) In Saliva of Potentially Malignant Disorders and Oral Squamous Cell Carcinoma. Biomed Pharmacol J. 2019;12(4):1881–6.10.13005/bpj/1818
27. Deepthi G Nandan SRK Kulkarni PG Salivary Tumour Necrosis Factor-α as a Biomarker in Oral Leukoplakia and Oral Squamous Cell Carcinoma Asian Pac J Cancer Prev 2019 720 7 2087 93
Deepthi G, Nandan SRK, Kulkarni PG. Salivary Tumour Necrosis Factor-α as a Biomarker in Oral Leukoplakia and Oral Squamous Cell Carcinoma. Asian Pac J Cancer Prev. 2019;720(7):2087–93.
28. Ameena M Rathy R Evaluation of tumor necrosis factor: Alpha in the saliva of oral cancer, leukoplakia, and healthy controls - A comparative study Journal of International Oral Health 2019 11 2 92 99 10.4103/jioh.jioh_202_18
Ameena M, Rathy R. Evaluation of tumor necrosis factor: Alpha in the saliva of oral cancer, leukoplakia, and healthy controls - A comparative study. Journal of International Oral Health. 2019;11(2):92–9.10.4103/jioh.jioh_202_18
29. Rajkumar K Validation of the diagnostic utility of salivary interleukin 8 in the differentiation of potentially malignant oral lesions and oral squamous cell carcinoma in a region with high endemicity Oral Surg Oral Med Oral Pathol Oral Radiol 2014 118 3 309 319 10.1016/j.oooo.2014.04.008 24950604
Rajkumar K, et al. Validation of the diagnostic utility of salivary interleukin 8 in the differentiation of potentially malignant oral lesions and oral squamous cell carcinoma in a region with high endemicity. Oral Surg Oral Med Oral Pathol Oral Radiol. 2014;118(3):309–19.24950604 10.1016/j.oooo.2014.04.008
30. Krishnan R Association of serum and salivary tumor necrosis factor-α with histological grading in oral cancer and its role in differentiating premalignant and malignant oral disease Asian Pac J Cancer Prev 2014 15 17 7141 7148 10.7314/APJCP.2014.15.17.7141 25227804
Krishnan R, et al. Association of serum and salivary tumor necrosis factor-α with histological grading in oral cancer and its role in differentiating premalignant and malignant oral disease. Asian Pac J Cancer Prev. 2014;15(17):7141–8.25227804 10.7314/APJCP.2014.15.17.7141
31. Sato J Correlation between salivary interleukin-6 levels and early locoregional recurrence in patients with oral squamous cell carcinoma: preliminary study Head Neck 2013 35 6 889 894 10.1002/hed.23056 22887132
Sato J, et al. Correlation between salivary interleukin-6 levels and early locoregional recurrence in patients with oral squamous cell carcinoma: preliminary study. Head Neck. 2013;35(6):889–94.22887132 10.1002/hed.23056
32. Punyani SR Sathawane RS Salivary level of interleukin-8 in oral precancer and oral squamous cell carcinoma Clin Oral Investig 2013 17 2 517 524 10.1007/s00784-012-0723-3 22526890
Punyani SR, Sathawane RS. Salivary level of interleukin-8 in oral precancer and oral squamous cell carcinoma. Clin Oral Investig. 2013;17(2):517–24.22526890 10.1007/s00784-012-0723-3
33. Sato J Changes in saliva interleukin-6 levels in patients with oral squamous cell carcinoma Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2010 110 3 330 336 10.1016/j.tripleo.2010.03.040 20598594
Sato J, et al. Changes in saliva interleukin-6 levels in patients with oral squamous cell carcinoma. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2010;110(3):330–6.20598594 10.1016/j.tripleo.2010.03.040
34. SahebJamee M Salivary concentration of TNFalpha, IL1 alpha, IL6, and IL8 in oral squamous cell carcinoma Med Oral Patol Oral Cir Bucal 2008 13 5 E292 E295 18449112
SahebJamee M, et al. Salivary concentration of TNFalpha, IL1 alpha, IL6, and IL8 in oral squamous cell carcinoma. Med Oral Patol Oral Cir Bucal. 2008;13(5):E292–5.18449112
35. Katakura A Comparison of salivary cytokine levels in oral cancer patients and healthy subjects Bull Tokyo Dent Coll 2007 48 4 199 203 10.2209/tdcpublication.48.199 18360107
Katakura A, et al. Comparison of salivary cytokine levels in oral cancer patients and healthy subjects. Bull Tokyo Dent Coll. 2007;48(4):199–203.18360107 10.2209/tdcpublication.48.199
36. Lee LT Evaluation of saliva and plasma cytokine biomarkers in patients with oral squamous cell carcinoma Int J Oral Maxillofac Surg 2018 47 6 699 707 10.1016/j.ijom.2017.09.016 29174861
Lee LT, et al. Evaluation of saliva and plasma cytokine biomarkers in patients with oral squamous cell carcinoma. Int J Oral Maxillofac Surg. 2018;47(6):699–707.29174861 10.1016/j.ijom.2017.09.016
37. Zhang S Variation and significance of secretory immunoglobulin A, interleukin 6 and dendritic cells in oral cancer Oncol Lett 2017 13 4 2297 2303 10.3892/ol.2017.5703 28454394
Zhang S, et al. Variation and significance of secretory immunoglobulin A, interleukin 6 and dendritic cells in oral cancer. Oncol Lett. 2017;13(4):2297–303.28454394 10.3892/ol.2017.5703
38. Shahidi, M, et al. Predictive value of salivary microRNA-320a, vascular endothelial growth factor receptor 2, CRP and IL-6 in Oral lichen planus progression. Inflammopharmacology. 2017.
39. Khyani IAM Detection of interleukins-6 and 8 in saliva as potential biomarkers of oral pre-malignant lesion and oral carcinoma: A breakthrough in salivary diagnostics in Pakistan Pak J Pharm Sci 2017 30 3 817 823 28653927
Khyani IAM, et al. Detection of interleukins-6 and 8 in saliva as potential biomarkers of oral pre-malignant lesion and oral carcinoma: A breakthrough in salivary diagnostics in Pakistan. Pak J Pharm Sci. 2017;30(3):817–23.28653927
40. Dineshkumar T Salivary and Serum Interleukin-6 Levels in Oral Premalignant Disorders and Squamous Cell Carcinoma: Diagnostic Value and Clinicopathologic Correlations Asian Pac J Cancer Prev 2016 17 11 4899 4906 28032493
Dineshkumar T, et al. Salivary and Serum Interleukin-6 Levels in Oral Premalignant Disorders and Squamous Cell Carcinoma: Diagnostic Value and Clinicopathologic Correlations. Asian Pac J Cancer Prev. 2016;17(11):4899–906.28032493
41. Panneer Selvam N Sadaksharam J Salivary interleukin-6 in the detection of oral cancer and precancer Asia Pac J Clin Oncol 2015 11 3 236 41 10.1111/ajco.12330 25560781
Panneer Selvam N, Sadaksharam J. Salivary interleukin-6 in the detection of oral cancer and precancer. Asia Pac J Clin Oncol. 2015;11(3):236–41.25560781 10.1111/ajco.12330
42. Sato J Differences in sequential posttreatment salivary IL-6 levels between patients with and patients without locoregional recurrences of oral squamous cell carcinoma: Part III of a cohort study Oral Surg Oral Med Oral Pathol Oral Radiol 2015 120 6 751 60.e2 10.1016/j.oooo.2015.08.016 26548727
Sato J, et al. Differences in sequential posttreatment salivary IL-6 levels between patients with and patients without locoregional recurrences of oral squamous cell carcinoma: Part III of a cohort study. Oral Surg Oral Med Oral Pathol Oral Radiol. 2015;120(6):751–60.e2.26548727 10.1016/j.oooo.2015.08.016
43. Aziz S Salivary Immunosuppressive Cytokines IL-10 and IL-13 Are Significantly Elevated in Oral Squamous Cell Carcinoma Patients Cancer Invest 2015 33 7 318 328 10.3109/07357907.2015.1041642 26046681
Aziz S, et al. Salivary Immunosuppressive Cytokines IL-10 and IL-13 Are Significantly Elevated in Oral Squamous Cell Carcinoma Patients. Cancer Invest. 2015;33(7):318–28.26046681 10.3109/07357907.2015.1041642
44. Piyarathne NS Salivary Interleukin Levels in Oral Squamous Cell Carcinoma and Oral Epithelial Dysplasia: Findings from a Sri Lankan Study Cancers (Basel). 2023 15 5 1510 10.3390/cancers15051510 36900301
Piyarathne NS, et al. Salivary Interleukin Levels in Oral Squamous Cell Carcinoma and Oral Epithelial Dysplasia: Findings from a Sri Lankan Study. Cancers (Basel). 2023;15(5):1510.36900301 10.3390/cancers15051510
45. Babiuch K Evaluation of Proinflammatory, NF-kappaB Dependent Cytokines: IL-1α, IL-6, IL-8, and TNF-α in Tissue Specimens and Saliva of Patients with Oral Squamous Cell Carcinoma and Oral Potentially Malignant Disorders J Clin Med. 2020 9 3 867 10.3390/jcm9030867 32245251
Babiuch K, et al. Evaluation of Proinflammatory, NF-kappaB Dependent Cytokines: IL-1α, IL-6, IL-8, and TNF-α in Tissue Specimens and Saliva of Patients with Oral Squamous Cell Carcinoma and Oral Potentially Malignant Disorders. J Clin Med. 2020;9(3):867.32245251 10.3390/jcm9030867
46. Márton IJ Salivary IL-6 mRNA is a Robust Biomarker in Oral Squamous Cell Carcinoma J Clin Med 2019 8 11 1958 10.3390/jcm8111958 31766212
Márton, IJ. et al. Salivary IL-6 mRNA is a Robust Biomarker in Oral Squamous Cell Carcinoma. J Clin Med. 2019;8(11):1958.31766212 10.3390/jcm8111958
47. Csősz É Proteomics investigation of OSCC-specific salivary biomarkers in a Hungarian population highlights the importance of identification of population-tailored biomarkers PLoS ONE 2017 12 5 e0177282 10.1371/journal.pone.0177282 28545132
Csősz É, et al. Proteomics investigation of OSCC-specific salivary biomarkers in a Hungarian population highlights the importance of identification of population-tailored biomarkers. PLoS ONE. 2017;12(5): e0177282.28545132 10.1371/journal.pone.0177282
48. Polz-Dacewicz M Salivary and serum IL-10, TNF-α, TGF-β, VEGF levels in oropharyngeal squamous cell carcinoma and correlation with HPV and EBV infections Infect Agent Cancer 2016 11 45 10.1186/s13027-016-0093-6 27547238
Polz-Dacewicz M, et al. Salivary and serum IL-10, TNF-α, TGF-β, VEGF levels in oropharyngeal squamous cell carcinoma and correlation with HPV and EBV infections. Infect Agent Cancer. 2016;11:45.27547238 10.1186/s13027-016-0093-6
49. Bagan L Salivary and serum interleukin-6 levels in proliferative verrucous leukoplakia Clin Oral Investig 2016 20 4 737 743 10.1007/s00784-015-1551-z 26254143
Bagan L, et al. Salivary and serum interleukin-6 levels in proliferative verrucous leukoplakia. Clin Oral Investig. 2016;20(4):737–43.26254143 10.1007/s00784-015-1551-z
50. Radulescu R Biomarkers of Oxidative Stress, Proliferation, Inflammation and Invasivity in Saliva from Oral Cancer Patients Journal of Analytical Oncology 2015 4 52 57 10.6000/1927-7229.2015.04.01.9
Radulescu R, et al. Biomarkers of Oxidative Stress, Proliferation, Inflammation and Invasivity in Saliva from Oral Cancer Patients. Journal of Analytical Oncology. 2015;4:52–7.10.6000/1927-7229.2015.04.01.9
51. Gonçalves AS Immunosuppressive mediators of oral squamous cell carcinoma in tumour samples and saliva Hum Immunol 2015 76 1 52 58 10.1016/j.humimm.2014.11.002 25500427
Gonçalves AS, et al. Immunosuppressive mediators of oral squamous cell carcinoma in tumour samples and saliva. Hum Immunol. 2015;76(1):52–8.25500427 10.1016/j.humimm.2014.11.002
52. Juretić M Salivary levels of TNF-α and IL-6 in patients with oral premalignant and malignant lesions Folia Biol (Praha) 2013 59 2 99 102 10.14712/fb2013059020099 23746176
Juretić M, et al. Salivary levels of TNF-α and IL-6 in patients with oral premalignant and malignant lesions. Folia Biol (Praha). 2013;59(2):99–102.23746176 10.14712/fb2013059020099
53. Brailo V Salivary and serum interleukin 1 beta, interleukin 6 and tumor necrosis factor alpha in patients with leukoplakia and oral cancer Med Oral Patol Oral Cir Bucal 2012 17 1 e10 e15 10.4317/medoral.17323 21743397
Brailo V, et al. Salivary and serum interleukin 1 beta, interleukin 6 and tumor necrosis factor alpha in patients with leukoplakia and oral cancer. Med Oral Patol Oral Cir Bucal. 2012;17(1):e10–5.21743397 10.4317/medoral.17323
54. Laliberté C Characterization of Oral Squamous Cell Carcinoma Associated Inflammation: A Pilot Study Front Oral Health 2021 2 740469 10.3389/froh.2021.740469 35048057
Laliberté C, et al. Characterization of Oral Squamous Cell Carcinoma Associated Inflammation: A Pilot Study. Front Oral Health. 2021;2: 740469.35048057 10.3389/froh.2021.740469
55. Gleber-Netto FO Salivary Biomarkers for Detection of Oral Squamous Cell Carcinoma in a Taiwanese Population Clin Cancer Res 2016 22 13 3340 3347 10.1158/1078-0432.CCR-15-1761 26847061
Gleber-Netto FO, et al. Salivary Biomarkers for Detection of Oral Squamous Cell Carcinoma in a Taiwanese Population. Clin Cancer Res. 2016;22(13):3340–7.26847061 10.1158/1078-0432.CCR-15-1761
56. Lisa Cheng YS Salivary interleukin-6 and -8 in patients with oral cancer and patients with chronic oral inflammatory diseases J Periodontol 2014 85 7 956 965 10.1902/jop.2013.130320 24147842
Lisa Cheng YS, et al. Salivary interleukin-6 and -8 in patients with oral cancer and patients with chronic oral inflammatory diseases. J Periodontol. 2014;85(7):956–65.24147842 10.1902/jop.2013.130320
57. Elashoff D Prevalidation of salivary biomarkers for oral cancer detection Cancer Epidemiol Biomarkers Prev 2012 21 4 664 672 10.1158/1055-9965.EPI-11-1093 22301830
Elashoff D, et al. Prevalidation of salivary biomarkers for oral cancer detection. Cancer Epidemiol Biomarkers Prev. 2012;21(4):664–72.22301830 10.1158/1055-9965.EPI-11-1093
58. Korostoff A The role of salivary cytokine biomarkers in tongue cancer invasion and mortality Oral Oncol 2011 47 4 282 287 10.1016/j.oraloncology.2011.02.006 21397550
Korostoff A, et al. The role of salivary cytokine biomarkers in tongue cancer invasion and mortality. Oral Oncol. 2011;47(4):282–7.21397550 10.1016/j.oraloncology.2011.02.006
59. Brinkmann O Oral squamous cell carcinoma detection by salivary biomarkers in a Serbian population Oral Oncol 2011 47 1 51 55 10.1016/j.oraloncology.2010.10.009 21109482
Brinkmann O, et al. Oral squamous cell carcinoma detection by salivary biomarkers in a Serbian population. Oral Oncol. 2011;47(1):51–5.21109482 10.1016/j.oraloncology.2010.10.009
60. Arellano-Garcia ME Multiplexed immunobead-based assay for detection of oral cancer protein biomarkers in saliva Oral Dis 2008 14 8 705 712 10.1111/j.1601-0825.2008.01488.x 19193200
Arellano-Garcia ME, et al. Multiplexed immunobead-based assay for detection of oral cancer protein biomarkers in saliva. Oral Dis. 2008;14(8):705–12.19193200 10.1111/j.1601-0825.2008.01488.x
61. Rhodus NL The feasibility of monitoring NF-kappaB associated cytokines: TNF-alpha, IL-1alpha, IL-6, and IL-8 in whole saliva for the malignant transformation of oral lichen planus Mol Carcinog 2005 44 2 77 82 10.1002/mc.20113 16075467
Rhodus NL, et al. The feasibility of monitoring NF-kappaB associated cytokines: TNF-alpha, IL-1alpha, IL-6, and IL-8 in whole saliva for the malignant transformation of oral lichen planus. Mol Carcinog. 2005;44(2):77–82.16075467 10.1002/mc.20113
62. St John MA Interleukin 6 and interleukin 8 as potential biomarkers for oral cavity and oropharyngeal squamous cell carcinoma Arch Otolaryngol Head Neck Surg 2004 130 8 929 935 10.1001/archotol.130.8.929 15313862
St John MA, et al. Interleukin 6 and interleukin 8 as potential biomarkers for oral cavity and oropharyngeal squamous cell carcinoma. Arch Otolaryngol Head Neck Surg. 2004;130(8):929–35.15313862 10.1001/archotol.130.8.929
63. Rhodus NL NF-kappaB dependent cytokine levels in saliva of patients with oral preneoplastic lesions and oral squamous cell carcinoma Cancer Detect Prev 2005 29 1 42 45 10.1016/j.cdp.2004.10.003 15734216
Rhodus NL, et al. NF-kappaB dependent cytokine levels in saliva of patients with oral preneoplastic lesions and oral squamous cell carcinoma. Cancer Detect Prev. 2005;29(1):42–5.15734216 10.1016/j.cdp.2004.10.003
64. Selvam NP Sadaksharam J Salivary interleukin-6 in the detection of oral cancer and precancer Asia Pac J Clin Oncol 2015 11 3 236 241 10.1111/ajco.12330 25560781
Selvam NP, Sadaksharam J. Salivary interleukin-6 in the detection of oral cancer and precancer. Asia Pac J Clin Oncol. 2015;11(3):236–41.25560781 10.1111/ajco.12330
65. Piyarathne NS Diagnostic salivary biomarkers in oral cancer and oral potentially malignant disorders and their relationships to risk factors - A systematic review Expert Rev Mol Diagn 2021 21 8 789 807 10.1080/14737159.2021.1944106 34148471
Piyarathne NS, et al. Diagnostic salivary biomarkers in oral cancer and oral potentially malignant disorders and their relationships to risk factors - A systematic review. Expert Rev Mol Diagn. 2021;21(8):789–807.34148471 10.1080/14737159.2021.1944106
66. Galdiero MR. Marone G Mantovani A  Cancer Inflammation and Cytokines Cold Spring Harb Perspect Biol, 2018 10 8 a028662. 10.1101/cshperspect.a028662 28778871
Galdiero MR., Marone G, Mantovani A.  Cancer Inflammation and Cytokines. Cold Spring Harb Perspect Biol,. 2018;10(8):a028662.28778871 10.1101/cshperspect.a028662
67. Li L Effects of immune cells and cytokines on inflammation and immunosuppression in the tumor microenvironment Int Immunopharmacol 2020 88 106939 10.1016/j.intimp.2020.106939 33182039
Li L, et al. Effects of immune cells and cytokines on inflammation and immunosuppression in the tumor microenvironment. Int Immunopharmacol. 2020;88: 106939.33182039 10.1016/j.intimp.2020.106939
68. Rezaei F Evaluation of Serum and Salivary Interleukin-6 and Interleukin-8 Levels in Oral Squamous Cell Carcinoma Patients: Systematic Review and Meta-Analysis J Interferon Cytokine Res 2019 39 12 727 739 10.1089/jir.2019.0070 31314647
Rezaei F, et al. Evaluation of Serum and Salivary Interleukin-6 and Interleukin-8 Levels in Oral Squamous Cell Carcinoma Patients: Systematic Review and Meta-Analysis. J Interferon Cytokine Res. 2019;39(12):727–39.31314647 10.1089/jir.2019.0070
69. Mahdavi Sharif P Importance of TNF-alpha and its alterations in the development of cancers Cytokine 2020 130 155066 10.1016/j.cyto.2020.155066 32208336
Mahdavi Sharif P, et al. Importance of TNF-alpha and its alterations in the development of cancers. Cytokine. 2020;130: 155066.32208336 10.1016/j.cyto.2020.155066
70. Sun Z Effect of interleukin-1β and tumor necrosis factor α gene silencing on mouse gastric cancer cell proliferation and migration Oncol Lett 2016 11 4 2559 2565 10.3892/ol.2016.4253 27073517
Sun Z, et al. Effect of interleukin-1β and tumor necrosis factor α gene silencing on mouse gastric cancer cell proliferation and migration. Oncol Lett. 2016;11(4):2559–65.27073517 10.3892/ol.2016.4253
71. Ho MY TNF-α induces epithelial-mesenchymal transition of renal cell carcinoma cells via a GSK3β-dependent mechanism Mol Cancer Res 2012 10 8 1109 1119 10.1158/1541-7786.MCR-12-0160 22707636
Ho MY, et al. TNF-α induces epithelial-mesenchymal transition of renal cell carcinoma cells via a GSK3β-dependent mechanism. Mol Cancer Res. 2012;10(8):1109–19.22707636 10.1158/1541-7786.MCR-12-0160
72. Glogauer JE Neutrophils Increase Oral Squamous Cell Carcinoma Invasion through an Invadopodia-Dependent Pathway Cancer Immunol Res 2015 3 11 1218 1226 10.1158/2326-6066.CIR-15-0017 26112922
Glogauer JE, et al. Neutrophils Increase Oral Squamous Cell Carcinoma Invasion through an Invadopodia-Dependent Pathway. Cancer Immunol Res. 2015;3(11):1218–26.26112922 10.1158/2326-6066.CIR-15-0017
73. Serefoglou Z Genetic association of cytokine DNA polymorphisms with head and neck cancer Oral Oncol 2008 44 12 1093 1099 10.1016/j.oraloncology.2008.02.012 18486534
Serefoglou Z, et al. Genetic association of cytokine DNA polymorphisms with head and neck cancer. Oral Oncol. 2008;44(12):1093–9.18486534 10.1016/j.oraloncology.2008.02.012
74. Jones SA Jenkins BJ Recent insights into targeting the IL-6 cytokine family in inflammatory diseases and cancer Nat Rev Immunol 2018 18 12 773 789 10.1038/s41577-018-0066-7 30254251
Jones SA, Jenkins BJ. Recent insights into targeting the IL-6 cytokine family in inflammatory diseases and cancer. Nat Rev Immunol. 2018;18(12):773–89.30254251 10.1038/s41577-018-0066-7
75. Matsushima K Yang D Oppenheim JJ Interleukin-8: An evolving chemokine Cytokine 2022 153 155828 10.1016/j.cyto.2022.155828 35247648
Matsushima K, Yang D, Oppenheim JJ. Interleukin-8: An evolving chemokine. Cytokine. 2022;153: 155828.35247648 10.1016/j.cyto.2022.155828
76. Fousek K Horn LA Palena C Interleukin-8: A chemokine at the intersection of cancer plasticity, angiogenesis, and immune suppression Pharmacol Ther 2021 219 107692 10.1016/j.pharmthera.2020.107692 32980444
Fousek K, Horn LA, Palena C. Interleukin-8: A chemokine at the intersection of cancer plasticity, angiogenesis, and immune suppression. Pharmacol Ther. 2021;219: 107692.32980444 10.1016/j.pharmthera.2020.107692
77. Watanabe H Role of interleukin-8 secreted from human oral squamous cell carcinoma cell lines Oral Oncol 2002 38 7 670 679 10.1016/S1368-8375(02)00006-4 12167419
Watanabe H, et al. Role of interleukin-8 secreted from human oral squamous cell carcinoma cell lines. Oral Oncol. 2002;38(7):670–9.12167419 10.1016/S1368-8375(02)00006-4
78. Lee CH Interleukin-1 beta transactivates epidermal growth factor receptor via the CXCL1-CXCR2 axis in oral cancer Oncotarget 2015 6 36 38866 38880 10.18632/oncotarget.5640 26462152
Lee CH, et al. Interleukin-1 beta transactivates epidermal growth factor receptor via the CXCL1-CXCR2 axis in oral cancer. Oncotarget. 2015;6(36):38866–80.26462152 10.18632/oncotarget.5640
79. Lee CH IL-1β promotes malignant transformation and tumor aggressiveness in oral cancer J Cell Physiol 2015 230 4 875 884 10.1002/jcp.24816 25204733
Lee CH, et al. IL-1β promotes malignant transformation and tumor aggressiveness in oral cancer. J Cell Physiol. 2015;230(4):875–84.25204733 10.1002/jcp.24816
80. Zhang D Association of IL-1beta gene polymorphism with cachexia from locally advanced gastric cancer BMC Cancer 2007 7 45 10.1186/1471-2407-7-45 17359523
Zhang D, et al. Association of IL-1beta gene polymorphism with cachexia from locally advanced gastric cancer. BMC Cancer. 2007;7:45.17359523 10.1186/1471-2407-7-45
81. Kondoh N Immunomodulatory aspects in the progression and treatment of oral malignancy Jpn Dent Sci Rev 2019 55 1 113 120 10.1016/j.jdsr.2019.09.001 31660091
Kondoh N, et al. Immunomodulatory aspects in the progression and treatment of oral malignancy. Jpn Dent Sci Rev. 2019;55(1):113–20.31660091 10.1016/j.jdsr.2019.09.001
82. Arantes DA Overexpression of immunosuppressive cytokines is associated with poorer clinical stage of oral squamous cell carcinoma Arch Oral Biol 2016 61 28 35 10.1016/j.archoralbio.2015.10.013 26513679
Arantes DA, et al. Overexpression of immunosuppressive cytokines is associated with poorer clinical stage of oral squamous cell carcinoma. Arch Oral Biol. 2016;61:28–35.26513679 10.1016/j.archoralbio.2015.10.013
83. Nguyen KG Localized Interleukin-12 for Cancer Immunotherapy Front Immunol 2020 11 575597 10.3389/fimmu.2020.575597 33178203
Nguyen KG, et al. Localized Interleukin-12 for Cancer Immunotherapy. Front Immunol. 2020;11: 575597.33178203 10.3389/fimmu.2020.575597
84. Jaén M Interleukin 13 receptor alpha 2 (IL13Rα2): Expression, signaling pathways and therapeutic applications in cancer Biochim Biophys Acta Rev Cancer 2022 1877 5 188802 10.1016/j.bbcan.2022.188802 36152905
Jaén M, et al. Interleukin 13 receptor alpha 2 (IL13Rα2): Expression, signaling pathways and therapeutic applications in cancer. Biochim Biophys Acta Rev Cancer. 2022;1877(5): 188802.36152905 10.1016/j.bbcan.2022.188802
85. Raeber ME Sahin D Boyman O Interleukin-2-based therapies in cancer Sci Transl Med 2022 14 670 eabo5409 10.1126/scitranslmed.abo5409 36350987
Raeber ME, Sahin D, Boyman O. Interleukin-2-based therapies in cancer. Sci Transl Med. 2022;14(670):eabo5409.36350987 10.1126/scitranslmed.abo5409
86. Han Y IL-1β-associated NNT acetylation orchestrates iron-sulfur cluster maintenance and cancer immunotherapy resistance Mol Cell 2023 83 11 1887 1902.e8 10.1016/j.molcel.2023.05.011 37244254
Han Y, et al. IL-1β-associated NNT acetylation orchestrates iron-sulfur cluster maintenance and cancer immunotherapy resistance. Mol Cell. 2023;83(11):1887–1902.e8.37244254 10.1016/j.molcel.2023.05.011
