Six IL-8 gene polymorphisms and the entire cancer susceptibility according to a comprehensive analysis especially in prostate cancer

doi:10.21203/rs.3.rs-4366820/v1

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Six IL-8 gene polymorphisms and the entire cancer susceptibility according to a comprehensive analysis especially in prostate cancer

https://doi.org/10.21203/rs.3.rs-4366820/v1

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Background: Interleukin-8 (IL-8) primarily regulates cytotoxicity- and local immune response, antibody production, cellular immunity, and delayed hypersensitive inflammation. Emerging evidences suggest that IL-8 polymorphisms are strongly linked to various cancer risks, however, above correlation requires further confirmation.

Methods and Results: We screened and analyzed the aforementioned relationship from relevant published sources including Embase, PubMed, Chinese database, Google Scholar, and Web of Science till Jun 25, 2023. Associated strength analysis was employed through odds ratios and 95% confidence intervals. In addition, serum IL-8 expression about prostate cancer patients was detected by ELISA method. In all, we reviewed 104 case-control investigations, involving 26,029 cancer incidences and 31,577 healthy controls. Firstly, we demonstrated a strong correlation between the +2767 polymorphism and augmented cancer risk. Additionally, the +781 polymorphism elicited a strong increase in cancer risk among Caucasians. However, based on our cancer type subgroup analysis, there had markedly reduced association for hepatocellular carcinoma. Then, enhanced correlation was observed in all cancer samples for -251 polymorphism. Besides, we also revealed comparable results among in the Mixed/Asian populations, gastric cancer, lung cancer, hospital-based subgroup, and genotype method subgroup. Finally, -251 individuals carried AA/AC genotype had higher expression of IL-8 in serum than carrying CC individuals from prostate cancer patients.

Conclusion: Three IL-8 polymorphisms (+2767, +781 and -251) were intricately linked to cancer risk. Additional, -251 polymorphism may influence the expression of IL-8 in prostate cancer patients. Therefore, these polymorphisms may be excellent candidates for tumor biomarkers in the future.

Interleukin-8

polymorphism

risk

prostate cancer

meta-analysis

Rudolf Virchow reported a link between inflammation and cancer in the 19th century, based out of an observation that leukocytes specifically invaded tumor tissue(Balkwill and Mantovani). Inflammation is an essential component governing all stages of tumor progression, including initiation, progression, malignant transformation, infiltration, and metastasis(Deng et al.). Meanwhile, prolonged inflammation, lasting many years, causes severe DNA damage, which, in turn, can accelerate cancer progression(Greten and Grivennikov). In addition, inflammation can also accelerate drug resistance, thus, combating drug resistance is a robust tool for cancer prevention, recovery, and intervention in cancer (Tikoo et al.). Hence, an extensive elucidation of underlying inflammatory- and cancer-related mechanisms may be highly beneficial to the establishment of new, robust, and specific cancer therapies(Deng et al. ; Place and Kanneganti).

Interleukin 8 (IL-8) is an important inflammatory factor and strongly upregulated during inflammation, and it has enhanced interacting capacities with receptors, compared to C-X-C motif chemokine relatives. Thus, it is believed to be the primary agent that recruits neutrophils to sites of inflammation. Despite significant downregulation in neutrophil recruitment with monoclonal anti-IL-8 antibodies or small antagonists among disease animal models, scientists achieved no clinical benefit with IL-8 inhibition alone, indicating the necessity for combinational therapy(Matsushima et al.). For example, IL-8 or associated receptors C-X-C chemokine receptor 1 and 2 suppression among cancer patients, who underwent chemotherapy, exhibited greater tumor development and metastasis inhibition than controls(Ha et al.).

Given its critical roles in cancer development and polymorphisms may influence the expression of IL-8, numerous studies reported significant correlations between IL-8 polymorphisms and augmented cancer susceptibility. Despite several meta-analyses just for only one type cancer have been reported(Aleagha et al. 2021; Farbod et al. 2022), the link between IL-8 polymorphisms and cancer still remains unclear. Hence, we extensively analyzed the published articles from 104 case-control investigations to establish an evidenced-based conclusion regarding IL-8 polymorphisms and cancer risk, and evaluate the association between IL-8 -251 polymorphism and prostate cancer risk.

Screening and Assessment of Relevant Investigations

We retrieved relevant information from multiple scientific databases (Embase, PubMed, Chinese database, Google Scholar, and Web of Science) from the date of establishment till Jun 25, 2023. The employed search terms were ‘Interleukin-8’ or ‘IL-8’, and ‘polymorphism’, and ‘cancer’ or ‘tumor’. Collectively, we identified 973 relevant scientific papers, among which, 104 fit our strict inclusion and exclusion criteria. Additionally, we also manually screened references of relevant review articles.

Inclusion and Exclusion Criteria

The following research articles were included: (a) examined cancer association with IL-8 gene polymorphisms; (b) case-control study; and (c) case/control groups with adequate genotype frequency; (d) study based on the Hardy-Weinberg equilibrium (HWE). The following research articles were excluded from analysis: (a) absence of control, (b) no available data on genotype frequency, and (c) duplicated case-control groups.

Data Retrieval

We extracted the following information from the selected articles: last name of first author, publication year, corresponding author residing country, cancer category, ethnicity, control source, number of each genotype of cases and controls, HWE for control, and genotyping method.

Statistical Analysis

Study subjects were classified as Asian, Caucasian, African, and Mixed population. The control subgroup source was stratified into hospital-based (HB) and population-based (PB). The genotype methods were classified into Taqman, PCR-RFLP, ARMS-PCR, PCR, and AS-PCR. To determine genotype frequencies among cases and healthy controls (HCs), we used the odds ratios (OR) with 95% confidence intervals (CI) to evaluated the associations among the IL-8 gene polymorphisms and the whole cancer risk. Besides, the overall OR was assessed with the Z-test (Higgins and Thompson 2002). In presence of significance heterogeneity by Q-test (P >0.05), we employed the random-effects model; otherwise, the fixed-effects model was used (DerSimonian and Laird 1986; Mantel and Haenszel 1959). Five models (allelic contrast, homozygote comparison, dominant genetic model, heterozygote comparison, and recessive genetic model) was assessed to the correlation between various IL-8 gene polymorphisms and the entire cancer risk. The HWE from control groups was computed using the Pearson Chi-Square test. The Egger’s regression test and Begg’s funnel plots were employed for publication bias detection(Hayashino et al. 2005). All data analyses were conducted using Stata V11.2 (StataCorp LP, College Station, TX).

Participant Demographics

Herein, 100 patients, who were newly diagnosed of prostate cancer between Jun 1th, 2017 and Nov 1th, 2022, were recruited from the Affiliated Hospital of Jiangnan University. All diagnoses were based on histological examinations. HCs were age-matched to cancer patients, prostate specific antigen < 4.0 ng/mL, negative results from digital rectal examination, and no family history of prostate cancer. This work received ethical approval from the Affiliated Hospital of Jiangnan University, and obtained informed consent from all participants prior to the initiation of study.

Enzyme-Linked Immunosorbent Assay (ELISA)

Following standard blood collection without anticoagulants, the serum IL-8 content was measured using theELISA kit (Abcam Co. Ltd.), as described in a previous publication(Shao et al.). For further information, please refer to the following website: (https://www.abcam.cn/products/elisa/human-il-8-elisa-kit-ab214030.html).

Meta-Analysis Study Selection and Characteristics

In all, we selected 973 eligible articles using the aforementioned search terms, and only 104 (retrieved on 25 Jun 2023) fit our strict inclusion and exclusion criteria. In short, 698 duplications were eliminated. We identified 28 meta-analyses, 32 other gene polymorphisms, 16 clinical trials, 6 randomized controlled trials, 31 reviews, and 13 systematic reviews. Among the remaining 149 articles, 45 lacked complete genotyping information, which were excluded as well (Figure 1). Table 1 summarizes all characteristics of included studies (namely, first author information, ethnicity, year of publication, country, cancer category, HC and case quantity, genotyping methodology, HWE, and control sources). Among these, we identified 2 publications on -353 polymorphism, 2 on +678 polymorphism, 2 on +2767 polymorphism, 4 on +1633 polymorphism, 19 on +781 polymorphism, and 81 on -251 polymorphism. We also acquired the minor allele frequency (MAF) of +781 and -251 polymorphisms in six major global populations analyzed from 1000 Genomes Browser (https://www.ncbi.nlm.nih.gov/snp/rs2227306 or rs4073) (Figure 2). All analyzed studies were based on HWE.

Meta-Analysis

Table 2 lists the relationship between six distinct IL-8 polymorphisms and the overall cancer risk. No association was detected among IL-8 -353, +678, +1633 polymorphisms and cancer risk.

+2767 A/G site

In case of the +2767 site, we observed reduced association with cancer risk in three genetic models (A-allele vs. G-allele: OR = 0.766, 95%CI:0.616-0.953, P = 0.017; AA vs. GG: OR = 0.592, 95%CI:0.378-0.928, P = 0.022; AA vs. AG+GG: OR = 0.652, 95%CI:0.429-0.991, P = 0.045, Figure 3A).

+781 T/C site

We revealed enhanced association among Caucasians for the +781 T/C polymorphism (TT vs. TC+CC: OR = 1.472, 95%CI:1.078-2.009, P = 0.015, Figure 3B), but reduced relation in hepatocellular carcinoma (TT vs. CC: OR = 0.437, 95%CI:0.235-0.812, P = 0.009, Figure 3C; TT vs. TC+CC: OR = 0.499, 95%CI:0.349-0.711, P = 0.000).

-251A/G site

There were increased associations between the -251 polymorphism and total cancer risk (for example: A-allele vs. C-allele: OR=1.055, 95%CI:1.000-1.112, P = 0.049) among Mixed populations (AG vs. CC: OR=1.402, 95%CI:1.041-1.889, P = 0.026, Figure 4A), Asians (for example: A- vs. C-allele: OR = 1.102, 95%CI:1.014-1.197, P = 0.022, Figure 4B). In addition, in the ethnicity subgroup, similar positive results were found in gastric cancer (for example: A- vs. C-allele: OR = 1.155, 95%CI:1.057-1.262, P = 0.002, Figure 4C). However, reduced relation was present between -251 polymorphism and lung cancer risk (A- vs. C-allele: OR = 0.845, 95%CI:0.717-0.996, P = 0.045, Figure 4D). In the source of control, significant association was observed in HB (for example: A- vs. C-allele: OR = 1.078, 95%CI:1.005-1.155, P = 0.035, Figure 4E). Finally, in the subgroup of genotype method, increased relationship was detected in the PCR-RFLP (AG vs. CC: OR = 1.131, 95%CI:1.000-1.278, P = 0.050, Figure 4F), and AS-PCR methods (A- vs. C-allele: OR = 1.323, 95%CI:1.074-1.629, P = 0.008, Figure 4G).

Serum IL-8 Expression in Prostate Cancer Patients

Herein, we collected 100 serum samples from prostate cancer patients, specifically representing various genotypes of the IL-8 -251 variant. Based on our observation, the AA, AC, and CC genotype distribution was 19, 27, and 54, respectively. Additionally, we also assessed the serum IL-8 expression using ELISA. In particular, we examined the AA/AC and CC genotypes, our analysis revealed that the circulating IL-8 content among prostate cancer patients with the AA/AC genotypes were substantially elevated, compared to those with the CC genotypes (P = 0.0012, Figure 5).

Long-term inflammation or autoimmune diseases are intricately linked to numerous human diseases, including asthma, rheumatoid arthritis, systemic lupus erythematosus, inflammatory bowel disease, and cancer(Sohrab et al.). Tumor-related inflammation is the seventh major characteristic of all cancers(Colotta et al.). In tumor immune microenvironment, innate immune cells, particularly, monocytes and adaptive immune cells (e.g., T lymphocytes), associate with or release several inflammatory regulators like tumor necrosis factor and IL-8 which transmit abnormal signals from tumors(Sahai et al. ; Wang et al.).

Multiple meta-analyses reported on the strong connection between IL-8 gene polymorphisms and cancer. For example, Zhang et al. comprised 22 case-control investigations, involving 4259 cancer cases, 7006 HCs, and 5 polymorphisms (rs2227307, rs2227306, + 678T/C, rs1126647 and + 1633C/T), and revealed that only the rs2227306 polymorphism was protective against hepatocellular carcinoma development(Zhang et al.). In addition, Wang et al. analyzed 12917 cases with varying cancer categories and 17689 HCs from 47 publications, and demonstrated that the − 251 polymorphism was strongly related to enhanced cancer risk(Wang et al.). However, despite multiple investigations examining this potential relationship, the overall conclusion remains unclear.

Herein, we employed 104 case-control studies, involving 26,029 cancer incidences and 31,577 HCs. We revealed no discernible differences in tumor risk based on three IL-8 polymorphisms (-353, + 678, +1633) in our genetic model. Meanwhile, the + 2767 polymorphism protected against cancer susceptibility. However, the + 781 polymorphism exhibited differing relations with cancer risk. Alternately, we observed an increased relationship with Caucasians; and a decreased relationship with hepatocellular carcinoma incidence. We observed comparable results in the − 251 polymorphism, with reduced correlation with lung cancer. Conversely, there had enhanced association in the whole samples, ethnicity (Mixed and Asian population), gastric cancer, HB, PCR-RFLP, and AS-PCR subgroups. The potential reasons may be as follows: a given gene polymorphism may serve varying functions in distinct cancer categories, likely due to differences in cancer pathology. Additionally, the same gene and its polymorphisms may be responsible for several physiological activities. Inter-ethnic genetic and environmental differences may be another factor, along with linkage disequilibrium patterns, that regulates differential gene polymorphisms’ function among different patient populations. The two aforementioned polymorphisms (-251 and + 781) have great potential as clinical bioindicators of cancer risk. For instance, someone carrying A-allele or the AA genotype may possess an enhanced likelihood of developing prostate cancer. Thus, early detection, intervention, and prevention may potentially reduce cancer risk and enhance patient outcome.

Some limitations of our investigation need to be considered. Firstly, this study did not discuss the effect of synergistic environment-gene or gene-gene interaction, thus, this needs to be addressed in the future. Secondly, the carcinogenic effect of a single factor within a given population may be concealed by other stronger carcinogenic agents, which may exert synergistic or antagonistic effects. Thirdly, it is imperative to develop an extensive research model or database, with a vast patient population, influencing factors elimination, and enhanced ethnic group separation for homogeneity minimization before conducting a systematic multi-factorial analysis to alter the detection, diagnosis, and treatment of distinct patient populations. Fourthly, we recommend the increasing sample size for the − 353, + 678, +1633, and + 2767 polymorphisms in future research. Fifthly, there needs to be extensive studies on the various functions of the six IL-8 gene polymorphisms based on different genotypes.

Herein, we demonstrated that the three IL-8 gene polymorphisms, including + 2767, +781, and − 251 were essential genetic factors that regulate cancer susceptibility. In addition, -251 polymorphism may be considered as a warning factor for prostate cancer detection. We warrant additional extensive investigations on these polymorphisms in the laboratory and clinic.

Acknowledgements

Not applicable.

Author contributions

Conceptualization, Z.-X.; methodology, S.-J.; data analysis and interpretation, D.-X.Q.; writing—original draft preparation, D.-X.Q.; writing— review and editing, D.-X.Q.; supervision, Z.-X.; project administration, Z.-X.; funding acquisition, Z.-X. All authors have read and agreed to the published version of the manuscript.

Data Availability

The manuscript contains all data supporting the reported results.

Declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Human subjects/informed consent statement

Ethical review and approval were not required for this animal study, in accordance with the local legislation and institutional requirements.

Funding

None

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Table 1 Characteristics of included studies about polymorphisms in IL-8 gene polymorphisms and cancer risk.

Author	Year	Country	Ethnicity	Cancer type	Case	Control	SOC	HWE	Genotype
251
Smith	2004	UK	Caucasian	BRC	119	235	PB	0.131	ARMS-PCR
Zhang	2017	China	Asian	BRC	442	447	HB	0.948	PCR-RFLP
Kamali-Sarvestani	2007	Iran	Asian	BRC	257	233	HB	0.26	ASO-PCR
Snoussi	2010	Tunisia	African	BRC	409	301	PB	0.173	AS-PCR
Wang	2022	China	Asian	BRC	1232	1232	HB	0.231	PCR-RFLP
Althubyani	2020	Eygypt	African	COC	70	70	HB	0.932	TaqMan
Burada	2013	Romania	Caucasian	COC	144	233	HB	0.291	TaqMan
Theodoropoulos	2006	Greece	Caucasian	COC	222	196	HB	0.327	PCR-RFLP
Basavaraju	2015	USA	Caucasian	COC	388	491	PB	0.711	TaqMan
Tsilidis	2009	USA	Caucasian	COC	205	362	PB	0.058	TaqMan
Gunter	2006	Italy	Caucasian	COC	205	191	HB	0.84	TaqMan
Wilkening	2008	Sweden	Caucasian	COC	300	580	HB	0.476	TaqMan
Vogel	2007	Denmark	Caucasian	COC	355	753	PB	0.627	PCR-CE-SSCP
Malespín-Bendana	2021	Costa Rica	Mixed	GC	46	81	HB	0.907	PCR-RFLP
Kamali-Sarvestani	2006	Iran	Asian	GC	19	153	HB	0.797	ASO-PCR
Qadri	2014	India	Asian	GC	130	200	HB	0.066	PCR-RFLP
Kamangar	2006	USA	Caucasian	GC	112	207	PB	0.055	TaqMan
Felipe	2012	Brasil	Mixed	GC	104	196	HB	0.065	PCR-RFLP
Garza-Gonzalez	2007	USA	Mixed	GC	78	207	HB	0.492	PCR-RFLP
Ye	2009	Korea	Asian	GC	153	206	PB	0.72	PCR-RFLP
Shirai	2006	Japan	Asian	GC	181	468	HB	0.343	PCR-RFLP
Song	2009	China	Asian	GC	125	140	HB	0.72	PCR-RFLP
Burada	2012	Craiova	Caucasian	GC	105	242	HB	0.386	AS-PCR
Vinagre	2011	Brasil	Mixed	GC	102	103	HB	0.15	PCR-RFLP
Wang	2016	China	Asian	GC	132	296	HB	0.946	PCR-RFLP
Zeng	2005	China	Asian	GC	104	94	HB	0.212	PCR-RDB
Chang	2017	Korea	Asian	GC	283	176	HB	0.136	PCR-RFLP
Chang	2017	Korea	Asian	GC	283	284	HB	0.082	PCR-RFLP
Bo	2010	China	Asian	GC	208	190	HB	0.389	PCR-RFLP
Taguchi	2005	Japan	Asian	GC	396	252	HB	0.994	PCR-RFLP
Oliveira	2015	Brazil	Mixed	GC	240	207	HB	0.488	PCR-RFLP
Kumar	2015	India	Asian	GC	200	182	PB	0.801	ASO-PCR
Kang	2009	Korea	Asian	GC	334	322	PB	0.226	PCR-RFLP
Canedo	2008	France	Caucasian	GC	333	693	PB	0.459	TaqMan
Lu	2005	China	Asian	GC	250	300	PB	0.516	PCR-DHPLC
Lee	2005	China	Asian	GC	461	303	HB	0.184	PCR-RFLP
Savage	2006	USA	Caucasian	GC	287	428	PB	0.391	TaqMan
Zhang	2010	China	Asian	GC	519	504	PB	0.754	PCR-RFLP
Li	2010	China	Asian	GC	101	137	HB	0.579	PCR-DHPLC
Ohyauchi	2005	Japan	Asian	GC	212	244	HB	0.847	DS
Crusius	2008	France	Caucasian	GC	236	1139	PB	0.705	Real-Time PCR
Leung	2006	China	Asian	GC	83	179	HB	0.638	TaqMan
Szoke	2008	Hungary	Caucasian	GC	35	168	HB	0.165	ARMS-PCR
Ramis	2017	Brazil	Mixed	GC	9	38	PB	0.691	PCR-RFLP
Fu	2016	China	Asian	glioma	127	284	HB	0.251	PCR-RFLP
Liu	2015	China	Asian	glioma	300	300	HB	0.772	PCR-RFLP
Chien	2011	China	Asian	HC	131	340	HB	0.445	PCR-RFLP
Wang	2014	China	Asian	HC	205	208	HB	0.266	PCR-RFLP/PCR-SSP
Liao	2011	China	Asian	HC	390	150	HB	0.104	PCR-RFLP
Elsamanoudy	2015	Egypt	African	HC	112	105	HB	0.551	PCR-RFLP
Qin	2012	China	Asian	HC	150	150	HB	0.104	PCR-RFLP
Lu	2015	China	Asian	HC	454	446	HB	0.115	PCR-RFLP
Rafrafi	2013	Tunisia	African	LC	170	225	PB	0.181	PCR-RFLP
Yamamoto	2017	Japan	Asian	LC	462	379	HB	0.939	TaqMan
Campa	2004	Norway	Caucasian	LC	239	210	PB	0.317	TaqMan
Kaanane	2022	Morocco	African	LC	150	150	PB	0.169	TaqMan
Campa	2005	Germany	Caucasian	LC	2144	2116	PB	0.203	TaqMan
Vogel	2008	Denmark	Caucasian	LC	403	744	PB	0.672	PCR-FLP
Li	2015	China	Asian	LC	132	150	HB	0.894	PCR-HRM
Tai	2007	China	Asian	NC	105	109	HB	0.886	PCR-RFLP
Huang	2018	China	Asian	NC	176	352	HB	0.109	PCR-RFLP
Nasr	2007	Tunisia	African	NC	160	169	PB	0.349	PCR-SSP
Wei	2007	China	Asian	NC	280	290	PB	0.164	PCR-RFLP
Matos	2019	Brazil	Mixed	OC	66	130	HB	0.493	PCR
Qin	2012	China	Asian	OC	150	150	HB	0.104	PCR-RFLP
Liu	2012	China	Asian	OC	270	350	HB	0.454	PCR-RFLP
Campa	2017	Germany	Caucasian	OC	153	725	HB	0.524	TaqMan
Shimizu	2008	Japan	Asian	OC	69	91	HB	0.296	PCR-FLP
Kietthubthew	2010	Thailand	Asian	OC	63	99	PB	0.813	TaqMan
Moreno-Guerrero	2021	Mexico	Mixed	neuroblastoma	27	38	HB	0.152	PCR-RFLP
Kilic	2016	Turkey	Caucasian	thyroid cancer	101	109	HB	0.586	PCR
Wu	2013	China	Asian	urothelial carcinoma	300	594	HB	0.075	PCR-RFLP
Kuyl	2004	Netherlands	Caucasian	kaposi’s sarcoma	84	153	HB	0.382	PCR-RFLP
Howell	2003	UK	Caucasian	melanoma	142	233	HB	0.16	ARMS–PCR
Cacev	2008	Croatia	Caucasian	colon cancer	160	160	PB	0.346	PCR-RFLP
Franz	2017	Brazil	Mixed	PC	175	185	HB	0.127	PCR-SSP
Chen	2016	China	Asian	PC	439	524	HB	0.129	PCR-RFLP
Taheri	2019	Iran	Asian	PC	355	200	HB	0.689	ARMS-PCR
Yang	2006	USA	Caucasian	PC	520	418	PB	0.168	ht-SNP
McCarron	2002	UK	Caucasian	PC	238	235	HB	0.131	PCR
Michaud	2006	USA	Caucasian	PC	484	613	PB	0.777	PCR
353
Wei	2007	China	Asian	NC	280	290	PB	0.406	PCR-RFLP
Wang	2014	China	Asian	HC	205	208	HB	0.474	PCR-RFLP/PCR-SSP
678
Wei	2007	China	Asian	NC	280	290	PB	0.064	PCR-RFLP
Wang	2014	China	Asian	HC	205	208	HB	0.161	AS-PCR
1633
Chien	2011	China	Asian	HC	131	340	HB	0.562	PCR-RFLP
Liu	2012	China	Asian	OC	270	350	HB	0.569	PCR-RFLP
Koensgen	2014	Germany	Caucasian	ovarian cancer	246	62	HB	0.865	PCR-RFLP
Huang	2018	China	Asian	NC	176	352	HB	0.109	PCR-RFLP
2767
Chien	2011	China	Asian	HC	131	340	HB	0.392	PCR-RFLP
Hsieh	2007	China	Asian	leiomyoma	162	156	HB	0.078	PCR-RFLP
781
Kamangar	2006	USA	Caucasian	GC	111	208	PB	0.158	TaqMan
Bo	2010	China	Asian	GC	208	190	HB	0.225	PCR-RFLP
Chien	2011	China	Asian	HC	131	340	HB	0.776	PCR-RFLP
Liu	2012	China	Asian	OC	270	350	HB	0.781	PCR-RFLP
Rafrafi	2013	Tunisia	African	LC	170	225	PB	0.329	PCR-RFLP
Wang	2014	China	Asian	HC	205	208	HB	0.549	PCR-RFLP/PCR-SSP
Koensgen	2014	Germany	Caucasian	ovarian cancer	267	426	HB	0.1	PCR-RFLP
Chen	2016	China	Asian	osteosarcoma	190	190	HB	0.116	PCR-RFLP
Taheri	2019	Iran	Asian	PC	355	200	HB	0.639	ARMS-PCR
Kaanane	2022	Morocco	African	LC	150	150	PB	0.307	TaqMan
Alkanli	2023	Turkey	Caucasian	bladder cancer	88	89	HB	0.608	PCR-RFLP
Moreno-Guerrero	2021	Mexico	Mixed	neuroblastoma	27	38	HB	0.313	PCR-RFLP
Song	2009	China	Asian	GC	125	140	HB	0.48	PCR-RFLP
Fu	2016	China	Asian	glioma	127	284	HB	0.788	PCR-RFLP
Zhang	2017	China	Asian	BRC	442	447	HB	0.327	PCR-RFLP
Huang	2018	China	Asian	NC	176	352	HB	0.671	PCR-RFLP
Ghazy	2021	Saudi Arabia	Asian	PC	40	40	HB	0.673	real-time PCR
Elsamanoudy	2015	Egypt	African	HC	112	105	HB	0.178	PCR-RFLP
Lu	2015	China	Asian	HC	454	446	HB	0.062	PCR-RFLP

HB: hospital-based; PB: population-based; SOC; source of control; PCR-RFLP: polymerase chain reaction followed by restriction fragment length polymorphism; SSP: sequence specific primer; AS: allele specific primer; ARMS: amplification refractory mutation system; MALDI-TOF MS: matrix-assisted laser desorption/Ionization time of flight mass spectrometry; HRM: high resolution melt; DHPLC: denaturing high performance liquid chromatography；CE-SSCP: capillary electrophoresis-single strand conformation polymorphism; HWE: Hardy-Weinberg equilibrium of control group, BRC: breast cancer; COC: colorectal cancer; GC: gastric cancer; HC: hepatocellular carcinoma; LC: lung cancer; NC: nasopharyngeal carcinoma; OC: oral cancer; PC: prostate cancer

Table 2 Stratified analyses of IL-8 genes common polymorphisms on cancer risk

Variables	No	Case/Controls	M-allele vs. W-allele	MM vs. WW	MW vs. WW	MM+MW vs. WW	MM vs. MW+WW
			OR(95%CI) P_h P	OR(95%CI) P_h P	OR(95%CI) P_h P	OR(95%CI) P_h P	OR(95%CI) P_h P
IL-8 -353	2	485/498	1.192 (0.996-1.427)0.456 0.056	1.374 (0.954-1.980)0.516 0.088	1.257(0.951-1.661)0.442 0.108	1.287(0.991-1.672)0.399 0.059	1.205(0.868-1.675)0.737 0.265
IL-8 +678	2	485/498	1.025(0.848-1.239)0.822 0.799	1.092(0.738-1.617)0.830 0.659	0.966(0.738-1.266)0.922 0.804	0.997(0.776-1.280)0.868 0.980	1.109(0.763-1.612)0.847 0.589
IL-8 +2767	2	293/496	0.766(0.616-0.953)0.704 0.017	0.592(0.378-0.928)0.829 0.022	0.823(0.596-1.137)0.443 0.238	0.754(0.557-1.020)0.517 0.067	0.652(0.429-0.991)0.938 0.045
IL-8 +1633	4	823/1104	0.960(0.836-1.103)0.166 0.564	0.924(0.698-1.223)0.197 0.580	0.977(0.789-1.211)0.569 0.835	0.958(0.783-1.172)0.304 0.675	0.935(0.726-1.203)0.372 0.600
IL-8 +781
Total	19	3648/4428	0.928(0.803-1.073)0.000 0.313	0.841(0.613-1.152)0.000 0.281	1.008(0.865-1.175)0.002 0.920	0.971(0.816-1.156)0.000 0.739	0.842(0.650-1.089)0.000 0.190
Ethnicity
Asian	12	2723/3187	0.934(0.813-1.072)0.001 0.329	0.799(0.588-1.084)0.001 0.150	1.030(0.870-1.220)0.019 0.728	0.984(0.824-1.175)0.004 0.860	0.790(0.613-1.019)0.007 0.069
Caucasian	3	466/723	1.189(0.856-1.653)0.043 0.302	1.528(0.773-3.020)0.063 0.223	1.225(0.761-1.973)0.067 0.404	1.276(0.746-2.181)0.024 0.374	1.472(1.078-2.009)0.366 0.015
African	3	432/480	0.826(0.406-1.681)0.000 0.598	0.809(0.199-3.297)0.000 0.767	0.746(0.461-1.205)0.070 0.231	0.750(0.370-1.521)0.001 0.426	0.932(0.282-3.077)0.001 0.907
Mixed	1	27/38	0.424(0.208-0.866)0.000 0.018	0.164(0.033-0.810)0.000 0.027	0.933(0.271-3.209)0.000 0.913	0.536(0.167-1.718)0.000 0.294	0.172(0.044-0.671)0.000 0.011
Cancer type
Hepatocellular carcinoma	4	902/1099	0.692(0.467-1.026)0.000 0.067	0.437(0.235-0.812)0.014 0.009	0.848(0.505-1.424)0.000 0.533	0.723(0.417-1.253)0.000 0.248	0.499(0.349-0.711)0.250 0.000
Other cancer	12	2302/2791	0.981(0.822-1.171)0.000 0.834	0.957(0.635-1.445)0.000 0.836	1.032(0.869-1.225)0.066 0.720	1.031(0.842-1.263)0.003 0.765	0.946(0.679-1.319)0.000 0.744
Gastric cancer	3	444/538	1.119(0.931-1.346)0.456 0.232	1.267(0.864-1.859)0.675 0.226	1.118(0.845-1.479)0.411 0.434	1.148(0.883-1.494)0.368 0.303	1.171(0.826-1.659)0.859 0.375
Source of control
HB	16	3217/3845	0.897(0.761-1.057)0.000 0.194	0.764(0.536-1.090)0.000 0.138	1.022(0.855-1.221)0.001 0.814	0.958(0.781-1.175)0.000 0.681	0.769(0.580-1.019)0.000 0.067
PB	3	431/583	1.087(0.846-1.397)0.191 0.514	1.336(0.735-2.428)0.147 0.343	0.911(0.693-1.198)0.919 0.505	1.002(0.776-1.294)0.512 0.987	1.383(0.799-2.393)0.170 0.247
Genotype
PCR-RFLP	14	2787/3622	0.936(0.792-1.107)0.000 0.441	0.841(0.585-1.209)0.000 0.351	1.023(0.849-1.234)0.001 0.809	0.980(0.794-1.209)0.000 0.849	0.832(0.619-1.118)0.000 0.222
Other type	5	861/806	0.892(0.643-1.238)0.001 0.495	0.812(0.387-1.702)0.001 0.581	0.972(0.753-1.256)0.278 0.828	0.946(0.679-1.318)0.064 0.744	0.872(0.475-1.601)0.003 0.659
IL-8 -251
Total	81	20295/25547	1.055(1.000-1.112)0.000 0.049	1.098(0.991-1.215)0.000 0.073	1.077(0.997-1.162 )0.000 0.059	1.086(1.005-1.173)0.000 0.037	1.046(0.966-1.133)0.000 0.268
Ethnicity
Caucasian	25	7714/11634	0.989(0.941-1.039)0.220 0.652	0.982(0.891-1.083)0.254 0.719	0.948(0.884-1.017)0.538 0.139	0.959(0.896-1.026)0.432 0.223	1.016(0.935-1.103)0.248 0.714
Mixed	9	847/1185	1.076(0.876-1.321)0.023 0.483	1.093(0.737-1.619)0.047 0.659	1.402(1.041-1.889)0.086 0.026	1.288(0.954-1.740)0.042 0.099	0.874(0.646-1.183)0.122 0.384
Asian	41	10663/11708	1.102(1.014-1.197)0.000 0.022	1.196(1.015-1.410)0.000 0.033	1.121(0.994-1.264)0.000 0.062	1.144(1.014-1.292)0.000 0.029	1.114(0.979-1.267)0.000 0.100
African	6	1071/1020	0.979(0.660-1.453)0.000 0.917	0.947(0.458-1.960)0.000 0.884	1.013(0.657-1.563)0.004 0.952	0.981(0.578-1.663)0.000 0.942	0.962(0.577-1.606)0.000 0.883
Cancer type
Gastric cancer	31	5861/8339	1.155(1.057-1.262)0.000 0.002	1.297(1.079-1.560)0.000 0.006	1.24(1.085-1.418)0.000 0.002	1.252(1.096-1.430)0.000 0.001	1.137(0.986-1.311)0.001 0.077
Colorectal cancer	8	1889/2876	1.025(0.907-1.157)0.056 0.697	1.036(0.817-1.314)0.061 0.770	0.914(0.793-1.054)0.871 0.217	0.950(0.832-1.085)0.544 0.447	1.103(0.892-1.363)0.032 0.365
Other cancer	8	1241/1871	1.098(0.917-1.314)0.016 0.308	1.198(0.844-1.700)0.039 0.313	1.042(0.868-1.250)0.326 0.660	1.099(0.896-1.348)0.146 0.364	1.119(0.807-1.55)0.022 0.500
Hepatocellular carcinoma	6	1442/1399	1.023(0.844-1.241)0.014 0.814	0.963(0.690-1.344)0.096 0.825	1.209(0.793-1.842)0.000 0.377	1.149(0.779-1.693)0.000 0.484	0.828(0.647-1.06)0.255 0.134
Oral cancer	6	771/1545	0.951(0.836-1.082)0.570 0.449	0.931(0.713-1.214)0.680 0.596	0.902(0.734-1.108)0.465 0.326	0.905(0.745-1.098)0.557 0.312	0.987(0.782-1.244)0.534 0.910
Nasopharyngeal carcinoma	4	721/920	1.079(0.717-1.623)0.000 0.715	1.131(0.535-2.392)0.000 0.746	1.116(0.703-1.772) 0.005 0.640	1.124(0.658-1.920)0.000 0.670	1.075(0.646-1.789)0.018 0.780
Prostate cancer	6	2211/2175	0.958(0.862-1.064)0.200 0.422	0.936(0.753-1.163)0.168 0.549	0.929(0.770-1.119)0.121 0.436	0.927(0.782-1.099)0.143 0.383	0.977(0.816-1.169)0.210 0.798
Breast cancer	5	2459/2448	1.127(0.823-1.544)0.000 0.422	1.299(0.716-2.358)0.000 0.389	1.095(0.761-1.576)0.000 0.625	1.159(0.765-1.757)0.000 0.486	1.208(0.791-1.846)0.000 0.382
Lung cancer	7	3700/3974	0.845(0.717-0.996)0.000 0.045	0.758(0.557-1.031)0.004 0.077	0.91(0.794-1.042)0.292 0.173	0.843(0.694-1.024)0.028 0.086	0.812(0.632-1.044)0.003 0.105
Source of control
HB	55	11613/14192	1.078(1.005-1.155)0.000 0.035	1.126(0.984-1.289)0.000 0.085	1.137(1.024-1.261)0.000 0.016	1.139(1.027-1.264)0.000 0.014	1.040(0.936-1.157)0.000 0.465
PB	26	8682/11355	1.017(0.935-1.105)0.000 0.699	1.058(0.903-1.239)0.000 0.487	0.986(0.886-1.097)0.001 0.792	1.004(0.895-1.126)0.000 0.947	1.057(0.934-1.196)0.000 0.380
Genetype
Taqman	16	5338/7113	1.003(0.906-1.109)0.000 0.961	1.03(0.843-1.258)0.001 0.772	0.922(0.808-1.052)0.037 0.228	0.951(0.827-1.094)0.005 0.485	1.053(0.906-1.223) 0.004 0.503
PCR-RFLP	39	9505/10768	1.053(0.966-1.148)0.000 0.237	1.083(0.915-1.282)0.000 0.352	1.131(1.000-1.278)0.000 0.050	1.120(0.989-1.268)0.000 0.075	1.001(0.876-1.144)0.000 0.986
Other type	13	2922/4632	1.103(0.973-1.25)0.000 0.125	1.16(0.927-1.45)0.013 0.194	1.127(0.930-1.367)0.001 0.222	1.147(0.949-1.385)0.000 0.155	1.096(0.915-1.313)0.035 0.318
ARMS-PCR	4	651/836	0.974(0.834-1.137)0.893 0.735	0.933(0.684-1.271)0.826 0.659	1.030(0.763-1.391)0.258 0.846	1.002(0.792-1.269)0.538 0.984	0.923(0.705-1.207)0.415 0.557
PCR	4	889/1087	0.955(0.782-1.166)0.128 0.651	0.926(0.637-1.347)0.187 0.689	0.992(0.669-1.469)0.037 0.967	0.967(0.663-1.409)0.032 0.860	0.939(0.756-1.167)0.760 0.570
AS-PCR	5	990/1111	1.323(1.074-1.629)0.055 0.008	1.697(1.162-2.478)0.089 0.006	1.261(1.000-1.591)0.338 0.050	1.381(1.071-1.78)0.204 0.013	1.511(1.066-2.142)0.050 0.020

P_h: value of Q-test for heterogeneity test; P: Z-test for the statistical significance of the OR; HB: hospital-based; PB: population-based; SOC; source of control

No competing interests reported.

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Six IL-8 gene polymorphisms and the entire cancer susceptibility according to a comprehensive analysis especially in prostate cancer

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