Skip to main content
Download PDF

Association between TAB2 genetic polymorphisms and the susceptibility to cervical cancer: a case-control study

Cancer Cell International volume 24, Article number: 413 (2024) Cite this article

Abstract

Background

Cervical cancer (CC) ranks as the fourth most common cancer and the fourth leading cause of cancer-related deaths among women globally, with declining incidence and mortality rates in recent decades. Previous studies have suggested that the transforming growth factor-beta (TGF-β) activated kinase 1 (TAK1) binding protein 2 (TAB2) can influence the stemness characteristics of squamous CC cells. However, the specific genetic impact of the TAB2 gene on CC remains unclear. This study aimed to evaluate the relationship between TAB2 genetic polymorphisms and susceptibility to CC using a hospital-based retrospective analysis.

Methods

A total of 306 CC patients and 309 healthy controls were included in this study. Genetic analysis involved genotyping of subjects using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Statistical analyses were conducted using SNPstats online analysis software and SPSS software.

Results

The frequency of the G allele of rs521845 polymorphism was significantly higher in CC patients (P = 0.048, OR = 1.26, 95%CI = 1.00-1.59), with GG homozygotes showing an increased susceptibility to CC compared to CC/CG genotype carriers (P = 0.045, OR = 1.57, 95%CI = 1.01–2.45). Additionally, all three tag single nucleotide polymorphisms (SNPs) were associated with lymph node involvement in patients (P = 0.0006, OR = 0.01, 95%CI = 0.00-0.31 for rs237028 GG genotype; P = 0.009, OR = 0.17, 95%CI = 0.04–0.68 for rs521845 GG genotype; and P = 0.004, OR = 0.14, 95%CI = 0.03–0.59 for rs652921 CC genotype, respectively).

Conclusion

This study highlighted that TAB2 rs521845 polymorphism was significantly associated with susceptibility to CC, suggesting that the TAB2 gene may play a crucial role in the progression of CC.

Introduction

Cervical cancer (CC) ranks as the fourth most frequently diagnosed cancer and the fourth leading cause of cancer death in women worldwide, following breast, colorectal, and lung cancers. In 2020, an estimated 604,000 new cases and 342,000 deaths were reported globally [1]. According to the Global Cancer Observatory report 2022, there were 113,912 new CC cases in China, accounting for approximately 40.3% of new cases in Asia, followed by India (81,479 cases, 28.8%), Indonesia (27,872 cases, 9.9%), and Japan (9,886 cases, 3.5%) [2]. Human papillomavirus (HPV), with 12 oncogenic types classified as Group 1 carcinogens by the International Agency for Research on Cancer Monographs [3, 4], is a necessary but not sufficient cause of CC. Other contributing factors include sexually transmitted infections (such as human immunodeficiency virus and Chlamydia trachomatis), smoking, multiple childbirths, and long-term use of oral contraceptives, which also increase the risk of CC [5]. The burden of CC is closely associated with socioeconomic development [6]. It has been observed that areas with higher poverty rates tend to have higher mortality rates, with the CC death rate being twice as high among women in high-poverty areas compared to those in low-poverty areas [7]. However, incidence and mortality rates have declined in most regions worldwide over the past few decades, especially in areas with effective CC screening programs and HPV vaccination initiatives. These declines are attributed to factors linked to improving average socioeconomic levels and reducing the risk of persistent infection with high-risk HPV [1, 6].

Although more than 70% of women may contract HPV casually one or multiple times in their lives, approximately 30–60% of these infections resolve spontaneously within a short period. Only a small percentage of infections persist and can progress to CC, indicating that host genetic factors may affect the risk of progression from HPV infection to cervical precancer or cancer [8]. Moreover, numerous studies have demonstrated associations between CC and genetic variants, such as the tumor suppressor gene: tumor protein p53 (TP53), the p53-regulating ubiquitin ligase gene: murine double minute 2 (MDM2), DNA damage response or cell cycle genes: ataxia-telangiectasia mutated gene (ATM), breast cancer susceptibility gene 1 interacting protein C-terminal helicase 1 (BRIP1), cyclin dependent kinase inhibitor 1 A (CDKN1A), and Fanconi anemia complementation group L (FANCL) [9].

The TAB2 gene is located on chromosome 6 at 6q25.1 and encodes the transforming growth factor-beta (TGF-β) activated kinase 1 (TAK1) binding protein 2. TAB2 plays a crucial role in regulating cell proliferation and apoptosis by activating the nuclear factor kappa-B (NF-κB) and mitogen-activated protein kinase (MAPK) signaling pathways through processes such as phosphorylation and ubiquitination [10,11,12]. Additionally, TAB2 is involved in DNA damage repair and cancer development [13]. A recent in vitro study on CC has indicated that down-regulation of TAB2 expression can reduce the stemness of CC cells and potentially inhibit CC progression [14]. However, the exact mechanism of TAB2 in CC susceptibility and development in vivo remains incompletely understood. Thus, this study aims to initially explore whether polymorphic variants of TAB2 contribute to CC susceptibility.

Materials and methods

Study subjects

This case-control study included 306 patients diagnosed with CC, with a mean age of 42.74 ± 8.08 years, and 309 healthy controls with a mean age of 47.49 ± 13.14 years, recruited from the West China Second University Hospital between 2008 and 2019. Histopathological analysis confirmed the diagnosis based on resected tissue specimens obtained from the patients. Exclusion criteria comprised individuals with a history of prior cancer, autoimmune or infectious diseases, or those who had undergone radiotherapy or chemotherapy. Healthy controls were selected from the hospital’s department of physical examination, excluding individuals with personal or family histories of CC or other severe illnesses. All participants were genetically unrelated. Written informed consent was obtained from all participants, and the study was approved by the ethics committee of West China Second University Hospital in accordance with the Declaration of Helsinki.

Fig. 1
figure 1

Genotypes of TAB2 rs237028, rs521845 and rs652921 polymorphisms in individuals. A: Genotypes of rs237028 polymorphism (Lane 1: GG genotype; Lane 2: AA genotype; Lane 3: AG genotype); B: Genotypes of rs521845 polymorphism (Lane 1: GG genotype; Lane 2: TT genotype; Lane 3: TG genotype); C: Genotypes of rs652921 polymorphism (Lane 1: CC genotype; Lane 2: TT genotype; Lane 3: TC genotype)

Full size image

Gene selection and genotyping

Three target single nucleotide polymorphisms (tag SNPs) of the TAB2 gene (rs237028 A > G, rs652921 C > T, rs521845 T > G) were selected based on data from the HapMap Project [15]. Primers for polymerase chain reaction (PCR) were designed using Primer 3 web version 4.1.0. (http://primer3.ut.ee/) [16], and the sequences were as follows: rs237028 forward primer: 5′-GCAGACTTGGAAAAGCAAACA-3′, reverse primer: 5′-CCAGCCTGAGCAACAAGAG-3′; rs652921 forward primer: 5′-CAGTGAAACTTTTTCCCGATG-3′, reverse primer: 5′-TCGCTGTGAACAGTGTGAGA-3′; rs521845 forward primer: 5′-TAGGGCGGTTGAGAAGTGAA-3′, reverse primer: 5′-CCTGGGTGACTGAGCTCTTA-3′.

Genomic DNA was extracted from a 200 µL Ethylenediamine tetraacetic acid (EDTA)-anticoagulated peripheral blood sample using a DNA isolation kit (BioTeke, China), following the manufacturer’s instructions rigorously. The polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method was employed for genotyping each sample. Genomic DNA fragments were amplified in a reaction volume of 10 µL, containing 5 µL of 2x Power Taq PCR Master Mix (BioTeke, China), 4.5 picomoles of each primer, and 100 ng of genomic DNA. The PCR conditions included initial denaturation at 95 °C for 4 min, followed by 33 cycles at 94 °C for 30 s, annealing at 60 °C for 30 s, extension at 72 °C for 30 s, and a final extension step at 72 °C for 10 min. Subsequently, PCR products for rs237028 polymorphism were digested into 106 bp and 32 bp fragments for the G allele using the restriction enzyme Hpy188I (New England Biolabs, Peking, China) at 37 °C for 2 h. Similarly, rs521845 polymorphism products were digested into 100 bp and 26 bp fragments for the G allele by AcII (Thermo Fisher Scientific, Shanghai, China) at 37 °C for 2 h, while rs652921 polymorphism products were cut into 99 bp and 21 bp fragments for the C allele using BseJI (Thermo Fisher Scientific, Shanghai, China) at 60 °C for 1 h. The resulting fragments were separated by electrophoresis on a 6% polyacrylamide gel stained with a 1.5 g/L silver nitrate solution for genotyping (Fig. 1). Finally, genotypes were confirmed through DNA sequencing analysis. Approximately 10% of the samples were randomly chosen for repeated assays, with results showing complete agreement (100%).

Statistical analyses

Data analysis was carried out using SPSS version 20.0 (SPSS Inc., Chicago, IL, USA). Allelic and genotypic frequencies were determined by direct counting. The online SNPstats analysis software was used to assess differences in allelic and genotypic distributions between the case and control groups under various genetic models, including codominant, dominant, recessive, and over-dominant models [17]. Additionally, the Hardy-Weinberg equilibrium was evaluated using the chi-squared test. Odds ratios (OR) and 95% confidence intervals (CI) were calculated to assess the association between specific genotypes and clinical characteristics. Statistical significance was defined as P < 0.05.

Results

Subject characteristics

A total of 306 CC patients and 309 female healthy controls participated in this retrospective case-control study. Clinical characteristic data for CC patients were extracted from medical records and are summarized in Table 1.

Table 1 Characteristics of patients with cervical cancer
Full size table

TAB2 genetic distribution and susceptibility to CC

The allele and genotype distributions of the three tag SNPs were consistent with the assumption of Hardy-Weinberg equilibrium (P > 0.05), and their frequencies are shown in Table 2. Specifically, for the rs521845 T > G polymorphism, the frequency of the G allele among CC patients was significantly higher compared to controls (40.9% versus 35.4%, P = 0.048, OR = 1.26, 95% CI = 1.00-1.59). This finding was consistent across both the GG homozygous genotype in the codominant model (P = 0.04, OR = 1.67, 95% CI = 1.03–2.70) and the recessive model (P = 0.045, OR = 1.57, 95% CI = 1.01–2.45), indicating a more than 1.5-fold higher risk of CC susceptibility in GG genotype carriers compared to those with CC/CG genotype. No significant differences were detected between CC patients and controls in the analysis of rs237028 or rs652921 polymorphisms.

Table 2 Distribution of TAB2 polymorphisms in cervical cancer patients and controls
Full size table

TAB2 SNPs and subgroup analyses

To investigate the potential effect of TAB2 polymorphisms on CC, stratified analyses were conducted to explore the distribution of genotypes among CC patients across various clinical characteristics, including age (< 43 years and ≥ 43 years), federation international of gynecology and obstetrics (FIGO) stage (stage I and stage II-III), pathological type (squamous and others), tumor differentiation (low and moderate-high), myometrial invasion (> 1/2 and ≤ 1/2), lymph node involvement, peritumoral intravascular cancer emboli, and involvement of other organs.

Regarding the rs237028 polymorphism as depicted in Table 3, CC patients with the GG genotype showed a heightened risk of lymph node involvement (P = 0.0006, OR = 0.01, 95%CI = 0.00-0.31) and superficial layer-myometrial invasion (P = 0.006, OR = 17.97, 95%CI = 1.50-216.02) compared to those with AA/AG genotypes, after adjusting for variables such as age, FIGO stage, pathological type, tumor differentiation, lymph node involvement, myometrial invasion, and peritumoral intravascular cancer emboli. Similar patterns were observed for lymph node involvement risk in patients homozygous for the GG genotype of the rs521845 polymorphism (P = 0.009, OR = 0.17, 95%CI = 0.04–0.68, Table 4) and the CC homozygotes for the rs652921 polymorphism (P = 0.004, OR = 0.14, 95%CI = 0.03–0.59, Table 5). However, as shown in Table 5, TC heterozygotes for the rs652921 polymorphism exhibited a reduced risk of lymph node involvement compared to TT/CC genotype carriers (P = 0.03, OR = 3.52, 95%CI = 1.12–11.07). Regarding FIGO stage, TC heterozygotes showed an elevated risk of stage II-III cancer (P = 0.04, OR = 2.46, 95%CI = 1.00-6.05) compared to TT/CC homozygotes, whereas CC homozygotes displayed a significantly lower risk (P = 0.005, OR = 0.20, 95%CI = 0.06–0.67) compared to TT/TC genotype carriers after adjusting for age, pathological type, tumor differentiation, lymph node involvement, myometrial invasion, and peritumoral intravascular cancer emboli.

Table 3 Association between the distribution of TAB2 rs237028 genotypes and patient’s characteristics
Full size table
Table 4 Association between the distribution of TAB2 rs521845 genotypes and patient’s characteristics
Full size table
Table 5 Association between the distribution of TAB2 rs652921 genotypes and patient’s characteristics
Full size table

TAB2 gene haplotype analyses

These three tag SNPs exhibited a low level of linkage disequilibrium with each other (rs237028 versus rs521845: D’ = 0.9008, r2 = 0.6703; rs237028 versus rs652921: D’ = 0.9344, r2 = 0.5982; rs521845 versus rs652921: D’ = 0.8284, r2 = 0.7127), indicating that the three tag SNPs are representative of the genetic variations under investigation. As shown in Table 6, haplotype analysis identified a significantly distinct haplotype from the combination of rs237028, rs521845, and rs652921: AGC (P = 0.003), which was associated with increased susceptibility to CC.

Table 6 Haplotype frequencies of TAB2 gene in patients and controls
Full size table

Discussion

TAB2 is an essential adaptor that links TAK1 and tumor necrosis factor receptor-associated factor 6 (TRAF6) [18], playing a crucial role in cardiovascular development and the homeostasis of the extracellular matrix (ECM) [19]. Loss-of-function mutations in TAB2 result in ECM disorganization and alterations in collagen-related pathways, as the truncated protein encoded by these mutations loses its ability to bind TAK1 following nonsense-mediated mRNA decay [19]. Previous research has highlighted severe syndromes associated with TAB2 gene variations. Haplo-insufficiency of TAB2 is associated with conditions such as short stature, facial dysmorphisms, connective tissue abnormalities, hearing loss, cardiac disease, skeletal dysplasia, and sacral dimples. Additionally, heterozygous nonsense variants in TAB2 have been associated with caudal appendage, skeletal abnormalities, and prenatally-detected cardiomyopathy [20]. Woods et al. identified several phenotypes, including ‘wandering spleen’ (absence of the splenic ligament), cryptorchidism, and glandular hypospadias, in 14 newly identified individuals with pathogenic TAB2 variants [21]. Our previous retrospective study confirmed these findings and indicated an association between TAB2 variations and an increased risk of cryptorchidism [22].

TAB2 plays a crucial role in the proliferation and migration of tumor cells through multiple pathways. In oral squamous cell carcinoma (OSCC) cells, studies have shown that TAB2 deletion leads to decreased proliferation and increased apoptosis. Conversely, overexpression of TAB2 regulates the progression of OSCC by upregulating epithelial-mesenchymal transition (EMT) and the phosphatidylinositol 3 kinase(PI3K)-protein kinase B(AKT) signaling pathways [23]. TAB2 also plays a role in inhibiting EMT through the TGF-β/Smad pathway in response to berberine [24]. Additionally, TAB2 inhibits starvation-induced autophagy and maintains cell viability by activating the TAB2/p38 MAPK pathway, thereby promoting cell migration [25]. In organoids derived from resected primary human colorectal cancer (CRC) tissues, TAB2 has been implicated in the regulation of Regulator of G protein signaling 16 (RGS16) in CRC progression. The highly conserved zinc finger domain of TAB2 competitively binds with RGS16 or TRAF6, inhibiting the TAB2-TRAF6 interaction and thereby suppressing TAK1- c-Jun N-terminal kinase (JNK)/p38-mediated apoptosis [26].

The present study elucidated the potential role of TAB2 SNPs in CC, highlighting a higher susceptibility to CC in individuals with the GG genotype of rs521845, an increased risk of lymph node involvement across all three tag SNPs, and an association between the TC genotype of rs652921 and advanced FIGO stage. Lymph node involvement and advanced stage are often indicators of poor prognosis, with higher rates of recurrence and metastasis in patients. Research on OSCC has indicated that elevated TAB2 expression correlates inversely with prognosis [23], corroborating findings in our study. Furthermore, TAB2’s regulatory mechanism in cervical squamous cell carcinoma cells promotes malignant transformation and invasiveness, attributed to its stem cell-like properties [14]. These findings suggest that TAB2 could potentially serve as a prognostic marker for squamous cell carcinomas, particularly in CC.

A study based on RNA sequencing data from the TCGA cohort has developed a risk score model incorporating three necroptosis-related mRNAs: cysteine X chemokine ligand 8 (CXCL8), C-type lectin domain family 9 member A (CLEC9A), and TAB2, to assess prognosis and immune responses in cervical squamous carcinoma and adenocarcinoma. These mRNAs-related pathways are pivotal in regulating carcinoma progression by promoting malignant phenotypes such as proliferation, invasion, metastasis, and drug resistance [27]. TAB2, recognized as an estrogen-sensitive gene, interacts with steroid receptors and contributes to the mechanism of mammographic density affecting breast cancer risk [28]. Moreover, TAB2 has been implicated in conjunction with the nuclear receptor corepressor (NCoR) complex, modulating gene regulatory regions of antagonist-bound estrogen and androgen receptors, thereby influencing their transcriptional activity and contributing to pharmacological resistance in breast and prostate cancer cells. Conversely, reduced interaction between TAB2 and estrogen receptor alpha domain can restore the antiproliferative response to Tamoxifen in Tamoxifen-resistant breast cancer cells [29]. These findings underscored TAB2’s potential to reverse drug resistance and enhance anti-estrogen effects. In our study, we did not collect data on estrogen levels among all subjects, thus missing a potential mechanism involving estrogen levels in the progression of CC. In future, further in vitro and in vivo experimental studies to validate this hypothesis and verify our results more comprehensively.

Conclusion

In conclusion, our findings suggest that TAB2 may represent a significant genetic risk locus for the susceptibility to CC. All three tag SNPs were identified to be associated with lymph node involvement. The TC heterozygous genotype of rs652921 was found to be related to advanced FIGO stages in CC. However, this study indeed has several limitations. Firstly, The missing clinical data for certain variables in some patients reduced the effective sample size in characteristics analysis in a partial, and may affect the objectivity and veracity of the results, although the missing was randomized. And then, this study ignored the evaluation based on individual’s HPV vaccination status and usage of contraceptives, which might cause a bias in the results of susceptibility analysis. Lastly, despite conducting stratified analyses of clinical features, this study was limited by the absence of evaluation regarding TAB2 protein expression, estrogen levels, patient prognosis data, and underlying molecular mechanisms involved. Therefore, studies based on larger cohort, more comprehensive clinical data, and in-depth analyses experiments are needed to verify our findings in the future.

Data availability

Data is provided within the manuscript or supplementary information files.

References

  1. Sung HA-O, Ferlay J, Siegel RA-O, Laversanne M, Soerjomataram I, Jemal A, Bray F. 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.

    Article  PubMed  Google Scholar 

  2. Ferlay JEM, Lam F et al. Global Cancer Observatory: Cancer Today. International Agency for Research on Cancer; 2022. Accessed February 8, 2024. gco.iarc.fr/today. 2024.

  3. Walboomers JM, Jacobs Mv Fau -, Manos MM, Manos Mm Fau - Bosch FX, Bosch Fx Fau - Kummer JA, Kummer Ja Fau - Shah KV, Shah Kv Fau - Snijders PJ, Snijders Pj Fau -, Peto J, Peto J. Fau - Meijer CJ, Meijer Cj Fau - Muñoz N, Muñoz N: Human papillomavirus is a necessary cause of invasive cervical cancer worldwide. J Pathol 1999, 189(1):12–19.

  4. Humans IWGECR. Human papillomaviruses. IARC Monogr Eval Carcinog Risks Hum. 2007;90:1–636.

    Google Scholar 

  5. Castellsagué X, Muñoz N. J Natl Cancer Inst Monogr. 2003;31:20–8. Chap. 3: Cofactors in human papillomavirus carcinogenesis–role of parity, oral contraceptives, and tobacco smoking.

    Article  Google Scholar 

  6. Lin S, Gao K, Gu S, You L, Qian S, Tang M, Wang J, Chen K, Jin MA-O. Worldwide trends in cervical cancer incidence and mortality, with predictions for the next 15 years. cancer 2021, 127(21):4030–4039.

  7. Singh GK, Azuine RE, Siahpush M. Global inequalities in Cervical Cancer incidence and mortality are linked to deprivation, low socioeconomic status, and Human Development. Int J MCH AIDS. 2012;1(1):17–30.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Li N, Yi H, Sun W, Sundquist J, Sundquist K, Zhang X, Zheng DA-O, Ji JA-O. Revealing genes associated with cervical cancer in distinct immune cells: a comprehensive mendelian randomization analysis. Int J Cancer. 2024;155(1):149–58.

    Article  CAS  PubMed  Google Scholar 

  9. Ramachandran DA-O, Dörk TA-O. Genomic risk factors for cervical Cancer. LID – 10.3390/cancers13205137 [doi] LID – 5137. Cancers (Basel). 2021;13(20):5137.

    Article  CAS  PubMed  Google Scholar 

  10. Wang X, Jiang J, Fau - Lu Y, Lu Y, Fau - Shi G, Shi G, Fau - Liu R, Liu R, Fau - Cao Y, Cao Y. TAB2, an important upstream adaptor of interleukin-1 signaling pathway, is subject to SUMOylation. Mol Cell Biochem. 2014;385(1–2):69–77.

    Article  CAS  PubMed  Google Scholar 

  11. Braun HA-O, Staal JA-O. Stabilization of the TAK1 adaptor proteins TAB2 and TAB3 is critical for optimal NF-κB activation. FEBS J. 2020;287(15):3161–4.

    Article  CAS  PubMed  Google Scholar 

  12. Davis RJ. Signal transduction by the JNK group of MAP kinases. Cell. 2000;103(2):239–52.

    Article  CAS  PubMed  Google Scholar 

  13. Hinz M, Stilmann M, Fau - Arslan SÇ, Arslan SÇ, Fau - Khanna KK, Khanna Kk Fau -, Dittmar G, Dittmar G, Fau - Scheidereit C, Scheidereit C. A cytoplasmic ATM-TRAF6-cIAP1 module links nuclear DNA damage signaling to ubiquitin-mediated NF-κB activation. Mol Cell. 2010;40(1):63–74.

    Article  CAS  PubMed  Google Scholar 

  14. Zhou YA-OX, Liao Y, Zhang C, Liu J, Wang W, Huang J, Du Q, Liu T, Zou Q, Huang H et al. TAB2 Promotes the Stemness and Biological Functions of Cervical Squamous Cell Carcinoma Cells. Stem Cells Int 2021, 2021:6550388.

  15. Xu Z, Taylor JA. SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies. Nucleic Acids Res. 2009;37:W600–605.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Untergasser A, Cutcutache I, Fau - Koressaar T, Koressaar T, Fau - Ye J, Ye J. Fau - Faircloth BC, Faircloth Bc Fau - Remm M, Remm M Fau - Rozen SG, Rozen SG: Primer3–new capabilities and interfaces. Nucleic Acids Res. 2012;40(15):e115.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Solé X, Guinó E, Fau - Valls J, Valls J, Fau - Iniesta R, Iniesta R, Fau - Moreno V, Moreno V. SNPStats: a web tool for the analysis of association studies. Bioinformatics. 2006;22(15):1928–9.

    Article  PubMed  Google Scholar 

  18. Xia ZP, Sun L, Fau - Chen X, Chen X, Fau - Pineda G, Pineda G, Fau - Jiang X, Jiang X, Fau - Adhikari A, Adhikari A, Fau - Zeng W, Zeng W, Fau - Chen ZJ, Chen ZJ. Direct activation of protein kinases by unanchored polyubiquitin chains. Nature. 2009;461(7260):114–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Morlino S, Carbone A, Ritelli M, Fusco CA-O, Giambra V, Nardella G, Notarangelo A, Panelli P, Mazzoccoli G, Zoppi N, et al. TAB2 c.1398dup variant leads to haploinsufficiency and impairs extracellular matrix homeostasis. Hum Mutat. 2019;40(10):1886–98.

    Article  CAS  PubMed  Google Scholar 

  20. Koene SA-OX, Klerx-Melis F, Roest AAW, Kleijwegt MC, Bootsma M, Haak MC, van Haeringen MH, Ruivenkamp CAL, Nibbeling EAR, van Haeringen A. Sacral abnormalities including caudal appendage, skeletal dysplasia, and prenatal cardiomyopathy associated with a pathogenic TAB2 variant in a 3-generation family. Am J Med Genet A. 2022;188(12):3510–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Woods EA-O, Marson IA-OX, Coci E, Spiller M, Kumar A, Brady A, Homfray T, Fisher R, Turnpenny P, Rankin J, et al. Expanding the phenotype of TAB2 variants and literature review. Am J Med Genet A. 2022;188(11):3331–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Su M, Li ZL, Song YP, Wang YY, Zhou B, Li Q. Association between TAB2 Gene Polymorphisms and susceptibility to Cryptorchidism in Han Chinese Population in Southwest China. Sichuan Da Xue Xue Bao Yi Xue Ban. 2022;53(4):642–8.

    PubMed  Google Scholar 

  23. Liu H, Zhang H, Fan H, Tang S, Weng JA-O. TAB2 Promotes the Biological Functions of Head and Neck Squamous Cell Carcinoma Cells via EMT and PI3K Pathway. Dis Markers 2022, 2022:1217918.

  24. Du H, Gu J, Peng Q, Wang X, Liu L, Shu X, He Q, Tan YA-O. Berberine Suppresses EMT in Liver and Gastric Carcinoma Cells through Combination with TGFβR Regulating TGF-β/Smad Pathway. Oxid Med Cell Longev 2021, 2021:2337818.

  25. Zhou Y, Wu Pw Fau - Yuan XW, Yuan Xw Fau - Li J, Li J, Fau - Shi XL, Shi XL. Interleukin-17A inhibits cell autophagy under starvation and promotes cell migration via TAB2/TAB3-p38 mitogen-activated protein kinase pathways in hepatocellular carcinoma. Eur Rev Med Pharmacol Sci. 2016;20(2):250–63.

    CAS  PubMed  Google Scholar 

  26. Shen H, Yuan J, Tong D, Chen B, Yu E, Chen G, Peng C, Chang W, E JA-O, Cao FA-O. Regulator of G protein signaling 16 restrains apoptosis in colorectal cancer through disrupting TRAF6-TAB2-TAK1-JNK/p38 MAPK signaling. Cell Death Dis. 2024;15(6):438.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Zou J, Lin Z, Jiao W, Chen J, Lin L, Zhang F, Zhang X, Zhao J. A multi-omics-based investigation of the prognostic and immunological impact of necroptosis-related mRNA in patients with cervical squamous carcinoma and adenocarcinoma. Sci Rep. 2022;12(1):16773.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Brand JS, Li J, Humphreys K, Karlsson R, Eriksson M, Ivansson E, Hall P, Czene K. Identification of two novel mammographic density loci at 6Q25.1. Breast Cancer Res. 2015;17(1):75.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Reineri S, Agati S, Miano V, Sani M, Berchialla P, Ricci L, Iannello A, Coscujuela Tarrero L, Cutrupi S, De Bortoli M. A Novel Functional Domain of TAB2 involved in the Interaction with Estrogen Receptor Alpha in breast Cancer cells. PLoS ONE. 2016;11(12):e0168639.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 32171264, 81974365 and 81974226) and Sichuan Science and Technology Program (No. 2023ZYD0124).

Author information

Author notes

  1. Qin Li and Min Su contributed equally to this work.

Authors and Affiliations

  1. Laboratory of Molecular Translational Medicine, Center for Translational Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, 610041, P.R. China

    Qin Li, Min Su, Yanyun Wang, Zhilong Li, Yaping Song, Bin Zhou & Lin Zhang

Authors
  1. Qin Li
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Min Su
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Yanyun Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Zhilong Li
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Yaping Song
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Bin Zhou
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Lin Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Q.L, M.S, L.Z and B.Z conceived of the study, participated in its design, carried out most of the experiments and drafted the manuscript. Y.W, Z.L and Y.S performed sample collection, DNA extraction and genotyping. Q.L and M.S did the statistics. All authors have read and approved the final manuscript.

Corresponding authors

Correspondence to Bin Zhou or Lin Zhang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

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

Rights and permissions

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/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Q., Su, M., Wang, Y. et al. Association between TAB2 genetic polymorphisms and the susceptibility to cervical cancer: a case-control study. Cancer Cell Int 24, 413 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12935-024-03603-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12935-024-03603-y

Keywords

Cancer Cell International

ISSN: 1475-2867

Contact us