DNA base excision repair genes variants rs25487 (X-ray repair cross-complementing 1) and rs1052133 (human 8-oxoguanine glycosylase 1) with susceptibility to ovarian cancer in the population of the Jammu region, India

Verma, Sonali; Sharma, Varun; Nagpal, Ashna; Bhat, Amrita; Bhat, Ghulam Rasool; Shah, Ruchi; Wakhloo, Ajay K.; Suri, Jyotsna; Abrol, D. P.; Kaul, Sandeep; Bhat, Audesh; Verma, Vivek; Kumar, Rakesh

doi:10.4103/jcrt.jcrt_65_18

Cited by 8 publications

(9 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Variant rs751402 of ERCC5 on the other hand was not found associated with OC. These results were consistent with our previous report 45 , whereas another polymorphisms of DNA repair pathway rs25487 (XRCC1) was significantly not associated with OC.…”

Section: Discussionsupporting

confidence: 93%

“…The population of Jammu and Kashmir is ethnically and genetically diverse compared to the other population groups 8 , thus creating a heterogeneous gene pool. Despite being ethnically diverse, the population groups of J&K have high incidence rate of OC 9 .…”

mentioning

confidence: 99%

“…SNPs investigated in the present study include genes like DNMT3A, PIK3CA, FGFR2, GSTP1, ERCC5, AKT1, CASC16, CYP19A1, BCL2, andERCC1.SNPs of these genes have been found in association with cancers of ovary, breast, stomach and lung among different populations, globally [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] . Recently, reported association of XRCC1 (rs25487), HoGG1 (rs1052133), DNAH11(rs2285947) and LRFN2(rs2494938) gene variants with OC provided an insight that genetic variants provide increased risk in the present populations 9,31 . Besides these two reports, no genetic data is available on OC from the J&K region.…”

mentioning

confidence: 99%

See 2 more Smart Citations

MassArray analysis of genomic susceptibility variants in ovarian cancer

Verma

Sharma²,

Sharma³

et al. 2020

Sci Rep

Self Cite

View full text Add to dashboard Cite

Ovarian cancer (OC), a multifaceted and genetically heterogeneous malignancy is one of the most common cancers among women. The aim of the study is to unravel the genetic factors associated with OC and the extent of genetic heterogeneity in the populations of Jammu and Kashmir (J&K).Using the high throughput Agena MassARRAY platform, present case control study was designed which comprises 200 histopathological confirmed OC patients and 400 age and ethnicity matched healthy controls to ascertain the association of previously reported eleven single nucleotide polymorphisms (SNPs) spread over ten genes (DNMT3A, PIK3CA, FGFR2, GSTP1, ERCC5, AKT1, CASC16, CYP19A1, BCL2 and ERCC1) within the OC population of Jammu and Kashmir, India. The association of each variant was estimated using logistic regression analyses. Out of the 11 SNPs the odds ratio observed for three SNPs; rs2699887 was (1.72 at 95% CI: 1.19–2.48, p = 0.004), rs1695 was (1.87 at 95% CI: 1.28–2.71, p = 0.001), and rs2298881 was (0.66 at 95% CI: 0.46–0.96, p = 0.03) were found significantly associated with the OC after correction with confounding factors i.e. age & BMI. Furthermore, the estimation of interactive analyses was performed and odds ratio observed was 2.44 (1.72–3.47), p value < 0. 001 suggests that there was a strong existence of interplay between the selected genetic variants in OC, which demonstrate that interactive analysis highlights the role of gene–gene interaction that provides an insight among multiple little effects of various polymorphisms in OC.

show abstract

Section: Discussionsupporting

confidence: 93%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

MassArray analysis of genomic susceptibility variants in ovarian cancer

Verma

Sharma²,

Sharma³

et al. 2020

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, there are still many inconsistencies. An increased risk was found by some studies [13][14][15][16][17], but was not confirmed by others [18][19][20][21][22][23][24][25][26]. Thus, a meta-analysis is a good approach to investigate the association between the hOGG1 Ser326Cys polymorphism and the susceptibility to gynecologic cancer.…”

Section: Introductionmentioning

confidence: 98%

“…Nonetheless, there has been no meta-analysis that has specifically focused on gynecologic cancer types, such as cervical, ovarian, and endometrial cancer. In addition, several additional studies on gynecologic cancer have been published since 2014 [14,15,18]. Thus, the aim of the present study was to perform an updated meta-analysis investigating the association between the hOGG1 Ser326Cys polymorphism and susceptibility to gynecologic cancer.…”

Section: Introductionmentioning

confidence: 99%

Association of the hOGG1 Ser326Cys polymorphism with gynecologic cancer susceptibility: a meta-analysis

Shi

Xia

2020

Bioscience Reports

View full text Add to dashboard Cite

The association between the hOGG1 Ser326Cys polymorphism and gynecologic cancer susceptibility is inconclusive. We performed a comprehensive meta-analysis to precisely estimate of the impact of the hOGG1 Ser326Cys polymorphism on gynecologic cancer susceptibility. Electronic databases including PubMed, Embase, WanFang, and the China National Knowledge Infrastructure were searched for relevant studies. Odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were determined to assess the strength of the association. Fourteen studies with 2712 cases and 3638 controls were included in the final meta-analysis. The pooled analysis yielded a significant association between the hOGG1 Ser326Cys polymorphism and overall gynecologic cancer susceptibility (dominant model: OR = 1.16, 95% CI = 1.03–1.30, P=0.017). A significantly higher gynecologic cancer risk was found for the European population (homozygous model: OR = 2.17, 95% CI = 1.80–2.61, P<0.001; recessive model: OR = 2.11, 95% CI = 1.41–3.17, P<0.001; dominant model: OR = 1.29, 95% CI = 1.12–1.48, P<0.001; and allele model: OR = 1.40, 95% CI = 1.13–1.74, P=0.002), but not in the Asian population. The stratified analysis by cancer type revealed endometrial cancer was significantly associated with the hOGG1 Ser326Cys polymorphism (dominant model: OR = 1.29, 95% CI = 1.09–1.54, P=0.003; and allele model: OR = 1.28, 95% CI = 1.02–1.60, P=0.031). In conclusion, the hOGG1 Ser326Cys polymorphism was associated with higher overall gynecologic cancer susceptibility, especially for endometrial cancer in the European population.

show abstract