Interactive potential of genetic polymorphism in Xenobiotic metabolising and DNA repair genes for predicting lung cancer predisposition and overall survival in North Indians

XRCC1 and hOGG1 polymorphisms and endometrial carcinoma: A meta-analysis

Endometrial carcinoma's (EC) etiology is complex and involves DNA repair gene polymorphisms like XRCC1-Arg399Gln and hOGG1-Ser326Cys, but their association with the disease is unclear. Following PRISMA, we conducted a systematic review and meta-analysis, collecting data from four databases. The studies needed to be population-based case-control studies examining the association between the named polymorphisms and EC. Quality was assessed with the Newcastle-Ottawa Scale. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated, and subgroup analyses were conducted based on ethnicity. Seven studies were included. Both polymorphisms were found to significantly increase EC risk, particularly in Caucasians. XRCC1-Arg399Gln showed a dominant model OR of 1.14 (95% CI: 1.01-1.29) and a homozygous model OR of 1.59 (95% CI: 1.12-2.25). The heterozygote model OR for hOGG1-Ser326Cys was 1.29 (95% CI: 1.02-1.63), and the allele OR was 1.31 (95% CI: 1.07-1.60). XRCC1-Arg399Gln and hOGG1-Ser326Cys may increase EC risk, primarily in Caucasian women, emphasizing the role of DNA repair in disease susceptibility. More extensive studies are needed to validate these findings in diverse ethnicities and investigate other DNA repair gene polymorphisms.

A 13-Gene Metabolic Prognostic Signature Is Associated With Clinical and Immune Features in Stomach Adenocarcinoma

Patients with advanced stomach adenocarcinoma (STAD) commonly show high mortality and poor prognosis. Increasing evidence has suggested that basic metabolic changes may promote the growth and aggressiveness of STAD; therefore, identification of metabolic prognostic signatures in STAD would be meaningful. An integrative analysis was performed with 407 samples from The Cancer Genome Atlas (TCGA) and 433 samples from Gene Expression Omnibus (GEO) to develop a metabolic prognostic signature associated with clinical and immune features in STAD using Cox regression analysis and least absolute shrinkage and selection operator (LASSO). The different proportions of immune cells and differentially expressed immune-related genes (DEIRGs) between high- and low-risk score groups based on the metabolic prognostic signature were evaluated to describe the association of cancer metabolism and immune response in STAD. A total of 883 metabolism-related genes in both TCGA and GEO databases were analyzed to obtain 184 differentially expressed metabolism-related genes (DEMRGs) between tumor and normal tissues. A 13-gene metabolic signature (GSTA2, POLD3, GLA, GGT5, DCK, CKMT2, ASAH1, OPLAH, ME1, ACYP1, NNMT, POLR1A, and RDH12) was constructed for prognostic prediction of STAD. Sixteen survival-related DEMRGs were significantly related to the overall survival of STAD and the immune landscape in the tumor microenvironment. Univariate and multiple Cox regression analyses and the nomogram proved that a metabolism-based prognostic risk score (MPRS) could be an independent risk factor. More importantly, the results were mutually verified using TCGA and GEO data. This study provided a metabolism-related gene signature for prognostic prediction of STAD and explored the association between metabolism and the immune microenvironment for future research, thereby furthering the understanding of the crosstalk between different molecular mechanisms in human STAD. Some prognosis-related metabolic pathways have been revealed, and the survival of STAD patients could be predicted by a risk model based on these pathways, which could serve as prognostic markers in clinical practice.