Association of Methylenetetrahydrafolate Reductase Gene Polymorphism (MTHFR) in Patients with Gallbladder Cancer

Gallbladder cancer: Progress in the Indian subcontinent

Gallbladder cancer (GBC) is one of the commonest biliary malignancies seen in India, Argentina, and Japan. The disease has dismal outcome as it is detected quite late due to nonspecific symptoms and signs. Early detection is the only way to improve the outcome. There have been several advances in basic as well as clinical research in the hepatobiliary and pancreatic diseases in the West and other developed countries but not enough has been done in GBC. Therefore, it is important and the responsibility of the countries with high burden of GBC to find solutions to the many unanswered questions like etiopathogenesis, early diagnosis, treatment, and prognostication. As India being one of the largest hubs for GBC in the world, it is important to know how the country has progressed on GBC. In this review, we will discuss the outcome of the publications from India highlighting the work and the developments taken place in past several decades both in basic and clinical research.

MAP kinase and mammalian target of rapamycin are main pathways of gallbladder carcinogenesis: results from bioinformatic analysis of next generation sequencing data from a hospital-based cohort (NCT05404347)

BACKGROUND

Gallbladder Cancer (GBC) is one of the most common cancers of the biliary tract and the third commonest gastrointestinal (GI) malignancy worldwide. The disease is characterized by the late presentation and poor outcome despite treatment, and hence, newer therapies and targets need to be identified.

METHODS

The current study investigated various functionally enriched pathways in GBC pathogenesis involving the genes identified through Next Generation Sequencing (NGS) in a hospital-based cohort. The Pathway enrichment analysis and Gene Ontology (GO) were carried out after NGS, followed by the construction of the protein-protein interaction (PPI) network to discover associations among the genes.

RESULTS

Of the thirty-three patients with GBC who were screened through next-generation sequencing (NGS), 27somatic mutations were identified. These mutations involved a total of 14 genes. The p53 and KRAS were commonly found to be mutated, while mutations in other genes were seen in one case each, the mean number of mutations were 1.2, and maximum mutation in a single case (eight) was seen in one case. The bioinformatics analysis identified MAP kinase, PI3K-AKT, EGF/EGFR, and Focal Adhesion PI3K-AKT-mTOR signaling pathways and cross-talk between these.

CONCLUSION

The results suggest that the complex crosstalk between the mTOR, MAPK, and multiple interacting cell signaling cascades can promote GBC progression, and hence, mTOR-MAPK targeted treatment will be an attractive option.

Pan-cancer analysis of m5C regulator genes reveals consistent epigenetic landscape changes in multiple cancers

BACKGROUND

5-Methylcytosine (m5C) is a reversible modification to both DNA and various cellular RNAs. However, its roles in developing human cancers are poorly understood, including the effects of mutant m5C regulators and the outcomes of modified nucleobases in RNAs.

METHODS

Based on The Cancer Genome Atlas (TCGA) database, we uncovered that mutations and copy number variations (CNVs) of m5C regulatory genes were significantly correlated across many cancer types. We then assessed the correlation between the expression of individual m5C regulators and the activity of related hallmark pathways of cancers.

RESULTS

After validating m5C regulators' expression based on their contributions to cancer development and progression, we observed their upregulation within tumor-specific processes. Notably, our research connected aberrant alterations to m5C regulatory genes with poor clinical outcomes among various tumors that may drive cancer pathogenesis and/or survival.

CONCLUSION

Our results offered strong evidence and clinical implications for the involvement of m5C regulators.

LncRNA TTN-AS1 acts as a tumor promoter in gallbladder carcinoma by regulating miR-107/HMGA1 axis

Background

The incidence of gallbladder carcinoma (GBM) in China has increased in recent years. Here, the functional mechanism of lncRNA TTN-AS1 in GBC was preliminary elucidated.

Methods

The expression levels of lncRNA TTN-AS1, miR-107, and HMGA1 in tissues and cell lines were assessed by RT-qPCR. Cell proliferation was measured by MTT assays. Cell invasion and migration abilities were evaluated by Transwell assays. The relationship between miR-107 and lncRNA TTN-AS1 or HMGA1 was confirmed by luciferase reporter assay.

Results

Upregulation of lncRNA TTN-AS1 and downregulation of miR-107 were detected in GBC. Furthermore, the expressions between TTN-AS1 and miR-107 were mutually inhibited in GBC. Functionally, lncRNA TTN-AS1 promoted cell viability and motility in GBC by sponging miR-107. In addition, miR-107 directly targets HMGA1. And HMGA1 can be positively regulated by lncRNA TTN-AS1 in GBC. Furthermore, HMGA1 promoted GBC progression by interacting with lncRNA TTN-AS1/miR-107 axis.

Conclusion

LncRNA TTN-AS1 acted as a tumor promoter in GBC by sponging miR-107 and upregulating HMGA1.

Computational Prediction of Probable Single Nucleotide Polymorphism-Cancer Relationships

Genetic variations such as single nucleotide polymorphisms (SNPs) can cause susceptibility to cancer. Although thousands of genetic variants have been identified to be associated with different cancers, the molecular mechanisms of cancer remain unknown. There is not a particular dataset of relationships between cancer and SNPs, as a bipartite network, for computational analysis and prediction. Link prediction as a computational graph analysis method can help us to gain new insight into the network. In this article, after creating a network between cancer and SNPs using SNPedia and Cancer Research UK databases, we evaluated the computational link prediction methods to foresee new SNP-Cancer relationships. Results show that among the popular scoring methods based on network topology, for relation prediction, the preferential attachment (PA) algorithm is the most robust method according to computational and experimental evidence, and some of its computational predictions are corroborated in recent publications. According to the PA predictions, rs1801394-Non-small cell lung cancer, rs4880-Non-small cell lung cancer, and rs1805794-Colorectal cancer are some of the best probable SNP-Cancer associations that have not yet been mentioned in any published article, and they are the most probable candidates for additional laboratory and validation studies. Also, it is feasible to improve the predicting algorithms to produce new predictions in the future.