The identification of driver genes is of great importance in modern medical research. It is also an essential factor in the development of individualization and has a positive effect on understanding the causes of cancer. Gene mutations are the primary cause of the outcomes of the process of tumorigenesis. Driver genes can be used as therapeutic targets for tumor-specific mutation-dependent overexpression. This study sought to identify mutation-based driver genes in gastric cancer (GC) by applying comprehensive gene expression and copy number analysis. Multiplatform analysis was used to identify four major genomic subtypes of GC. The most prominent cancer-related variations observed in this cohort were mutations (found in 56% of tumors), followed by (51%), (7%), and (6%) mutations. In our analysis, mutation characteristics were mainly related to the DNA mismatch repair system. In addition, 34 candidate driver oncogenes were identified in GC. Further research identified six GC-related driver genes associated with the levels of immune infiltration of different immune cells and the majority of immune markers. Our mutation-based study of driver oncogenes identified potential drug targets in GC.
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http://dx.doi.org/10.3389/fonc.2022.920207 | DOI Listing |
Commun Biol
January 2025
Department of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, CO, USA.
Symbioses are major drivers of organismal diversification and phenotypic innovation. However, how long-term symbioses shape whole genome evolution in metazoans is still underexplored. Here, we use a giant clam (Tridacna maxima) genome to demonstrate how symbiosis has left complex signatures in an animal's genome.
View Article and Find Full Text PDFNat Commun
January 2025
State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Sciences, Beijing, China.
The relative contributions of mutation rate variation, selection, and recombination in shaping genomic variation in bacterial populations remain poorly understood. Here we analyze 3318 Yersinia pestis genomes, spanning nearly a century and including 2336 newly sequenced strains, to shed light on the patterns of genetic diversity and variation distribution at the population level. We identify 45 genomic regions ("hot regions", HRs) that, although comprising a minor fraction of the genome, are hotbeds of genetic variation.
View Article and Find Full Text PDFMol Oncol
January 2025
Department of Medicine, Clinic III - Hematology, Oncology, Palliative Medicine, Rostock University Medical Center, Germany.
Hypermethylation of tumor suppressor genes is a hallmark of leukemia. The hypomethylating agent decitabine covalently binds, and degrades DNA (cytosine-5)-methyltransferase 1 (DNMT1). Structural similarities within DNA-binding domains of DNMT1, and the leukemic driver histone-lysine N-methyltransferase 2A (KMT2A) suggest that decitabine might also affect the latter.
View Article and Find Full Text PDFNat Genet
January 2025
Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
Transcription factors are frequent cancer driver genes, exhibiting noted specificity based on the precise cell of origin. We demonstrate that ZIC1 exhibits loss-of-function (LOF) somatic events in group 4 (G4) medulloblastoma through recurrent point mutations, subchromosomal deletions and mono-allelic epigenetic repression (60% of G4 medulloblastoma). In contrast, highly similar SHH medulloblastoma exhibits distinct and diametrically opposed gain-of-function mutations and copy number gains (20% of SHH medulloblastoma).
View Article and Find Full Text PDFNat Cancer
January 2025
Cancer Systems Biology Laboratory, The Francis Crick Institute, London, UK.
CDKN2A is a tumor suppressor located in chromosome 9p21 and frequently lost in Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC). How CDKN2A and other 9p21 gene co-deletions affect EAC evolution remains understudied. We explored the effects of 9p21 loss in EACs and cancer progressor and non-progressor BEs with matched genomic, transcriptomic and clinical data.
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