bioRxivCancer Biology
Copy number alterations and epithelial-mesenchymal transition genes in diffuse and intestinal gastric cancers in Mexican patients
V. Larios-Serrato, J. D. Martinez-Ezquerro, H.-A. Valdez-Salazar, J. Torres, M. Camorlinga-Ponce, P. Pina-Sanchez, M.-E. Ruiz-Tachiquin
Abstract
Gastric cancer (GC) is a malignancy with the highest mortality among diseases of the digestive system worldwide. The study of GC-alterations is crucial to understand tumor biology, to establish important aspects of cancer prognosis and treatment response. Here, we purified DNA and performed whole-genome analysis with high-density arrays in samples from Mexican patients diagnosed with GC: diffuse (DGC) or intestinal (IGC), or non-atrophic gastritis (NAG) samples that served as controls. We identified shared and unique copy number alterations (CNA) between these altered tissues involving key genes and signaling pathways associated with cancer, allowing their molecular distinction and identification of the most relevant molecular functions impacted. When focused on epithelial-mesenchymal transition (EMT) genes, our bioinformatic analysis revealed that the altered network associated with chromosomal alterations included 11 genes shared between DGC, IGC, and NAG, as well as 19 DGC- and 7 IGC-exclusive genes, whose main molecular functions included adhesion, angiogenesis, migration, metastasis, morphogenesis, proliferation, and survival. This study presents the first whole-genome high-density array study in GC from Mexican patients and reveals shared and exclusive CNA-genes in DGC and IGC. In addition, we provide a bioinformatically predicted network focused on CNA-altered genes involved in the EMT, associated with the hallmarks of cancer, as well as precancerous alterations that could lead to gastric cancer. ImplicationsMolecular signatures of diffuse and intestinal GC, predicted bioinformatically, involve common and distinct CNA-EMT genes related to the hallmarks of cancer that are potential candidates for screening GC biomarkers, including early stages.
- organism: human
- assay: whole-genome sequencing
- research focus: differential expression
- approach: statistical model
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