Phylostratigraphy Study of Cancer-related Genes
10.13748/j.cnki.issn1007-7693.20233174
- VernacularTitle:癌症相关基因的系统发育地层学研究
- Author:
Siqi WANG
1
;
Xun GU
2
;
Zhan ZHOU
1
Author Information
1. College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
2. Iowa State University, Ames 50011, USA
- Publication Type:Journal Article
- Keywords:
cancer atavism theory;
phylostratigraphy;
genes of different functional categories;
transcriptome age index
- From:
Chinese Journal of Modern Applied Pharmacy
2024;41(2):177-191
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE :To analyze the evolution of the transition from unicellular organisms to multicellular organisms from a phylogenetic stratigraphy perspective, combining the "cancer atavism hypothesis". To investigate the evolutionary chronology of cancer-related genes to guide research on cancer mechanisms and the development of treatment strategies.
METHODS
Phylostratr was used to identify the systematic evolutionary strata of all human protein-coding genes, housekeeping genes, cancer driver genes, tumor suppressor genes, oncogenes, neutral genes, and differentiation genes. Differential distribution of genes from different functional categories and human protein-coding genes was analyzed using log-odds ratios and hypergeometric distributions. TCGA was utilized to investigate transcriptional expression datas in cancer tumor samples and normal samples, and calculations and analysis were performed using transcriptome age index.
RESULTS
A total of 20291 protein-coding genes were classified into 27 different strata based on the farthest homologous species in the sequence alignment results. Within the phylogenetic stratigraphic structure, the datasets of 4159 housekeeping genes, 527 cancer driver genes, 87 tumor suppressor genes, 134 oncogenes, 10755 neutral genes, and 4274 differentiation genes exhibit distinct distribution patterns. The overall distribution of these genes significantly differs from that of all human protein-coding genes. Cancer-related genes exhibited a more ancient phylogenetic stratigraphic distribution. Transcriptome age index results for bile duct cancer, colon cancer, lung cancer, liver cancer, head and neck cancer, and kidney chromophobe samples showed strong expression of highly conserved and ancient genes within the tumors.
CONCLUSION
Cancer-related genes exhibit older evolutionary origins within the phylogenetic context suggesting a more conserved function during species evolution. And the phenomenon of enhanced expression of highly conserved ancient genes in tumor tissues can be used to explore tumor gene expression patterns, and provide new ideas for the discovery of new anti-tumor drug targets and drug research.
