ArticleComputational and structural biotechnology journal2022
Survival estimation in patients with stomach and esophageal carcinoma using miRNA expression profiles.
Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Regulatory role of N-nitroso compounds and lncRNA NEAT1 in endoplasmic reticulum stress and malignant transformation of gastric epithelial cells.Cancer cell international · 2025Article
- Exploring prognostic implications of miRNA signatures and telomere maintenance genes in kidney cancer.Molecular therapy. Oncology · 2024Article
- An evolutionary learning-based method for identifying a circulating miRNA signature for breast cancer diagnosis prediction.NAR genomics and bioinformatics · 2024Article
- Expression Profiles of Hypoxia-Related Genes of Cancers Originating from Anatomically Similar Locations Using TCGA Database Analysis.Medicines (Basel, Switzerland) · 2023Article
- Artificial intelligence-driven pan-cancer analysis reveals miRNA signatures for cancer stage prediction.HGG advances · 2023Article
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying a miRNA signature associated with survival will open a new window for developing miRNA-targeted treatment strategies in stomach and esophageal cancers (STEC). Here, using data from The Cancer Genome Atlas on 516 patients with STEC, we developed a Genetic Algorithm-based Survival Estimation method, GASE, to identify a miRNA signature that could estimate survival in patients with STEC. GASE identified 27 miRNAs as a survival miRNA signature and estimated the survival time with a mean squared correlation coefficient of 0.80 ± 0.01 and a mean absolute error of 0.44 ± 0.25 years between actual and estimated survival times, and showed a good estimation capability on an independent test cohort. The miRNAs of the signature were prioritized and analyzed to explore their roles in STEC. The diagnostic ability of the identified miRNA signature was analyzed, and identified some critical miRNAs in STEC. Further, miRNA-gene target enrichment analysis revealed the involvement of these miRNAs in various pathways, including the somatotrophic axis in mammals that involves the growth hormone and transforming growth factor beta signaling pathways, and gene ontology annotations. The identified miRNA signature provides evidence for survival-related miRNAs and their involvement in STEC, which would aid in developing miRNA-target based therapeutics.
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