Investigating Combined Hypoxia and Stemness Indices for Prognostic Transcripts in Gastric Cancer: Machine Learning and Network Analysis Approaches
Sharareh Mahmoudian-Hamedani,
Maryam Lotfi-Shahreza,
Parvaneh Nikpour
Abstract:IntroductionGastric cancer (GC) is among the deadliest malignancies globally, characterized by hypoxia-driven pathways that promote cancer progression, including mechanisms associated with stemness facilitating invasion and metastasis. This study aimed to develop a prognostic decision tree using genes implicated in hypoxia and stemness pathways to predict outcomes in GC patients.Material and MethodsGC RNA-seq data from The Cancer Genome Atlas (TCGA) were utilized to compute hypoxia and stemness scores via Gene… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.