Prognostic modeling and Emerging therapeutic targets Unveiled through single-cell sequencing in esophageal squamous Cell carcinoma.

ABSTRACT: ESCC presents a significant global health challenge due to its high mortality rates and varying responses to treatment. This underscores the critical need for novel diagnostic and predictive biomarkers to improve treatment outcomes. Initially, we conducted single-cell transcriptome sequencing on a total of 128,688 cells obtained from 10 patients as part of our research. Utilizing machine learning and cross-validation techniques, we developed a model incorporating 12 genes that distinguish malignant cells from non-malignant ones. In vitro, we explored the effects of IGFBP2 knockdown on the proliferation, invasion, and migration of ESCC cells. The clinical relevance of IGFBP2 was confirmed through IHC and Kaplan-Meier survival analyses. Furthermore, using bioinformatics tools such as GSVA an

SUBMITTER: Pan B 

PROVIDER: S-EPMC11470424 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature