Integrating single-cell and bulk expression data to identify and analyze cancer prognosis-related genes.

ABSTRACT: Compared with traditional evaluation methods of cancer prognosis based on tissue samples, single-cell sequencing technology can provide information on cell type heterogeneity for predicting biomarkers related to cancer prognosis. Therefore, the bulk and single-cell expression profiles of breast cancer and normal cells were comprehensively analyzed to identify malignant and non-malignant markers and construct a reliable prognosis model. We first screened highly reliable differentially expressed genes from bulk expression profiles of multiple breast cancer tissues and normal tissues, and inferred genes related to cell malignancy from single-cell data. Then we identified eight critical genes related to breast cancer to conduct Cox regression analysis, calculate polygenic risk score (PRS), and

SUBMITTER: Bao S 

PROVIDER: S-EPMC10877256 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature