Leveraging diverse cell-death patterns to predict the prognosis, immunotherapy and drug sensitivity of clear cell renal cell carcinoma.

ABSTRACT: Clear cell renal cell carcinoma (ccRCC) poses clinical challenges due to its varied prognosis, tumor microenvironment attributes, and responses to immunotherapy. We established a novel Programmed Cell Death-related Signature (PRS) for ccRCC assessment, derived through the Least Absolute Shrinkage and Selection Operator (LASSO) regression method. We validated PRS using the E-MTAB-1980 dataset and created PCD-related clusters via non-negative matrix factorization (NMF). Our investigation included an in-depth analysis of immune infiltration scores using various algorithms. Additionally, we integrated data from the Cancer Immunome Atlas (TCIA) for ccRCC immunotherapy insights and leveraged the Genomics of Drug Sensitivity in Cancer (GDSC) database to assess drug sensitivity models. We compleme

SUBMITTER: Zhang X 

PROVIDER: S-EPMC10662159 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature