Pan-cancer analysis implicates novel insights of lactate metabolism into immunotherapy response prediction and survival prognostication.

ABSTRACT:

Background

Immunotherapy has emerged as a potent clinical approach for cancer treatment, but only subsets of cancer patients can benefit from it. Targeting lactate metabolism (LM) in tumor cells as a method to potentiate anti-tumor immune responses represents a promising therapeutic strategy.

Methods

Public single-cell RNA-Seq (scRNA-seq) cohorts collected from patients who received immunotherapy were systematically gathered and scrutinized to delineate the association between LM and the immunotherapy response. A novel LM-related signature (LM.SIG) was formulated through an extensive examination of 40 pan-cancer scRNA-seq cohorts. Then, multiple machine learning (ML) algorithms were employed to validate the capacity of LM.SIG for immunotherapy response prediction and surviva

SUBMITTER: Chen D 

PROVIDER: S-EPMC11044366 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature