Robust metabolic transcriptional components in 34,494 patient-derived cancer-related samples and cell lines.

ABSTRACT:

Background

Patient-derived bulk expression profiles of cancers can provide insight into the transcriptional changes that underlie reprogrammed metabolism in cancer. These profiles represent the average expression pattern of all heterogeneous tumor and non-tumor cells present in biopsies of tumor lesions. Hence, subtle transcriptional footprints of metabolic processes can be concealed by other biological processes and experimental artifacts. However, consensus independent component analyses (c-ICA) can capture statistically independent transcriptional footprints of both subtle and more pronounced metabolic processes.

Methods

We performed c-ICA with 34,494 bulk expression profiles of patient-derived tumor biopsies, non-cancer tissues, and cell lines. Gene set enrichment analys

SUBMITTER: Leeuwenburgh VC 

PROVIDER: S-EPMC8474886 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature