A risk score model based on lipid metabolism-related genes could predict response to immunotherapy and prognosis of lung adenocarcinoma: a multi-dataset study and cytological validation.

ABSTRACT:

Background

Lipid metabolism is a key factor in tumorigenesis and drug resistance, and models related to lipid metabolism have shown potential to predict survival and curative effects of adjuvant therapy in various cancers. However, the relationship between lipid metabolism and prognosis and treatment response of lung adenocarcinoma (LUAD) are still unclear.

Methods

We enrolled seven bulk RNA-sequence datasets (GSE37745, GSE19188, GSE30219, GSE31547, GSE41271, GSE42127, and GSE72094) from the GEO database and one single-cell RNA-sequencing dataset (GSE117570) from the TISCH2 database. Non-negative matrix factorization (NMF) was utilized to construct the risk score model based on lipid score calculated by GSVA algorithm. Phs000452.v3, PMID: 26359337, PMID: 32472114, PRJEB23709

SUBMITTER: Lei Y 

PROVIDER: S-EPMC10597940 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature