Establishment, immunological analysis, and drug prediction of a prognostic signature of ovarian cancer related to histone acetylation.

ABSTRACT: In recent years, epigenetic modifications have been increasingly regarded as an important hallmark of cancer. Histone acetylation, as an important part of epigenetic modification, plays a key role in the progress, treatment, and prognosis of many cancers. In this study, based on the TCGA database, we performed LASSO regression and the Cox algorithm to establish a prognostic signature of ovarian cancer associated with histone acetylation modulator genes and verified it externally in the GEO database. Subsequently, we performed an immunological bioinformatics analysis of the model from multiple perspectives using the CIBERSORT algorithm, ESTIMATE algorithm, and TIDE algorithm to verify the accuracy of the model. Based on the prognostic model, we divided ovarian cancer patients into high-risk

SUBMITTER: Fang Y 

PROVIDER: S-EPMC9510621 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature