Pan-cancer integrative analysis of whole-genome De novo somatic point mutations reveals 17 cancer types.

ABSTRACT:

Background

The advent of high throughput sequencing has enabled researchers to systematically evaluate the genetic variations in cancer, identifying many cancer-associated genes. Although cancers in the same tissue are widely categorized in the same group, they demonstrate many differences concerning their mutational profiles. Hence, there is no definitive treatment for most cancer types. This reveals the importance of developing new pipelines to identify cancer-associated genes accurately and re-classify patients with similar mutational profiles. Classification of cancer patients with similar mutational profiles may help discover subtypes of cancer patients who might benefit from specific treatment types.

Results

In this study, we propose a new machine learning pipeline to

SUBMITTER: Ghareyazi A 

PROVIDER: S-EPMC9316662 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature