Topological integration of RPPA proteomic data with multi-omics data for survival prediction in breast cancer via pathway activity inference.

ABSTRACT:

Background

The analysis of integrated multi-omics data enables the identification of disease-related biomarkers that cannot be identified from a single omics profile. Although protein-level data reflects the cellular status of cancer tissue more directly than gene-level data, past studies have mainly focused on multi-omics integration using gene-level data as opposed to protein-level data. However, the use of protein-level data (such as mass spectrometry) in multi-omics integration has some limitations. For example, the correlation between the characteristics of gene-level data (such as mRNA) and protein-level data is weak, and it is difficult to detect low-abundance signaling proteins that are used to target cancer. The reverse phase protein array (RPPA) is a highly sensitive anti

SUBMITTER: Kim TR 

PROVIDER: S-EPMC6624183 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature