Pseudogene-gene functional networks are prognostic of patient survival in breast cancer.

ABSTRACT:

Background

Given the vast range of molecular mechanisms giving rise to breast cancer, it is unlikely universal cures exist. However, by providing a more precise prognosis for breast cancer patients through integrative models, treatments can become more individualized, resulting in more successful outcomes. Specifically, we combine gene expression, pseudogene expression, miRNA expression, clinical factors, and pseudogene-gene functional networks to generate these models for breast cancer prognostics. Establishing a LASSO-generated molecular gene signature revealed that the increased expression of genes STXBP5, GALP and LOC387646 indicate a poor prognosis for a breast cancer patient. We also found that increased CTSLP8 and RPS10P20 and decreased HLA-K pseudogene expression indicate p

SUBMITTER: Smerekanych S 

PROVIDER: S-EPMC7118805 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature