Journal Article


Identification of novel cancer biomarkers of prognostic value using specific gene regulatory networks (GRN): a novel role of RAD51AP1 for ovarian and lung cancers

Abstract

To date, microarray analyses have led to the discovery of numerous individual “molecular signatures” associated with specific cancers. However, there are serious limitations for the adoption of these multi-gene signatures in the clinical environment for diagnostic or prognostic testing as studies with more power need to be carried out. This may involve larger richer cohorts and more advanced analyses. In this study, we conduct analyses -based on GRN- to reveal distinct and common biomarkers across cancer types. Using microarray data of triple negative and medullary breast, ovarian and lung cancers applied to a combination of glasso and Bayesian Networks, we derived a unique-network containing genes that are uniquely involved : small proline-rich protein 1A (SPRR1A), follistatin like 1 (FSTL1), collagen type XII alpha 1 (COL12A1) and RAD51 associated protein 1 (RAD51AP1). RAD51AP1 and FSTL1 are significantly overexpressed in ovarian cancer patients but only RAD51AP1 is upregulated in lung cancer patients compared to healthy controls. The upregulation of RAD51AP1 was mirrored in the bloods of both ovarian and lung cancer patients and KM plots predicted poorer overall survival in patients with high expression of RAD51AP1. Suppression of RAD51AP1 by RNA interference reduced cell proliferation in vitro in ovarian (SKOV3) and lung (A549) cancer cells. This effect appears to be modulated by a decrease in the expression of mTOR-related genes and pro-metastatic candidate genes. Our data describes how an initial in silico approach can generate novel biomarkers that could potentially support current clinical practice and improve long term outcomes.

Attached files

Authors

Chudasama , Dimple
Bo, Valeria
Hall, Marcia
Anikin, Vladimir
Jeyaneethi, Jeyarooban
Gregory, Jane
Pados, George
Tucker, Allan
Harvey, Amanda
Pink, Ryan
Karteris, Emmanouil

Oxford Brookes departments

Faculty of Health and Life Sciences\Department of Biological and Medical Sciences

Dates

Year of publication: 2017
Date of RADAR deposit: 2017-11-23


Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License


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