The role of KPNA2 mutations in breast cancer prognosis : a survey of publicly available databases

Alnoumas, Layla and Van Den Driest, Lisa and Lannigan, Alison and Johnson, Caroline H and Rattray, Nicholas JW and Rattray, Zahra (2021) The role of KPNA2 mutations in breast cancer prognosis : a survey of publicly available databases. Other. medRxiv, New York. (https://doi.org/10.1101/2021.11.10.21266193)

[thumbnail of Alnoumas-etal-medRxiv-2021-The-role-of-KPNA2-mutations-in-breast-cancer-prognosis]
Preview
Text. Filename: Alnoumas_etal_medRxiv_2021_The_role_of_KPNA2_mutations_in_breast_cancer_prognosis.pdf
Final Published Version
License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 logo

Download (797kB)| Preview

Abstract

Breast cancer, comprising of several sub-phenotypes, is a leading cause of female cancer-related mortality in the UK and accounts for 15% of all cancer cases. Chemoresistant sub phenotypes of breast cancer remain a particular challenge. However, the rapidly-growing availability of clinical datasets, presents the scope to underpin a data driven precision medicine-based approach exploring new targets for diagnostic and therapeutic interventions. We report a survey of several publicly available databases probing the expression and prognostic role of Karyopherin-2 alpha (KPNA2) in breast cancer prognosis. Aberrant KPNA2 overexpression is directly correlated with aggressive tumour phenotypes and poor patient survival outcomes. We examined the existing information available on a range of commonly occurring mutations of KPNA2 and their correlation with patient survival. Our analysis of clinical gene expression datasets show that KPNA2 is frequently amplified in breast cancer, with differences in expression levels observed as a function of patient age and clinicopathologic parameters. We also found that aberrant KPNA2 overexpression is directly correlated with poor patient prognosis, warranting further investigation of KPNA2 as an actionable target for patient stratification or the design of novel chemotherapy agents. In the era of big data, the wealth of datasets available in the public domain can be used to underpin proof of concept studies evaluating the biomolecular pathways implicated in chemotherapy resistance in breast cancer.