Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK.
Wishaw General Hospital, NHS Lanarkshire, Scotland, UK.
BMC Cancer. 2022 Aug 10;22(1):874. doi: 10.1186/s12885-022-09969-4.
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 the application of a bioinformatics-based approach 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 clinical data 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.
乳腺癌包括几种亚表型，是英国女性癌症相关死亡的主要原因，占所有癌症病例的 15%。乳腺癌的化疗耐药亚表型仍然是一个特别的挑战。然而，临床数据集的可用性迅速增加，为基于数据的精准医学方法提供了支持，探索用于诊断和治疗干预的新靶点。我们报告了一种基于生物信息学的方法在乳腺癌预后中探测核转运蛋白 2 阿尔法 (KPNA2) 的表达和预后作用的应用。异常的 KPNA2 过表达与侵袭性肿瘤表型和患者生存不良结果直接相关。我们检查了 KPNA2 的一系列常见突变的现有临床数据及其与患者生存的相关性。我们对临床基因表达数据集的分析表明，KPNA2 在乳腺癌中经常扩增，观察到表达水平的差异是作为患者年龄和临床病理参数的函数。我们还发现异常的 KPNA2 过表达与患者预后不良直接相关，需要进一步研究 KPNA2 作为患者分层或设计新型化疗药物的可操作靶点。在大数据时代，公共领域中可用的大量数据集可用于支持概念验证研究，评估涉及乳腺癌化疗耐药的生物分子途径。
