Evaluation of the role of KPNA2 mutations in breast cancer prognosis using bioinformatics datasets.
Evaluation of the role of KPNA2 mutations in breast cancer prognosis using bioinformatics datasets.
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DOI：
10.1186/s12885-022-09969-4
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发表时间：
2022-08-10
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影响因子：
3.8
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中科院分区：
文献类型：
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乳腺癌由几种亚表型组成，是英国女性癌症相关死亡率的主要原因，占所有癌症病例的15%。乳腺癌的耐药亚表型仍然是一个特别的挑战。然而，临床数据集的快速增长为基于数据驱动的精准医学方法提供了支持，该方法探索了诊断和治疗干预的新目标。我们报告了一种基于生物信息学的方法在乳腺癌预后中的应用，该方法探讨了Karyopherin-2 alpha（KPNA 2）的表达和预后作用。异常KPNA 2过表达与侵袭性肿瘤表型和患者生存结局差直接相关。我们研究了现有的临床数据，这些数据涉及一系列常见的KPNA 2突变及其与患者生存率的相关性。我们对临床基因表达数据集的分析表明，KPNA 2在乳腺癌中经常扩增，观察到患者年龄和临床病理参数的表达水平差异。我们还发现，异常KPNA 2过表达与患者预后不良直接相关，这表明KPNA 2可作为患者分层或设计新型化疗药物的可行靶点。在大数据时代，公共领域中可用的丰富数据集可用于支持概念验证研究，评估与乳腺癌化疗耐药性有关的生物分子途径。在线版本包含补充材料，可通过10.1186/s12885-022-09969-4获得。
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. The online version contains supplementary material available at 10.1186/s12885-022-09969-4.
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