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雄激素受体对激素受体阳性且人表皮生长因子受体2阴性的印度乳腺癌患者复发评分的影响:一种比较方法

Androgen Receptor Influenced Recurrence Score Correlation in Hormone Positive and HER2 Negative Breast Cancer Indian Patients: A Comparative Approach.

作者信息

Chowdhury Amit Roy, Swain Somya Saswati, Mohanty Sandip Kumar, Banerjee Birendranath

机构信息

Molecular Stress and Stem Cell Biology Group, School of Biotechnology, KIIT University, Bhubaneswar, Odisha, India.

inDNA Centre for Research and Innovation in Molecular Diagnostics, inDNA Life Sciences Private Limited, Bhubaneswar, Odisha, India.

出版信息

Genome Integr. 2024 Jul 4;15:e20240001. doi: 10.14293/genint.15.1.001. eCollection 2024.

Abstract

Breast cancer (BC) recurrence is a major concern for both patients and healthcare providers. Accurately predicting the risk of BC recurrence can help guide treatment decisions and improve patient outcomes for a disease-free survival. There are several approaches and models that have been developed to predict BC recurrence risk. These include derived clinical assays such as genetic profiling (Oncotye Dx, MammaPrint, CanAssist and others), and algorithm derived open access tools such as Magee equations (ME), CTS5 Calculator and Predict Breast cancer. All the clinical assays are well accepted, but affordability and feasibility remain the challenge due to a noteworthy price tag of USD 3000. As per The American Society of Clinical Oncology (ASCO) updates, open access tools are possible substitutes but the availability of limited information on their applicability is a concern. These tools take into consideration the histopathologic parameters and immunohistochemistry (IHC) biomarkers data for estrogen receptor/progesterone (ER/PR), human epidermal growth factor receptor 2 (HER2), and Ki67. The current study focuses on the application of these tools in a subset of 55 Indian BC patients considering the influence of the androgen receptor (AR) IHC expression profile. AR is a potent target and a close interacting neighbor protein to ER and available literature also suggests their crosstalk expression in BC clinical models. Our comparative recurrence scores (RSs) predictive data showed a statistically significant AR expression correlation with average ME scores. No significance was noted across different prediction tools. The findings are suggestive that ME predictive scores are more relevant and informative compared to other online tools and with an additional AR IHC expression analysis the recurrence prediction might prove to be beneficial and feasible to many deprived BC patients.

摘要

乳腺癌(BC)复发是患者和医疗服务提供者共同关注的主要问题。准确预测BC复发风险有助于指导治疗决策,并改善患者无病生存的预后。目前已开发出多种方法和模型来预测BC复发风险。这些方法包括衍生临床检测,如基因谱分析(Oncotye Dx、MammaPrint、CanAssist等),以及算法衍生的开放获取工具,如马吉方程(ME)、CTS5计算器和预测乳腺癌工具。所有临床检测都得到了广泛认可,但由于价格高达3000美元,可承受性和可行性仍然是一个挑战。根据美国临床肿瘤学会(ASCO)的更新,开放获取工具可能是替代方案,但关于其适用性的信息有限,这是一个令人担忧的问题。这些工具考虑了雌激素受体/孕激素(ER/PR)、人表皮生长因子受体2(HER2)和Ki67的组织病理学参数和免疫组织化学(IHC)生物标志物数据。本研究聚焦于这些工具在55例印度BC患者亚组中的应用,并考虑雄激素受体(AR)免疫组化表达谱的影响。AR是一个重要靶点,也是与ER密切相互作用的邻近蛋白,现有文献也表明它们在BC临床模型中有相互作用的表达。我们的比较复发评分(RSs)预测数据显示,AR表达与平均ME评分之间存在统计学显著相关性。不同预测工具之间未发现显著差异。研究结果表明,与其他在线工具相比,ME预测评分更具相关性和信息量,并且通过额外的AR免疫组化表达分析,复发预测可能对许多贫困BC患者有益且可行。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a061/11622693/a3ce6c8a4d87/genint-15-20240001-001g.jpg

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