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潜在生物标志物作为预测乳腺癌患者对初始化疗反应的因素。

Potential biomarkers as a predictive factor of response to primary chemotherapy in breast cancer patients.

机构信息

Departamento de Ginecologia e Obstetrícia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brasil.

Laboratório de Ciência de Dados Translacionais, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brasil.

出版信息

Braz J Med Biol Res. 2024 Oct 7;57:e13599. doi: 10.1590/1414-431X2024e13599. eCollection 2024.

Abstract

In this study, we identified miRNAs and their potential mRNA targets that are intricately linked to primary chemotherapy response in patients with invasive ductal carcinomas. A cohort of individuals diagnosed with advanced invasive breast ductal carcinoma who underwent primary chemotherapy served as the cornerstone of our study. We conducted a comparative analysis of microRNA expression among patients who either responded or did not respond to primary systemic therapy. To analyze the correlation between the expression of the whole transcriptome and the 24 differentially expressed (DE) miRNAs, we harnessed the extensive repository of The Cancer Genome Atlas (TCGA) database. We mapped molecular mechanisms associated with these miRNAs and their targets from TCGA breast carcinomas. The resultant expression profile of the 24 DE miRNAs emerged as a potent and promising predictive model, offering insights into the intricate dynamics of chemotherapy responsiveness of advanced breast tumors. The discriminative analysis based on the principal component analysis identified the most representative miRNAs across breast cancer samples (miR-210, miR-197, miR-328, miR-519a, and miR-628). Moreover, the consensus clustering generated four possible clusters of TCGA patients. Further studies should be conducted to advance these findings.

摘要

在这项研究中,我们鉴定了与浸润性导管癌患者原发性化疗反应密切相关的 miRNAs 及其潜在的 mRNA 靶标。我们的研究以一组接受原发性化疗的晚期浸润性乳腺导管癌患者为基石。我们对原发性全身治疗有反应和无反应的患者的 microRNA 表达进行了比较分析。为了分析整个转录组表达与 24 个差异表达(DE)miRNA 之间的相关性,我们利用了癌症基因组图谱(TCGA)数据库的广泛资源。我们从 TCGA 乳腺癌中分析了与这些 miRNAs 及其靶标相关的分子机制。这 24 个 DE miRNAs 的表达谱呈现出一个强大而有前途的预测模型,深入了解了晚期乳腺癌化疗反应的复杂动态。基于主成分分析的判别分析确定了乳腺癌样本中最具代表性的 miRNAs(miR-210、miR-197、miR-328、miR-519a 和 miR-628)。此外,共识聚类生成了 TCGA 患者的四个可能聚类。应该进行进一步的研究来推进这些发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aca/11463908/f49957d34d0b/1414-431X-bjmbr-57-e13599-gf001.jpg

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