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基于转录组学的病理性血管生成特征可预测乳腺癌患者的生存情况。

A transcriptome-based signature of pathological angiogenesis predicts breast cancer patient survival.

机构信息

Biochemistry Department, Institute of Chemistry, University of São Paulo, São Paulo, Brazil.

Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.

出版信息

PLoS Genet. 2019 Dec 17;15(12):e1008482. doi: 10.1371/journal.pgen.1008482. eCollection 2019 Dec.

Abstract

The specific genes and molecules that drive physiological angiogenesis differ from those involved in pathological angiogenesis, suggesting distinct mechanisms for these seemingly related processes. Unveiling genes and pathways preferentially associated with pathologic angiogenesis is key to understanding its mechanisms, thereby facilitating development of novel approaches to managing angiogenesis-dependent diseases. To better understand these different processes, we elucidated the transcriptome of the mouse retina in the well-accepted oxygen-induced retinopathy (OIR) model of pathological angiogenesis. We identified 153 genes changed between normal and OIR retinas, which represent a molecular signature relevant to other angiogenesis-dependent processes such as cancer. These genes robustly predict the survival of breast cancer patients, which was validated in an independent 1,000-patient test cohort (40% difference in 15-year survival; p = 2.56 x 10-21). These results suggest that the OIR model reveals key genes involved in pathological angiogenesis, and these may find important applications in stratifying tumors for treatment intensification or for angiogenesis-targeted therapies.

摘要

推动生理性血管生成的特定基因和分子与病理性血管生成中涉及的不同,这表明这些看似相关的过程有不同的机制。揭示与病理性血管生成优先相关的基因和途径是理解其机制的关键,从而有助于开发管理血管生成依赖性疾病的新方法。为了更好地理解这些不同的过程,我们阐明了在公认的氧诱导视网膜病变(OIR)病理性血管生成模型中,小鼠视网膜的转录组。我们在正常和 OIR 视网膜之间鉴定出 153 个发生变化的基因,这些基因代表了与其他血管生成依赖性过程(如癌症)相关的分子特征。这些基因可以强有力地预测乳腺癌患者的生存情况,在一个独立的 1000 名患者测试队列中得到了验证(15 年生存率差异为 40%;p=2.56×10-21)。这些结果表明,OIR 模型揭示了参与病理性血管生成的关键基因,这些基因可能在为治疗强化或针对血管生成的治疗而对肿瘤进行分层方面有重要应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b88/6917213/77f641ab547e/pgen.1008482.g001.jpg

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