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2017年1月30日，英国《自然》旗下《癌基因》在线发表密歇根州立大学的研究报告，发现通过基因表达分析预测细胞信号通路激活的三阴性乳腺癌有效个体化疗法。 乳腺癌有众多亚型，因为驱动这些癌症发生的基因不同，所以治疗方法也不相同。雌激素或孕激素受体阳性的乳腺癌属于激素驱动癌细胞生长的亚型，其他还包括HER1或HER2阳性乳腺癌、三阴性乳腺癌等亚型。 三阴性乳腺癌不受HER2和激素受体驱动，是该研究主要分析的乳腺癌亚型。该研究首先检测三阴性乳腺癌的基因特征和区别，随后将收集到的基因信息与各种靶向药物进行比对。 三阴性乳腺癌具有高度的侵袭性，目前可以选择的治疗方法也比较有限，通过观察这种癌症特定的基因表达模式，确定被激活的信号通路，就可以选择能够关闭这些信号通路以阻止肿瘤生长的药物。 该研究检测了各种药物组合，并且在患者肿瘤来源异种移植（PDX）小鼠模型对结果进行验证。结果发现一种由阿法替尼（靶向EGFR通路）、曲美替尼（靶向RAS/MEK通路）、SB505124（靶向TGFβ/ALK通路）形成的组合，可以靶向与三阴性乳腺癌有关的Myc、Stat3、Akt信号通路，有效阻止肿瘤生长。其中，阿法替尼、曲美替尼已被批准已经用于其他癌症类型的治疗。 该研究是明确这种治疗方法可行性的第一步，这使我们认识到三阴性乳腺癌个体化靶向疗法将来能够取得成功。该研究为利用基因表达模式帮助指导治疗方法选择提供了证据，也为更多靶向疗法和精准治疗方法的应用奠定了基础。 Oncogene. 2017 Jan 30. [Epub ahead of print] Effective personalized therapy for breast cancer based on predictions of cell signaling pathway activation from gene expression analysis. Jhan JR, Andrechek ER. Department of Physiology, Michigan State University, East Lansing, MI, USA. Current therapeutic outcomes for breast cancer underscore the complexity of treating a heterogeneous disease. Indeed, studies have shown that differences in gene expression among patients with the same subtype of breast cancer are correlated with the response to treatment. This strongly suggests that there is an urgent need to treat breast cancer with a personalized approach. Here we employed cell signaling pathway signatures to predict pathway activity in subtypes of MMTV-Myc mammary tumors. We then split tumors into subsets and developed individualized combinatorial treatments for two subtypes with distinct pathway activation patterns. Elevation of the EGFR, RAS and TGFβ pathways was observed in one subtype whereas these pathways were not predicted to be active in the other subtype that had high predicted activity of the Myc, Stat3 and Akt pathways. In a proof-of-principle experiment, treatment of these two subtypes with targeted therapies inhibited tumor growth only in the subtype of tumor where the therapy was designed to be active. We then analyzed gene expression profiles of human breast cancer patients and patient-derived xenograft (PDX) samples to predict pathway activity, and validated our approach of developing individualized treatments in mice with PDX tumors. Importantly, our combinatorial therapy resulted in tumor regression, including regression in PDX samples from triple-negative breast cancer. Together our data is a proof-of-principle experiment that demonstrates that cell signaling pathway signature-guided treatment for breast cancer is viable. PMID: 28135251 DOI: 10.1038/onc.2016.503 |
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