2017年1月30日，英國《自然》旗下《癌基因》在線發(fā)表密歇根州立大學(xué)的研究報告，發(fā)現(xiàn)通過基因表達分析預(yù)測細胞信號通路激活的三陰性乳腺癌有效個體化療法。
乳腺癌有眾多亞型，因為驅(qū)動這些癌癥發(fā)生的基因不同，所以治療方法也不相同。雌激素或孕激素受體陽性的乳腺癌屬于激素驅(qū)動癌細胞生長的亞型，其他還包括HER1或HER2陽性乳腺癌、三陰性乳腺癌等亞型。
三陰性乳腺癌不受HER2和激素受體驅(qū)動，是該研究主要分析的乳腺癌亞型。該研究首先檢測三陰性乳腺癌的基因特征和區(qū)別，隨后將收集到的基因信息與各種靶向藥物進行比對。
三陰性乳腺癌具有高度的侵襲性，目前可以選擇的治療方法也比較有限，通過觀察這種癌癥特定的基因表達模式，確定被激活的信號通路，就可以選擇能夠關(guān)閉這些信號通路以阻止腫瘤生長的藥物。
該研究檢測了各種藥物組合，并且在患者腫瘤來源異種移植（PDX）小鼠模型對結(jié)果進行驗證。結(jié)果發(fā)現(xiàn)一種由阿法替尼（靶向EGFR通路）、曲美替尼（靶向RAS/MEK通路）、SB505124（靶向TGFβ/ALK通路）形成的組合，可以靶向與三陰性乳腺癌有關(guān)的Myc、Stat3、Akt信號通路，有效阻止腫瘤生長。其中，阿法替尼、曲美替尼已被批準已經(jīng)用于其他癌癥類型的治療。
該研究是明確這種治療方法可行性的第一步，這使我們認識到三陰性乳腺癌個體化靶向療法將來能夠取得成功。該研究為利用基因表達模式幫助指導(dǎo)治療方法選擇提供了證據(jù)，也為更多靶向療法和精準治療方法的應(yīng)用奠定了基礎(chǔ)。
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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