报告题目：a multidimensional network approach reveals micrornas as determinants of the mesenchymal colorectal cancer subtype
colorectal cancer (crc) is a heterogeneous disease posing a challenge for accurateclassification and treatment of this malignancy. there is no common genetic molecular feature that would allow for the identification of patients at risk for developing recurrences and thus selecting patients that would benefit from more stringent therapies still poses a major clinical challenge. recently, an international multicenter consortium (crc subtyping consortium) was established aiming at the classification of crc patients in biologically homogeneous crc subtypes. four consensus molecular subtypes (cms) were identified, of which the mesenchymal cms4 presented with worse prognosis signifying the importance of identifying these patients. despite the large number of samples analyzed and their clear association with unifying biological programs and clinical features, single driver mutations could not be identified and patients are heterogeneous with regard to currently used clinical markers. we therefore set out to define the regulatory mechanisms underlying the distinct gene expression profiles using a network-based approach involving multiple molecular modalities such as gene expression, methylation levels, and microrna (mir) expression. the mir-200 family presented as the most powerful determinant of cms4-specific gene expression, tuning the majority of genes differentially expressed in the poor prognosis subtype including genes associated with the epithelial-mesenchymal transition program. furthermore, our data show that two epigenetic marks, namely the methylation of the two mir-200 promoter regions, can identify tumors belonging to the mesenchymal subtype and is predictive of disease-free survival in crc patients. importantly, epigenetic silencing of the mir-200 family is also detected in epithelial crc cell lines that belong to the mesenchymal cms. we thus show that determining regulatory networks is a powerful strategy to define drivers of distinct cancer subtypes, which possess the ability to identify subtype affiliation and to shed light on biological behavior.
wang xin博士是香港城市大学生物医学系助理教授。他于2013年在英国剑桥大学肿瘤与癌症研究所获得博士学位，主要研究如何从表型中推断细胞内信号传导途径。与实验肿瘤学家合作，他使用无监督分类方法确定了多种结肠癌亚型。2013年至2015年，wang xin 博士在哈佛医学院生物医学信息学系进行博士后研究工作，他利用新一代测序数据，研究brd4-nut融合基因在nut midline carcinoma中的作用，并将lrf表征为胎儿血红蛋白独立抑制性转录因子。wang xin博士目前的主要研究兴趣是使用新颖的机器学习方法更好地理解癌症的生物学基础。他与癌症生物学家合作，致力于分析乳腺癌，结肠癌，胰腺癌，卵巢癌和肝癌等主要恶性肿瘤的分子异质性和亚型特异性调节机制。
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●de sousa e mello, f†, wang x†, jansen m, fessler e, trinh a, et al., poor prognosis colon cancer is defined by a distinct molecular subtype and develops from serrated precursor lesions,nature medicine2013, 19(5):614-618(co-first author)