Dr Huang has been awarded the AACR Annual Meeting 2012 Scholar-in-Training Award, which has provided more than 3,300 grants to young investigators and has received support from more than 40 cancer research foundations, corporations, individuals and other organizations dedicated to the fight against cancer. Dr Huang is currently a Senior Research Fellow in Prof Jean-Paul Thiery’s laboratory at CSI Singapore as well as a Clinician Scientist at the Department of Obstetrics and Gynaecology in NUH.
Title: Epithelial-mesenchymal gene expression signature defines clinically relevant subtypes in epithelial ovarian cancer.
Abstract: Epithelial ovarian cancer (EOC) represents a broad and heterogeneous entity which includes different invasive behavior as well as distinct histopathological subtypes. The heterogeneity of EOC is further complicated by the fact that EOC is characterized by a high degree of genetic damages and multiple genetic alterations resulting from different mechanisms. Even within the seemingly similar histo-pathological group, molecular subtypes with different gene/pathway activations have been identified. In this study, we described a classification scheme based on in silico meta-analysis of gene expression profiling of 1,538 EOC microarray data and identified five major robust subtypes termed Epithelial-A, Epithelial-B, Mesenchymal, Stem-A, and Stem-B that were distinctive in gene expression patterns. The epithelial subtype is hallmarked by genes known to confer epithelial characteristics, such as Keratin genes (KRT17, 14, 19, and 7), E-cadherin (CDH1), and Ep-CAM (EPCAM) and show the second best prognosis in Kaplan-Meier analysis. On the other hand, the mesenchymal subtype consists of genes such as fibronectin (FN1) and known EMT inducers ZEB1 and TWIST1. The Stem-A subtype consists of genes which confer stemness (LGR5, NCAM1). The Mesenchymal and Stem-A subtypes are linked with poorer outcomes. We further utilized a panel of 42 ovarian cancer cell lines to model EMT in vitro by performing phenotypic EMT characterization. Four EMT subgroups (epithelial, intermediate epithelial, intermediate mesenchymal, mesenchymal) representing different epithelial-mesenchymal compositions on the EMT spectrum were identified. We also demonstrated that this EMT spectrum can be used to refine the analysis of data generated in cell-based functional studies. By performing EMT-related functional assays, we found that ovarian cancer cells harbouring intermediate phenotypes are more migratory, invasive, anoikis resistant, and more spheroidogenic. We further utilized this cell line model to apply a cell line-based EMT scoring system to re-classify the 1,538 EOC microarray data. It revealed that the Mesenchymal and Stem-A subtypes were both enriched in higher mesenchymal scores. This supported the hypothesis of EMT’s contribution to the aggressiveness of solid tumors. In conclusion, our results showed that EOC is sub-classified into distinct molecular subtypes correlated with clinical outcomes that are linked to EMT.