Abstract PO-008: Know thy neighbor: Deciphering the intra-tumor heterogeneity in ovarian cancer with molecular assessment of subtype heterogeneity (MASH)
Authors: Tuan Zea Tan, Valerie Heong, Jieru Ye, Diana Lim, Jeffrey Low, Mahesh Choolani, Clare Scott, David S.P. Tan, Ruby Y.J. Huang
Journal: Cancer Research (2020)

Abstract The treatment of ovarian cancer has shifted away from the one-model-fit-all practice in this era of precision medicine. The current treatment for ovarian cancer has evolved to stratify patients based on histology and the mutation status. For instance, BRCA mutated non-mucinous ovarian cancer will be recommended for PARP inhibitor treatment in both the first- and second-line maintenance settings. However, beyond this concept of BRCAness, there still exists background heterogeneity at the transcriptomic level. In high grade serous carcinoma (HGSC), diverse molecular heterogeneity based on gene expression profiling has been shown by the Australian and the TCGA cohorts. This molecular heterogeneity has been demonstrated to be very robust and reproducible by a large-scale meta-analysis study consisting of 1,538 samples. At least 5 distinct gene-expression based molecular subtypes (GEMS) have been identified. The C1 and C5 subtype from the Tothill dataset corresponds to the Mesenchymal and Proliferative subtype from the TCGA dataset and the Mes and Stem-A subtype from the 1,538 meta-analysis dataset, respectively. These GEMS have been correlated with patient survival. The C1/Mesenchymal/Mes and C5/Proliferative/Stem-A GEMS are associated with poorer survival outcomes. Contentions have always been whether these GEMS could be used for patient stratification. To achieve this, a tool to decipher the intra-tumor heterogeneity (ITH) of GEMS is needed to ascertain whether a robust stratification scheme is feasible. Molecular assessment of subtype heterogeneity (MASH) was developed to comprehensively report on the composition of all transcriptomic subtypes within a tumor. Using MASH on 3431 ovarian cancer samples, correlation and association analyses with survival, metastasis and clinical outcomes were performed to assess the impact of GEMS composition as a surrogate for ITH. We identified that 30% of ovarian tumours consist of two or more GEMS. When biological features of the GEMS constituents were examined, we identified significant impact on clinical outcomes with the presence of poor prognostic GEMS (Mes or Stem-A). Poorer outcomes correlated with having higher degrees of poor prognostic GEMS populations within the tumor. Finally, a clinically applicable MASH assay using NanoString® technology was developed to comprehensively describe constituents of GEMS in ovarian cancer. Citation Format: Tuan Zea Tan, Valerie Heong, Jieru Ye, Diana Lim, Jeffrey Low, Mahesh Choolani, Clare Scott, David S.P. Tan, Ruby Y.J. Huang. Know thy neighbor: Deciphering the intra-tumor heterogeneity in ovarian cancer with molecular assessment of subtype heterogeneity (MASH) [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-008.