Decoding transcriptomic intra-tumour heterogeneity to guide personalised medicine in ovarian cancer.

Tan TZ1, Heong V1,2,3, Ye J1, Lim D4,5, Low J6, Choolani M6, Scott C3, Tan DSP1,2,7, Huang RY1,6,8.

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Abstract

The evaluation of intra-tumour heterogeneity (ITH) from a transcriptomic point of view is limited. Single-cell cancer studies reveal significant genomic and transcriptomic ITH within a tumour and it is no longer adequate to employ single-subtype assignment as this does not acknowledge the ITH that exists. Molecular assessment of subtype heterogeneity (MASH) was developed to comprehensively report on the composition of all transcriptomic subtypes within a tumour lesion. Using MASH on 3,431 ovarian cancer samples, correlation and association analyses with survival, metastasis, and clinical outcomes were performed to assess the impact of subtype composition as a surrogate for ITH. The association was validated on two independent cohorts. We identified that 30% of ovarian tumours consist of two or more subtypes. When biological features of the subtype constituents were examined, we identified significant impact on clinical outcomes with the presence of poor prognostic subtypes (Mes or Stem-A). Poorer outcomes correlated with having higher degrees of poor prognostic subtype populations within the tumour. Subtype prediction in several independent datasets reflected a similar prognostic trend. In addition, paired analysis of primary and recurrent/metastatic tumours demonstrated Mes and/or Stem-A subtypes predominated in recurrent and metastatic tumours regardless of the original primary subtype. Given the biologic and prognostic value in delineating individual subtypes within a tumour, a clinically applicable MASH assay using NanoString technology was developed as a classification tool to comprehensively describe constituents of molecular subtypes. This article is protected by copyright. All rights reserved.