Introduction: Low Grade Serous Ovarian Carcinoma (LGSOC) is a rare, molecularly distinct subtype of epithelial ovarian cancer, constituting ≈5-10% of all serous carcinomas. The NSMP (No Specific Molecular Profile) subtype is defined by their lack of pathogenic mutations, mismatch repair defects, very low frequency of copy-number changes (median 4%) and high levels of ER/PR expression (93.7% of cases). Accounting for ≈23% of all LGSOC, the NSMP subgroup poses significant clinical challenges, as demonstrated by the worst disease-specific survival (DSS) outcomes (5 DSS <38% versus 75% for MAPK mutant). Whilst we await further molecular refinement, tumour stage and hormone status remain the only factors available for determining adjuvant therapy for this subtype.

Methods: NSMP driver mutations must exist but involve mechanisms other than exonic point mutations or gene amplifications. As such we have undertaken preliminary whole genome, whole methylome and RNA-Seq analysis of LGSOC patient samples and cell lines to tease apart the underlying biology of NSMP LGSOC. To investigate alternative drivers of disease beyond the genome, we also employed a mass-spectroscopy approach to profile the cell surface landscape (receptors, transporters, channels, cell-adhesion proteins etc) of NSMP cell lines filtered against normal cell lines to unveil potential diagnostic and therapeutic targets.

Results: Surfaceome analysis of 12 LGSOC and 4 normal cell lines identified 15 high-confidence cell surface proteins (>2 fold expressed from 4 normal controls) unique to NSMP cell lines. Preliminary RNA-Seq analysis showed no distinct transcriptional profile for NSMP compared to other LGSOC subtypes (MAPK mutant, USP9X p16 aberrant expression), but whole genome analysis unveiled novel translocations and lack of recurrent mutations.

Conclusion: We postulate NSMP tumors may be driven by large genomic rearrangements, pathogenic non-coding mutations, and/or CpG methylation alterations, highlighting the need for further research into these mechanisms for personalized therapeutic strategies.