Molecular classification of ovarian cancer — ASN Events

Molecular classification of ovarian cancer (#63)

Clare Scott 1
  1. Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia

Ovarian cancer (OC) refers to a broad array of tumours found in anatomic association with the ovary, perhaps reflecting the permissive nature of the ovarian milieu as a site of tumour growth. Histologic classification of OC has proved inadequate in terms of guiding effective therapy and molecular approaches may reveal susceptibilities which are more effectively targeted with novel therapies.

All histologic subsets of OC are rare, as defined by Rarecare (<6/100,000 incidence). Although epithelial OC account for the majority of “OC”, most of these likely do not actually arise from the epithelial components of the ovary (the single cell layer of ovarian surface epithelium and epithelial inclusion cysts or similar remnants). Instead these are thought to arise from the fallopian tube, endometrial tissues and possibly the GI tract. Only five percent of OC are non-epithelial in origin (mixed sarcomatous, sex cord, teratoma, germ cell (each 1-2% of total)).

Molecular stratification has been best described for the most common histologic types of OC, serous and endometrial OC (Tothill et al 2008; Nature 2011). Similar molecular analyses have been published or are underway for clear cell OC, mucinous OC and some extra-uterine sarcomas. However, the majority of other OC subsets, all of which are extremely rare (<0.2/100,000 incidence), remain unexplored. Recurring actionable targets have been reported in large molecular studies (Frampton et al, Nat Biotech 2013), but a concerted effort to identify these across all rare OC subtypes is essential in order to design treatments targeted to these tumours. Specific examples, including SMARCA4 mutations in the extremely rare entity, small cell cancer of the ovary, and DNA repair gene mutations in rare high-grade endometrioid ovarian cancer will underpin a discussion of new approaches to streamlining classification of rare OC based on novel tumour testing.

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