Identification of potential therapeutic targets through whole transcriptome analysis of early versus advanced stage Granulosa cell tumours — ASN Events

Identification of potential therapeutic targets through whole transcriptome analysis of early versus advanced stage Granulosa cell tumours (#293)

Maria Alexiadis 1 , Simon Chu 1 , Peter J Fuller 1
  1. Prince Henry's Institute, Clayton, VIC, Australia
Ovarian granulosa cell tumours (GCT) are hormonally-active neoplasms characterized by an indolent course and unexplained propensity for late recurrence. ~80% of patients with aggressive or recurrent tumours die from their disease; aside from surgery the therapeutic options are very limited. 

To address the key questions of pathogenesis and targeted therapeutics, we have defined the tumours on a molecular basis using whole transcriptome analysis of adult GCT (FOXL2-C134W mutation positive) to identify genes that are differentially expressed between early (Stage 1) and advanced GCT.  We established transcriptome profiles for early (n=6) and advanced (n=7) adult GCT using Agilent Whole Human Genome 4X44K Expression Microarrays. Our preliminary analysis, using GeneSpring GX software, identified 140 genes with >3-fold (p<0.05) differential expression between early and advanced GCT. 

Several features emerge from our preliminary analysis: (1) clearly discriminant patterns of expression suggest that the clinicopathological-derived distinction of the tumour stage appears robust; (2) confirmation of the relative homogeneity of expression for many genes; (3) several genes associated with differentiated granulosa cell function are significantly down-regulated with advanced disease including INSL3 (insulin-like-3; >30-fold, p<0.001); and desmin (>7-fold, p<0.001), while genes with known roles in advanced malignancy including HOXA7 (>4-fold, p <0.005); FOXD2 (2.8-fold, p <0.01) and FAP (fibroblast activating protein; >4-fold, p <0.005) are up-regulated. These changes have been independently validated by RT-PCR. FAP is a membrane serine protease, and its overexpression is potentially significant for GCT, as FAP is an established target for therapeutic development. We are currently using Pathway Analysis and Hierarchical Clustering to further interrogate this unique data set. 

These studies will validate the functional significance of the differential expression of the identified genes which in turn may identify specific targets and/or pathways of relevance to the treatment of advanced GCT.

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