Ovarian Cancer
(Professor Ruby Huang, A/Prof Mahesh Choolani)
Gene Expression Molecular Subtype (GEMS)-Specific Ovarian Cancer Management
Cancer management has entered the era for precision management. A promising approach is the clustering of patients based on the gene expression profiling. Ovarian cancer is known to be molecularly heterogeneous with several gene expression molecular subtypes (GEMS) being reported. Previously, we have identified 5 GEMS that showed clinical significance in survival outcomes and therapeutic options1. Our research focuses on dissecting the biology of each GEMS aiming to find GEMS-specific management options for ovarian cancer patients. To do this, we have established a pre-clinical translational research pipeline dedicated for the GEMS scheme.
Current active projects include:
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GEMS Pre-screening in the VIP Trial.
Among these GEMS, the “Stem-A” subtype confers the worst survival outcome as an independent prognostic factor. In vivo data have demonstrated sensitivity of platinum-refractory Stem-A patients being sensitive to vinorelbine1, leading to an international multicenter Phase II single-arm clinical trial, VIP (NCT: 03188159), initiated by the Gynaecologic Cancer Group Singapore (GCGS) and the Australian New Zealand Gynaecologic Oncology Group (ANZGOG), the first in the world to prospectively stratify platinum-resistant ovarian cancer patients by GEMS. Currently, we are actively engaging in the GEMS pre-screening by using a nanoString-based assay for the VIP trial.
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GEMS-specific treatment options: anti-AXL
The mesenchymal (“Mes”) subtype is an aggressive GEMS. Previously, we searched for therapeutic options specific for patients with Mes-type tumors by comparing kinase activity profiles in Mes-type and epithelial (“Epi”)–type tumor cells. Relative to Epi-type cells, an increased abundance and distinct localization and activity signature of the receptor tyrosine kinase AXL were associated with metastatic phenotypes in Mes-type cells. AXL inhibition with the small-molecule drug R428 made the Mes-type tumor cells more “Epi-type” and increased survival in tumor-bearing mice3. Thus, AXL inhibitors may halt tumor progression and prolong survival in patients with advanced ovarian cancer. Currently, we are actively searching for novel combinations with AXL inhibitors.
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Intra-tumoral heterogeneity of GMES.
By using the collective big-data analysis approach to assemble CSIOVDB2, a comprehensive gene expression database for ovarian cancer consisting of 3400 samples, we have further deciphered the intra-tumoral heterogeneity (ITH) of GEMS within ovarian cancer4. 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. Currently, we are adopting the Digital Spatial Profiling (DSP) platform to understand the neighbourhood effect of ITH.
Publications
- Tan TZ, Miow QH, Huang RY, Wong MK, Ye J, Lau JA, Wu MC, Bin Abdul Hadi LH, Soong R, Choolani M, Davidson B, Nesland JM, Wang LZ, Matsumura N, Mandai M, Konishi I, Goh BC, Chang JT, Thiery JP, Mori S. Functional genomics identifies five distinct molecular subtypes with clinical relevance and pathways for growth control in epithelial ovarian cancer. EMBO Mol Med. 2013 Jul;5(7):1051-66.
- Tan TZ, Yang H, Ye J, Low J, Choolani M, Tan D, Thiery JP, Huang RY. CSIOVDB: a microarray gene expression database of epithelial ovarian cancer subtype. Oncotarget. 2015 6(41):43843-52.
- The GAS6-AXL signaling network is a mesenchymal (Mes) molecular subtype-specific therapeutic target for ovarian cancer. Antony J, Tan TZ, Kelly Z, Low J, Choolani M, Recchi C, Gabra H, Thiery JP, Huang RY. Sci Signal. 2016 Oct 4;9(448):ra97.
- Decoding transcriptomic intra-tumour heterogeneity to guide personalised medicine in ovarian cancer. Tan TZ, Heong V, Ye J, Lim D, Low J, Choolani M, Scott C, Tan DSP, Huang RY. J Pathol. 2019 Mar;247(3):305-319.