‘Identifying and Characterising gene co-expression modules underlying resistance to Androgen Deprivation Therapy in prostate cancer‘
University of Melbourne, VIC
Co-funded by the Rotary Club of Williamstown ‘Rotary Ride for a Cure’ Ronnie Goldberg PhD Scholarship
“Understanding how these genes function within larger gene networks will enable us to get a more complete picture of the biological processes driving drug resistance.”
My name is Mikhail Dias, I recently completed an honours year at Monash University where I researched an in silico approach to studying synthetic lethality in cancer to identify novel gene targets.
I am become passionate about cancer biology during my undergraduate studies at RMIT university, where I learned about cancer genomics and how genetic alterations can lead to devastating consequences. I pursued a pathway into research by undertaking an honours year project at Monash University. During my honour’s year, I developed sought after computational skills and experience which I will continue to use throughout my research career.
My Project presents a new paradigm in prostate cancer biology to understand how genes cooperate in complex networks to drive drug resistance in Prostate Cancer (PC). I will build on previous research conducted by my supervisor Dr David Goode and his bioinformatic group, which identified “gene expression modules” within prostate tumours and normal prostate tissue. These modules represent groups of genes whose activity or expression is highly correlates and therefore are likely to be co-regulated and perform important functions together. Gene expression modules from prostate cancer differ greatly from normal prostate tissue which may be linked to specific alterations which may reveal how communication and coordination between genes are lost in PC.
I will use these modules to uncover gene co-expression patterns across Castrate Resistant Prostate Cancer (CRPC) to identify genes responsible for driving drug resistance.
To achieve this, I have three distinct aims:
- Identify modules of co-expressed genes in large CRPC patient cohorts.
- Investigate CRPC gene expression modules as markers of drug response and therapy resistance in laboratory models of CRPC.
- Develop prognostic gene expression module-based signatures.
This project presents a new approach in prostate cancer biology to understand how genes cooperate in complex networks to drive formation of lethal PC. Studying these gene expression signatures will allow us to gain a more complete picture of the molecular landscape of PC, which will be immensely valuable when developing robust therapeutic strategies. My innovative approach will improve PC treatments by uncovering key biological pathways in CRPC driving drug resistance.
Supervisors: Dr David Goode