Understanding the Genetics of Prostate Cancer with an Emphasis on Kallikreins

Overview

Topic status: We're looking for students to study this topic.

Prostate cancer (PrCa) is the most frequently occurring cancer (after skin cancers) in Australian males, and the second most common cause of cancer death. Age at diagnosis, family history and ethnicity are the most common predictors of disease risk, and there is strong evidence to suggest that up to 44% of PrCa is genetic in basis. Kallikreins (KLKs) are serine proteases that are part of an enzymatic cascade pathway activated in PrCa. Prostate specific antigen (PSA/KLK3), has a well established use as a diagnostic marker for PrCa. Recently, single nucleotide polymorphisms (SNPs) in the KLK2-KLK3 genes were found to be related to PrCa risk in a large international genome-wide association study (GWAS) and a follow-up study involving our laboratories [1, 2]. However, no studies have been undertaken to fully understand the molecular basis of KLK2-KLK3 SNPs genetic association.

Also, many KLK SNPs already lodged in public databases have not been covered by current GWAS platforms. In preliminary studies, we have identified at least three such PrCa risk associated SNPs. Further, nextgen sequencing is revealing numerous additional novel genetic variants in the KLK genes [3]. The role of these SNPs in genetic association or in regulating the expression of KLK3 and other KLK genes has not yet been explored.

Hypothesis: Various reported and newly identified germline SNPs in the PSA (KLK3) and related KLK genes that are not captured by current GWAS might be associated with PrCa and have molecular consequences that underpin their genetic association.

Aim 1: To investigate novel KLK3 and other KLK gene SNPs extracted from Nextgen sequencing for an association with PrCa risk and/or prognostic features

Aim 2: To identify the molecular consequences of PrCa risk-associated KLK SNPs

Methods and techniques that will be developed in the course of this project:

  • Genotyping using Sequenom MassArray for approximately 3500 individuals.
  • Bioinformatic analysis and exposure to various in silico softwares
  • Cell culture to grow cancer cells
  • Electrophoretic Mobility Shift Assays to identify Transcription Factor binding
Study level
PhD, Honours
Supervisors
QUT
Organisational unit

Science and Engineering Faculty

Research area

Cell and Molecular Biosciences

Contact

Please contact the supervisor.