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Researchers have identified a biomarker on a gene that can help doctors determine how aggressive prostate cancer is right at diagnosis. The team from the University of Texas MD Anderson Cancer Center pinpointed a biomarker next to the gene, KLK3 that can be used to predict the severity of GS7 prostate cancer.

"This is the first report that I am aware of that indicates a genetic variant can stratify GS7 prostate cancer patients," said study researcher, Jian Gu, Ph.D., associate professor at MD Anderson according to the press release. "This is important because this group with heterogeneous prognosis is difficult to predict and there are no reliable biomarkers to stratify this group."

The KLK3 gene is located on chromosome 19 and linked to encoding the prostate-specific antigen (PSA). PSA levels are measured to determine one's risk of prostate cancer. For this study, the researchers set out to analyze any genetic variants that could indicate one's risk of prostate cancer. They used data on 1,827 prostate cancer patients taken from genome-wide association studies (GWAS) and examined 72 single nucleotide polymorphisms (SNPs).

The team was able to identify one SNP on the KLK3 gene that was more apparent in the patients with GS7 prostate cancers. The particular SNP was tied to a more aggressive form of the cancer. By identifying this biomarker, the researchers hope that treatment for GS7 cancers improves.

"Treatment options for the GS7 disease are controversial because the burden of combined treatment modalities may outweigh the potential benefit in some patients," said Xifeng Wu, M.D., Ph.D., professor and chair of Epidemiology, and lead investigator on the study. "It is critical that we develop personalized treatments based on additional biomarkers to stratify GS7 prostate cancers. Additional biomarkers may help us achieve personalized clinical management of low and intermediate risk prostate cancer patients."

She added, "We are also working on circulating biomarkers. Eventually, we will incorporate all biomarkers, epidemiological and clinical variants into nomograms to best predict the prognosis of prostate cancer patients at diagnosis."

The study was published in the American Association of Cancer Research journal, Clinical Cancer Research.