Gene signature might assist develop new therapies in opposition to superior prostate most cancers
Researchers have identified a genetic signature in localized prostate cancer that can predict whether the cancer is likely to spread or metastasize early in the disease and whether it will respond to anti-androgen therapy, a common treatment for advanced disease.
The new gene signature can also be useful in assessing response to treatment and in developing new therapies to prevent or treat advanced prostate cancer.
“If we could know in advance which patients will develop metastases, we could start treatment earlier and treat the cancer more aggressively,” says lead author of the study, Cory Abate-Shen, PhD, chair of the division of molecular pharmacology and therapeutics Michael and Stella Chernow Professor of Urological Sciences (in Urology) and Professor of Pathology and Cell Biology (in the Herbert Irving Comprehensive Cancer Center) at Columbia University’s Vagelos College of Physicians and Surgeons.
“Conversely, patients whose disease is likely to be restricted to the prostate could be spared unnecessary therapy.”
The study was published online in Nature Cancer.
Existing tests cannot identify aggressive cancers
Prostate cancer is the second leading cause of death in men in the United States. This year, 33,330 men are expected to die from the disease.
Most prostate cancers are confined to the prostate and can be successfully treated with active surveillance or local therapy (mainly surgery or radiation therapy) with a five-year survival rate in excess of 99%. Once prostate cancer spreads, it is considered incurable and the five-year survival rate drops to around 30%.
“The problem is that existing tests make it difficult to know which cancers are which,” says the study’s lead author, Juan M. Arriaga, PhD, Associate Research Scientist in Molecular Pharmacology and Therapeutics at Vagelos College of Physicians and Surgeons Columbia University.
“We are missing a lot of aggressive cancers that should have been treated earlier and we are treating some slow-growing cancers that probably wouldn’t have spread.”
New gene signature identified for the first time in the new mouse model
To identify a more accurate way of predicting advanced prostate cancer, the researchers first created a mouse model of prostate cancer that accurately reflected the human form of the disease, including the spread of the cancer to the bone, the tissue most commonly affected by prostate cancer metastasis.
Using this unique mouse model, the researchers discovered that bone metastases have a different molecular profile than primary tumors. “By focusing on these differences, we were able to identify 16 genes that metastasize localized prostate cancer,” says Abate-Shen.
16 genes predict metastases in patients
The genetic signature, called META-16, was then tested on biopsies from several hundred patients with localized prostate cancer. The results from these patients were blind to the researchers.
The Columbia team found that META-16 was highly effective in predicting time to metastasis and response to anti-androgen therapy (which is used to suppress androgen, the male hormone that promotes tumor progression).
The team is currently refining the test, which it will then evaluate in a prospective clinical study.
In theory, META-16 could also be used to develop therapies for metastatic prostate cancer.
The genes in our signature not only correlate with metastases, they also appear to be driving metastases. That said, if we can suppress the activity of these genes, we may be able to prevent the cancer from spreading, or at least improve outcomes. “
Juan M. Arriaga, PhD, Study Leader, Associate Research Scientist in Molecular Pharmacology and Therapeutics, Columbia University’s Vagelos College of Physicians and Surgeons
Irving Medical Center at Columbia University
Arriaga, JM et al. (2020) A signature of simultaneous activation of MYC and RAS in localized prostate cancer leads to bone metastases and castration resistance. Natural cancer. doi.org/10.1038/s43018-020-00125-0.