Cellanyx has reported results of a prostate cancer clinical trial that indicated the ability of its live tumor cell phenotypic biomarker test in identifying patients suffering from low and intermediate grade prostate cancer who are at risk of aggressive disease progression.
This risk stratification study is intended to offer a new tool to aid in making clinical decisions on the kind of patient care required.
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New York-based Crouse Hospital chief of urology and the paper’s author David Albala said: “In the study, which analysed tissue collected from radical prostatectomy specimens, the live tumor cell phenotypic test predicted specific post-surgical adverse pathology features, the gold standard of prostate cancer clinical diagnosis, with a high degree of sensitivity and specificity.”
This test has identified subgroups of prostate cancer patients within low and intermediate Gleason and Prostate Cancer Grading Group (PGGC) tumor grades. Based on adverse pathology features such as positive surgical margins, lymph node involvement, and extra-prostatic extension, these patients were considered to be at a higher risk of disease progression.
Albala added: “These initial clinical results suggest considerable potential of this phenotypic test as a risk stratification tool for prostate cancer patients with low and intermediate grade disease. The results will need to be confirmed in future studies in prostate cancer patients at the time of initial biopsy.”
Risk stratification in prostate cancer is considered to be a huge challenge in men who have low and intermediate grade disease. Inadequate proper risk stratification leads to either insufficient treatment or missed diagnoses.
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By GlobalDataDr Albala, who is also a member of the Cellanyx Scientific Advisory Board, said: “A subset of these patients may develop aggressive disease and we currently lack sufficiently precise, personalised risk stratification tools to distinguish between indolent and potentially aggressive disease.”
This was a multi-centre, blinded, prospective trial that analysed fresh prostate tissue samples from 251 men undergoing radical prostatectomy. Of these samples, 237 were successfully cultured and analysed.
Samples were tested in a central laboratory where they were tested on a coated microfluidic chip. These samples were tested for phenotypic biomarkers in individual cells with the help of machine vision and learning algorithms.
The adverse pathology features were subsequently compared to the actual post-surgical pathology reported findings after data un-blinding.
Cellanyx co-founder Ashok Chander said: “The machine vision learning and intelligent algorithms developed by our team allowed objective prioritisation and scoring of phenotypic biomarkers for each cell, actionable scores for predicting adverse pathological features that clinicians can use to risk-stratify patients.”
An estimated 164,690 news cases were diagnosed this year in the US, according to the American Cancer Society.
Even though most men do not die of this cancer type, it is estimated that there will be around 39,500 deaths this year.
