OncoCyte (OCX) Announces Peer-Reviewed Publication of Data Assessing Use of DetermaIO to Identify Patients Likely to Benefit from Immunotherapy Across Multiple Tumor Types
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Oncocyte Corporation (Nasdaq: OCX), a molecular diagnostics company with a mission to provide actionable answers at critical decision points across the cancer care continuum, announced findings from a study using the DetermaIO™ immuno-oncology algorithm to assess patients likely to benefit from immunotherapy across multiple cancer types. The study, “A novel immuno-oncology algorithm measuring tumor microenvironment to predict response to immunotherapies,” was recently published in a peer-reviewed article in Heliyon, and is accessible at this link.
Immunotherapies using immune checkpoint inhibitors (ICIs) are widely considered standard of care in the treatment of lung cancer, breast cancer, and other solid tumor types. However, while ICI therapies have been shown to improve clinical outcomes for certain patients, data indicate that only 20-40% of the approximately 750,000 patients in the US eligible annually for ICI respond to those therapies. In addition, ICI therapies have been shown to cause adverse immune-related events that can be life-threatening for some patients. Standard of care PD-L1 testing incorrectly identifies many patients as potential responders to immune checkpoint inhibitors, and misses certain other patients who may respond. Therefore, there appears to be an unmet need for a better predictive biomarker that can identify patients that will likely benefit from ICI therapy.
The study’s researchers hypothesized that measuring the activity of the tumor microenvironment (TME) may be useful in patient selection for ICI therapy, and developed a novel algorithm that can be applied to gene expression data from a small set of most relevant genes, potentially making the assay practical and cost effective for clinical use.
“Unlike previously described biomarker models, the novel immuno-oncology algorithm behind DetermaIO measures the immunological state of the TME as a means to capture the interplay of the patient’s immune system and tumor immune evasion. Our hypothesis was that because the test measures the TME as a whole, the predefined threshold may have utility across several tumor types,” said Tyler Nielsen, lead author of the study and Senior Scientist at Oncocyte. “We established a threshold for positivity in triple negative breast cancer specimens, and as this study shows we were able to apply it to a non-small cell lung cancer cohort. We believe that this algorithm may give DetermaIO independent and incremental predictive value over the current gold standard biomarkers in the clinic.”
“As demonstrated by the translation of this signature from triple negative breast cancer to non-small cell lung cancer, the classifier appears to be applicable across multiple solid tumor types,” stated Doug Ross, M.D., Ph.D., and Chief Science Officer of Oncocyte. “We believe that DetermaIO may also be highly appealing for use in both pharma driven clinical studies and well as in the clinic. The test is currently performed centrally in our labs using our CLIA certified RT-PCR assay starting with very little tissue from biopsy specimens. The test utilizes gene expression data from any type of biopsy or surgical specimen, which can be generated on most NGS or PCR platforms, making it suitable for worldwide distribution. It can also be assessed on gene expression data that has often already been generated by pharmaceutical companies in their clinical trials, avoiding the need for tissue. This has been a very attractive value proposition to our pharmaceutical clients because we can help generate data quickly to demonstrate the utility of DetermaIO for their specific drug in development.”
Dr. Ross continued, “As DetermaIO works primarily by assessing the inflammatory cells and the cancer wound response, we are encouraged that DetermaIO may be relevant across multiple tumor types and useful in clinical studies being conducted by pharma companies, providing a means to distinguish patients likely to benefit from treatment with ICIs.”
Other key highlights of the study include:
- The study examined ten patients with two samples each—one from the tumor itself and one from the surrounding TME and used the algorithm to generate DetermaIO scores for each pair of matched samples. The agreement between the two samples across the ten patients was 92%. The ability to get concordant results from two different sampling sites may imply that DetermaIO will have greater flexibility in tissue requirements than similar tests.
- The DetermaIO score generated by the algorithm was applied to samples from lung cancer patients treated with ICI and was able to distinguish between tumors that responded to ICI and tumors that did not respond.
- The endpoint used in the study was sustained response, measured by no progression within six months. Using the six month response endpoint reflects DetermaIO’s ability to identify a durable response.
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