Cofactor Genomics has presented data indicating that its OncoPrism-HNSCC clinical biomarker assay can more accurately predict which patients with head and neck squamous cell carcinoma (HNSCC) will benefit from immune checkpoint inhibitor (ICI) treatments. The assay uses RNA-sequencing and machine learning (ML) to analyze cancer cells, assigning patients a score that corresponds to their likelihood of responding to ICIs.
The current methods for predicting patient responses to ICIs, such as measuring PD-L1 combined positive score (CPS) and tumor mutational burden (TMB), have shown inconsistent predictive value. This inconsistency can lead to over-treatment and poorer outcomes for HNSCC patients.
Improved Prediction of ICI Benefit
Data from the PREDAPT clinical trial (NCT04510129) demonstrated that the OncoPrism test significantly improved the prediction of patient benefit from anti-PD-1 ICIs, both as a monotherapy and in combination with chemotherapy. The results showed a 300% improvement in specificity over PD-L1 CPS and a 400% improvement in sensitivity over TMB.
The study involved 1,650 patients with recurrent or metastatic HNSCC. Patients underwent a tumor biopsy before anti-PD-1/PD-L1 treatment or were scheduled for biopsy before treatment. According to GlobalData’s Pharma Intelligence Center, there will be 338,790 cases of HNSCC by 2030 in the eight major markets (US, France, Germany, Italy, Spain, UK, Japan, and urban China).
Mechanism and Clinical Significance
ICIs are designed to help the immune system recognize and attack cancer cells by blocking proteins like PD-L1 or PD-1, which cancer cells use to evade immune detection. While ICIs have become a crucial treatment option for HNSCC, not all patients respond effectively, highlighting the need for accurate predictive tests.
Douglas Adkins, head and neck oncologist and professor of medicine at Washington University School of Medicine, stated, "The OncoPrism assay provides a new and important tool to help clinicians decide about treatment options for their patients with recurrent or metastatic head and neck cancer."
Other Predictive Biomarker Tests
Other companies are also developing predictive biomarker tests. For example, in August 2024, io9 released data showing that its AI-powered biomarker test DeepHRD could identify biomarkers to determine the best initial treatment for patients with ovarian and breast cancer, outperforming FDA-approved companion diagnostics for the same biomarkers.
