RNA-Based Test Predicts Immunotherapy Response in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) represents the largest U.S. patient population eligible for immune checkpoint inhibitor therapy. Treatment selection often relies on PD-L1 expression, but a single protein marker may not fully capture the complexity of the tumor-immune response. To provide a broader assessment, a newly validated RNA-based test integrates signals from the tumor-immune microenvironment to predict potential benefit from immunotherapy.

Cofactor Genomics (San Francisco, CA, USA) has announced published clinical validation of OncoPrism-NSCLC in npj Precision Oncology, a peer-reviewed Nature Portfolio journal. The test is based on the same multidimensional RNA biomarker used in OncoPrism-HNSCC, a clinically validated, Medicare-covered test for recurrent or metastatic head and neck squamous cell carcinoma. The OncoPrism platform uses patented Gene Expression Classifiers that combine machine learning with RNA analysis to generate high-dimensional models of tumor biology and treatment response.

Image: The test combines RNA signals from the tumor-immune microenvironment to predict treatment response, rather than relying on a single marker such as PD-L1 expression.(Image Credit: Adobe Stock)

The NSCLC validation was conducted through Cofactor’s multisite PREDAPT clinical trial. The study found that the underlying biomarker was represented across NSCLC, clear cell renal cell carcinoma, colon adenocarcinoma, triple-negative breast cancer, and bladder carcinoma. Investigators from 17 U.S. health care systems then calibrated the test specifically for NSCLC and validated its performance against treatment response and survival outcomes.

Patients with high OncoPrism scores were significantly more likely to respond to immune checkpoint inhibitors and had significantly longer survival, with median overall survival twice that of the remainder of the study population. The test appeared specifically predictive of immunotherapy response rather than generally prognostic, as it was not associated with outcomes among patients treated with chemotherapy or other therapies.

The publication also evaluated OncoPrism alongside PD-L1 testing and suggested that the two biomarkers may provide complementary information across PD-L1 expression levels. Among tumors with high PD-L1 expression, defined as a score of at least 50%, patients classified as OncoPrism-high had significantly longer progression-free and overall survival.

“Precision medicine is not just about finding a target. It is about prioritizing treatment selection based on a patient’s current condition and presence of actionable biomarkers. This work represents an emerging approach to immunotherapy diagnostics: integrating RNA signals from the tumor-immune microenvironment into a clinically validated prediction, rather than asking a single marker, like PD-L1 expression, to represent a complex biological response,” said Dr. Howard Bailey, Chief Medical Officer of Cofactor Genomics.

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