Plasma proteome-based test (PROphetNSCLC) predicts response to immune checkpoint inhibitors (ICI) independent of tumor programmed death-ligand 1(PD-L1) expression and tumor mutational burden (TMB)

Despite the approval of PD-(L)1 inhibitors for the first-line treatment of all metastatic, driver-negative, non-small cell lung cancer patients (mNSCLC) in the United States since 2018, there still is a lack discerning biomarkers to predict which patients will derive significant benefit. Tumor expression of programmed-death ligand 1 (PD-L1), measured as the tumor proportion score (TPS), is a standard biomarker approved for the selection of initial therapy. Tumor mutational burden (TMB), a promising biomarker, thought to represent the tumors’ ability to engage the host’s immune system, has demonstrated clinical utility primarily in the context of immunotherapy monotherapy. PROphetNSCLC, a test developed through proteomic analysis and machine learning, provides a novel approach by capturing biological processes from both tumor and host. In a previously published study, PROphetNSCLC, was validated to correlate with the probability of clinical benefit, independent of but also complementary to PD-L1 expression levels predicting specific treatment-related survival outcomes. Utilizing available tumor TMB measurements from this investigation, we sought to assess the correlation between the PROphetNSCLC clinical benefit probability score and TMB measurement. PROphetNSCLC demonstrated a correlation with various outcomes from PD-(L)1 inhibitor treatment independent of TMB status, whereas TMB did not exhibit an association with outcomes. This finding emphasizes the significance in of novel systemic biomarkers in refining personalized treatment strategies for mNSCLC.