1. Multidimensional biomarker predicts disease control in response to immunotherapy in recurrent or metastatic head and neck squamous-cell carcinoma.
- Author
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Flanagan KC, Earls J, Schillebeeckx I, Hiken J, Wellinghoff RL, LaFranzo NA, Bradley ZS, Babbitt J, Westra WH, Hsu R, Nadauld L, Mcleod H, Firth SD, Sharp B, Fuller J, Vavinskaya V, Sutton L, Deichaite I, Bailey SD, Sandulache VC, Rendo MJ, Macdonald OK, Welaya K, Wade JL 3rd, Pippas AW, Slim J, Bank B, Saccaro SJ, Sui X, Akhtar A, Balaraman S, Kossman SE, Sonnier SA, Shenkenberg TD, Alexander WL, Price KA, Bane CL, Ley J, Messina DN, Glasscock JI, Cohen EEW, Adkins DR, and Duncavage EJ
- Abstract
Purpose: Anti-PD-1 therapy provides clinical benefit in 40-50% of patients with relapsed and/or metastatic head and neck squamous cell carcinoma (RM-HNSCC). Selection of anti- PD-1 therapy is typically based on patient PD-L1 immunohistochemistry (IHC) which has low specificity for predicting disease control. Therefore, there is a critical need for a clinical biomarker that will predict clinical benefit to anti-PD-1 treatment with high specificity., Methods: Clinical treatment and outcomes data for 103 RM-HNSCC patients were paired with RNA-sequencing data from formalin-fixed patient samples. Using logistic regression methods, we developed a novel biomarker classifier based on expression patterns in the tumor immune microenvironment to predict disease control with monotherapy PD-1 inhibitors (pembrolizumab and nivolumab). The performance of the biomarker was internally validated using out-of-bag methods., Results: The biomarker significantly predicted disease control (65% in predicted non-progressors vs. 17% in predicted progressors, p < 0.001) and was significantly correlated with overall survival (OS; p = 0.004). In addition, the biomarker outperformed PD-L1 IHC across numerous metrics including sensitivity (0.79 vs 0.64, respectively; p = 0.005) and specificity (0.70 vs 0.61, respectively; p = 0.009)., Conclusion: This novel assay uses tumor immune microenvironment expression data to predict disease control and OS with high sensitivity and specificity in patients with RM-HNSCC treated with anti-PD-1 monotherapy., (© 2023. The Author(s).)
- Published
- 2023
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