Data from Validation of Immunotherapy Response Score as predictive of pan-solid tumor anti-PD-1/PD-L1 benefit
Year: 2023
Type: other
Abstract: Immunotherapy Response Score (IRS) integrates tumor mutation burden (TMB) and quantitative expression biomarkers to predict anti-PD-1/PD-L1 (PD-[L]1) monotherapy benefit. Here, we evaluated IRS in additional cohorts. Patients from an observational trial (NCT03061305) treated with anti-PD-(L)1 monotherapy were included and assigned to IRS-High (-H) vs. -Low (-L) groups. Associations with real-world progression free survival (rwPFS) and overall survival (OS) were determined by Cox proportional hazards (CPH) modeling. Those with available PD-L1 immunohistochemistry treated with anti-PD-(L)1 with or without chemotherapy were separately assessed. Patients treated with PD-(L)1 and/or chemotherapy (five relevant tumor types) were assigned to three IRS groups (IRS-L divided into IRS-Ultra-Low [-UL] and Intermediate-Low [-IL] and similarly assessed. In the 352 patient anti-PD-(L)1 monotherapy validation cohort (31 tumor types), IRS-H vs. IRS-L patients had significantly longer rwPFS and OS. IRS significantly improved CPH associations with rwPFS and OS beyond microsatellite instability (MSI)/TMB alone. In a 189 patient (10 tumor types) PD-L1 IHC comparison cohort, IRS, but not PD-L1 IHC nor TMB, was significantly associated with anti-PD-L1 rwPFS. In a 1,103-patient cohort (from five relevant tumor types), rwPFS did not significantly differ in IRS-UL patients treated with chemotherapy vs. chemotherapy plus anti-PD-(L)1, nor in IRS-H patients treated with anti-PD-(L)1 vs. anti-PD-(L)1 + chemotherapy. IRS associations were consistent across subgroups, including both Europeans and non-Europeans. These results confirm the utility of IRS utility for predicting pan-solid tumor PD-(L)1 monotherapy benefit beyond available biomarkers and demonstrate utility for informing on anti-PD-(L)1 and/or chemotherapy treatment.
Authors: Benjamin J Bulen, Nickolay A Khazanov, Daniel H. Hovelson, Laura E Lamb, Marc Matrana, Mark E Burkard, Eddy Shih-Hsin Yang, William J. Edenfield, Elizabeth Claire Dees, Adedayo A. Onitilo, Gary L Buchschacher, Alan M Miller, Benjamin M. Parsons, Timothy R. Wassenaar, Jennifer M. Suga, Robert D Siegel, William Irvin, Suresh Nair, Jennifer N. Slim, Jamal Misleh, Jamil Khatri, Gregory A Masters, Sachdev Thomas, Malek M. Safa, Daniel M. Anderson, Jonathan Mowers, Anna C Dusenbery, Stephanie Drewery, Komal Plouffe, Travis Reeder, Hana Vakil, Lynnae Patrias, Amanda Falzetta, Ryan Hamilton, Kat Kwiatkowski, D. Bryan Johnson, Daniel R Rhodes, Scott A. Tomlins
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W4382988413