FIGURE 2 from Validation of Immunotherapy Response Score as Predictive of Pan-solid Tumor Anti-PD-1/PD-L1 Benefit
Year: 2023
Type: other
Abstract: Confirmation of the added utility of the IRS versus clinical PD-L1 IHC and TMB alone. A, Normalized PD-L1 (CD274) expression (and the other IRS expression components) by the qTP platform used to generate IRS were validated versus qRT-PCR in a validation cohort of 96 FFPE tumor tissue samples tested by clinical CGP and in parallel qTP. The Pearson correlation and linear range of each component is shown (Supplementary Fig. S1). B and C, The Pearson correlation of normalized PD-L1 expression by qTP [log2 normalized reads per million (nRPM) units] versus clinical PD-L1 IHC score (in submitted pathology reports) was determined in two cohorts of clinical FFPE tumor tissues [regardless of TMB availability and anti-PD-(L)1 treatment]. B, PD-L1 expression by qTP (log2 normalized units) versus PD-L1 IHC by TPS [using the 22C3 antibody clone (log2 TPS) in 276 clinically tested FFPE NSCLC tumors with available TPS is plotted]. The linear fit, Pearson correlation (r), and P value are shown. C, PD-L1 expression by qTP versus PD-L1 IHC by CPS using the 22C3 antibody clone (log2 CPS) in 221 clinically tested FFPE tumors (23 tumor types; most frequently EGC) with available TPS is plotted. The linear fit, Pearson correlation (r), and P value are shown. D, Using B and C, we identified a cohort of all 189 eligible NCT03061305 patients with IRS and PD-(L)1 IHC in accompanying pathology reports who were treated with anti-PD-(L)1 therapy (± chemotherapy). The association of biomarkers with anti-PD-(L)1 rwPFS was determined by Cox proportional hazards modeling [adjusting for age, sex assigned at birth, line of therapy, tumor type, therapy type (monotherapy vs. chemotherapy combination), and inclusion in IRS discovery status]. PD-L1 IHC score (continuous; log2) was included in the baseline model (Model 1), with the aHR, 95% CI, number (n) of patients and events, and P value shown for the biomarker term by forest plot. TMB status (-H vs. -L; pink) and IRS status (-H vs. -L; light blue) were separately added to this model (Models 2 and 3, respectively). The significance of each biomarker term is shown and the P value of the LRT comparing the full (Model 2 or 3) versus reduced (Model 1) model is shown. Model 4 includes PD-L1 IHC, TMB, and IRS. Significant biomarker terms are shown by filled in aHR estimates. E, Anti-PD-(L)1 rwPFS stratified by IRS group is shown by unadjusted Kaplan–Meier analysis, with the aHR from Model 4 in D shown. See Supplementary Table S7 for full subgroup analysis.
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: W4385251124