PEOPLE (NTC03447678), a phase II trial to test pembrolizumab as first-line treatment in patients with advanced NSCLC with PD-L1 <50%: a multiomics analysis

Abstract

Background: Chemoimmunotherapy represents the standard of care for patients with advanced non-small cell lung cancer (NSCLC) and programmed death-ligand 1 (PD-L1) <50%. Although single-agent pembrolizumab has also demonstrated some activity in this setting, no reliable biomarkers yet exist for selecting patients likely to respond to single-agent immunotherapy. The main purpose of the study was to identify potential new biomarkers associated with progression-free-survival (PFS) within a multiomics analysis.

Methods: PEOPLE (NTC03447678) was a prospective phase II trial evaluating first-line pembrolizumab in patients with advanced EGFR and ALK wild type treatment-naïve NSCLC with PD-L1 <50%. Circulating immune profiling was performed by determination of absolute cell counts with multiparametric flow cytometry on freshly isolated whole blood samples at baseline and at first radiological evaluation. Gene expression profiling was performed using nCounter PanCancer IO 360 Panel (NanoString) on baseline tissue. Gut bacterial taxonomic abundance was obtained by shotgun metagenomic sequencing of stool samples at baseline. Omics data were analyzed with sequential univariate Cox proportional hazards regression predicting PFS, with Benjamini-Hochberg multiple comparisons correction. Biological features significant with univariate analysis were analyzed with multivariate least absolute shrinkage and selection operator (LASSO).

Results: From May 2018 to October 2020, 65 patients were enrolled. Median follow-up and PFS were 26.4 and 2.9 months, respectively. LASSO integration analysis, with an optimal lambda of 0.28, showed that peripheral blood natural killer cells/CD56dimCD16+ (HR 0.56, 0.41-0.76, p=0.006) abundance at baseline and non-classical CD14dimCD16+monocytes (HR 0.52, 0.36-0.75, p=0.004), eosinophils (CD15+CD16-) (HR 0.62, 0.44-0.89, p=0.03) and lymphocytes (HR 0.32, 0.19-0.56, p=0.001) after first radiologic evaluation correlated with favorable PFS as well as high baseline expression levels of CD244 (HR 0.74, 0.62-0.87, p=0.05) protein tyrosine phosphatase receptor type C (HR 0.55, 0.38-0.81, p=0.098) and killer cell lectin like receptor B1 (HR 0.76, 0.66-0.89, p=0.05). Interferon-responsive factor 9 and cartilage oligomeric matrix protein genes correlated with unfavorable PFS (HR 3.03, 1.52-6.02, p 0.08 and HR 1.22, 1.08-1.37, p=0.06, corrected). No microbiome features were selected.

Conclusions: This multiomics approach was able to identify immune cell subsets and expression levels of genes associated to PFS in patients with PD-L1 <50% NSCLC treated with first-line pembrolizumab. These preliminary data will be confirmed in the larger multicentric international I3LUNG trial (NCT05537922).

Trial registration number: 2017-002841-31.

Keywords: biomarkers, tumor; immunotherapy; non-small cell lung cancer.

Figure 1

The correlation matrix visualizes the correlation between the features selected at univariate analysis and the most relevant clinical features. Green boxes indicate positive correlation, golden boxes indicate negative correlation, X indicates absence of correlation. bCIP, circulating immune profiling at baseline; COMP, cartilage oligomeric matrix protein; GEP, gene expression profiling; IRF9, interferon-responsive factor 9; KLRB1, killer cell lectin like receptor B1; LKT, last known taxon; NK, natural killer; pCIP, circulating immune profiling post-immunotherapy; PSMB5, proteasome 20S subunit beta 5; PTPRC, protein tyrosine phosphatase receptor type C; SCC, squamous cell carcinoma.

Figure 2

Feature selection using LASSO algorithm: LASSO coefficient profile for all features selected using univariant analysis. A vertical line was drawn at the optimal lambda value selected using the 10-fold cross-validation process. COMP, cartilage oligomeric matrix protein; IRF9, interferon-responsive factor 9; KLRB1, killer cell lectin like receptor B1; LASSO, least absolute shrinkage and selection operator; NK, natural killer; PSMB5, proteasome 20S subunit beta 5; PTPRC, protein tyrosine phosphatase receptor type C.

Figure 3

Feature selection using least absolute shrinkage and selection operator algorithm: Zoom-in on optimal lambda and selected features. COMP, cartilage oligomeric matrix protein; KLRB1, killer cell lectin like receptor B1.

Figure 4

The figure represents all features selected by LASSO for each set of data. The green or gold color code of the features indicates a positive or negative correlation with PFS. bCIP, circulating immune profiling at baseline; CIP, circulating immune profiling; COMP, cartilage oligomeric matrix protein; GEP, gene expression profiling; IRF9, interferon-responsive factor 9; KLRB1, killer cell lectin like receptor B1; LASSO, least absolute shrinkage and selection operator; NK, natural killer; pCIP, circulating immune profiling post-immunotherapy; PFS, progression-free-survival; PTPRC, protein tyrosine phosphatase receptor type C.