Abstract
Non-small-cell lung cancer (NSCLC) with
has inferior outcomes to immune checkpoint inhibitors (ICIs). Using multiomics, we evaluated whether a subtype of
NSCLC with a uniquely inflamed tumor immune microenvironment (TIME) harboring
comutations could have favorable outcomes to ICIs.
NSCLC tumors (N = 16,896) were analyzed by next-generation sequencing (DNA-Seq/592 genes). A subset (n = 5,034) underwent gene expression profiling (RNA-Seq/whole transcriptome). Exome-level neoantigen load for
NSCLC was obtained from published pan-immune analysis. Tumor immune cell content was obtained from transcriptome profiles using the microenvironment cell population (MCP) counter. ICI data from POPLAR/OAK (n = 34) and the study by Rizvi et al (n = 49) were used to model progression-free survival (PFS), and a separate ICI-treated cohort (n = 53) from Dana-Farber Cancer Institute (DFCI) was used to assess time to treatment failure (TTF) and tumor RECIST response for
versus
NSCLC.
Overall, 12.6% of NSCLC tumors had a
with the proportions of tumor mutational burden (TMB)-high (≥10 mut/Mb), PD-L1 ≥50%, and microsatellite instability-high being 38.3%, 11.8%, and 0.72%, respectively. Unsupervised hierarchical clustering of
(n = 463) for stimulator of interferon-gamma (STING) pathway genes identified a STING-high cluster, which was significantly enriched in
NSCLC (
< .01). Compared with
, tumors with
had higher CD8+T cells and natural killer cells (
< .01), higher TMB (
< .001) and neoantigen load (
< .001), and increased expression of
and
(
< .01), along with higher expression (
< .01) of glycolysis/glutamine metabolism genes. Meta-analysis of data from OAK/POPLAR and the study by Rizvi et al showed a trend toward improved PFS in patients with
. In the DFCI cohort, compared with the
cohort, the
tumors had higher objective response rates (42.9%
16.7%;
= .04) and also had longer TTF (14.5
4.5 months,
adj = .054) with ICI.
NSCLC with
comutation is a distinct subgroup with an immunologically active TIME and metabolic reprogramming. These properties should be exploited to guide patient selection for novel ICI-based combination approaches.