Real-world multiomic characterization of small cell lung cancer subtypes to reveal differential expression of clinically relevant biomarkers.

Abstract

8508 Background: The dominant expression of four lineage-defining transcription factors ( ASCL1, NEUROD1, YAP1, or POU2F3) has enabled the classification of small cell lung cancer (SCLC) into four subtypes (SCLC-A/N/Y/P, respectively). Emerging evidence suggests that YAP1 expression is associated with a T-cell inflamed phenotype, and SCLC has significant intra-tumor heterogeneity mediated by MYC-driven activation of NOTCH signaling. We performed a large-scale analysis of real-world SCLC patient samples to examine the expression of clinically relevant biomarkers across SCLC subtypes. Methods: Comprehensive molecular profiling of 437 small cell lung neuroendocrine tumors (including 7.3% high-grade neuroendocrine lung carcinomas) was performed using next-generation DNA sequencing (592-gene panel), RNA sequencing (whole transcriptome), and immunohistochemistry at Caris Life Sciences (Phoenix, AZ). Tumors were stratified into 5 subgroups (SCLC-A/N/Y/P and -mixed) based on the relative expression of the four transcription factors. RNA expression of key genes and previously validated immune signatures (T-cell inflamed, NK cell, and STING pathway signatures) were evaluated across subgroups. Significance was tested by Chi-square, Fisher’s exact test, or Mann-Whitney U test. Results: Median age of the study cohort was 66 years (IQR: 59-72) and 50.6% of patients were female. The majority (67.3%) of samples were derived from metastatic sites. Stratification of tumors by expression resulted in 35.7% SCLC-A, 17.6% SCLC-N, 21.1% SCLC-Y, 6.4% SCLC-P, and 19.2% SCLC-mixed samples. Compared to tumors from metastatic sites, YAP1 expression was significantly increased (p < 0.001) in primary tumors. Amongst the 14 tumors obtained from the CNS, SCLC-N (36%, n = 5) was the most common subtype identified. dMMR/MSI-high (negative MMR protein expression/ ≥46 altered loci per tumor) was rare overall (0.5%, n = 2); TMB (median of 9-10 mut/Mb) was similar between the SCLC subtypes. SCLC-Y was associated with the highest expression of T-cell inflamed, NK cell and STING pathway signatures (p < 0.0001 each). MYC and NOTCH gene expression ( NOTCH1/2/3/4) strongly correlated with YAP1 expression. Analysis of co-mutations revealed that EGFR-sensitizing mutations (L858R and Exon 19 deletions) were recurrent (5.2%, n = 4) in SCLC-N tumors. The expression of SNF11, SSTR2, and MYC varied significantly among SCLC subtypes (p < 0.001 each), with the highest median expression of SNF11 and SSTR2 observed in SCLC-N, while MYC expression was highest in SCLC-P. Conclusions: Our analysis represents the largest real-world dataset of human SCLC tumors profiled by whole transcriptomic sequencing. The differential expression of immune genes and predictive biomarkers across SCLC subtypes may inform therapeutic vulnerabilities for rational and personalized treatment approaches in SCLC.