Integrated genomic and transcriptomic characterization of neuroendocrine carcinomas for improved treatment decision-making.

e15138 Background: Neuroendocrine carcinomas (NECs) are poorly characterized due to their innate heterogeneity, thus limiting treatment and clinical trial options for patients. Here, we used whole exome sequencing (WES) and RNA sequencing (RNA-seq) to explore the genetic and microenvironmental landscape of NECs in order to understand the unique features of different NEC types, with the aim of improving treatment modalities. Methods: We analyzed 51 NEC clinical samples morphologically verified by a pathologist: lung NEC (20 small cell NEC and 1 large cell NEC cases), gastroenteropancreatic NEC (GEP, 12 cases), cancer of unknown primary (7 cases), Merkel cell carcinoma (MCC, 5 cases), genitourinary tract NEC (3 cases), and breast NEC (3 cases). Findings on tumor mutational burden (TMB, mut/Mb), microsatellite instability (MSI), gene expression signatures, and tumor microenvironment (TME) profiling were reported. Small cell lung cancer (SCLC) subtyping was performed as reported by Gay et al. on the entire NEC cohort. Results: Half of the patients with lung NEC and 84% of those with extrapulmonary NEC satisfied the molecular inclusion criteria for clinical trials, with the most frequent criterion being KRAS G12X or G13X mutations. Among the extrapulmonary NEC samples, 13.7% were deemed eligible for targeted therapy, specifically for cases with BRAF V600E mutation and/or high TMB (> 10 mut/Mb). We detected varying TMB and distinct gene expression features across the entire cohort. Specifically, we found 2 MCC cases to be Merkel cell polyomavirus-positive with low TMB and devoid of UV-associated mutations. One GEP-NEC case exhibited a high MSI (MSI-high) status. We detected 6 SCLC cases (3 non-smokers, 3 former smokers) with surprisingly low levels of tobacco-associated mutations (<10% of all mutations). Two GEP-NEC cases had high levels of mutations associated with tobacco smoking. While TME profiling showed no significant difference in cell population makeup across all samples, transcriptional SCLC subtyping revealed significant differences among the cases. Inflammatory SCLC (SCLC-I) samples showed statistically significant enrichment of all subpopulations of the immune microenvironment (i.e., B cells, T cells, NK cells), supporting the use of immune checkpoint blockade for treatment. The POU2F3+ SCLC (SCLC-P) samples showed low expression of all neuroendocrine diagnostic markers (i.e., INSM1, NCAM1, SYP, CHGA). Conclusions: Given the heterogeneous molecular features across diverse NEC tumors, a uniform treatment strategy is unlikely to benefit all NEC patients. Hence, our ability to detect these unique molecular features is crucial for matching individual NEC patients with specific clinical trials and targeted therapies that may improve their outcomes. Thus, a concerted effort using in-depth genomic, transcriptomic, and TME profiling for NEC tumors is warranted.