Need Help?
Copied to clipboard!

Integrative Somatic and Germline Computational Biology to Redefine Clinical Actionability in Solid Tumors

Version 1: Neuroendocrine tumors (NETs) are rare cancers that arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic NETs (GEP-NETs) growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we performed single-cell RNA-sequencing (scRNA-seq) of fresh resections of GEP-NETs, including four pancreatic NETs, three small intestinal NETs, and one perigastric NET. We used single-cell sequencing to investigate the tumor and immune cellular landscapes of GEP-NET patients. Malignant GEP-NET gene and regulon expression was compared with normal, gastrointestinal endocrine cell differentiation and fate determination stages. We further characterized immune-immune and immune-tumor interaction networks within GEP-NETs, identifying novel therapeutic opportunities in the myeloid compartment of the microenvironment. Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

Version 2: Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare malignancies with variable clinical behavior. To better understand the cellular and molecular programs underlying GEP-NET pathophysiology, we performed single-cell RNA-sequencing (scRNA-seq) and ATAC-sequencing (scATAC-seq) of 38 tumors, including 21 pancreatic and 17 small intestinal NETs, across both primary and metastatic sites. We used these approaches to comprehensively profile the tumor and immune microenvironments at single-cell resolution, revealing lineage-specific transcriptional states, distinct chromatin accessibility patterns, and diverse immune interactions. This work provides a foundational resource for understanding GEP-NET heterogeneity and for identifying new avenues for therapeutic intervention.