Single-Cell Comparison of Small Intestinal Neuroendocrine Tumors and Enterochromaffin Cells from Two Patients

Several studies have attempted to identify the initiating drivers of small intestinal neuroendocrine tumor (SI-NET) development and the molecular mechanisms underlying their progression and metastatic spread. Previous gene expression studies have used bulk microarrays or RNA sequencing to compare tumor tissue with normal intestinal mucosa. However, the intestine comprises multiple distinct cell types, and bulk analyses are limited by this cellular heterogeneity, which can confound tumor-specific signals.

We performed single-cell RNA sequencing on primary SI-NETs and paired normal mucosa from two patients to directly compare tumor cells with their cells of origin, the enterochromaffin (EC) cells. To minimize type I errors, we applied a two-step validation strategy by overlapping differentially expressed genes with an external single-cell dataset and cross-referencing candidate genes for enteroendocrine expression in the Human Protein Atlas.

For further distinction and characterization, ECs were subdivided into serotonergic and non-serotonergic clusters. This analysis revealed that the SI-NET cells are transcriptionally more similar to serotonergic ECs, consistent with serum metabolite profiles derived from clinical parameters. Our analyses uncovered a loss-of-expression program characterized by regulators of epithelial differentiation and in parallel, a gain-of-expression program displayed neuronal signaling gene induction, implicating functional reprogramming toward neuronal-like properties. Together, these specific losses and gains suggest that our patient-derived SI-NETs undergo adaptation through both loss of enteroendocrine functions and acquisition of neurobiological-promoting signaling pathways.

These findings nominate candidate drivers for further functional validation and highlight potential therapeutic strategies in our patient cohort, including restoring suppressed Notch signaling and targeting aberrant neuronal signaling networks. However, even with a two-step validation procedure, the modest cohort size limits statistical power and generalizability, particularly for the proposed association to a serotonergic phenotype. Larger, multi-patient single-cell studies are required to confirm these mechanisms and establish their clinical relevance.