Genome-Wide Association Study Identifies 4 Novel Risk Loci for Small Intestinal Neuroendocrine Tumors Including a Missense Mutation in LGR5.

BACKGROUND & AIMS: Small intestinal neuroendocrine tumor (SI-NET) is a rare disease, but its incidence has increased over the past 4 decades. Understanding the genetic risk factors underlying SI-NETs can help in disease prevention and may provide clinically beneficial markers for diagnosis. Here the results of the largest genome-wide association study of SI-NETs performed to date with 405 cases and 614,666 controls are reported. METHODS: Samples from 307 patients with SI-NETs and 287,137 controls in the FinnGen study were used for the identification of SI-NET risk-associated genetic variants. The results were also meta-analyzed with summary statistics from the UK Biobank (n = 98 patients with SI-NET and n = 327,529 controls). RESULTS: We identified 6 genome-wide significant (P < 5 × 10-8) loci associated with SI-NET risk, of which 4 (near SEMA6A, LGR5, CDKAL1, and FERMT2) are novel and 2 (near LTA4H-ELK and in KIF16B) have been reported previously. Interestingly, the top hit (rs200138614; P = 1.80 × 10-19) was a missense variant (p.Cys712Phe) in the LGR5 gene, a bona-fide marker of adult intestinal stem cells and a potentiator of canonical WNT signaling. The association was validated in an independent Finnish collection of 70 patients with SI-NETs, as well as in the UK Biobank exome sequence data (n = 92 cases and n = 392,814 controls). Overexpression of LGR5 p.Cys712Phe in intestinal organoids abolished the ability of R-Spondin1 to support organoid growth, indicating that the mutation perturbed R-Spondin-LGR5 signaling. CONCLUSIONS: Our study is the largest genome-wide association study to date on SI-NETs and reported 4 new associated genome-wide association study loci, including a novel missense mutation (rs200138614, p.Cys712Phe) in LGR5, a canonical marker of adult intestinal stem cells.

Fibroblast-derived EGF ligand neuregulin 1 induces fetal-like reprogramming of the intestinal epithelium without supporting tumorigenic growth.

Growth factors secreted by stromal fibroblasts regulate the intestinal epithelium. Stroma-derived epidermal growth factor (EGF) family ligands are implicated in epithelial regeneration and tumorigenesis, but their specific contributions and associated mechanisms remain unclear. Here, we use primary intestinal organoids modeling homeostatic, injured and tumorigenic epithelia to assess how the fibroblast-derived EGF family ligands neuregulin 1 (NRG1) and epiregulin (EREG) regulate the intestinal epithelium. NRG1 was expressed exclusively in the stroma, robustly increased crypt budding and protected intestinal epithelial organoids from radiation-induced damage. NRG1 also induced regenerative features in the epithelium, including a fetal-like transcriptome, suppression of the Lgr5+ stem cell pool and remodeling of the epithelial actin cytoskeleton. Intriguingly, unlike EGF and EREG, NRG1 failed to support the growth of pre-tumorigenic intestinal organoids lacking the tumor suppressor Apc, commonly mutated in human colorectal cancer (CRC). Interestingly, high expression of stromal NRG1 was associated with improved survival in CRC cohorts, suggesting a tumor-suppressive function. Our results highlight the power of stromal NRG1 in transcriptional reprogramming and protection of the intestinal epithelium from radiation injury without promoting tumorigenesis.

Tellu - an object-detector algorithm for automatic classification of intestinal organoids.

Intestinal epithelial organoids recapitulate many of the in vivo features of the intestinal epithelium, thus representing excellent research models. Morphology of the organoids based on light-microscopy images is used as a proxy to assess the biological state of the intestinal epithelium. Currently, organoid classification is manual and, therefore, subjective and time consuming, hampering large-scale quantitative analyses. Here, we describe Tellu, an object-detector algorithm trained to classify cultured intestinal organoids. Tellu was trained by manual annotation of >20,000 intestinal organoids to identify cystic non-budding organoids, early organoids, late organoids and spheroids. Tellu can also be used to quantify the relative organoid size, and can classify intestinal organoids into these four subclasses with accuracy comparable to that of trained scientists but is significantly faster and without bias. Tellu is provided as an open, user-friendly online tool to benefit the increasing number of investigations using organoids through fast and unbiased organoid morphology and size analysis.