Title | Evaluating gastroenteropancreatic neuroendocrine tumors through microRNA sequencing. |
Publication Type | Journal Article |
Year of Publication | 2019 |
Authors | Panarelli N, Tyryshkin K, Wong JJong Mun, Majewski A, Yang X, Scognamiglio T, Kim MKang, Bogardus K, Tuschl T, Chen Y-T, Renwick N |
Journal | Endocr Relat Cancer |
Volume | 26 |
Issue | 1 |
Pagination | 47-57 |
Date Published | 2019 01 01 |
ISSN | 1479-6821 |
Keywords | Adolescent, Adult, Aged, Aged, 80 and over, Child, Female, Humans, Intestinal Neoplasms, Male, MicroRNAs, Middle Aged, Neuroendocrine Tumors, Pancreatic Neoplasms, Sequence Analysis, RNA, Stomach Neoplasms, Young Adult |
Abstract | Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) can be challenging to evaluate histologically. MicroRNAs (miRNAs) are small RNA molecules that often are excellent biomarkers due to their abundance, cell-type and disease stage specificity and stability. To evaluate miRNAs as adjunct tissue markers for classifying and grading well-differentiated GEP-NETs, we generated and compared miRNA expression profiles from four pathological types of GEP-NETs. Using quantitative barcoded small RNA sequencing and state-of-the-art sequence annotation, we generated comprehensive miRNA expression profiles from archived pancreatic, ileal, appendiceal and rectal NETs. Following data preprocessing, we randomly assigned sample profiles to discovery (80%) and validation (20%) sets prior to data mining using machine-learning techniques. High expression analyses indicated that miR-375 was the most abundant individual miRNA and miRNA cistron in all samples. Leveraging prior knowledge that GEP-NET behavior is influenced by embryonic derivation, we developed a dual-layer hierarchical classifier for differentiating GEP-NET types. In the first layer, our classifier discriminated midgut (ileum, appendix) from non-midgut (rectum, pancreas) NETs based on miR-615 and -92b expression. In the second layer, our classifier discriminated ileal from appendiceal NETs based on miR-125b, -192 and -149 expression, and rectal from pancreatic NETs based on miR-429 and -487b expression. Our classifier achieved overall accuracies of 98.5% and 94.4% in discovery and validation sets, respectively. We also found provisional evidence that low- and intermediate-grade pancreatic NETs can be discriminated based on miR-328 expression. GEP-NETs can be reliably classified and potentially graded using a limited panel of miRNA markers, complementing morphological and immunohistochemistry-based approaches to histologic evaluation. |
DOI | 10.1530/ERC-18-0244 |
Alternate Journal | Endocr Relat Cancer |
PubMed ID | 30021866 |
Related Faculty:
Theresa Scognamiglio, M.D.