scholarly journals Characterizing and classifying neuroendocrine neoplasms through microRNA sequencing and data mining

NAR Cancer ◽  
2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Jina Nanayakkara ◽  
Kathrin Tyryshkin ◽  
Xiaojing Yang ◽  
Justin J M Wong ◽  
Kaitlin Vanderbeck ◽  
...  
Keyword(s):  
Data Mining ◽  
Mirna Expression ◽  
Expression Profiles ◽  
Molecular Data ◽  
Neuroendocrine Neoplasms ◽  
Study Cohort ◽  
Learning Approaches ◽  
Mirna Expression Profiles ◽  
Small Regulatory Rnas ◽  
Microrna Sequencing

Abstract Neuroendocrine neoplasms (NENs) are clinically diverse and incompletely characterized cancers that are challenging to classify. MicroRNAs (miRNAs) are small regulatory RNAs that can be used to classify cancers. Recently, a morphology-based classification framework for evaluating NENs from different anatomical sites was proposed by experts, with the requirement of improved molecular data integration. Here, we compiled 378 miRNA expression profiles to examine NEN classification through comprehensive miRNA profiling and data mining. Following data preprocessing, our final study cohort included 221 NEN and 114 non-NEN samples, representing 15 NEN pathological types and 5 site-matched non-NEN control groups. Unsupervised hierarchical clustering of miRNA expression profiles clearly separated NENs from non-NENs. Comparative analyses showed that miR-375 and miR-7 expression is substantially higher in NEN cases than non-NEN controls. Correlation analyses showed that NENs from diverse anatomical sites have convergent miRNA expression programs, likely reflecting morphological and functional similarities. Using machine learning approaches, we identified 17 miRNAs to discriminate 15 NEN pathological types and subsequently constructed a multilayer classifier, correctly identifying 217 (98%) of 221 samples and overturning one histological diagnosis. Through our research, we have identified common and type-specific miRNA tissue markers and constructed an accurate miRNA-based classifier, advancing our understanding of NEN diversity.

scholarly journals Evaluating gastroenteropancreatic neuroendocrine tumors through microRNA sequencing

2019 ◽  
Vol 26 (1) ◽  
pp. 47-57 ◽  
Author(s):  
Nicole Panarelli ◽  
Kathrin Tyryshkin ◽  
Justin Jong Mun Wong ◽  
Adrianna Majewski ◽  
Xiaojing Yang ◽  
...  
Keyword(s):  
Neuroendocrine Tumors ◽  
Small Rna ◽  
Mirna Expression ◽  
Expression Profiles ◽  
Machine Learning Techniques ◽  
Disease Stage ◽  
Small Rna Sequencing ◽  
Gastroenteropancreatic Neuroendocrine Tumors ◽  
Mirna Expression Profiles ◽  
Microrna Sequencing

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.

The Predominant microRNAs in β-cell Clusters for Insulin Regulation and Diabetic Control

2020 ◽  
Vol 21 (7) ◽  
pp. 722-734
Author(s):  
Adele Soltani ◽  
Arefeh Jafarian ◽  
Abdolamir Allameh
Keyword(s):  
Mirna Expression ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Diabetic Control ◽  
In Vitro Proliferation ◽  
Cell Functions ◽  
Mirna Expression Profiles ◽  
Multiple Processes ◽  
The Impact

micro (mi)-RNAs are vital regulators of multiple processes including insulin signaling pathways and glucose metabolism. Pancreatic β-cells function is dependent on some miRNAs and their target mRNA, which together form a complex regulative network. Several miRNAs are known to be directly involved in β-cells functions such as insulin expression and secretion. These small RNAs may also play significant roles in the fate of β-cells such as proliferation, differentiation, survival and apoptosis. Among the miRNAs, miR-7, miR-9, miR-375, miR-130 and miR-124 are of particular interest due to being highly expressed in these cells. Under diabetic conditions, although no specific miRNA profile has been noticed, the expression of some miRNAs and their target mRNAs are altered by posttranscriptional mechanisms, exerting diverse signs in the pathobiology of various diabetic complications. The aim of this review article is to discuss miRNAs involved in the process of stem cells differentiation into β-cells, resulting in enhanced β-cell functions with respect to diabetic disorders. This paper will also look into the impact of miRNA expression patterns on in vitro proliferation and differentiation of β-cells. The efficacy of the computational genomics and biochemical analysis to link the changes in miRNA expression profiles of stem cell-derived β-cells to therapeutically relevant outputs will be discussed as well.

scholarly journals miRNA expression profiles in liver grafts of HCV and HIV/HCV infected recipients, six months after liver transplantation

2021 ◽  
Author(s):  
Michela Bulfoni ◽  
Riccardo Pravisani ◽  
Emiliano Dalla ◽  
Daniela Cesselli ◽  
Masaaki Hidaka ◽  
...  
Keyword(s):  
Liver Transplantation ◽  
Mirna Expression ◽  
Expression Profiles ◽  
Mirna Expression Profiles

Effects of the Co‐Administration of MK‐801 and Clozapine MiRNA Expression Profiles in Rats

2021 ◽  
Author(s):  
Wenhui Huang ◽  
Xuefeng Gu ◽  
Yingying Wang ◽  
Yuhan Bi ◽  
Yu. Yang ◽  
...  
Keyword(s):  
Mirna Expression ◽  
Expression Profiles ◽  
Mk 801 ◽  
Mirna Expression Profiles

scholarly journals Alpinia oxyphylla Miq. extract changes miRNA expression profiles in db-/db- mouse kidney

2017 ◽  
Vol 50 (1) ◽  
Author(s):  
Guankui Du ◽  
Man Xiao ◽  
Xuezi Zhang ◽  
Maoyu Wen ◽  
Chi Pang ◽  
...  
Keyword(s):  
Mirna Expression ◽  
Expression Profiles ◽  
Mouse Kidney ◽  
Alpinia Oxyphylla ◽  
Mirna Expression Profiles

scholarly journals MicroRNA Expression Profiles in Superficial Esophageal Squamous Cell Carcinoma before Endoscopic Submucosal Dissection: A Pilot Study

2021 ◽  
Vol 22 (9) ◽  
pp. 4789
Author(s):  
Shintaro Fujihara ◽  
Hideki Kobara ◽  
Noriko Nishiyama ◽  
Kayo Hirose ◽  
Hisakazu Iwama ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Endoscopic Submucosal Dissection ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Mirna Expression ◽  
Expression Profiles ◽  
Normal Tissues ◽  
Mirna Expression Profiles

Esophageal squamous cell carcinoma (ESCC) has a poor prognosis when diagnosed at an advanced stage, and early detection and treatment are essential to improve survival. However, intraobserver and interobserver variation make the diagnosis of superficial ESCC difficult, and suitable biomarkers are urgently needed. Here, we compared the microRNA (miRNA) expression profiles of superficial ESCC tissues and adjacent normal tissues obtained immediately before esophageal endoscopic submucosal dissection. We found that ESCC and normal tissues differed in their miRNA expression profiles. In particular, miR-21-5p and miR-146b-5p were significantly upregulated and miR-210-3p was significantly downregulated in tumor tissues compared with normal tissues. We also detected significant associations between miRNA expression and ESCC invasion depth and lymphovascular invasion. The same differential expression of miR-21-5p, miR-146b-5p, and miR-210-3p was detected in ESCC cell lines compared with normal esophageal epithelial cells in vitro. However, transfection of ESCC cells with miR-210-3p and miR-21-5p mimics or inhibitors had partial effects on cell proliferation and invasion in vitro. These results indicate that miRNA expression is significantly deregulated in superficial ESCC, and suggest that the potential contribution of differentially expressed miRNAs to the malignant phenotype should be further investigated.

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