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 ◽  
...  

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.

MicroRNA ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 61-67 ◽  
Author(s):  
Daniela Andrei ◽  
Roland A. Nagy ◽  
Aafke van Montfoort ◽  
Uwe Tietge ◽  
Martijn Terpstra ◽  
...  

Background: Mural Granulosa Cells (MGCs) and Cumulus Cells (CCs) are two specialized cell types that differentiate from a common progenitor during folliculogenesis. Although these two cell types have specialized functions and gene expression profiles, little is known about their microRNA (miRNA) expression patterns. Objective: To describe the miRNA profile of mural and cumulus granulosa cells from human preovulatory follicles. </P><P> Methods: Using small RNA sequencing, we defined the miRNA expression profiles of human primary MGCs and CCs, isolated from healthy women undergoing ovum pick-up for in vitro Fertilization (IVF). Results: Small RNA sequencing revealed the expression of several hundreds of miRNAs in MGCs and CCs with 53 miRNAs being significantly differentially expressed between MGCs and CCs. We validated the differential expression of miR-146a-5p, miR-149-5p, miR-509-3p and miR-182-5p by RT-qPCR. Analysis of proven targets revealed 37 targets for miR-146a-5p, 43 for miR-182-5p, 2 for miR-509-3p and 9 for miR-149-5p. Gene Ontology (GO) analysis for these 4 target gene sets revealed enrichment of 12 GO terms for miR-146a-5p and 10 for miR-182-5p. The GO term ubiquitin-like protein conjugation was enriched within both miRNA target gene sets. We generated miRNA expression profiles for MGCs and CCs and identified several differentially expressed miRNAs.


Genes ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1576
Author(s):  
Jin-Ok Lee ◽  
Minho Lee ◽  
Yeun-Jun Chung

Transfer RNA (tRNA), a key component of the translation machinery, plays critical roles in stress conditions and various diseases. While knowledge regarding the importance of tRNA function is increasing, its biological roles are still not well understood. There is currently no comprehensive database or web server providing the expression landscape of tRNAs across a variety of human tissues and diseases. Here, we constructed a user-friendly and interactive database, DBtRend, which provides a profile of mature tRNA expression across various biological conditions by reanalyzing the small RNA or microRNA sequencing data from the Cancer Genome Atlas (TCGA) and NCBI’s Gene Expression Omnibus (GEO) in humans. Users can explore not only the expression values of mature individual tRNAs in the human genome, but also those of isodecoders and isoacceptors based on our specific pipelines. DBtRend provides the expressed patterns of tRNAs, the differentially expressed tRNAs in different biological conditions, and the information of samples or patients, tissue types, and molecular subtype of cancers. The database is expected to help researchers interested in functional discoveries of tRNAs.


NAR Cancer ◽  
2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Jina Nanayakkara ◽  
Kathrin Tyryshkin ◽  
Xiaojing Yang ◽  
Justin J M Wong ◽  
Kaitlin Vanderbeck ◽  
...  

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.


2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Cheng-Tsung Pan ◽  
Kuo-Wang Tsai ◽  
Tzu-Min Hung ◽  
Wei-Chen Lin ◽  
Chao-Yu Pan ◽  
...  

MicroRNAs (miRNAs) present diverse regulatory functions in a wide range of biological activities. Studies on miRNA functions generally depend on determining miRNA expression profiles between libraries by using a next-generation sequencing (NGS) platform. Currently, several online web services are developed to provide small RNA NGS data analysis. However, the submission of large amounts of NGS data, conversion of data format, and limited availability of species bring problems. In this study, we developed miRSeq to provide alternatives. To test the performance, we had small RNA NGS data from four species, including human, rat, fly, and nematode, analyzed with miRSeq. The alignments results indicate that miRSeq can precisely evaluate the sequencing quality of samples regarding percentage of self-ligation read, read length distribution, and read category. miRSeq is a user-friendly standalone toolkit featuring a graphical user interface (GUI). After a simple installation, users can easily operate miRSeq on a PC or laptop by using a mouse. Within minutes, miRSeq yields useful miRNA data, including miRNA expression profiles, 3′ end modification patterns, and isomiR forms. Moreover, miRSeq supports the analysis of up to 105 animal species, providing higher flexibility.


2016 ◽  
Vol 34 (4_suppl) ◽  
pp. 506-506
Author(s):  
Robin Mjelle ◽  
Wenche Sjursen ◽  
Liv Thommesen ◽  
Eva Hofsli

506 Background: MicroRNAs (miRNAs) are promising biomarkers and therapeutic agents for colorectal cancer (CRC). However, much remains to be known about the biology of miRNAs and miRNA variants in tumor tissue and why the expression differs from normal tissue. Methods: RNA from 48 normal and 48 cancer tissue samples were sequenced using the Illumina small RNA sequencing protocol. Samples were taken from both male and female patients with tumor stage 1-4. Results: We show that almost 50% of microRNAs (miRNAs) are differentially expressed between normal and cancer tissue. When analyzing pre-miRNAs that map to genomic clusters, so-called clustered miRNAs, we show that miRNAs in the same cluster often have similar expression profiles. This shows that common changes in co-expressed miRNAs seem to explain some of the miRNA expression changes between normal and tumor samples and indicates that altered pri-miRNA transcription is the mechanism for at least some of the miRNA changes. Analyses of miRNA variants, so-called isomiRs, revealed large variations between tumor and normal samples, similar to those observed for the canonical miRNAs. Different isomiR types show different expression profiles in tumor vs normal samples, indicating that miRNA processing is altered in tumor cells. Finally, we show that several canonical miRNAs and isomiRs correlate with genetic signatures in the tumor samples, including KRAS and BRAF mutation, Microsatellite instability and MLH1 methylation, indicating that tumor subtypes have different miRNA expression. Conclusions: Our results show that miRNA expression predicts tumor subtypes with different genetic signatures. We show that some of the changes in miRNA expression are due to different transcription programs in cancer vs normal tissue.


2020 ◽  
Vol 21 (7) ◽  
pp. 722-734
Author(s):  
Adele Soltani ◽  
Arefeh Jafarian ◽  
Abdolamir Allameh

micro (mi)-RNAs are vital regulators of multiple processes including insulin signaling pathways and glucose metabolism. Pancreatic &#946;-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 &#946;-cells functions such as insulin expression and secretion. These small RNAs may also play significant roles in the fate of &#946;-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 &#946;-cells, resulting in enhanced &#946;-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 &#946;-cells. The efficacy of the computational genomics and biochemical analysis to link the changes in miRNA expression profiles of stem cell-derived &#946;-cells to therapeutically relevant outputs will be discussed as well.


Author(s):  
Michela Bulfoni ◽  
Riccardo Pravisani ◽  
Emiliano Dalla ◽  
Daniela Cesselli ◽  
Masaaki Hidaka ◽  
...  

Author(s):  
Wenhui Huang ◽  
Xuefeng Gu ◽  
Yingying Wang ◽  
Yuhan Bi ◽  
Yu. Yang ◽  
...  

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