Lila E. Mullany

Bio: Lila E. Mullany is an academic researcher from University of Utah. The author has contributed to research in topics: microRNA & Population. The author has an hindex of 21, co-authored 38 publications receiving 1063 citations.

An evaluation and replication of miRNAs with disease stage and colorectal cancer-specific mortality

Abstract: MicroRNAs (miRNAs) have been implicated in colorectal cancer (CRC) development and associated with prognostic indicators such as disease stage and survival. Prognostic associations are often based on few individuals and imprecise. In this study, we utilize population-based data from 1,141 CRC cases to replicate previously reported associations between 121 miRNAs and disease stage and survival. The Agilent Human miRNA Microarray V19.0 was used to generate miRNA data following a stringent quality control protocol. Assessment of survival was done using Cox Proportional Hazard models adjusting for age, disease stage and tumor molecular phenotype. Five miRNAs were associated with more advanced disease stage; hsa-miR-145-5p and hsa-miR-31-5p showed increased expression with more advanced tumor stage, while hsa-miR-200b-3p, hsa-miR-215 and hsa-miR-451a had decreased expression with more advanced tumors. Thirteen miRNAs were associated with CRC mortality among individuals diagnosed with colon cancer while 14 were associated with CRC mortality after a diagnosis with rectal cancer. Strongest associations were observed for those miRNAs that were expressed in a small subset of tumors. Most notable associations were for hsa-miR-145-3p [hazard ratio (HR) 2.94, 95% confidence interval (CI) 1.54, 5.61], and hsa-miR-9-3p (HR 10.28, 95% CI 1.31, 80.84) with colon cancer and hsa-miR-335-5p (HR 0.17, 95% CI 0.05, 0.54) for rectal cancer. hsa-miR-374a-5p, hsa-miR-570-3p and hsa-miR-18a-5p significantly reduced the hazard of dying for all cases, regardless of tumor site. Our findings illustrate the need for a large sample to evaluate the association of miRNAs with survival and disease stage in order to determine associations by tumor site.

MicroRNA profiles in colorectal carcinomas, adenomas and normal colonic mucosa: variations in miRNA expression and disease progression

Abstract: MiRNAs are small, non-protein-coding RNA molecules that regulate gene expression either by post-transcriptionally suppressing mRNA translation or by mRNA degradation. We examine differentially expressed miRNAs in colorectal carcinomas, adenomas and normal colonic mucosa. Data come from population-based studies of colorectal cancer conducted in Utah and the Kaiser Permanente Medical Care Program. A total of 1893 carcinoma/normal-paired samples and 290 adenoma tissue samples were run on the Agilent Human miRNA Microarray V19.0 which contained 2006 miRNAs. We tested for significant differences in miRNA expression between paired carcinoma/adenoma/normal colonic tissue samples. Fewer than 600 miRNAs were expressed in >80% of people for colonic tissue; of these 86.5% were statistically differentially expressed between carcinoma and normal colonic mucosa using a false discovery rate of 0.05. Roughly half of these differentially expressed miRNAs showed a progression in levels of expression from normal to adenoma to carcinoma tissue. Other miRNAs appeared to be altered at the normal to adenoma stage, while others were only altered at the adenoma to carcinoma stage or only at the normal to carcinoma stage. Evaluation of the Agilent platform showed a high degree of repeatability (r = 0.98) and reasonable agreement with the NanoString platform. Our data suggest that miRNAs are highly dysregulated in colorectal tissue among individuals with colorectal cancer; the pattern of disruption varies by miRNA as tissue progresses from normal to adenoma to carcinoma.

Expression Profiles of miRNA Subsets Distinguish Human Colorectal Carcinoma and Normal Colonic Mucosa

Abstract: Expression Profiles of miRNA Subsets Distinguish Human Colorectal Carcinoma and Normal Colonic Mucosa

The co-regulatory networks of tumor suppressor genes, oncogenes, and miRNAs in colorectal cancer.

Abstract: Tumor suppressor genes (TSGs) and oncogenes (OG) are involved in carcinogenesis. MiRNAs also contribute to cellular pathways leading to cancer. We use data from 217 colorectal cancer (CRC) cases to evaluate differences in TSGs and OGs expression between paired CRC and normal mucosa and evaluate how TSGs and OGs are associated with miRNAs. Gene expression data from RNA-Seq and miRNA expression data from Agilent Human miRNA Microarray V19.0 were used. We focus on genes most strongly associated with CRC (fold change (FC) of ≥1.5 or ≤0.67) that were statistically significant after adjustment for multiple comparisons. Of the 74 TSGs evaluated, 22 were associated with carcinoma/normal mucosa differential expression. Ten TSGs were up-regulated (FAM123B, RB1, TP53, RUNX1, MSH2, BRCA1, BRCA2, SOX9, NPM1, and RNF43); six TSGs were down-regulated (PAX5, IZKF1, GATA3, PRDM1, TET2, and CYLD); four were associated with MSI tumors (MLH1, PTCH1, and CEBPA down-regulated and MSH6 up-regulated); and two were associated with MSS tumors (PHF6 and ASXL1 up-regulated). Thirteen of these TSGs were associated with 44 miRNAs. Twenty-seven of the 59 OGs evaluated were dysregulated: 14 down-regulated (KLF4, BCL2, SSETBP1, FGFR2, TSHR, MPL, KIT, PDGFRA, GNA11, GATA2, FGFR3, AR, CSF1R, and JAK3), seven up-regulated (DNMT1, EZH2, PTPN11, SKP2, CCND1, MET, and MYC); three down-regulated for MSI (FLT3, CARD11, and ALK); two up-regulated for MSI (IDH2 and HRAS); and one up-regulated with MSS tumors (CTNNB1). These findings suggest possible co-regulatory function between TSGs, OGs, and miRNAs, involving both direct and indirect associations that operate through feedback and feedforward loops.

The PI3K/AKT signaling pathway: Associations of miRNAs with dysregulated gene expression in colorectal cancer

Abstract: The PI3K/AKT-signaling pathway is one of the most frequently activated signal-transduction pathways in cancer. We examined how dysregulated gene expression is associated with miRNA expression in this pathway in colorectal cancer (CRC). We used data from 217 CRC cases to evaluate differential pathway gene expression between paired carcinoma and normal mucosa and identify miRNAs that are associated with these genes. Gene expression data from RNA-Seq and miRNA expression data from Agilent Human miRNA Microarray V19.0 were analyzed. We focused on genes most associated with CRC (fold change (FC) of >1.5 or <0.67) that were statistically significant after adjustment for multiple comparisons. Of the 304 genes evaluated, 76 had a FC of 1.50; 47 of these genes were associated with miRNA differential expression. There were 145 mRNA:miRNA seed-region matches of which 26 were inversely associated suggesting a greater likelihood of a direct association. Most miRNA:mRNA associations were with factors that stimulated the pathway. For instance, both IL6R and PDGFRA had inverse seed-region matches with seven miRNAs, suggesting that these miRNAs have a direct effect on these genes and may be key elements in activation of the pathway. Other miRNA:mRNA associations with similar impact on the pathway were miR-203a with ITGA4, miR-6071 with ITGAV, and miR-375 with THBS2, all genes involved in extracellular matrix function that activate PI3Ks. Gene expression in the PI3K/Akt-signaling pathway is dysregulated in CRC. MiRNAs were associated with many of these dysregulated genes either directly or in an indirect manner. This article is protected by copyright. All rights reserved

MicroRNAs: Target Recognition and Regulatory Functions

Abstract: MicroRNAs (miRNAs) are endogenous ∼23 nt RNAs that play important gene-regulatory roles in animals and plants by pairing to the mRNAs of protein-coding genes to direct their posttranscriptional repression. This review outlines the current understanding of miRNA target recognition in animals and discusses the widespread impact of miRNAs on both the expression and evolution of protein-coding genes.

Emerging roles of circRNA_001569 targeting miR-145 in the proliferation and invasion of colorectal cancer.

Abstract: // Huijun Xie 1, 2, 3, * , Xiaoli Ren 1, 2, 3, * , Sainan Xin 1, 2, 3, * , Xiaoliang Lan 4 , Guifeng Lu 1, 2, 3 , Yuan Lin 1, 2, 3 , Shaoshan Yang 1, 2, 3 , Zhicheng Zeng 1, 2, 3 , Wenting Liao 1, 2, 3 , Yan-Qing Ding 1, 2, 3 , Li Liang 1, 2, 3 1 Department of Pathology, Nanfang Hospital, Guangzhou, Guangdong, China 2 Department of Pathology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China 3 Guangdong Province Key Laboratory of Molecular Tumor Pathology, Guangzhou, Guangdong, China 4 Department of General Surgery, Nanfang Hospital, Guangzhou, Guangdong, China * These authors contributed equally to this work Correspondence to: Li Liang, email: redsnow007@hotmail.com Yan-Qing Ding, email: dyq@fimmu.com Keywords: hsa_circ_001569, miR-145, colorectal cancer, FMNL2, BAG4 Received: December 08, 2015 Accepted: March 07, 2016 Published: April 05, 2016 ABSTRACT Circular RNAs (circRNAs), a large class of RNAs, have recently shown huge capabilities as gene regulators in mammals. Some of them bind with microRNAs (miRNAs) and act as natural miRNA sponges to inhibit related miRNAs’ activities. Here we showed that hsa_circ_001569 acted as a positive regulator in cell proliferation and invasion of colorectal cancer (CRC). Moreover, hsa_circ_001569 was identified as a sponge of miR-145 and up-regulated miR-145 functional targets E2F5, BAG4 and FMNL2. In CRC tissues, circ_001569 negatively correlated with miR-145, and miR-145 correlated negatively with E2F5, BAG4 and FMNL2 expressions. Our study reveals a novel regulatory mechanism of circ_001569 in cell proliferation and invasion in CRC, provides a comprehensive landscape of circ_001569 that will facilitate further biomarker discoveries in the progression of CRC.

Tools for Sequence-Based miRNA Target Prediction: What to Choose?

Abstract: MicroRNAs (miRNAs) are defined as small non-coding RNAs ~22 nt in length. They regulate gene expression at a post-transcriptional level through complementary base pairing with the target mRNA, leading to mRNA degradation and therefore blocking translation. In the last decade, the dysfunction of miRNAs has been related to the development and progression of many diseases. Currently, researchers need a method to identify precisely the miRNA targets, prior to applying experimental approaches that allow a better functional characterization of miRNAs in biological processes and can thus predict their effects. Computational prediction tools provide a rapid method to identify putative miRNA targets. However, since a large number of tools for the prediction of miRNA:mRNA interactions have been developed, all with different algorithms, the biological researcher sometimes does not know which is the best choice for his study and many times does not understand the bioinformatic basis of these tools. This review describes the biological fundamentals of these prediction tools, characterizes the main sequence-based algorithms, and offers some insights into their uses by biologists.