miRNA Expression Data Research Articles

Higher miR-543 levels correlate with lower STK31 expression and longer pancreatic cancer survival.

Pancreatic cancer (PC) is one of the most malignant gastrointestinal tumors and the 5‐year survival is only 9%. The expression of miRNAs in serum has been proved to be related to tumorigenesis and development of cancers. The miRNA targets and gene targets were predicted in microRNA.org, miRDB, TargetScan, and RNAInter. The expression data of STK31 (Serine/Threonine Kinase 31) and miRNAs generated from PC samples was from TCGA and the relationship of expression of STK31 and miR‐543 was confirmed in PC samples from our center. Double luciferase reporter gene assay was used to demonstrate the direct binding between miR‐543 and STK31. The effect of expression level of miRNAs on survival time was assessed by Kaplan–Meier curves. The Go Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of miR‐543‐related genes were performed. The results showed that miR‐543 had a statistically significant correlation with the expression of STK31 and contained the direct binding site with STK31. The expression level of miR‐543 may affect the survival of PC. The results of GO and KEGG pathway analysis showed that miR‐543 might play a key role in Insulin signaling pathway. MiR‐543 could be combined with STK31 and affect the expression of STK31. The expression of miR‐543 could also predict the survival of patients with PC, which suggested that miR‐543 might play an important role in PC. The GO and KEGG pathway analysis also displayed that miR‐543 was involved in several other pathways of pancreas.

IODA: An integrated tool for analysis of cancer pathway consistency from heterogeneous multi-omics data

The latest advances in the next generation sequencing technology have greatly facilitated the extensive research of genomics and transcriptomics, thereby promoting the decoding of carcinogenesis with unprecedented resolution. Considering the contribution of analyzing high-throughput multi-omics data to the exploration of cancer molecular mechanisms, an integrated tool for heterogeneous multi-omics data analysis (iODA) is proposed for the systems-level interpretation of multi-omics data, i.e., transcriptomic profiles (mRNA or miRNA expression data) and protein-DNA interactions (ChIP-Seq data). Considering the data heterogeneity, iODA can compare six statistical algorithms in differential analysis for the selected sample data and assist users in choosing the globally optimal one for dysfunctional mRNA or miRNA identification. Since molecular signatures are more consistent at the pathway level than at the gene level, the tool is able to enrich the identified dysfunctional molecules onto the KEGG pathways and extracted the consistent items as key components for further pathogenesis investigation. Compared with other tools, iODA is multi-functional for the systematic analysis of different level of omics data, and its analytical power was demonstrated through case studies of single and cross-level prostate cancer omics data. iODA is open source under GNU GPL and can be downloaded from http://www.sysbio.org.cn/iODA.

ASDmiR: A Stepwise Method to Uncover miRNA Regulation Related to Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a class of neurodevelopmental disorders characterized by genetic and environmental risk factors. The pathogenesis of ASD has a strong genetic basis, consisting of rare de novo or inherited variants among a variety of multiple molecules. Previous studies have shown that microRNAs (miRNAs) are involved in neurogenesis and brain development and are closely associated with the pathogenesis of ASD. However, the regulatory mechanisms of miRNAs in ASD are largely unclear. In this work, we present a stepwise method, ASDmiR, for the identification of underlying pathogenic genes, networks, and modules associated with ASD. First, we conduct a comparison study on 12 miRNA target prediction methods by using the matched miRNA, lncRNA, and mRNA expression data in ASD. In terms of the number of experimentally confirmed miRNA–target interactions predicted by each method, we choose the best method for identifying miRNA–target regulatory network. Based on the miRNA–target interaction network identified by the best method, we further infer miRNA–target regulatory bicliques or modules. In addition, by integrating high-confidence miRNA–target interactions and gene expression data, we identify three types of networks, including lncRNA–lncRNA, lncRNA–mRNA, and mRNA–mRNA related miRNA sponge interaction networks. To reveal the community of miRNA sponges, we further infer miRNA sponge modules from the identified miRNA sponge interaction network. Functional analysis results show that the identified hub genes, as well as miRNA-associated networks and modules, are closely linked with ASD. ASDmiR is freely available at https://github.com/chenchenxiong/ASDmiR.

Integrated analysis identifies low microRNA-215 expression as associated with a poor prognosis of patients with colorectal cancer through the IKβ-α signaling pathway.

BackgroundmiRNA expression data on colorectal cancer (CRC) are constantly updated. Therefore, integrated analysis of these datasets prior to experiments is necessary in translational medicine and oncology research. Abnormal low expression of hsa-miRNA-215-5p (miR-215) is detected in several cancer types, but the role of miR-215 in CRC remains unclear. Therefore, the aim of this work was to identify the expression and role of miR-215 involved in CRC.MethodsAn integrated analysis of 4 sets of miRNA microarray data of CRC in GEO was implemented. The low expression of miR-215 in CRC was confirmed by TCGA datasets. In addition, frozen tissue and paired formalin-fixed paraffin-embedded samples were collected from 214 CRC patients who underwent CRC surgery at the Affiliated Hospital of Jiangnan University, China, and used as an independent clinical validation study. Furthermore, colon cancer cells HCT116 and SW480 transfected with miR-215 mimic/inhibitor were used to evaluate its mechanism of action and to perform experiments to confirm our results obtained from human samples.ResultsCRC patients with a decreased miR-215 expression in adenocarcinoma tissues had a significantly poor prognosis with lower cumulative survival as revealed by the TCGA-COAD dataset. In our 214 CRC patients cohort study this result was confirmed and it was also found that low miR-215 expression was inversely correlated with the expression of IKβ-α. Downregulation of miR-215 in HCT116 and SW480 cells resulted in an upregulation of TRAF5 and TAK1 protein expression, and interfered with IKβ-α protein expression. Furthermore, with the inhibition of miR-215, important Epithelial-Mesenchymal Transition (EMT) biomarker proteins were significantly upregulated in HCT116 and SW480 cells. Moreover, an inhibition was obtained using miR-215-mimic.ConclusionsOur integrated microRNA dataset approach identified miR-215 as an independent factor associated with the prognosis of CRC patients. In addition, our results demonstrated that miR-215 might be considered as a potential biomarker for poor prognosis in CRC patients and its role as a potent suppressor of IKβ-α and TRAF5.

Integration of postmortem amygdala expression profiling, GWAS, and functional cell culture assays: neuroticism-associated synaptic vesicle glycoprotein 2A (SV2A) gene is regulated by miR-133a and miR-218

Recent genome-wide studies have begun to identify gene variants, expression profiles, and regulators associated with neuroticism, anxiety disorders, and depression. We conducted a set of experimental cell culture studies of gene regulation by micro RNAs (miRNAs), based on genome-wide transcriptome, proteome, and miRNA expression data from twenty postmortem samples of lateral amygdala from donors with known neuroticism scores. Using Ingenuity Pathway Analysis and TargetScan, we identified a list of mRNA–protein–miRNA sets whose expression patterns were consistent with miRNA-based translational repression, as a function of trait anxiety. Here, we focused on one gene from that list, which is of particular translational significance in Psychiatry: synaptic vesicle glycoprotein 2A (SV2A) is the binding site of the anticonvulsant drug levetiracetam ((S)-α-Ethyl-2-oxo-1-pyrrolidineacetamide), which has shown promise in anxiety disorder treatments. We confirmed that SV2A is associated with neuroticism or anxiety using an original GWAS of a community cohort (N = 1,706), and cross-referencing a published GWAS of multiple cohorts (Ns ranging from 340,569 to 390,278). Postmortem amygdala expression profiling implicated three putative regulatory miRNAs to target SV2A: miR-133a, miR-138, and miR-218. Moving from association to experimental causal testing in cell culture, we used a luciferase assay to demonstrate that miR-133a and miR-218, but not miR-138, significantly decreased relative luciferase activity from the SV2A dual-luciferase construct. In human neuroblastoma cells, transfection with miR-133a and miR-218 reduced both endogenous SV2A mRNA and protein levels, confirming miRNA targeting of the SV2A gene. This study illustrates the utility of combining postmortem gene expression data with GWAS to guide experimental cell culture assays examining gene regulatory mechanisms that may contribute to complex human traits. Identifying specific molecular mechanisms of gene regulation may be useful for future clinical applications in anxiety disorders or other forms of psychopathology.

Potential pathophysiological role of microRNA 193b-5p in human placentae from pregnancies complicated by preeclampsia and intrauterine growth restriction.

Preeclampsia (PE) and intrauterine growth restriction (IUGR) are pregnancy complications resulting from abnormal placental development. MicroRNAs can regulate placental development and contribute to disease, by influencing gene expression. Our previous study revealed an increase in miR-193b-5p expression in placentae from patients with early-onset pregnancy complications and identified candidate gene targets for miR-193b-5p. The purpose of this study is two-fold, first to validate candidate gene targets predicted for miR-193b-5p from microRNA-RNA expression data. Second, to overexpress miR-193b-5p in a trophoblast cell line (HTR-8/SVneo) to assess impact on trophoblast cell proliferation and migration. Integration of the miRNA and RNA sequencing expression data revealed 10 candidate gene targets for miR-193b-5p across all patient groups (PE only, IUGR only, PE + IUGR). Luciferase experiments identified two gene targets for miR-193b-5p, APLN and FGF13. Real-time PCR confirmed a median 45% decrease of FGF13 expression across 3 patient groups, and 50% decrease of APLN expression in patients with PE + IUGR. Following transfection of HTR-8/SVneo cells with miR-193b-5p mimics, APLN and FGF13 mRNA expression in HTR-8/SVneo was reduced by a median percentage of 30% and 45%, respectively. Concomitantly, HTR-8/SVneo cells demonstrate 40% reduction in cell migration. APLN and FGF13 immunoreactivity was identified strongly in the cytotrophoblast cells of the human placentae. These findings suggest that miR-193b-5p may contribute to trophoblast dysfunction observed in pregnancy complications such as PE and IUGR.

Integrative Proteomic and MicroRNA Analysis: Insights Into Mechanisms of Eyestalk Ablation-Induced Ovarian Maturation in the Swimming Crab Portunus trituberculatus.

Eyestalk ablation is the most common method to induce ovarian maturation in decapod crustacean aquaculture, but it jeopardizes broodstock survival and larvae production. It is important to understand the molecular basis underlying the maturation triggered by ablation and thereby develop an alternative measure for maturation manipulation. In this study, we investigate alterations of ovarian proteome and miRNA profile after ablation in a commercially important marine crab Portunus trituberculatus. Quantitative proteomic analysis using iTRAQ reveals that 163 proteins are differentially expressed following ablation, and modulation of methyl farnesoate metabolism and activation of calcium signaling may play important roles in the ovarian maturation induced by ablation. miRNA expression profiling identifies 31 miRNAs that show statistically significant changes. Integration of miRNA and proteome expression data with miRNA target prediction algorithms generates a potential regulatory network consisting of 26 miRNAs and 30 proteins linked by 71 possible functional associations. The miRNA-protein network analysis suggests that miRNAs are involved in promoting ovarian maturation by controlling expression of proteins related to methyl farnesoate synthesis, calcium signals, and energy metabolism. Experimental validation and temporal expression analysis indicate multiple miRNAs can act synergistically to regulate expression of Farnesoic acid O-methyltransferase and Calmodulin. Our findings provide new insights for elucidating the mechanisms underlying eyestalk ablation-induced ovarian maturation and could be useful for devising an alternative technique for manipulating reproduction in P. trituberculatus and other decapods.

Abstract 35: Construction of ce-RNA networks and comprehensive analysis with tumor infiltrating immune cells in hepatocellular carcinoma

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with a high recurrence rate. Although immune-checkpoint treatment provides survival benefits for patients with HCC, the mortality of HCC is still high. Therefore, it is necessary to understand the molecular mechanism, immune microenvironment and related prognostic factors of HCC. Methods: HCC patients with both RNAseq and miRNA expression data and their clinical information were downloaded from the NCI's Genomic Data Commons. Gene expression data were analyzed to identify differentially expressed genes (DEGs). The results were further used to construct the competing endogenous RNA (ceRNA) networks related to HCC. Meanwhile, the proportions of 22 immune cell types in HCC were estimated by using CIBERSORT (https://cibersort.stanford.edu). Subsequently, two nomograms based on the expression value of ceRNAs and the percentage of immune cells were constructed to predict the prognosis of HCC patients, respectively. The calibration and time series ROC curves were used to evaluate these models. Finally, the correlation between ceRNAs and immune cells were explored to reveal the underlying molecular mechanism. Results: Gene expression data and clinical information of 367 primary HCC and 50 adjacent normal samples were downloaded from the TCGA database. These data were used to identify DEGs. A total of 12 lncRNAs, 71 mRNAs and 39 miRNAs were identified to be in ceRNA networks according to starBase v2.0 database. The results showed that stages of cancer, the expression values of CBX2, MAFG, DNM3, BUB1, ARL5B and other 23 genes were important predictors. The AUCs of the constructed nomogram in predicting the 3- and 5-year OS were 0.79 and 0.81 respectively. Stages of cancer, proportions of resting memory CD4+ T cell, M0 macrophages and resting mast cells constructed another nomogram with AUC of 0.79 and 0.81 in predicting the 3- and 5-year OS. CIBERSORT results showed that the proportions of regulatory T cells, CD8+ T cells, follicular helper T cells and M0 macrophages were slightly higher while the proportions of M2 macrophages, monocytes and activated mast cells were slightly lower in HCC than in adjacent normal samples. Integration analysis of CIBERSORT results, ceRNAs and gene set enrichment analysis of immunologic signatures identified BUB1, E2F8, H2AFZ, JPT1, LPCAT1, MAFG and PSMC3IP to be positively related with regulatory T cells, follicular helper T cells, activated memory CD4+ T cells and M0 macrophages. This is consistent with current knowledge that immune activity is suppressed in certain types of cancers. However, the underlying mechanism warrant further exploration. Conclusions: In this study, two nomograms were constructed to predict the prognosis of HCC patients, which might be useful in predicting the prognosis of HCC patients. The results suggest that the immune suppress effect of HCC may be related to BUB1, E2F8, H2AFZ, JPT1, LPCAT1, MAFG and PSMC3IP genes. These genes may serve as potential therapeutic targets. Acknowledgments: This work was supported by the National Science and Technology Major Project of China (2018ZX10302205). Citation Format: Jianxiang Shi, Chi Cui, Yaru Duan, Hua Ye, Peng Wang, Jitian Li, Shuiling Jin, Liping Dai, Jianying Zhang. Construction of ce-RNA networks and comprehensive analysis with tumor infiltrating immune cells in hepatocellular carcinoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 35.

MiR-125 family regulates XIRP1 and FIH in response to myocardial infarction.

MicroRNAs (miRNAs) are powerful regulators of protein expression. Many play important roles in cardiac development and disease. While several miRNAs and targets have been well characterized, the abundance of miRNAs and the numerous potential targets for each suggest that the vast majority of these interactions have yet to be described. The goal of this study was to characterize miRNA expression in the mouse heart after coronary artery ligation (LIG) and identify novel mRNA targets altered during the initial response to ischemic stress. We performed small RNA sequencing (RNA-Seq) of ischemic heart tissue 1 day and 3 days after ligation and identified 182 differentially expressed miRNAs. We then selected relevant mRNA targets from all potential targets by correlating miRNA and mRNA expression from a corresponding RNA-Seq data set. From this analysis we chose to focus, as proof of principle, on two miRNAs from the miR-125 family, miR-125a and miR-351, and two of their potential mRNA targets, Xin actin-binding repeat-containing protein 1 (XIRP1) and factor inhibiting hypoxia-inducible factor (FIH). We found miR-125a to be less abundant and XIRP1 more abundant after ligation. In contrast, the related murine miRNA miR-351 was substantially upregulated in response to ischemic injury, and FIH expression correspondingly decreased. Luciferase reporter assays confirmed direct interactions between these miRNAs and targets. In summary, we utilized a correlative analysis strategy combining miRNA and mRNA expression data to identify functional miRNA-mRNA relationships in the heart after ligation. These findings provide insight into the response to ischemic injury and suggest future therapeutic targets.

A novel serum miRNA-pair classifier for diagnosis of sarcoma.

Soft tissue sarcomas (STS) is a set of rare malignant tumor originated from mesoderm. For the prognosis of sarcoma, early diagnosis is important, however, currently no mature and non-invasive method for diagnosis exists. MicroRNAs (miRNAs) are a class of noncoding RNAs and their expression varies greatly, especially during tumor activity. The purpose of this study was to construct a predictive model for the diagnosis of sarcomas based on the relative expression level of miRNA in serum. miRNA array expression data of 677 samples including 402 malignant sarcoma samples and 275 healthy samples was used to construct the prediction model. Based on 6 gene pairs, random generalized linear model (RGLM) was constructed, with an accuracy of 100% in the internal test dataset and of 74.3% in the merged external dataset in prediction whether a serum sample was obtained from a sarcoma patient, with a specificity of 100% in the internal test dataset and 90.5% in the external dataset. In conclusion, our serum miRNA-pair classifier has the potential to be used for the screening of sarcoma with high accuracy and specificity.

Integrative Network Fusion: A Multi-Omics Approach in Molecular Profiling.

Recent technological advances and international efforts, such as The Cancer Genome Atlas (TCGA), have made available several pan-cancer datasets encompassing multiple omics layers with detailed clinical information in large collection of samples. The need has thus arisen for the development of computational methods aimed at improving cancer subtyping and biomarker identification from multi-modal data. Here we apply the Integrative Network Fusion (INF) pipeline, which combines multiple omics layers exploiting Similarity Network Fusion (SNF) within a machine learning predictive framework. INF includes a feature ranking scheme (rSNF) on SNF-integrated features, used by a classifier over juxtaposed multi-omics features (juXT). In particular, we show instances of INF implementing Random Forest (RF) and linear Support Vector Machine (LSVM) as the classifier, and two baseline RF and LSVM models are also trained on juXT. A compact RF model, called rSNFi, trained on the intersection of top-ranked biomarkers from the two approaches juXT and rSNF is finally derived. All the classifiers are run in a 10x5-fold cross-validation schema to warrant reproducibility, following the guidelines for an unbiased Data Analysis Plan by the US FDA-led initiatives MAQC/SEQC. INF is demonstrated on four classification tasks on three multi-modal TCGA oncogenomics datasets. Gene expression, protein expression and copy number variants are used to predict estrogen receptor status (BRCA-ER, N = 381) and breast invasive carcinoma subtypes (BRCA-subtypes, N = 305), while gene expression, miRNA expression and methylation data is used as predictor layers for acute myeloid leukemia and renal clear cell carcinoma survival (AML-OS, N = 157; KIRC-OS, N = 181). In test, INF achieved similar Matthews Correlation Coefficient (MCC) values and 97% to 83% smaller feature sizes (FS), compared with juXT for BRCA-ER (MCC: 0.83 vs. 0.80; FS: 56 vs. 1801) and BRCA-subtypes (0.84 vs. 0.80; 302 vs. 1801), improving KIRC-OS performance (0.38 vs. 0.31; 111 vs. 2319). INF predictions are generally more accurate in test than one-dimensional omics models, with smaller signatures too, where transcriptomics consistently play the leading role. Overall, the INF framework effectively integrates multiple data levels in oncogenomics classification tasks, improving over the performance of single layers alone and naive juxtaposition, and provides compact signature sizes1.

In silico identification of therapeutic compounds against microRNA targets in drug-resistant pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a major health issue that has been eluding efforts to identify viable therapeutic treatment options. Besides having the lowest survival rate among all types of cancer, almost all conventional methods of treatment are futile against this condition, leaving patients to succumb to this ailment faster than ever. As it is increasingly becoming difficult to come up with new compounds for the treatment of various diseases, alternative solutions are required for tackling these problems. In this study, publically available miRNA and gene expression data were used to identify common elements that were present in gemcitabine-resistant PDAC cell lines. By selecting overexpressed genes involved in pancreatic cancer and cancer pathways in general, potential drug candidates for the treatment of PDAC were identified. In this study, 21 differentially expressed miRNAs were identified from PANC-1 cell line treated with gemcitabine. Pathway analysis revealed that MET and PPARG were overexpressed in cancer-related pathways, including pancreatic cancer, and could be targeted for PDAC treatment. Using CMap, fisetin was identified a likely candidate drug for the treatment of PDAC. Docking studies indicated that fisetin was bound to c-Met and PPARG with an XP G score of –12.819 and –7.021 kcal/mol, respectively. As miRNAs have increasingly been shown to part take in important cancer-related processes and pathways, researching drug development methods based on miRNA targets could be beneficial for pharmaceutical industries. Communicated by Ramaswamy H. Sarma

The roles of miRNAs' clinical efficiencies in the colorectal cancer pathobiology: A review article.

MiRNAs (microRNAs) are defined as micro directors and regulators of gene expression. Since altered miRNA expression is signified in the pathobiology of diverse cancers such as colorectal cancers (CRCs), these molecules are described as therapeutic targets, either. Manipulation of miRNAs could lead to further therapy for chemo and radio-resistant CRCs. The usage of microRNAs has indicated prominent promise in the prognosis and diagnosis of CRC, because of their unique expression pattern associated with cancer types and malignancies. Nowadays, many researchers are analyzing the correlation between miRNA polymorphisms and cancer risk. With continuous incompatibility in colorectal cancer (CRC) miRNAs expression data, it is critical to move toward the content of a "pre-laboratory" analysis to speed up efficient accuracy medicine and translational study. Pathway study for the highest expressed miRNAs- regulated target genes resulted in the identification of a considerable number of genes associated with CRC pathway including PI3K, TGFβ, and APC. In this review, we aimed to collect fruitful information about miRNAs and their potential roles in CRC, and provide a meta-analysis of the most frequently studied miRNAs in association with the disease.

Expression of let-7i and miR-192 is associated with resistance to cisplatin-based chemoradiotherapy in patients with larynx and hypopharynx cancer.

The majority of patients with locally advanced larynx or hypopharynx squamous cell carcinoma are treated with organ-preserving chemoradiotherapy (CRT). Clinical outcome following CRT varies greatly. We hypothesized that tumor microRNA (miRNA) expression is predictive for outcome following CRT. Next-generation sequencing (NGS) miRNA profiling was performed on 37 formalin-fixed paraffin-embedded (FFPE) tumor samples. Patients with a recurrence-free survival (RFS) of less than 2years and patients with late/no recurrence within 2years were compared by differential expression analysis. Tumor-specific miRNAs were selected based on normal mucosa miRNA expression data from The Cancer Genome Atlas database. A model was constructed to predict outcome using group-regularized penalized logistic ridge regression. Candidate miRNAs were validated by RT-qPCR in the initial sample set as well as in 46 additional samples. Thirteen miRNAs were differentially expressed (p<0.05, FDR<0.1) according to outcome group. Initial class prediction in the NGS cohort (n=37) resulted in a model combining five miRNAs and disease stage, able to predict CRT outcome with an area under the curve (AUC) of 0.82. In the RT-qPCR cohort (n=83), 25 patients (30%) experienced early recurrence (median RFS 8months; median follow-up 42months). Class prediction resulted in a model combining let-7i-5p, miR-192-5p and disease stage, able to discriminate patients with good versus poor clinical outcome (AUC:0.80). The combined miRNA expression and disease stage prediction model for CRT outcome is superior to using either factor alone. This study indicates NGS miRNA profiling using FFPE specimens is feasible, resulting in clinically relevant biomarkers.

563-P: Differentially Expressed Plasma miRNAs Are Closely Associated with the Presence of Microvascular Complications in Type 2 Diabetes: The 1000 Qatar-Omics Study Cohort

Background: In the light of growing global epidemic of T2D and related microvascular complications, it is important to find early detection marker for the disease. Circulating miRNAs serve as a potential biomarker for monitering the progression to DR in diabetic individuals. Hypothesis and Aims: miRNAs play a substantial role in metabolic homeostasis through regulation of multiple genes, and could serve as a prognostic biomarker in DR. This study aims to assess a functional role of selected miRNAs in the Qatari population recruited for the Qatar Genome Project through Qatar BioBank. Methods: Plasma samples from 470 T2D subjects with and without DR and 500 matched-healthy controls has been included in this study. Total RNA was extracted and the expression profiling of 56 miRNA that previously reported as a player in the pathogenesis of DR was performed using custom open array panel. The miRNA expression data were normalized using ath-mir159a. Statistical analysis was performed to study the association between the phenotypes (HbA1c, C-peptide, age, BMI) and miRNA. Results: The patients and controls phenotypic and miRNA expression data were analyzed to interepret the differential expression of the miRNA in DR subjects. Initial analysis by applying the generalized additive model reveals that six miRNA (hsa-miR-27a, hsa-miR-376c, hsa-miR-92a, hsa-miR-1 hsa-miR-223, and mmu-miR-451) were found to be significantly associated with DR (p&amp;gt;0.05). Furthermore, two differentially expressed miRNAs, (hsa-miR-1274A and hsa-miR-24) found to be associated with higher level of C-peptide in DR patients, which suggest the correlation of these miRNAs with the glucose hemostasis and DR. Conclusion: The etiology of DR is unclear, and present treatments have limited effectiveness. The biomarkers and downstream functional studies are required to deepen the understanding of this chronic diseases and its complications. Disclosure A.S. Akil: None. S. Subash Padmajeya: None. L.A. Jerman: None. A. Al-Kurbi: None. A.M. Hussein: None. A. Hardikar: None. M. Joglekar: None. T. Habib: None. M. El Anbari: None. K. Fakhro: None.

Abstract A112: Integrative epigenomic and transcriptomic analyses of kidney cancers from African Americans and European Americans

Abstract Background: Kidney cancer ranks as a top ten leading site of new cancer cases (~64,000) in the United States each year. Renal cell carcinoma (RCC) is the most common type of kidney cancer (90% cases), with clear cell RCC (ccRCC) being the most prevalent histology (70% RCC cases). RCC risk factors include nonmodifiable, modifiable, environmental, and occupational causes. RCC subtypes each have a different histology, clinical course, and response to therapy, in addition to distinctive genetic and molecular alterations. African Americans (AA) have higher incidence rates of ccRCC than European Americans (EA) for reasons that are unclear. Biologic determinants of this cancer health disparity have been largely understudied. Recent work has identified population-specific genomic drivers in ccRCC tumors from AA compared with EA. To date, no study has explored epigenomic or transcriptomic determinants of kidney cancer health disparities in AA. Hypothesis: We hypothesized population-specific changes in DNA methylation, between AA and EA, drive differences in ccRCC biology through regulation of the transcriptome. Methods: Comparative integrative genomic and transcriptomic analyses were performed using clinical demographic and ccRCC data (Illumina 450K methylation array and mRNA-seq) from TCGA (n=50 AA, 266 EA) and Partek Genomics Suite. Results: Differential methylation analysis discovered 2,048 genes varied significantly by race (P value + FDR = ≤0.01). Gene Ontology Enrichment Score (ES) analysis revealed these genes were involved with various molecular functions (nucleic acid binding ES 38.52, protein binding ES 38.03), biologic processes (cellular metabolic process ES 78.60), and cellular component localization (intracellular organelles ES 87.24). Differential gene expression analysis revealed 3,296 genes were altered in AA compared with EA race (P value + FDR = ≤0.01). GSEA analysis revealed distinct biologic pathways were enriched. Conclusion and Future Directions: Collectively, our data suggest that DNA methylation and mRNA expression drive differences in tumor biology amongst AA and EA kidney cancer patients. Future studies include integrating miRNA expression data, validating these findings in a separate cohort, profiling other RCC histologies for population-specific signatures, and using kidney cancer cell lines from AA and EA to explore novel biologic mechanisms for therapeutic purposes. Citation Format: Heinric Williams, Khadijah A. Mitchell. Integrative epigenomic and transcriptomic analyses of kidney cancers from African Americans and European Americans [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr A112.

MiRNA-mRNA Profiling Reveals Prognostic Impact of SMC1A Expression in Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) with NPM1 mutation is a disease driving genetic alteration with good prognosis. Although it has been suggested that NPM1 mutation induces chemosensitivity in leukemic cells, the underlying cause for the better survival of NPM1 mutated patients is still not clear. Mutant NPM1 AML has a unique microRNA and their target gene (mRNA) signature compared to wild-type NPM1. Dynamic regulation of miRNA–mRNA has been reported to influence the prognostic outcome. In the present study, in silico expression data of miRNA and mRNA in AML patients was retrieved from genome data commons, and differentially expressed miRNA and mRNA among NPM1 mutated (n = 21) and NPM1 wild-type (n = 162) cases were identified to establish a dynamic association at the molecular level. In vitro experiments using high-throughput RNA sequencing were performed on human AML cells carrying NPM1 mutated and wild-type allele. The comparison of in vitro transcriptomics data with in silico miRNA–mRNA expression network data revealed downregulation of SMC1A. On establishing miRNA–mRNA interactive pairs, it has been observed that hsa-mir-215-5p (logFC: 0.957; p = 0.0189) is involved in the downregulation of SMC1A (logFC: –0.481; p = 0.0464) in NPM1 mutated AML. We demonstrated that transient expression of NPM1 mutation upregulates miR-215-5p, which results in downregulation of SMC1A. We have also shown using a rescue experiment that neutralizing miR-215-5p reverses the effect of NPM1 mutation on SMC1A. Using the leukemic blasts from AML patients, we observed higher expression of miR-215-5p and lower expression of SMC1A in NPM1 mutated patients compared to wild-type cases. The overall survival of AML patients was significantly inferior in SMC1A high expressers compared to low expressers (20.3% vs. 58.5%, p = 0.018). The data suggest that dynamic miR-215-SMC1A regulation is potentially modulated by NPM1 mutation, which might serve as an explanation for the better outcome in NPM1 mutated AML.

Genetic regulators of mineral amount in Nelore cattle muscle predicted by a new co-expression and regulatory impact factor approach

Mineral contents in bovine muscle can affect meat quality, growth, health, and reproductive traits. To better understand the genetic basis of this phenotype in Nelore (Bos indicus) cattle, we analysed genome-wide mRNA and miRNA expression data from 114 muscle samples. The analysis implemented a new application for two complementary algorithms: the partial correlation and information theory (PCIT) and the regulatory impact factor (RIF), in which we included the estimated genomic breeding values (GEBVs) for the phenotypes additionally to the expression levels, originally proposed for these methods. We used PCIT to determine putative regulatory relationships based on significant associations between gene expression and GEBVs for each mineral amount. Then, RIF was adopted to determine the regulatory impact of genes and miRNAs expression over the GEBVs for the mineral amounts. We also investigated over-represented pathways, as well as pieces of evidences from previous studies carried in the same population and in the literature, to determine regulatory genes for the mineral amounts. For example, NOX1 expression level was positively correlated to Zinc and has been described as Zinc-regulated in humans. Based on our approach, we were able to identify genes, miRNAs and pathways not yet described as underlying mineral amount. The results support the hypothesis that extracellular matrix interactions are the core regulator of mineral amount in muscle cells. Putative regulators described here add information to this hypothesis, expanding the knowledge on molecular relationships between gene expression and minerals.

Changes in microRNA expression associated with metastasis and survival in patients with uveal melanoma.

Uveal melanoma (UM) is a major intraocular cancer that is molecularly distinct from cutaneous melanoma. Approximately half of patients with UM eventually develop metastasis. The prognosis of metastatic UM is poor, with a median overall survival (OS) of less than a year. In this study, we sought to identify microRNAs (miRNAs) associated with metastasis and OS in UM. We analyzed the miRNA expression and clinical outcomes data from The Cancer Genome Atlas (TCGA) dataset for UM. Differential expression analyses were conducted for each miRNA with respect ever-development of metastasis. Multiple survival analyses were done, using the Cox proportional hazards model, to evaluate interactions between miRNA expression, metastasis, and OS. A total of 22 miRNAs (3 upregulated and 19 downregulated) were differentially expressed between patients with vs. without metastatic UM. These 22 miRNAs could be grouped into four clusters based on similarities in expression patterns. Of the 22 miRNAs differentially expressed with respect to metastasis, 21 were significantly associated with OS. The expression of multiple miRNAs was significantly associated with metastasis and overall survival in patients with UM. Further investigation of these miRNAs as biomarkers and/or therapeutic targets is warranted in the push to improve outcomes for patients with metastatic UM.

Defining the Prognostic Role of MicroRNAs in Cutaneous Melanoma

Breslow thickness (BT) is the most important histopathologic factor for primary melanoma staging. BT determines the margins for wide local excision whether sentinel lymph node biopsy should be performed and subsequent melanoma staging, and patient management. The correct determination of a 0.8-mm cutoff in melanoma is important for pathologists because discrepancies leading to a change in stage can have significant clinical implications, including incorrect and/or inappropriate prognostic information, investigation, management, and follow-up. Difficulties in BT determination are mostly represented by the presence of regression or melanoma associated with a pre-existing nevus. This study aimed at investigating a molecular parameter, namely microRNA (miRNA) expression, in reference to BT assessment. Melanoma cell proliferation is influenced by miRNA dysregulation. Indeed, some miRNAs sustain and induce proliferative signals or repress growth-suppressive pathways, thereby promoting melanoma carcinogenesis. To identify the miRNAs correlating with BT, we analyzed our global miRNA expression data of 20 thin melanomas and identified two potential candidates, miR-21-5p and miR-146a-5p. We assessed the expression of these two specific miRNAs in 90 archive formalin-fixed and paraffin-embedded samples of superficially spreading melanomas (SSMs) and 25 nodular melanomas from two independent cohorts and correlated the individual and combined miRNA expression with BT and other tumor characteristics. The individually normalized expression of miR-21-5p and miR-146a-5p showed a highly significant and linear correlation with BT in SSM, and their combined expression value was more strongly correlated (Pearson's r= 0.799, 95% CI= 0.71-0.86) than their individual expressions. This correlation was not significant in nodular melanoma. In SSM, we observed that the combined miRNA expression above or below 1.5 was significantly associated with overall survival and successfully identified all patients with relapsing SSM. We concluded that the combined assessment of miR-21-5p and miR-146a-5p expression in superficially spreading melanoma, in association with BT measurement, could aid pathologists in SSM staging.