mintRULS: Prediction of miRNA-mRNA Target Site Interactions Using Regularized Least Square Method

Identification of miRNA-mRNA interactions is critical to understand the new paradigms in gene regulation. Existing methods show suboptimal performance owing to inappropriate feature selection and limited integration of intuitive biological features of both miRNAs and mRNAs. The present regularized least square-based method, mintRULS, employs features of miRNAs and their target sites using pairwise similarity metrics based on free energy, sequence and repeat identities, and target site accessibility to predict miRNA-target site interactions. We hypothesized that miRNAs sharing similar structural and functional features are more likely to target the same mRNA, and conversely, mRNAs with similar features can be targeted by the same miRNA. Our prediction model achieved an impressive AUC of 0.93 and 0.92 in LOOCV and LmiTOCV settings, respectively. In comparison, other popular tools such as miRDB, TargetScan, MBSTAR, RPmirDIP, and STarMir scored AUCs at 0.73, 0.77, 0.55, 0.84, and 0.67, respectively, in LOOCV setting. Similarly, mintRULS outperformed other methods using metrics such as accuracy, sensitivity, specificity, and MCC. Our method also demonstrated high accuracy when validated against experimentally derived data from condition- and cell-specific studies and expression studies of miRNAs and target genes, both in human and mouse

Ecdysoneless Overexpression Drives Mammary Tumorigenesis through Upregulation of C-MYC and Glucose Metabolism

Ecdysoneless (ECD) protein is essential for embryogenesis, cell-cycle progression, and cellular stress mitigation with an emerging role in mRNA biogenesis. We have previously shown that ECD protein as well as its mRNA are overexpressed in breast cancer and ECD overexpression predicts shorter survival in patients with breast cancer. However, the genetic evidence for an oncogenic role of ECD has not been established. Here, we generated transgenic mice with mammary epithelium-targeted overexpression of an inducible human ECD transgene (ECDTg). Significantly, ECDTg mice develop mammary hyperplasia, preneoplastic lesions, and heterogeneous tumors with occasional lung metastasis. ECDTg tumors exhibit epithelial to mesenchymal transition and cancer stem cell characteristics. Organoid cultures of ECDTg tumors showed ECD dependency for in vitro oncogenic phenotype and in vivo growth when implanted in mice. RNA sequencing (RNA-seq) analysis of ECDTg tumors showed a c-MYC signature, and alterations in ECD levels regulated c-MYC mRNA and protein levels as well as glucose metabolism. ECD knockdown-induced decrease in glucose uptake was rescued by overexpression of mouse ECD as well as c-MYC. Publicly available expression data analyses showed a significant correlation of ECD and c-MYC overexpression in breast cancer, and ECD and c-MYC coexpression exhibits worse survival in patients with breast cancer. Taken together, we establish a novel role of overexpressed ECD as an oncogenesis driver in the mouse mammary gland through upregulation of c-MYC-mediated glucose metabolism. IMPLICATIONS: We demonstrate ECD overexpression in the mammary gland of mice led to the development of a tumor progression model through upregulation of c-MYC signaling and glucose metabolism

Integrative Analysis of Multi-omics Kinome Data and Virtual Screening of Identified Targets with Pan-Cancer Application

Cancer is a heterogeneous disease characterized by the uncontrolled growth and dissemination of abnormal cells. Unfortunately, it is also challenging to treat due to the heterogeneous nature of the tumors and the lack of known drugs that are effective against all tumor subpopulations. The human protein kinases represent an essential and diverse family of enzymes and are often dysregulated in cancer. The human kinome comprises only around 2% of all coding genes of the human genome but phosphorylates about 30% of cellular proteins critical for regulating various biological processes such as cell proliferation, cell cycle progression, apoptosis, motility, growth, differentiation, among others. Dysregulation of kinase activity, such as altered expression and/or amplification, aberrant phosphorylation, mutation, chromosomal translocation, and epigenetic regulation, are frequently oncogenic and can be critical for the survival and spread of cancer cells. In this dissertation, the human kinome’s genomic, epigenomic, and proteomic patterns were analyzed using the TCGA, CCLE, and GTeX databases. Unsupervised clustering based on kinome multi-omics data revealed the grouping of cancers based on their organ and tissue type. We observed significant differences in the overall kinase methylation levels (hyper- and hypomethylation) between the tumor and adjacent normal samples from the same tissue. Methylation expression quantitative trait loci (meQTL) analysis using kinase gene expression with the corresponding methylated probes revealed a highly significant and mostly negative association (~92%) within 1.5 kb from the transcription start site (TSS). Copy number alterations and mutation analysis were performed, focusing on dark kinases. We further leveraged results from multi-omics data to identify potential kinase markers of prognostic and diagnostic importance. Several understudied (dark) kinases (PKMYT1, PNCK, BRSK2, ERN2, STK31, STK32A, and MAPK4) were identified with a significant role in patient survival. Using commercially available molecules, virtual screening was performed for two dark kinase targets (PKMYT1 and PNCK). This study aims at kinase-centered analysis using multiple layers of ‘omics’ data and computational approaches to prioritize candidate kinases that could serve as potential targets from a drug development perspective

Pan-Cancer Analysis of Human Kinome Gene Expression and Promoter DNA Methylation Identifies Dark Kinase Biomarkers in Multiple Cancers

Kinases are a group of intracellular signaling molecules that play critical roles in various biological processes. Even though kinases comprise one of the most well-known therapeutic targets, many have been understudied and therefore warrant further investigation. DNA methylation is one of the key epigenetic regulators that modulate gene expression. In this study, the human kinome’s DNA methylation and gene expression patterns were analyzed using the level-3 TCGA data for 32 cancers. Unsupervised clustering based on kinome data revealed the grouping of cancers based on their organ level and tissue type. We further observed significant differences in overall kinase methylation levels (hyper- and hypomethylation) between the tumor and adjacent normal samples from the same tissue. Methylation expression quantitative trait loci (meQTL) analysis using kinase gene expression with the corresponding methylated probes revealed a highly significant and mostly negative association (~92%) within 1.5 kb from the transcription start site (TSS). Several understudied (dark) kinases (PKMYT1, PNCK, BRSK2, ERN2, STK31, STK32A, and MAPK4) were also identified with a significant role in patient survival. This study leverages results from multi-omics data to identify potential kinase markers of prognostic and diagnostic importance and further our understanding of kinases in cancer

Molecular Subtyping and Survival Analysis of Osteosarcoma Reveals Prognostic Biomarkers and Key Canonical Pathways

Osteosarcoma (OS) is a common bone malignancy in children and adolescents. Although histological subtyping followed by improved OS treatment regimens have helped achieve favorable outcomes, a lack of understanding of the molecular subtypes remains a challenge to characterize its genetic heterogeneity and subsequently to identify diagnostic and prognostic biomarkers for developing effective treatments. In the present study, global analysis of DNA methylation, and mRNA and miRNA gene expression in OS patient samples were correlated with their clinical characteristics. The mucin family of genes, MUC6, MUC12, and MUC4, were found to be highly mutated in the OS patients. Results revealed the enrichment of molecular pathways including Wnt signaling, Calcium signaling, and PI3K-Akt signaling in the OS tumors. Survival analyses showed that the expression levels of several genes such as RAMP1, CRIP1, CORT, CHST13, and DDX60L, miRNAs and lncRNAs were associated with survival of OS patients. Molecular subtyping using Cluster-Of-Clusters Analysis (COCA) for mRNA, lncRNA, and miRNA expression; DNA methylation; and mutation data from the TARGET dataset revealed two distinct molecular subtypes, each with a distinctive gene expression profile. Between the two subtypes, three upregulated genes, POP4, HEY1, CERKL, and seven downregulated genes, CEACAM1, ABLIM1, LTBP2, ISLR, LRRC32, PTPRF, and GPX3, associated with OS metastasis were found to be differentially regulated. Thus, the molecular subtyping results provide a strong basis for classification of OS patients that could be used to develop better prognostic treatment strategies

KSR1- and ERK-dependent translational regulation of the epithelial-to-mesenchymal transition

The epithelial-to-mesenchymal transition (EMT) is considered a transcriptional process that induces a switch in cells from a polarized state to a migratory phenotype. Here, we show that KSR1 and ERK promote EMT-like phenotype through the preferential translation of Epithelial-Stromal Interaction 1 (EPSTI1), which is required to induce the switch from E- to N-cadherin and coordinate migratory and invasive behavior. EPSTI1 is overexpressed in human colorectal cancer (CRC) cells. Disruption of KSR1 or EPSTI1 significantly impairs cell migration and invasion in vitro, and reverses EMT-like phenotype, in part, by decreasing the expression of N-cadherin and the transcriptional repressors of E-cadherin expression, ZEB1 and Slug. In CRC cells lacking KSR1, ectopic EPSTI1 expression restored the E- to N-cadherin switch, migration, invasion, and anchorage-independent growth. KSR1-dependent induction of EMT-like phenotype via selective translation of mRNAs reveals its underappreciated role in remodeling the translational landscape of CRC cells to promote their migratory and invasive behavior