Network Modeling Identifies Molecular Functions Targeted by miR-204 to Suppress Head and Neck Tumor Metastasis

Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA target is currently challenging. Consequently, biological studies have yet to identify, on a genome scale, key regulatory networks perturbed by altered microRNA functions in the context of cancer. In this report, we demonstrate for the first time how phenotypic knowledge of inheritable cancer traits and of risk factor loci can be utilized jointly with gene expression analysis to efficiently prioritize deregulated microRNAs for biological characterization. Using this approach we characterize miR-204 as a tumor suppressor microRNA and uncover previously unknown connections between microRNA regulation, network topology, and expression dynamics. Specifically, we validate 18 gene targets of miR-204 that show elevated mRNA expression and are enriched in biological processes associated with tumor progression in squamous cell carcinoma of the head and neck (HNSCC). We further demonstrate the enrichment of bottleneckness, a key molecular network topology, among miR-204 gene targets. Restoration of miR-204 function in HNSCC cell lines inhibits the expression of its functionally related gene targets, leads to the reduced adhesion, migration and invasion in vitro and attenuates experimental lung metastasis in vivo. As importantly, our investigation also provides experimental evidence linking the function of microRNAs that are located in the cancer-associated genomic regions (CAGRs) to the observed predisposition to human cancers. Specifically, we show miR-204 may serve as a tumor suppressor gene at the 9q21.1–22.3 CAGR locus, a well established risk factor locus in head and neck cancers for which tumor suppressor genes have not been identified. This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases.</p

Network Modeling Identifies Molecular Functions Targeted by miR-204 to Suppress Head and Neck Tumor Metastasis

Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA target is currently challenging. Consequently, biological studies have yet to identify, on a genome scale, key regulatory networks perturbed by altered microRNA functions in the context of cancer. In this report, we demonstrate for the first time how phenotypic knowledge of inheritable cancer traits and of risk factor loci can be utilized jointly with gene expression analysis to efficiently prioritize deregulated microRNAs for biological characterization. Using this approach we characterize miR-204 as a tumor suppressor microRNA and uncover previously unknown connections between microRNA regulation, network topology, and expression dynamics. Specifically, we validate 18 gene targets of miR-204 that show elevated mRNA expression and are enriched in biological processes associated with tumor progression in squamous cell carcinoma of the head and neck (HNSCC). We further demonstrate the enrichment of bottleneckness, a key molecular network topology, among miR-204 gene targets. Restoration of miR-204 function in HNSCC cell lines inhibits the expression of its functionally related gene targets, leads to the reduced adhesion, migration and invasion in vitro and attenuates experimental lung metastasis in vivo. As importantly, our investigation also provides experimental evidence linking the function of microRNAs that are located in the cancer-associated genomic regions (CAGRs) to the observed predisposition to human cancers. Specifically, we show miR-204 may serve as a tumor suppressor gene at the 9q21.1–22.3 CAGR locus, a well established risk factor locus in head and neck cancers for which tumor suppressor genes have not been identified. This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases

The non-coding landscape of head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is an aggressive disease marked by frequent recurrence and metastasis and stagnant survival rates. To enhance molecular knowledge of HNSCC and define a non-coding RNA (ncRNA) landscape of the disease, we profiled the transcriptome-wide dysregulation of long non-coding RNA (lncRNA), microRNA (miRNA), and PIWI-interacting RNA (piRNA) using RNA-sequencing data from 422 HNSCC patients in The Cancer Genome Atlas (TCGA). 307 non-coding transcripts differentially expressed in HNSCC were significantly correlated with patient survival, and associated with mutations in TP53, CDKN2A, CASP8, PRDM9, and FBXW7 and copy number variations in chromosomes 3, 5, 7, and 18. We also observed widespread ncRNA correlation to concurrent TP53 and chromosome 3p loss, a compelling predictor of poor prognosis in HNSCCs. Three selected ncRNAs were additionally associated with tumor stage, HPV status, and other clinical characteristics, and modulation of their expression in vitro reveals differential regulation of genes involved in epithelial-mesenchymal transition and apoptotic response. This comprehensive characterization of the HNSCC non-coding transcriptome introduces new layers of understanding for the disease, and nominates a novel panel of transcripts with potential utility as prognostic markers or therapeutic targets

Computational Analysis of mRNA Expression Profiles Identifies MicroRNA-29a/c as Predictor of Colorectal Cancer Early Recurrence

Colorectal cancer (CRC) is one of the leading malignant cancers with a rapid increase in incidence and mortality. The recurrences of CRC after curative resection are sometimes unavoidable and often take place within the first year after surgery. MicroRNAs may serve as biomarkers to predict early recurrence of CRC, but identifying them from over 1,400 known human microRNAs is challenging and costly. An alternative approach is to analyze existing expression data of messenger RNAs (mRNAs) because generally speaking the expression levels of microRNAs and their target mRNAs are inversely correlated. In this study, we extracted six mRNA expression data of CRC in four studies (GSE12032, GSE17538, GSE4526 and GSE17181) from the gene expression omnibus (GEO). We inferred microRNA expression profiles and performed computational analysis to identify microRNAs associated with CRC recurrence using the IMRE method based on the MicroCosm database that includes 568,071 microRNA-target connections between 711 microRNAs and 20,884 gene targets. Two microRNAs, miR-29a and miR-29c, were disclosed and further meta-analysis of the six mRNA expression datasets showed that these two microRNAs were highly significant based on the Fisher p-value combination (p = 9.14×10−9 for miR-29a and p = 1.14×10−6 for miR-29c). Furthermore, these two microRNAs were experimentally tested in 78 human CRC samples to validate their effect on early recurrence. Our empirical results showed that the two microRNAs were significantly down-regulated (p = 0.007 for miR-29a and p = 0.007 for miR-29c) in the early-recurrence patients. This study shows the feasibility of using mRNA profiles to indicate microRNAs. We also shows miR-29a/c could be potential biomarkers for CRC early recurrence

Integration of breast cancer gene signatures based on graph centrality

<p>Abstract</p> <p>Background</p> <p>Various gene-expression signatures for breast cancer are available for the prediction of clinical outcome. However due to small overlap between different signatures, it is challenging to integrate existing disjoint signatures to provide a unified insight on the association between gene expression and clinical outcome.</p> <p>Results</p> <p>In this paper, we propose a method to integrate different breast cancer gene signatures by using graph centrality in a context-constrained protein interaction network (PIN). The context-constrained PIN for breast cancer is built by integrating complete PIN and various gene signatures reported in literatures. Then, we use graph centralities to quantify the importance of genes to breast cancer. Finally, we get reliable gene signatures that are consisted by the genes with high graph centrality. The genes which are well-known breast cancer genes, such as TP53 and BRCA1, are ranked extremely high in our results. Compared with previous results by functional enrichment analysis, graph centralities, especially the eigenvector centrality and subgraph centrality, based gene signatures are more tightly related to breast cancer. We validate these signatures on genome-wide microarray dataset and found strong association between the expression of these signature genes and pathologic parameters.</p> <p>Conclusions</p> <p>In summary, graph centralities provide a novel way to connect different cancer signatures and to understand the mechanism of relationship between gene expression and clinical outcome of breast cancer. Moreover, this method is not only can be used on breast cancer, but also can be used on other gene expression related diseases and drug studies.</p

Regulation of Cancer Aggressive Features in Melanoma Cells by MicroRNAs

MicroRNAs (miRNAs) are small non-coding RNAs with regulatory roles, which are involved in a broad spectrum of physiological and pathological processes, including cancer. A common strategy for identification of miRNAs involved in cell transformation is to compare malignant cells to normal cells. Here we focus on identification of miRNAs that regulate the aggressive phenotype of melanoma cells. To avoid differences due to genetic background, a comparative high-throughput miRNA profiling was performed on two isogenic human melanoma cell lines that display major differences in their net proliferation, invasion and tube formation activities. This screening revealed two major cohorts of differentially expressed miRNAs. We speculated that miRNAs up-regulated in the more-aggressive cell line contribute oncogenic features, while the down-regulated miRNAs are tumor suppressive. This assumption was further tested experimentally on five candidate tumor suppressive miRNAs (miR-31, -34a, -184, -185 and -204) and on one candidate oncogenic miRNA (miR-17-5p), all of which have never been reported before in cutaneous melanoma. Remarkably, all candidate Suppressive-miRNAs inhibited net proliferation, invasion or tube formation, while miR-17-5p enhanced cell proliferation. miR-34a and miR-185 were further shown to inhibit the growth of melanoma xenografts when implanted in SCID-NOD mice. Finally, all six candidate miRNAs were detected in 15 different metastatic melanoma specimens, attesting for the physiological relevance of our findings. Collectively, these findings may prove instrumental for understanding mechanisms of disease and for development of novel therapeutic and staging technologies for melanoma

The clinical potential of microRNAs

MicroRNAs are small noncoding RNAs that function to control gene expression. These small RNAs have been shown to contribute to the control of cell growth, differentiation and apoptosis, important features related to cancer development and progression. In fact, recent studies have shown the utility of microRNAs as cancer-related biomarkers. This is due to the finding that microRNAs display altered expression profiles in cancers versus normal tissue. In addition, microRNAs have been associated with cancer progression. In this review, the mechanisms to alter microRNA expression and their relation to cancer will be addressed. Moreover, the potential application of microRNAs in clinical settings will also be highlighted. Finally, the challenges regarding the translation of research involving microRNAs to the clinical realm will be discussed

Integrative network analysis reveals active microRNAs and their functions in gastric cancer

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are a class of endogenous, small and highly conserved noncoding RNAs that control gene expression either by degradation of target mRNAs or by inhibition of protein translation. They play important roles in cancer progression. A single miRNA can provoke a chain reaction and further affect protein interaction network (PIN). Therefore, we developed a novel integrative approach to identify the functional roles and the regulated PIN of oncomirs.</p> <p>Results</p> <p>We integrated the expression profiles of miRNA and mRNA with the human PIN to reveal miRNA-regulated PIN in specific biological conditions. The potential functions of miRNAs were determined by functional enrichment analysis and the activities of miRNA-regulated PINs were evaluated by the co-expression of protein-protein interactions (PPIs). The function of a specific miRNA, miR-148a, was further examined by clinical data analysis and cell-based experiments. We uncovered several miRNA-regulated networks which were enriched with functions related to cancer progression. One miRNA, miR-148a, was identified and its function is to decrease tumor proliferation and metastasis through its regulated PIN. Furthermore, we found that miR-148a could reduce the invasiveness, migratory and adhesive activities of gastric tumor cells. Most importantly, elevated miR-148a level in gastric cancer tissues was strongly correlated with distant metastasis, organ and peritoneal invasion and reduced survival rate.</p> <p>Conclusions</p> <p>This study provides a novel method to identify active oncomirs and their potential functions in gastric cancer progression. The present data suggest that miR-148a could be a potential prognostic biomarker of gastric cancer and function as a tumor suppressor through repressing the activity of its regulated PIN.</p

Curation-free biomodules mechanisms in prostate cancer predict recurrent disease

Abstract Motivation Gene expression-based prostate cancer gene signatures of poor prognosis are hampered by lack of gene feature reproducibility and a lack of understandability of their function. Molecular pathway-level mechanisms are intrinsically more stable and more robust than an individual gene. The Functional Analysis of Individual Microarray Expression (FAIME) we developed allows distinctive sample-level pathway measurements with utility for correlation with continuous phenotypes (e.g. survival). Further, we and others have previously demonstrated that pathway-level classifiers can be as accurate as gene-level classifiers using curated genesets that may implicitly comprise ascertainment biases (e.g. KEGG, GO). Here, we hypothesized that transformation of individual prostate cancer patient gene expression to pathway-level mechanisms derived from automated high throughput analyses of genomic datasets may also permit personalized pathway analysis and improve prognosis of recurrent disease. Results Via FAIME, three independent prostate gene expression arrays with both normal and tumor samples were transformed into two distinct types of molecular pathway mechanisms: (i) the curated Gene Ontology (GO) and (ii) dynamic expression activity networks of cancer (Cancer Modules). FAIME-derived mechanisms for tumorigenesis were then identified and compared. Curated GO and computationally generated "Cancer Module" mechanisms overlap significantly and are enriched for known oncogenic deregulations and highlight potential areas of investigation. We further show in two independent datasets that these pathway-level tumorigenesis mechanisms can identify men who are more likely to develop recurrent prostate cancer (log-rank_p = 0.019). Conclusion Curation-free biomodules classification derived from congruent gene expression activation breaks from the paradigm of recapitulating the known curated pathway mechanism universe.http://deepblue.lib.umich.edu/bitstream/2027.42/112452/1/12920_2013_Article_384.pd

The non-coding landscape of head and neck squamous cell carcinoma

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