Ramkrishna Mitra

TSGene 2.0: an updated literature-based knowledgebase for tumor suppressor genes

Tumor suppressor genes (TSGs) are a major type of gatekeeper genes in the cell growth. A knowledgebase with the systematic collection and curation of TSGs in multiple cancer types is critically important for further studying their biological functions as well as for developing therapeutic strategies. Since its development in 2012, the Tumor Suppressor Gene database (TSGene), has become a popular resource in the cancer research community. Here, we reported the TSGene version 2.0, which has substantial updates of contents (e.g. up-to-date literature and pan-cancer genomic data collection and curation), data types (noncoding RNAs and protein-coding genes) and content accessibility. Specifically, the current TSGene 2.0 contains 1217 human TSGs (1018 protein-coding and 199 non-coding genes) curated from over 9000 articles. Additionally, TSGene 2.0 provides thousands of expression and mutation patterns derived from pan-cancer data of The Cancer Genome Atlas. A new web interface is available at http://bioinfo.mc.vanderbilt.edu/TSGene/. Systematic analyses of 199 non-coding TSGs provide numerous cancer-specific non-coding mutational events for further screening and clinical use. Intriguingly, we identified 49 protein-coding TSGs that were consistently down-regulated in 11 cancer types. In summary, TSGene 2.0, which is the only available database for TSGs, provides the most updated TSGs and their features in pan-cancer.

Decoding critical long non-coding RNA in ovarian cancer epithelial-to-mesenchymal transition.

Long non-coding RNA (lncRNA) are emerging as contributors to malignancies. Little is understood about the contribution of lncRNA to epithelial-to-mesenchymal transition (EMT), which correlates with metastasis. Ovarian cancer is usually diagnosed after metastasis. Here we report an integrated analysis of >700 ovarian cancer molecular profiles, including genomic data sets, from four patient cohorts identifying lncRNA DNM3OS, MEG3, and MIAT overexpression and their reproducible gene regulation in ovarian cancer EMT. Genome-wide mapping shows 73% of MEG3-regulated EMT-linked pathway genes contain MEG3 binding sites. DNM3OS overexpression, but not MEG3 or MIAT, significantly correlates to worse overall patient survival. DNM3OS knockdown results in altered EMT-linked genes/pathways, mesenchymal-to-epithelial transition, and reduced cell migration and invasion. Proteotranscriptomic characterization further supports the DNM3OS and ovarian cancer EMT connection. TWIST1 overexpression and DNM3OS amplification provides an explanation for increased DNM3OS levels. Therefore, our results elucidate lncRNA that regulate EMT and demonstrate DNM3OS specifically contributes to EMT in ovarian cancer.The role of lncRNA is unclear with respect to epithelial-to-mesenchymal transition (EMT), which is linked to ovarian cancer metastasis. Here, the authors show lncRNA DNM3OS expression contributes to ovarian cancer EMT, cell migration/invasion, and correlates with worse overall patient survival.

The Potential Roles of Long Noncoding RNAs (lncRNA) in Glioblastoma Development

Long noncoding RNA (lncRNA) may contribute to the initiation and progression of tumor. In this study, we first systematically compared lncRNA and mRNA expression between glioblastoma and paired normal brain tissues using microarray data. We found 27 lncRNA and 82 mRNA significantly upregulated in glioblastoma, as well as 198 lncRNA and 285 mRNA significantly downregulated in glioblastoma. We identified 138 coexpressed lncRNA–mRNA pairs from these differentially expressed lncRNA and genes. Subsequent pathway analysis of the lncRNA-paired genes indicated that EphrinB–EPHB, p75-mediated signaling, TNFα/NF-κB, and ErbB2/ErbB3 signaling pathways might be altered in glioblastoma. Specifically, lncRNA RAMP2-AS1 had significant decrease of expression in glioblastoma tissues and showed coexpressional relationship with NOTCH3, an important tumor promoter in many neoplastic diseases. Our follow up experiment indicated that (i) an overexpression of RAMP2-AS1 reduced glioblastoma cell proliferation in vitro and also reduced glioblastoma xenograft tumors in vivo; (ii) NOTCH3 and RAMP2-AS1 coexpression rescued the inhibitory action of RAMP2-AS1 in glioblastoma cells; and (iii) RNA pull-down assay revealed a direct interaction of RAMP2-AS1 with DHC10, which may consequently inhibit, as we hypothesize, the expression of NOTCH3 and its downstream signaling molecule HES1 in glioblastoma. Taken together, our data revealed that lncRNA expression profile in glioblastoma tissue was significantly altered; and RAMP2-AS1 might play a tumor suppressive role in glioblastoma through an indirect inhibition of NOTCH3. Our results provided some insights into understanding the key roles of lncRNA–mRNA coregulation in human glioblastoma and the mechanisms responsible for glioblastoma progression and pathogenesis. Mol Cancer Ther; 15(12); 2977–86. ©2016 AACR.

microRNA regulation in cancer: One arm or two arms?

Dear Editor, microRNAs (miRNAs) have been frequently reported to play critical roles in tumorigenesis and to have great potential for the development of molecular cancer therapeutics. miRNAs are transcribed as long primary transcripts whose maturation occurs through sequential endonucleolytic steps that yield precursor miRNA (pre-miRNA) intermediates and then the mature miRNAs. Each pre-miRNA has two arms, 5′ arm and 3′ arm, and are denoted with -5p and -3p suffixes in its name 1. Depending on the tissue or cell type, both arms can be processed to become functional mature miRNAs 2-4. The two arms have different sequences; therefore, they either target different mRNAs or the same mRNA but at different sites in the mRNAs 3′ untranslated region. Until recently, in most miRNA studies, researchers usually reported the functions of only one arm (i.e., either -5p or -3p), rather than both. However, recent in vitro and in vivo studies 2-4 showed that miR-5p and miR-3p (hereafter referred to miR-5p/-3p) mediated synergistic regulations could enhance a more effective suppression of tumor-suppressor pathways or activation of oncogenic pathways in a specific cancer. For example, the synergistic effect of miR-17-5p/-3p pair was investigated in hepatocellular carcinoma (HCC) 3 and prostate tumor 4. In HCC, miR-17-5p repressed the expression of tumor suppressor gene PTEN, and miR-17-3p repressed the expression of genes Vimentin and GalNT7; whereas in prostate tumor, miR-17-5p and miR-17-3p co-regulated the tumor suppressor gene TIMP3 and repressed its expression. In both cancers, the abundant expression of miR-17-5p/-3p pair enhanced cell proliferation, migration, and invasion by silencing the above mentioned direct target genes. The synergistic effect of several other miR-5p/-3p pairs has been examined in specific cancer type (Supporting Information Table S1). However, there is no systematic examination about how frequently miR-5p/-3p pairs are dysregulated across multiple cancer types and involved in synergistic regulation. To explore this important issue, we used the publicly available, large-scale miRNA-Seq expression data for multiple cancer types that were generated by The Cancer Genome Atlas (TCGA) project (https://tcga-data.nci.nih.gov/tcga/). We extracted miRNA-Seq expression profiles from 3778 clinically-documented high-quality tumor and normal samples in 10 cancer types (Supporting Information Table S2) and identified differentially expressed miR-5p/-3p pairs in each cancer (Supporting Information Data S1 and Table S3). This massive amount of data made it possible for us not only to pinpoint abnormally expressed miR-5p/-3p pairs in a specific cancer type, but also to assess whether these pairs follow any dysregulation pattern in multiple cancers (i.e., pan-cancer). Interestingly, we found a strong trend that miR-5p/-3p pairs follow a concordant dysregulation pattern, i.e., both arms were either up- or down-regulated in cancer compared to normal tissue samples (Fig. 1A). We identified 23 miR-5p/-3p pairs that have consistent up- or down-regulation in five or more cancer types, suggesting their potentiality in pan-cancer regulation (labeled miR-5p/-3p pairs in Fig. 1B). For example, miR-130b-5p/-3p, miR-21-5p/-3p, miR-708-5p/-3p, and miR-93-5p/3p were up-regulated in eight cancer types. We used >1.5 fold-change and adjusted P-value < 0.05 (adjusted by Benjamini-Hochberg method 5) to denote differentially expressed miRNAs; this is because a 1.5-fold change of miRNA expression may have significant impact on cellular process 6. Notably, miR-17-5p/-3p and miR-31-5p/-3p pairs were up-regulated in six and five cancer types, respectively. The up-regulation of miR-17-5p/-3p pair in HCC 3 and prostate cancer 4, and the up-regulation of miR-31-5p/-3p pair in head and neck cancer 7 were confirmed by qRT-PCR in previous studies (Supporting Information Table S1). We also found that miR-5p/-3p pairs had stronger expression correlation (P-value < 2.2×10-16, one-sided Kolmogorov-Smirnov test) than that of the mature miRNA pairs that were randomly selected from different pre-miRNAs with the requirement of concordant dysregulation of the two miRNAs (Fig 1C). The observed concordant dysregulation might in many cases be a direct consequence of the deregulating mechanisms, for example, the two arms of the same precursor have very close proximity (< 30 nucleotides) in the human genome so that both arms are always located in minimally deleted/amplified regions 8 (Fig. 1D) or regulated by common upstream regulators (e.g. transcription factors). For instance, transcription factor SOX9 regulates both miR-202-5p and miR-202-3p expression during mouse testis differentiation 9. Previous reports, obtained from the OncomiRDB database 10 and Supporting Information Table S1, suggest that the well-studied arm of several pre-miRNAs (labeled in Fig. 1B) has oncogenic or tumor suppressive roles in one or more cancer types (Fig. 1E). Hence, future experimental works are warranted to uncover the oncogenic/tumor suppressive potential of the less studied arms. Figure 1 Concordant dysregulation of miR-5p/-3p pairs in cancer: potential causes and consequences While we first time reported that the concordant dysregulation of miR-5p/-3p pair is a common feature in cancer, several issues remain for future investigation. First, whether and how miR-5p/-3p pairs are under selective pressure to be concordantly dysregulated in cancer? Second, what are the specific subcellular systems or signaling pathways synergistically controlled by miR-5p/-3p pairs? Third, how can concordant dysregulation of miR-5p/3p pairs help us develop more accurate miRNA-based molecular therapeutic strategies? Fourth, whether this concordant dysregulation is universal in other phenotype or in other organisms remains for further investigation. Yours sincerely, Ramkrishna Mitra Jingchun Sun Zhongming Zhao

The homing and inhibiting effects of hNSCs-BMP4 on human glioma stem cells.

Malignant gliomas patients have a poor survival rate, partially due to the inability in delivering therapeutic agents to the tumors, especially to the metastasis of human glioma stem cells (hGSCs). To explore whether the human neural stem cells (hNSCs) with an over-expression of BMP4 (hNSCs-BMP4) can trace and inhibit hGSCs, in this study, we examined the migration of hNSCs to hGSCs using transwell assay in vitro and performed the fluorescent tracer experiment in vivo. We examined the proliferation, differentiation, apoptosis and migration of hGSCs after co-culturing with hNSCs-BMP4 in vitro and tested the tropism and antitumor effects of hNSCs-BMP4 in the established brain xenograft models of hGSCs. We found that hNSCs-BMP4 could secrete BMP4 and trace hGSCs both in vitro and in vivo. When compared to the normal human astrocytes (NHAs) and hNSCs, hNSCs-BMP4 could significantly inhibit the invasive growth of hGSCs, promote their differentiation and apoptosis by activating Smad1/5/8 signaling, and prolong the survival time of the tumor-bearing nude mice. Collectively, this study suggested that hNSCs-BMP4 may help in developing therapeutic approaches for the treatment of human malignant gliomas.

Algorithms for network-based identification of differential regulators from transcriptome data: a systematic evaluation

Identification of differential regulators is critical to understand the dynamics of cellular systems and molecular mechanisms of diseases. Several computational algorithms have recently been developed for this purpose by using transcriptome and network data. However, it remains largely unclear which algorithm performs better under a specific condition. Such knowledge is important for both appropriate application and future enhancement of these algorithms. Here, we systematically evaluated seven main algorithms (TED, TDD, TFactS, RIF1, RIF2, dCSA_t2t, and dCSA_r2t), using both simulated and real datasets. In our simulation evaluation, we artificially inactivated either a single regulator or multiple regulators and examined how well each algorithm detected known gold standard regulators. We found that all these algorithms could effectively discern signals arising from regulatory network differences, indicating the validity of our simulation schema. Among the seven tested algorithms, TED and TFactS were placed first and second when both discrimination accuracy and robustness against data variation were considered. When applied to two independent lung cancer datasets, both TED and TFactS replicated a substantial fraction of their respective differential regulators. Since TED and TFactS rely on two distinct features of transcriptome data, namely differential co-expression and differential expression, both may be applied as mutual references during practical application.

A Tri-Component Conservation Strategy Reveals Highly Confident MicroRNA-mRNA Interactions and Evolution of MicroRNA Regulatory Networks

MicroRNAs are small non-coding RNAs that can regulate expressions of their target genes at the post-transcriptional level. In this study, we propose a tri-component strategy that combines the conservation of microRNAs, homology of mRNA coding regions, and conserved microRNA binding sites in the 3′ untranslated regions to discover conserved microRNA-mRNA interactions. To validate the performance of our conservation strategy, we collected the experimentally validated microRNA-mRNA interactions from three databases as the golden standard. We found that the proposed strategy can improve the performance of existing target prediction algorithms by approximately 2–4 fold. In addition, we demonstrated that the proposed strategy could efficiently retain highly confident interactions from the intersection results of the existing algorithms and filter out the possible false positive predictions in the union one. Furthermore, this strategy can facilitate our ability to trace the homologues in different species that are targeted by the same miRNA family because it combines these three features to identify the conserved miRNA-mRNA interactions during evolution. Through an extensive application of the proposed conservation strategy to a study of the miR-1/206 regulatory network, we demonstrate that the target mRNA recruiting process could be associated with expansion of miRNA family during its evolution. We also uncovered the functional evolution of the miR-1/206 regulatory network. In this network, the early targeted genes tend to participate in more general and development-related functions. In summary, the conservation strategy is capable of helping to highlight the highly confident miRNA-mRNA interactions and can be further applied to reveal the evolutionary features of miRNA regulatory network and functions.

The oncogenic and prognostic potential of eight microRNAs identified by a synergetic regulatory network approach in lung cancer

Transcription factors (TFs) and microRNAs (miRNAs), the two main gene regulators in the biological system, control the gene expression at the transcriptional and post-transcriptional level, respectively. However, little is known regarding whether the miRNATF co-regulatory mechanisms, predicted by several studies, truly reflect the molecular interactions in cellular systems. To tackle this important issue, we developed an integrative framework by utilising four independent miRNA and matched mRNA expression profiling datasets to identify reproducible regulations, and demonstrated this approach in non-small cell lung cancer (NSCLC). Our analyses pinpointed several reproducible miRNA-TF co-regulatory networks in NSCLC from which we systematically prioritised eight hub miRNAs that may have strong oncogenic characteristics. Here, we discussed the major findings of our study and explored the oncogenic and prognostic potential of eight prioritised miRNAs through literature-mining based analysis and patient survival analysis. The findings provide additional insights into the miRNA-TF co-regulation in lung cancer.

Non-Hodgkin and Hodgkin Lymphomas Select for Overexpression of BCLW

Purpose: B-cell lymphomas must acquire resistance to apoptosis during their development. We recently discovered BCLW, an antiapoptotic BCL2 family member thought only to contribute to spermatogenesis, was overexpressed in diffuse large B-cell lymphoma (DLBCL) and Burkitt lymphoma. To gain insight into the contribution of BCLW to B-cell lymphomas and its potential to confer resistance to BCL2 inhibitors, we investigated the expression of BCLW and the other antiapoptotic BCL2 family members in six different B-cell lymphomas. Experimental Design: We performed a large-scale gene expression analysis of datasets comprising approximately 2,300 lymphoma patient samples, including non-Hodgkin and Hodgkin lymphomas as well as indolent and aggressive lymphomas. Data were validated experimentally with qRT-PCR and IHC. Results: We report BCLW is significantly overexpressed in aggressive and indolent lymphomas, including DLBCL, Burkitt, follicular, mantle cell, marginal zone, and Hodgkin lymphomas. Notably, BCLW was preferentially overexpressed over that of BCL2 and negatively correlated with BCL2 in specific lymphomas. Unexpectedly, BCLW was overexpressed as frequently as BCL2 in follicular lymphoma. Evaluation of all five antiapoptotic BCL2 family members in six types of B-cell lymphoma revealed that BCL2, BCLW, and BCLX were consistently overexpressed, whereas MCL1 and A1 were not. In addition, individual lymphomas frequently overexpressed more than one antiapoptotic BCL2 family member. Conclusions: Our comprehensive analysis indicates B-cell lymphomas commonly select for BCLW overexpression in combination with or instead of other antiapoptotic BCL2 family members. Our results suggest BCLW may be equally as important in lymphomagenesis as BCL2 and that targeting BCLW in lymphomas should be considered. Clin Cancer Res; 23(22); 7119–29. ©2017 AACR.

Mdm2 is required for survival and growth of p53-deficient cancer cells

p53 deletion prevents the embryonic lethality of normal tissues lacking Mdm2, suggesting that cells can survive without Mdm2 if p53 is also absent. Here we report evidence challenging this view, with implications for therapeutically targeting Mdm2. Deletion of Mdm2 in T-cell lymphomas or sarcomas lacking p53 induced apoptosis and G2 cell-cycle arrest, prolonging survival of mice with these tumors. p53-/- fibroblasts showed similar results, indicating that the effects of Mdm2 loss extend to premalignant cells. Mdm2 deletion in p53-/- cells upregulated p53 transcriptional target genes that induce apoptosis and cell-cycle arrest. Mdm2 deletion also increased levels of p73, a p53 family member. RNAi-mediated attenuation of p73 rescued the transcriptional and biological effects of Mdm2 loss, indicating that p73 mediates the consequences of Mdm2 deletion. In addition, Mdm2 deletion differed from blocking Mdm2 interaction with p53 family members, as Nutlin-3 induced G1 arrest but did not activate apoptosis in p53-/- sarcoma cells. Our results indicate that, in contrast to current dogma, Mdm2 expression is required for cell survival even in the absence of p53. Moreover, our results suggest that p73 compensates for loss of p53 and that targeting Mdm2 in p53-deficient cancers has therapeutic potential. Cancer Res; 77(14); 3823-33. ©2017 AACR.