The Evolutionary History of Metastatic Pancreatic Neuroendocrine Tumours Reveals a Therapy Driven Route to High-Grade Transformation.

Tumour evolution with acquisition of more aggressive disease characteristics is a hallmark of disseminated cancer. Metastatic pancreatic neuroendocrine tumours (PanNETs) in particular, show frequent progression from a low/intermediate to a high-grade disease. To understand the molecular mechanisms underlying this phenomenon, we performed multi-omics analysis of 32 longitudinal samples from six metastatic PanNET patients. Following MEN1 inactivation, PanNETs exhibit genetic heterogeneity on both spatial and temporal dimensions with parallel and convergent tumuor evolution involving the ATRX/DAXX and mTOR pathways. Following alkylating chemotherapy treatment, some PanNETs develop mismatch repair deficiency and acquire a hypermutator phenotype. This DNA hypermutation phenotype was only found in cases that also showed transformation into a high-grade PanNET. Overall, our findings contribute to broaden the understanding of metastatic PanNET, and suggests that therapy driven disease evolution is an important hallmark of this disease.

Expression of nonmuscle myosin IIC is regulated by non-canonical binding activity of miRNAs.

The expression of mechanoresponsive nonmuscle myosin II (NMII)C is found to be inducible during tumor progression, but its mechanism is yet to be explored. Here, we report a group of microRNAs (mmu-miR-200a-5p, mmu-miR-532-3p, mmu-miR-680, and mmu-miR-1901) can significantly repress the expression of nonmuscle myosin IIC (NMIIC). Interestingly, these microRNAs have both canonical and non-canonical binding sites at 3/UTR and coding sequence (CDS) of NMIIC's heavy chain (HC) mRNA. Each of the miRNA downregulates NMHC-IIC to a different degree as assessed by dual-luciferase and immunoblot analyses. When we abolish the complementary base pairing at canonical binding site, mmu-miR-532-3p can still bind at non-canonical binding site and form Argonaute2 (AGO2)-miRNA complex to downregulate the expression of NMIIC. Modulating the expression of NMIIC by miR-532-3p in mouse mammary tumor cells, 4T1, increases its tumorigenic potential both in vitro and in vivo. Together, these studies provide the functional role of miRNA's non-canonical binding mediated NMIIC regulation in tumor cells.

Immune signature of pheochromocytoma and paraganglioma in context of neuroendocrine neoplasms associated with prognosis.

PURPOSE: To understand prognostic immune cell infiltration signatures in neuroendocrine neoplasms (NENs), particularly pheochromocytoma and paraganglioma (PCPG), we analyzed tumor transcriptomic data from The Cancer Genome Atlas (TCGA) and other published tumor transcriptomic data of NENs. METHODS: We used CIBERSORT to infer immune cell infiltrations from bulk tumor transcriptomic data from PCPGs, in comparison to gastroenteropancreatic neuroendocrine tumors (GEPNETs) and small cell lung carcinomas (SCLCs). PCPG immune signature was validated with NanoString immune panel in an independent cohort. Unsupervised clustering of the immune infiltration scores from CIBERSORT was used to find immune clusters. A prognostic immune score model for PCPGs and the other NENs were calculated as a linear combination of the estimated infiltration of activated CD8+/CD4+ T cells, activated NK cells, and M0 and M2 macrophages. RESULTS: In PCPGs, we found five dominant immune clusters, associated with M2 macrophages, monocytes, activated NK cells, M0 macrophages and regulatory T cells, and CD8+/CD4+ T cells respectively. Non-metastatic tumors were associated with activated NK cells and metastatic tumors were associated with M0 macrophages and regulatory T cells. In GEPNETs and SCLCs, M0 macrophages and regulatory T cells were associated with unfavorable outcomes and features, such as metastasis and high-grade tumors. The prognostic immune score model for PCPGs and the NENs could predict non-aggressive and non-metastatic diseases. In PCPGs, the immune score was also an independent predictor of metastasis-free survival in a multivariate Cox regression analysis. CONCLUSION: The transcriptomic immune signature in PCPG correlates with clinical features like metastasis and prognosis.

PD-L1 expression and association with genetic background in pheochromocytoma and paraganglioma.

Metastatic pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors associated with poor prognosis and limited therapeutic options. Recent advances in oncology-related immunotherapy, specifically in targeting of programmed cell death-1 (PD-1)/programmed death-ligand 1 (PD-L1) pathways, have identified a new treatment potential in a variety of tumors, including advanced and rare tumors. Only a fraction of patients being treated by immune checkpoint inhibitors have shown to benefit from it, displaying a need for strategies which identify patients who may most likely show a favorable response. Building on recent, promising outcomes in a clinical study of metastatic PPGL using pembrolizumab, a humanized IgG4κ monoclonal antibody targeting the PD-1/PD-L1 pathway, we examined PD-L1 and PD-L2 expression in relation to oncogenic drivers in our PPGL patient cohort to explore whether expression can predict metastatic potential and/or be considered a predictive marker for targeted therapy. We evaluated RNA expression in the NIH cohort of 48 patients with known genetic predisposition (sporadic; pseudohypoxia: SDHB, VHL, EPAS1, EGLN1; kinase signaling: RET, NF1) and 6 normal medulla samples (NAM). For comparison, 72 PPGL samples from The Cancer Genome Atlas (TCGA) were used for analysis of gene expression based on the variant status (pseudohypoxia: SDHB, VHL, EPAS1, EGLN1; kinase signaling: NF1, RET). Expression of PD-L1 was elevated in the PPGL cohort compared to normal adrenal medulla, aligning with the TCGA analysis, whereas PD-L2 was not elevated. However, expression of PD-L1 was lower in the pseudohypoxia cluster compared to the sporadic and the kinase signaling subtype cluster, suggesting that sporadic and kinase signaling cluster PPGLs could benefit from PD-1/PD-L1 therapy more than the pseudohypoxia cluster. Within the pseudohypoxia cluster, expression of PD-L1 was significantly lower in both SDHB- and non-SDHB-mutated tumors compared to sporadic tumors. PD-L1 and PD-L2 expression was not affected by the metastatic status. We conclude that PD-L1 and PD-L2 expression in our cohort of PPGL tumors was not linked to metastatic behavior, however, the presence of PPGL driver mutation could be a predictive marker for PD-L1-targeted therapy and an important feature for further clinical studies in patients with PPGL.

A long noncoding RNA-microRNA expression signature predicts metastatic signature in pheochromocytomas and paragangliomas.

PURPOSE: In hopes of discovering new markers for metastatic or aggressive phenotypes of pheochromocytomas and paragangliomas (PCPG), we analyzed the noncoding transcriptome from patient gene expression data in The Cancer Genome Atlas. METHODS: Differential expression of miRNAs was observed between PCPG molecular subtypes. We specifically characterized candidate miRNAs that are upregulated in pseudohypoxic PCPGs with mutations in succinate dehydrogenase complex subunits, B and/or D (SDHB and/or SDHD, respectively), which are mutations associated with unfavorable clinical outcomes. RESULTS: Our computational analysis identified four candidate miRNAs that showed elevated expression in metastatic compared to non-metastatic PCPGs: miR-182, miR-183, miR-96, and miR-383. We also found six candidate lncRNAs harboring opposite expression patterns from the miRNAs when we analyzed the expression profiles of their predicted target lncRNAs. Three of these lncRNA candidates, USP3-AS1, LINC00877, and AC009312.1, were validated to have reduced expression in metastatic compared to non-metastatic PCPGs. Finally, using univariate and multivariate analysis, we found miRNA miR-182 to be an independent predictor of metastasis-free survival in PCPGs. CONCLUSIONS: We identified candidate miRNA and lncRNAs associated with metastasis-free survival in PCPGs.

Long intergenic noncoding RNA profiles of pheochromocytoma and paraganglioma: A novel prognostic biomarker.

Many long intergenic noncoding RNAs (lincRNAs) serve as cancer biomarkers for diagnosis or prognostication. To understand the role of lincRNAs in the rare neuroendocrine tumors pheochromocytoma and paraganglioma (PCPG), we performed first time in-depth characterization of lincRNA expression profiles and correlated findings to clinical outcomes of the disease. RNA-Seq data from patients with PCPGs and 17 other tumor types from The Cancer Genome Atlas and other published sources were obtained. Differential expression analysis and a machine-learning model were used to identify transcripts specific to PCPGs, as well as established PCPG molecular subtypes. Similarly, lincRNAs specific to aggressive PCPGs were identified, and univariate and multivariate analysis was performed for metastasis-free survival. The results were validated in independent samples using RT-PCR. From a pan-cancer context, PCPGs had a specific and unique lincRNA profile. Among PCPGs, five different molecular subtypes were identified corresponding to the established molecular classification. Upregulation of 13 lincRNAs was found to be associated with aggressive/metastatic PCPGs. RT-PCR validation confirmed the overexpression of four lincRNAs in metastatic compared to non-metastatic PCPGs. Kaplan-Meier analysis identified five lincRNAs as prognostic markers for metastasis-free survival of patients in three subtypes of PCPGs. Stratification of PCPG patients with a risk-score formulated using multivariate analysis of lincRNA expression profiles, presence of key driver mutations, tumor location, and hormone secretion profiles showed significant differences in metastasis-free survival. PCPGs thus exhibit a specific lincRNA expression profile that also corresponds to the established molecular subgroups and can be potential marker for the aggressive/metastatic PCPGs.

Genotype-phenotype correlations in pheochromocytoma and paraganglioma: a systematic review and individual patient meta-analysis.

Pheochromocytoma and paraganglioma (PPGL) can be divided into at least four molecular subgroups. Whether such categorizations are independent factors for prognosis or metastatic disease is unknown. We performed a systematic review and individual patient meta-analysis aiming to estimate if driver mutation status can predict metastatic disease and survival. Driver mutations were used to categorize patients according to three different molecular systems: two subgroups (SDHB mutated or wild type), three subgroups (pseudohypoxia, kinase signaling or Wnt/unknown) and four subgroups (tricarboxylic acid cycle, VHL/EPAS1, kinase signaling or Wnt/unknown). Twenty-one studies and 703 patients were analyzed. Multivariate models for association with metastasis showed correlation with SDHB mutation (OR 5.68 (95% CI 1.79-18.06)) as well as norepinephrine (OR 3.01 (95% CI 1.02-8.79)) and dopamine (OR 6.39 (95% CI 1.62-25.24)) but not to PPGL location. Other molecular systems were not associated with metastasis. In multivariate models for association with survival, age (HR 1.04 (95% CI 1.02-1.06)) and metastases (HR 6.13 (95% CI 2.86-13.13)) but neither paraganglioma nor SDHB mutation remained significant. Other molecular subgroups did not correlate with survival. We conclude that molecular categorization accordingly to SDHB provided independent information on the risk of metastasis. Driver mutations status did not correlate independently with survival. These data may ultimately be used to guide current and future risk stratification of PPGL.

Correlation of altered expression of a long non-coding RNA, NEAT1, in peripheral blood mononuclear cells with dengue disease progression.

The association of long non-coding RNAs (lncRNAs) with dengue disease progression is currently unknown. Therefore, the present study aimed to identify lncRNAs in different categories of dengue patients and evaluate their association with dengue disease progression. Herein, we examined the expression profiles of lncRNAs and protein-coding genes between other febrile illness (OFI) and different grade of dengue patients through high-throughput RNA sequencing. We identified Nuclear Enriched Abundant Transcript 1 (NEAT1) as one of the differentially expressed lncRNAs (adjusted P ≤ 0.05 and log-fold change ≥ 2) and subsequently validated the expression by qRT-PCR. The co-expression analysis further revealed that NEAT1 and the coding gene IFI27 were highly co-expressed and negatively correlated with dengue severity. Using regression analysis, we observed that NEAT1 expression was significantly dependent on disease progression (Coefficient = -0.27750, SE Coefficient = 0.07145, and t = -3.88).Further, receiver operating characteristic (ROC) curve revealed that NEAT1 expression could discriminate DI from DS (sensitivity and specificity of 100% (95%CI: 85.69 - 97.22) and area under the curve (AUC) = 0.97). Overall, the results of this study offer the first experimental evidence demonstrating the correlation between lncRNAs and severe dengue phenotype. Monitoring NEAT1and IFI27 expression in PBMC may be useful in understanding dengue virus-induced disease progression.

The Human CCHC-type Zinc Finger Nucleic Acid-Binding Protein Binds G-Rich Elements in Target mRNA Coding Sequences and Promotes Translation.

The CCHC-type zinc finger nucleic acid-binding protein (CNBP/ZNF9) is conserved in eukaryotes and is essential for embryonic development in mammals. It has been implicated in transcriptional, as well as post-transcriptional, gene regulation; however, its nucleic acid ligands and molecular function remain elusive. Here, we use multiple systems-wide approaches to identify CNBP targets and function. We used photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) to identify 8,420 CNBP binding sites on 4,178 mRNAs. CNBP preferentially bound G-rich elements in the target mRNA coding sequences, most of which were previously found to form G-quadruplex and other stable structures in vitro. Functional analyses, including RNA sequencing, ribosome profiling, and quantitative mass spectrometry, revealed that CNBP binding did not influence target mRNA abundance but rather increased their translational efficiency. Considering that CNBP binding prevented G-quadruplex structure formation in vitro, we hypothesize that CNBP is supporting translation by resolving stable structures on mRNAs.

miRepress: modelling gene expression regulation by microRNA with non-conventional binding sites.

Some earlier studies have reported an alternative mode of microRNA-target interaction. We detected target regions within mRNA transcripts from AGO PAR-CLIP that did not contain any conventional microRNA seed pairing but only had non-conventional binding sites with microRNA 3' end. Our study from 7 set of data that measured global protein fold change after microRNA transfection pointed towards the association of target protein fold change with 6-mer and 7-mer target sites involving microRNA 3' end. We developed a model to predict the degree of microRNA target regulation in terms of protein fold changes from the number of different conventional and non-conventional target sites present in the target, and found significant correlation of its output with protein expression changes. We validated the effect of non-conventional interactions with target by modulating the abundance of microRNA in a human breast cancer cell line MCF-7. The validation was done using luciferase assay and immunoblot analysis for our predicted non-conventional microRNA-target pair WNT1 (3' UTR) and miR-367-5p and immunoblot analysis for another predicted non-conventional microRNA-target pair MYH10 (coding region) and miR-181a-5p. Both experiments showed inhibition of targets by transfection of microRNA mimics that were predicted to have only non-conventional sites.

Dynamic changes in global microRNAome and transcriptome reveal complex miRNA-mRNA regulated host response to Japanese Encephalitis Virus in microglial cells.

Microglia cells in the brain play essential role during Japanese Encephalitis Virus (JEV) infection and may lead to change in microRNA (miRNA) and mRNA profile. These changes may together control disease outcome. Using Affymetrix microarray platform, we profiled cellular miRNA and mRNA expression at multiple time points during viral infection in human microglial (CHME3) cells. In silico analysis of microarray data revealed a phased pattern of miRNAs expression, associated with JEV replication and provided unique signatures of infection. Target prediction and pathway enrichment analysis identified anti correlation between differentially expressed miRNA and the gene expression at multiple time point which ultimately affected diverse signaling pathways including Notch signaling pathways in microglia. Activation of Notch pathway during JEV infection was demonstrated in vitro and in vivo. The expression of a subset of miRNAs that target multiple genes in Notch signaling pathways were suppressed and their overexpression could affect JEV induced immune response. Further analysis provided evidence for the possible presence of cellular competing endogenous RNA (ceRNA) associated with innate immune response. Collectively, our data provide a uniquely comprehensive view of the changes in the host miRNAs induced by JEV during cellular infection and identify Notch pathway in modulating microglia mediated inflammation.

HumanViCe: host ceRNA network in virus infected cells in human.

Host-virus interaction via host cellular components has been an important field of research in recent times. RNA interference mediated by short interfering RNAs and microRNAs (miRNA), is a widespread anti-viral defense strategy. Importantly, viruses also encode their own miRNAs. In recent times miRNAs were identified as key players in host-virus interaction. Furthermore, viruses were shown to exploit the host miRNA networks to suite their own need. The complex cross-talk between host and viral miRNAs and their cellular and viral targets forms the environment for viral pathogenesis. Apart from protein-coding mRNAs, non-coding RNAs may also be targeted by host or viral miRNAs in virus infected cells, and viruses can exploit the host miRNA mediated gene regulatory network via the competing endogenous RNA effect. A recent report showed that viral U-rich non-coding RNAs called HSUR, expressed in primate virus herpesvirus saimiri (HVS) infected T cells, were able to bind to three host miRNAs, causing significant alteration in cellular level for one of the miRNAs. We have predicted protein coding and non protein-coding targets for viral and human miRNAs in virus infected cells. We identified viral miRNA targets within host non-coding RNA loci from AGO interacting regions in three different virus infected cells. Gene ontology (GO) and pathway enrichment analysis of the genes comprising the ceRNA networks in the virus infected cells revealed enrichment of key cellular signaling pathways related to cell fate decisions and gene transcription, like Notch and Wnt signaling pathways, as well as pathways related to viral entry, replication and virulence. We identified a vast number of non-coding transcripts playing as potential ceRNAs to the immune response associated genes; e.g., APOBEC family genes, in some virus infected cells. All these information are compiled in HumanViCe (http://gyanxet-beta.com/humanvice), a comprehensive database that provides the potential ceRNA networks in virus infected human cells.

lnCeDB: database of human long noncoding RNA acting as competing endogenous RNA.

UNLABELLED: Long noncoding RNA (lncRNA) influences post-transcriptional regulation by interfering with the microRNA (miRNA) pathways, acting as competing endogenous RNA (ceRNA). These lncRNAs have miRNA responsive elements (MRE) in them, and control endogenous miRNAs available for binding with their target mRNAs, thus reducing the repression of these mRNAs. lnCeDB provides a database of human lncRNAs (from GENCODE 19 version) that can potentially act as ceRNAs. The putative mRNA targets of human miRNAs and the targets mapped to AGO clipped regions are collected from TargetScan and StarBase respectively. The lncRNA targets of human miRNAs (up to GENCODE 11) are downloaded from miRCode database. miRNA targets on the rest of the GENCODE 19 lncRNAs are predicted by our algorithm for finding seed-matched target sites. These putative miRNA-lncRNA interactions are mapped to the Ago interacting regions within lncRNAs. To find out the likelihood of an lncRNA-mRNA pair for actually being ceRNA we take recourse to two methods. First, a ceRNA score is calculated from the ratio of the number of shared MREs between the pair with the total number of MREs of the individual candidate gene. Second, the P-value for each ceRNA pair is determined by hypergeometric test using the number of shared miRNAs between the ceRNA pair against the number of miRNAs interacting with the individual RNAs. Typically, in a pair of RNAs being targeted by common miRNA(s), there should be a correlation of expression so that the increase in level of one ceRNA results in the increased level of the other ceRNA. Near-equimolar concentration of the competing RNAs is associated with more profound ceRNA effect. In lnCeDB one can not only browse for lncRNA-mRNA pairs having common targeting miRNAs, but also compare the expression of the pair in 22 human tissues to estimate the chances of the pair for actually being ceRNAs. AVAILABILITY: Downloadable freely from http://gyanxet-beta.com/lncedb/.

Competing endogenous RNA: the key to posttranscriptional regulation.

Competing endogenous RNA, ceRNA, vie with messenger RNAs (mRNAs) for microRNAs (miRNAs) with shared miRNAs responses elements (MREs) and act as modulator of miRNA by influencing the available level of miRNA. It has recently been discovered that, apart from protein-coding ceRNAs, pseudogenes, long noncoding RNAs (lncRNAs), and circular RNAs act as miRNA "sponges" by sharing common MRE, inhibiting normal miRNA targeting activity on mRNA. These MRE sharing elements form the posttranscriptional ceRNA network to regulate mRNA expression. ceRNAs are widely implicated in many biological processes. Recent studies have identified ceRNAs associated with a number of diseases including cancer. This brief review focuses on the molecular mechanism of ceRNA as part of the complex post-transcriptional regulatory circuit in cell and the impact of ceRNAs in development and disease.

Circ2Traits: a comprehensive database for circular RNA potentially associated with disease and traits.

Circular RNAs are new players in regulation of post transcriptional gene expression. Animal genomes express many circular RNAs from diverse genomic locations. A recent study has validated a fairly large number of circular RNAs in human, mouse, and nematode. Circular RNAs play a crucial role in fine tuning the level of miRNA mediated regulation of gene expression by sequestering the miRNAs. Their interaction with disease associated miRNAs indicates that circular RNAs are important for disease regulation. In this paper we studied the potential association of circular RNAs (circRNA) with human diseases in two different ways. Firstly, the interactions of circRNAs with disease associated miRNAs were identified, following which the likelihood of a circRNA being associated with a disease was calculated. For the miRNAs associated with individual diseases, we constructed a network of predicted interactions between the miRNAs and protein coding, long non-coding and circular RNA genes. We carried out gene ontology (GO) enrichment analysis on the set of protein coding genes in the miRNA- circRNA interactome of individual diseases to check the enrichment of genes associated with particular biological processes. Secondly, disease associated SNPs were mapped on circRNA loci, and Argonaute (Ago) interaction sites on circular RNAs were identified. We compiled a database of disease-circRNA association in Circ2Traits (http://gyanxet-beta.com/circdb/), the first comprehensive knowledgebase of potential association of circular RNAs with diseases in human.

SeedSeq: off-target transcriptome database.

Detection of potential cross-reaction between a short oligonucleotide sequence and a longer (unintended) sequence is crucial for many biological applications, such as high content screening (HCS), microarray nucleotide probes, or short interfering RNAs (siRNAs). However, owing to a tolerance for mismatches and gaps in base-pairing with target transcripts, siRNAs could have up to hundreds of potential target sequences in a genome, and some small RNAs in mammalian systems have been shown to affect the levels of many messenger RNAs (off-targets) besides their intended target transcripts (on-targets). The reference sequence (RefSeq) collection aims to provide a comprehensive, integrated, nonredundant, well-annotated set of sequences, including mRNA transcripts. We performed a detailed off-target analysis of three most commonly used kinome siRNA libraries based on the latest RefSeq version. To simplify the access to off-target transcripts, we created a SeedSeq database, a new unique format to store off-target information.

Long noncoding RNAs: new players in the molecular mechanism for maintenance and differentiation of pluripotent stem cells.

Maintenance of the pluripotent state or differentiation of the pluripotent state into any germ layer depends on the factors that orchestrate expression of thousands of genes through epigenetic, transcriptional, and post-transcriptional regulation. Long noncoding RNAs (lncRNAs) are implicated in the complex molecular circuitry in the developmental processes. The ENCODE project has opened up new avenues for studying these lncRNA transcripts with the availability of new datasets for lncRNA annotation and regulation. Expression studies identified hundreds of long noncoding RNAs differentially expressed in the pluripotent state, and many of these lncRNAs are found to control the pluripotency and stemness in embryonic and induced pluripotent stem cells or, in the reverse way, promote differentiation of pluripotent cells. They are generally transcriptionally activated or repressed by pluripotency-associated transcription factors and function as molecular mediators of gene expression that determine the pluripotent state of the cell. They can act as molecular scaffolds or guides for the chromatin-modifying complexes to direct them to bind into specific genomic loci to impart a repressive or activating effect on gene expression, or they can transcriptionally or post-transcriptionally regulate gene expression by diverse molecular mechanisms. This review focuses on recent findings on the regulatory role of lncRNAs in two main aspects of pluripotency, namely, self renewal and differentiation into any lineage, and elucidates the underlying molecular mechanisms that are being uncovered lately.

An siRNA designing tool with a unique functional off-target filtering approach.

Investigations have revealed that silencing unwanted transcripts or off-targeting can induce false positive phenotype during RNA interference (RNAi)-based gene function study. But still the standard computational approaches towards small interfering RNA (siRNA) off-target minimization fall short in terms of addressing this false positive phenotype issue. Some of these off-targets may interfere with the biochemical pathway being investigated. It may also inadvertently target cell's metabolic pathways with unquantifiable consequences on the processes of user's interest. Here, we report the development of a siRNA selection tool that, for the first time, implements a functional off-target filtering that aims to minimize false positive phenotypes arising from inadvertent targets that are functionally similar or related to the direct target gene, along with a multi-parametric classifier (support vector machine) for optimized selection of potent siRNAs. The functional off-target filtering minimizes the number of off-target genes which are functionally related to the direct target gene, i.e. involved in a common biological process and may have similar phenotype. A text-mining algorithm is used to find related biological processes associated with the direct target and each off-target transcript by comparison of the biological processes associated with these genes. It also gives the user a choice to select one or more off-targets that may be potentially more harmful, from a predicted off-target gene list to be filtered out. Testing with huge set of biologically validated siRNAs from three different sources showed consistent good performance of our tool in terms of effective siRNA selection. It outperformed four potent siRNA selection algorithms of present day in terms of specificity in the selection of highly efficient siRNAs when compared on a common test set. A genome wide testing with potent siRNAs used in high-content screening confirmed validation of 2767 designed siRNAs in terms of phenotypic output. This tool presently supports siRNA designs for human genes and is freely available at http://gyanxet-beta.com .

HNOCDB: a comprehensive database of genes and miRNAs relevant to head and neck and oral cancer.

In spite of the wide prevalence of head, neck and oral cancer, HNOC, there is no integrated database on genes and miRNAs associated with all the carcinoma subtypes of HNOC. The objective is to compile a multilayered and comprehensive database of HNOC as a user-friendly resource for researchers devising novel therapeutic strategies. We present HNOCDB, the head, neck and oral cancer database, with the following key features: (i) it tabulates all the different categories of HNOC separately under appropriate subtype-names, and then puts them together in a table headlined All; (ii) the oncogenes/oncomiRs that cause HNOC are listed; their mutations, methylations and polymorphisms loci are marked, and the variations in their expression profiles relative to the normal are recorded; (iii) HNOCDB contains a chromosomal map of HNOC genes and miRNA; (iv) contains references that experimentally validate the reason for the inclusion of the genes and the miRNAs in HNOCDB. HNOCDB is freely accessible for academic and non-profit users via http://gyanxet.com/hno.html.