Distinct and competitive regulatory patterns of tumor suppressor genes and oncogenes in ovarian cancer

NFE2L3 drives hepatocellular carcinoma cell proliferation by regulating the proteasome-dependent degradation of ISGylated p53

Nuclear factor erythroid 2-like 3 (NFE2L3) is a member of the cap 'n' collar basic-region leucine zipper (CNC-bZIP) transcription factor family that plays a vital role in modulating oxidation-reduction steady-state and proteolysis. Accumulating evidence suggests that NFE2L3 participates in cancer development; however, little is known about the mechanism by which NFE2L3 regulates hepatocellular carcinoma (HCC) cell growth. Here, we confirmed that NFE2L3 promotes HCC cell proliferation by acting as a transcription factor, which directly induces the expression of proteasome and interferon-stimulated gene 15 (ISG15) to enhance the proteasome-dependent degradation of ISGylated p53. Post-translational ISGylation abated the stability of p53 and facilitated HCC cell growth. In summary, we uncovered the pivotal role of NFE2L3 in promoting HCC cell proliferation during proteostasis. This finding may provide a new target for the clinical treatment of HCC.

Identification of consistent post-translational regulatory triplets related to oncogenic and tumour suppressive modulators in childhood acute lymphoblastic leukemia

Background

Acute lymphoblastic leukemia (ALL) is the most common type of childhood cancer. It can be caused by mutations that turn on oncogenes or turn off tumour suppressor genes. For instance, changes in certain genes including Rb and p53 are common in ALL cells. Oncogenes and TSGs may serve as a modulator gene to regulate the gene expression level via their respective target genes. To investigate the regulatory relationship between oncogenes, tumour suppressor genes and transcription factors at the post translational level in childhood ALL, we performed an integrative network analysis on the gene regulation in the post-translational level for childhood ALL based on many publicly available cancer gene expression data including TARGET and GEO database.

Methods

We collected 259 childhood ALL-related genes from the latest online leukemia database, Leukemia Gene Literature Database. These 259 genes were selected from a comprehensive systematic literature with experimental evidences. The identified and curated genes were also associated with patient survival cases and we incorporated this pediatric ALL-related gene list into our analysis. We extracted the known human TFs from the TRRUST database. Among 259 childhood ALL-related genes, 101 unique regulators were mapped to the list of oncogene and tumour suppressor genes (TSGs) from the ONGene and the TSGene databases, and these included 74 TSGs, 62 oncogenes and 46 TF genes.

Results

The resulted regulation was presented as a hierarchical regulatory network with transcription factors (TFs) as intermediate regulators connecting the top modulators (oncogene and TSGs) to the common target genes. Cross-validation was applied to the results from the TARGET dataset by identifying the consistent regulatory motifs based on three independent ALL expression datasets. A three-layer regulatory network of consistent positive modulators in childhood ALL was constructed in which 74 modulators (40 oncogenes, 34 TSGs) are considered as the most important regulators. The middle layer and the bottom layer contain 34 TFs and 176 target genes, respectively. Oncogenes mostly participated in positive regulation of gene expression and the transcription process of RNA II polymerase, while TSGs were mainly involved in the negative regulation of gene expression. In addition, the oncogene-specific targets were enriched with regulators of the MAPK cascade while tumour suppressor-specific targets were associated with cell death.

Conclusion

The results revealed that oncogenes and TSGs possess a different functional regulatory pattern with regard to not only their biological functions but also their specific target genes in childhood ALL cancer progression. Taken together, our findings could contribute to a better understanding of the important regulatory mechanisms and this method could be used to analyse the targeted genes at the post-translational level in childhood ALL through integrative network analysis.

Signaling, metabolism, and cancer: An important relationship for therapeutic intervention

In cancerous cells, significant changes occur in the activity of signaling pathways affecting a wide range of cellular activities ranging from growth and proliferation to apoptosis, invasiveness, and metastasis. Extensive changes also happen with respect to the metabolism of a cancerous cell encompassing a wide range of functions that include: nutrient acquisition, biosynthesis of macromolecules, and energy generation. These changes are important and some therapeutic approaches for treating cancers have focused on targeting the metabolism of cancerous cells. Oncogenes and tumor suppressor genes have a significant effect on the metabolism of cells. There appears to be a close interaction between metabolism and the signaling pathways in a cancerous cell, in which the interaction provides the metabolic needs of a cancerous cell for uncontrolled proliferation, resistance to apoptosis, and metastasis. In this review, we have reviewed the latest findings in this regard and briefly review the most recent research findings regarding targeting the metabolism of cancer cells as a therapeutic approach for treatment of cancer.

CIGene: a literature-based online resource for cancer initiation genes

Background

Cancer initiation genes (CIGs) are genes that can directly promote cell proliferation or induce cancer. There are thousands of published studies identifying various CIGs; however, no systematic collection or description is available.

Results

To construct a CIG reference for genetic screening, we have collected 177 human genes curated from 1507 PubMed abstracts. To facilitate data queries and browsing, the identified CIGs along with extensive bioinformatic annotations were stored in an online database called CIGene. Initial functional analysis revealed an overlooked role for cell motility in cancer initiation. Subsequent cross-referencing of known tumor suppressor genes and oncogenes against the 177 CIGs identified 96 and 81 CIGs with and without known oncogenic roles, respectively. Successive network analyses of all 177 CIGs determined that the two groups of genes were more likely to link within their group. The distinct molecular functions for these groups were also confirmed with functional studies. While the 96 known oncogenic genes had fundamental roles in gene regulation and signaling, the remaining 81 genes possessed more ancillary functions, such enhancer binding. Further network and mutational analysis of the 96 known oncogenic genes revealed that mutations in these genes were highly prevalent in multiple cancers. By focusing on breast cancer, we found that 32 of the 96 genes with mutations in breast cancers were significantly associated with patient survival.

Conclusions

As the first literature-based online resource for CIGs, CIGene will serve as a useful gateway for the systematic analysis of cancer initiation. CIGene is freely available to all academic users at http://soft.bioinfo-minzhao.org/cigene/.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4944-y) contains supplementary material, which is available to authorized users.

Next-generation sequencing unravels extensive genetic alteration in recurrent ovarian cancer and unique genetic changes in drug-resistant recurrent ovarian cancer

BACKGROUND

By using a high-throughput sequencing technique, we sought to delineate genetic alterations in recurrent ovarian cancer patients and further compare genetic changes in drug-resistant and -sensitive recurrent ovarian cancer patients. We also sought to study the specificity, sensitivity, and consistency of DNA biomarkers in liquid biopsy specimens and ovarian cancer tissue DNA.

METHODS

Tumor tissue specimens and blood samples were obtained from pathologically proven recurrent ovarian cancer patients. Genomic DNA was extracted from tumor tissues, blood cells, ascites, and urine samples. The DNA Library was constructed and sequencing was performed using the Illumina HiSeq 4000 high-throughput sequencing platform. Bioinformatic analysis was done using the Torrent Suite software.

RESULTS

Ten patients with pathologically proven drug-resistant recurrent ovarian cancer and 11 patients with sensitive recurrent ovarian cancer were included. The 5-year OS for drug-resistant recurrent ovarian cancer patients (44 ± 11.07 months, 95% CI: 231.24-53.66 months) was significantly lower than that of drug-sensitive recurrent ovarian cancer patients (58 ± 3.97 months; 95% CI: 50.05-65.59 months; p = 0.024) TP53 was the most frequently mutated gene in both drug-resistant (9/10, 90%) and drug-sensitive recurrent ovarian cancers (10/11, 91%). MYC and RB1 had the highest frequency of copy number variations (6/21, 29%) in recurrent ovarian cancers, followed by PIK3CA (3/21, 14%). BRCA2 N372H polymorphism was found in 40% (4/10) of drug-resistant recurrent ovarian cancer patients. The specificity, sensitivity, and consistency of TP53 and BRCA1 in circulating tumor-free DNA and tumor tissue DNA were 100%, 73.7%, 76.2% and 100%, 75%, 95.24%, respectively.

CONCLUSION

We uncovered extensive genetic alterations in recurrent ovarian cancer and drug-resistant recurrent ovarian cancer exhibited unique genetic changes compared with recurrent ovarian cancer and drug-sensitive recurrent ovarian cancer. We further showed that high-throughput sequencing using liquid biopsy specimens could provide an effective, specific, and sensitive approach for detecting genetic alterations in ovarian cancer.

Promoter Methylation of RASSF1A Gene in Egyptian Patients with Ovarian Cancer

Ovarian malignancy is diagnosed in nearly a fourth of a million women internationally every year. Methylation of RASSF1A tumor suppressor gene prompts its inactivation in diseases. In this study, the RASSF1A promoter methylation was detected by methylated-specific PCR and investigated serum RASSF1A protein level through enzyme-linked immunosorbant assay in 160 Egyptian patients with ovarian cancer and 160 healthy controls. The present work proved that there was a higher frequency of RASSF1A methylation and a decrease in its serum level in patients with ovarian cancer compared to controls as well as in the high-grade tumor patients compared to low grade ones and also in advanced ovarian tumor stage compared to early stages. Our study exhibited that RASSF1A promoter hypermethylation and its protein levels may be a reliable and sensitive tool for diagnosing and monitoring of ovarian malignancy patients.

Mutational analysis of driver genes with tumor suppressive and oncogenic roles in gastric cancer

Gastric cancer (GC) is a complex disease with heterogeneous genetic mechanisms. Genomic mutational profiling of gastric cancer not only expands our knowledge about cancer progression at a fundamental genetic level, but also could provide guidance on new treatment decisions, currently based on tumor histology. The fact that precise medicine-based treatment is successful in a subset of tumors indicates the need for better identification of clinically related molecular tumor phenotypes, especially with regard to those driver mutations on tumor suppressor genes (TSGs) and oncogenes (ONGs). We surveyed 313 TSGs and 160 ONGs associated with 48 protein coding and 19 miRNA genes with both TSG and ONG roles. Using public cancer mutational profiles, we confirmed the dual roles of CDKN1A and CDKN1B. In addition to the widely recognized alterations, we identified another 82 frequently mutated genes in public gastric cancer cohort. In summary, these driver mutation profiles of individual GC will form the basis of personalized treatment of gastric cancer, leading to substantial therapeutic improvements.

Concordance of copy number loss and down-regulation of tumor suppressor genes: a pan-cancer study

Background

Tumor suppressor genes (TSGs) encode the guardian molecules to control cell growth. The genomic alteration of TSGs may cause tumorigenesis and promote cancer progression. So far, investigators have mainly studied the functional effects of somatic single nucleotide variants in TSGs. Copy number variation (CNV) is another important form of genetic variation, and is often involved in cancer biology and drug treatment, but studies of CNV in TSGs are less represented in literature. In addition, there is a lack of a combinatory analysis of gene expression and CNV in this important gene set. Such a study may provide more insights into the relationship between gene dosage and tumorigenesis. To meet this demand, we performed a systematic analysis of CNVs and gene expression in TSGs to provide a systematic view of CNV and gene expression change in TSGs in pan-cancer.

Results

We identified 1170 TSGs with copy number gain or loss in 5846 tumor samples. Among them, 207 TSGs tended to have copy number loss (CNL), from which fifteen CNL hotspot regions were identified. The functional enrichment analysis revealed that the 207 TSGs were enriched in cancer-related pathways such as P53 signaling pathway and the P53 interactome. We further performed integrative analyses of CNV with gene expression using the data from the matched tumor samples. We found 81 TSGs with concordant CNL events and decreased gene expression in the tumor samples we examined. Remarkably, seven TSGs displayed concordant CNL and gene down-regulation in at least 50 tumor samples: MTAP (212 samples), PTEN (139), MCPH1 (85), FBXO25 (67), SMAD4 (64), TRIM35 (57), and RB1 (54). Specifically to MTAP, this concordance was found in 14 cancer types, an observation that is not much reported in literature yet. Further network-based analysis revealed that these TSGs with concordant CNL and gene down-regulation were highly connected.

Conclusions

This study provides a draft landscape of CNV in pan-cancer. Our findings of systematic concordance between CNL and down-regulation of gene expression may help better understand the TSG biology in tumorigenesis and cancer progression.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2904-y) contains supplementary material, which is available to authorized users.

Multi-tissue transcriptomics for construction of a comprehensive gene resource for the terrestrial snail Theba pisana

The land snail Theba pisana is native to the Mediterranean region but has become one of the most abundant invasive species worldwide. Here, we present three transcriptomes of this agriculture pest derived from three tissues: the central nervous system, hepatopancreas (digestive gland), and foot muscle. Sequencing of the three tissues produced 339,479,092 high quality reads and a global de novo assembly generated a total of 250,848 unique transcripts (unigenes). BLAST analysis mapped 52,590 unigenes to NCBI non-redundant protein databases and further functional analysis annotated 21,849 unigenes with gene ontology. We report that T. pisana transcripts have representatives in all functional classes and a comparison of differentially expressed transcripts amongst all three tissues demonstrates enormous differences in their potential metabolic activities. The genes differentially expressed include those with sequence similarity to those genes associated with multiple bacterial diseases and neurological diseases. To provide a valuable resource that will assist functional genomics study, we have implemented a user-friendly web interface, ThebaDB (http://thebadb.bioinfo-minzhao.org/). This online database allows for complex text queries, sequence searches, and data browsing by enriched functional terms and KEGG mapping.

CSGene: a literature-based database for cell senescence genes and its application to identify critical cell aging pathways and associated diseases

Cell senescence is a cellular process in which normal diploid cells cease to replicate and is a major driving force for human cancers and aging-associated diseases. Recent studies on cell senescence have identified many new genetic components and pathways that control cell aging. However, there is no comprehensive resource for cell senescence that integrates various genetic studies and relationships with cell senescence, and the risk associated with complex diseases such as cancer is still unexplored. We have developed the first literature-based gene resource for exploring cell senescence genes, CSGene. We complied 504 experimentally verified genes from public data resources and published literature. Pathway analyses highlighted the prominent roles of cell senescence genes in the control of rRNA gene transcription and unusual rDNA repeat that constitute a center for the stability of the whole genome. We also found a strong association of cell senescence with HIV-1 infection and viral carcinogenesis that are mainly related to promoter/enhancer binding and chromatin modification processes. Moreover, pan-cancer mutation and network analysis also identified common cell aging mechanisms in cancers and uncovered a highly modular network structure. These results highlight the utility of CSGene for elucidating the complex cellular events of cell senescence.

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.

An evidence-based knowledgebase of metastasis suppressors to identify key pathways relevant to cancer metastasis

Metastasis suppressor genes (MS genes) are genes that play important roles in inhibiting the process of cancer metastasis without preventing growth of the primary tumor. Identification of these genes and understanding their functions are critical for investigation of cancer metastasis. Recent studies on cancer metastasis have identified many new susceptibility MS genes. However, the comprehensive illustration of diverse cellular processes regulated by metastasis suppressors during the metastasis cascade is lacking. Thus, the relationship between MS genes and cancer risk is still unclear. To unveil the cellular complexity of MS genes, we have constructed MSGene (http://MSGene.bioinfo-minzhao.org/), the first literature-based gene resource for exploring human MS genes. In total, we manually curated 194 experimentally verified MS genes and mapped to 1448 homologous genes from 17 model species. Follow-up functional analyses associated 194 human MS genes with epithelium/tissue morphogenesis and epithelia cell proliferation. In addition, pathway analysis highlights the prominent role of MS genes in activation of platelets and coagulation system in tumor metastatic cascade. Moreover, global mutation pattern of MS genes across multiple cancers may reveal common cancer metastasis mechanisms. All these results illustrate the importance of MSGene to our understanding on cell development and cancer metastasis.

dbEMT: an epithelial-mesenchymal transition associated gene resource

As a cellular process that changes epithelial cells to mesenchymal cells, Epithelial-mesenchymal transition (EMT) plays important roles in development and cancer metastasis. Recent studies on cancer metastasis have identified many new susceptibility genes that control this transition. However, there is no comprehensive resource for EMT by integrating various genetic studies and the relationship between EMT and the risk of complex diseases such as cancer are still unclear. To investigate the cellular complexity of EMT, we have constructed dbEMT (http://dbemt.bioinfo-minzhao.org/), the first literature-based gene resource for exploring EMT-related human genes. We manually curated 377 experimentally verified genes from literature. Functional analyses highlighted the prominent role of proteoglycans in tumor metastatic cascades. In addition, the disease enrichment analysis provides a clue for the potential transformation in affected tissues or cells in Alzheimer's disease and Type 2 Diabetes. Moreover, the global mutation pattern of EMT-related genes across multiple cancers may reveal common cancer metastasis mechanisms. Our further reconstruction of the EMT-related protein-protein interaction network uncovered a highly modular structure. These results illustrate the importance of dbEMT to our understanding of cell development and cancer metastasis, and also highlight the utility of dbEMT for elucidating the functions of EMT-related genes.

Oncogenes and tumor suppressor genes: comparative genomics and network perspectives

BACKGROUND

Defective tumor suppressor genes (TSGs) and hyperactive oncogenes (OCGs) heavily contribute to cell proliferation and apoptosis during cancer development through genetic variations such as somatic mutations and deletions. Moreover, they usually do not perform their cellular functions individually but rather execute jointly. Therefore, a comprehensive comparison of their mutation patterns and network properties may provide a deeper understanding of their roles in the cancer development and provide some clues for identification of novel targets.

RESULTS

In this study, we performed a comprehensive survey of TSGs and OCGs from the perspectives of somatic mutations and network properties. For comparative purposes, we choose five gene sets: TSGs, OCGs, cancer drug target genes, essential genes, and other genes. Based on the data from Pan-Cancer project, we found that TSGs had the highest mutation frequency in most tumor types and the OCGs second. The essential genes had the lowest mutation frequency in all tumor types. For the network properties in the human protein-protein interaction (PPI) network, we found that, relative to target proteins, essential proteins, and other proteins, the TSG proteins and OCG proteins both tended to have higher degrees, higher betweenness, lower clustering coefficients, and shorter shortest-path distances. Moreover, the TSG proteins and OCG proteins tended to have direct interactions with cancer drug target proteins. To further explore their relationship, we generated a TSG-OCG network and found that TSGs and OCGs connected strongly with each other. The integration of the mutation frequency with the TSG-OCG network offered a network view of TSGs, OCGs, and their interactions, which may provide new insights into how the TSGs and OCGs jointly contribute to the cancer development.

CONCLUSIONS

Our study first discovered that the OCGs and TSGs had different mutation patterns, but had similar and stronger protein-protein characteristics relative to the essential proteins or control proteins in the whole human interactome. We also found that the TSGs and OCGs had the most direct interactions with cancer drug targets. The results will be helpful for cancer drug target identification, and ultimately, understanding the etiology of cancer and treatment at the network level.

Ovarian stem cells: From basic to clinical applications

The field of reproductive biology has undergone significant developments in the last decade. The notion that there is a fixed reserve pool of oocytes before birth was established by Zuckerman in 1951. However, in 2004, an article published in nature challenged this central dogma of mammalian reproductive biology. Tilly’s group reported the existence of ovarian germline stem cells (GSCs) in postnatal ovaries of mice and suggested that the bone marrow could be an extragonadal source of ovarian GSCs. These findings were strongly criticized; however, several independent groups have since successfully isolated and characterized ovarian GSCs in postnatal mice. The ovarian GSCs are located in the ovarian surface epithelium and express markers of undifferentiated GSCs. When transplanted into mouse ovaries, mouse ovarian GSCs could differentiate and produce embryos and offspring. Similarly, in a recent study, ovarian GSCs were found to be present in the ovaries of women of reproductive age. Conversely, there is increasing evidence that stem cells responsible for maintaining a healthy state in normal tissue may be a source of some cancers, including ovarian cancer. Cancer stem cells (CSCs) have been found in many tissues, including ovaries. Some researchers have suggested that ovarian cancer may be a result of the transformation and dysfunction of ovarian GSCs with self-renewal properties. Drug resistant and metastasis-generating CSCs are responsible for many important problems affecting ovarian cancer patients. Therefore, the identification of CSCs will provide opportunities for the development of new therapeutic strategies for treatments for infertility and ovarian cancer. In this article, we summarize the current understanding of ovarian GSCs in adult mammals, and we also discuss whether there is a relationship between GSCs and CSCs.

An evidence-based knowledgebase of pulmonary arterial hypertension to identify genes and pathways relevant to pathogenesis

Pulmonary arterial hypertension (PAH) is a major progressive form of pulmonary hypertension (PH) with more than 4800 patients in the United States. In the last two decades, many studies have identified numerous genes associated with this disease. However, there is no comprehensive research resource for PAH or other PH types that integrates various genetic studies and their related biological information. Thus, the number of associated genes, and their strength of evidence, is unclear. In this study, we tested the hypothesis that a web-based knowledgebase could be used to develop a biological map of highly interrelated, functionally important genes in PAH. We developed the pulmonary arterial hypertension knowledgebase (PAHKB, ), a comprehensive database with a user-friendly web interface. PAHKB extracts genetic data from all available sources, including those from association studies, genetic mutation, gene expression, animal model, supporting literature, various genomic annotations, gene networks, cellular and regulatory pathways, as well as microRNAs. Moreover, PAHKB provides online tools for data browsing and searching, data integration, pathway graphical presentation, and gene ranking. In the current release, PAHKB contains 341 human PH-related genes (293 protein coding and 48 non-coding genes) curated from over 1000 PubMed abstracts. Based on the top 39 ranked PAH-related genes in PAHKB, we constructed a core biological map. This core map was enriched with the TGF-beta signaling pathway, focal adhesion, cytokine-cytokine receptor interaction, and MAPK signaling. In addition, the reconstructed map elucidates several novel cancer signaling pathways, which may provide clues to support the application of anti-cancer therapeutics to PAH. In summary, we have developed a system for the identification of core PH-related genes and identified critical signaling pathways that may be relevant to PAH pathogenesis. This system can be easily applied to other pulmonary diseases.

Synergetic regulatory networks mediated by oncogene-driven microRNAs and transcription factors in serous ovarian cancer

Although high-grade serous ovarian cancer (OVC) is the most lethal gynecologic malignancy in women, little is known about the regulatory mechanisms in the cellular processes that lead to this cancer. Recently, accumulated lines of evidence have shown that the interplay between transcription factors (TFs) and microRNAs (miRNAs) is critical in cellular regulation during tumorigenesis. A comprehensive investigation of TFs and miRNAs, and their target genes, may provide a deeper understanding of the regulatory mechanisms in the pathology of OVC. In this study, we have integrated three complementary algorithms into a framework, aiming to infer the regulation by miRNAs and TFs in conjunction with gene expression profiles. We demonstrated the utility of our framework by inferring 67 OVC-specific regulatory feed-forward loops (FFL) initiated by miRNAs or TFs in high-grade serous OVC. By analyzing these regulatory behaviors, we found that all the 67 FFLs are consistent in their regulatory effects on genes that are jointly targeted by miRNAs and TFs. Remarkably, we unveiled an unbalanced distribution of FFLs with different oncogenic effects. In total, 31 of the 67 coherent FFLs were mainly initiated by oncogenes. On the contrary, only 4 of the FFLs were initiated by tumor suppressor genes. These overwhelmingly observed oncogenic genes were further detected in a sub-network with 32 FFLs centered by miRNA let-7b and TF TCF7L1 to regulate cell differentiation. Closer inspection of 32 FFLs revealed that 75% of the miRNAs reportedly play functional roles in cell differentiation, especially when enriched in epithelial-mesenchymal transitions. This study provides a comprehensive pathophysiological overview of recurring coherent circuits in OVC that are co-regulated by miRNAs and TFs. The prevalence of oncogenic coherent FFLs in serous OVC suggests that oncogene-driven regulatory motifs could cooperatively act upon critical cellular processes such as cell differentiation in a highly efficient and consistent manner.

CNVannotator: a comprehensive annotation server for copy number variation in the human genome

Copy number variation (CNV) is one of the most prevalent genetic variations in the genome, leading to an abnormal number of copies of moderate to large genomic regions. High-throughput technologies such as next-generation sequencing often identify thousands of CNVs involved in biological or pathological processes. Despite the growing demand to filter and classify CNVs by factors such as frequency in population, biological features, and function, surprisingly, no online web server for CNV annotations has been made available to the research community. Here, we present CNVannotator, a web server that accepts an input set of human genomic positions in a user-friendly tabular format. CNVannotator can perform genomic overlaps of the input coordinates using various functional features, including a list of the reported 356,817 common CNVs, 181,261 disease CNVs, as well as, 140,342 SNPs from genome-wide association studies. In addition, CNVannotator incorporates 2,211,468 genomic features, including ENCODE regulatory elements, cytoband, segmental duplication, genome fragile site, pseudogene, promoter, enhancer, CpG island, and methylation site. For cancer research community users, CNVannotator can apply various filters to retrieve a subgroup of CNVs pinpointed in hundreds of tumor suppressor genes and oncogenes. In total, 5,277,234 unique genomic coordinates with functional features are available to generate an output in a plain text format that is free to download. In summary, we provide a comprehensive web resource for human CNVs. The annotated results along with the server can be accessed at http://bioinfo.mc.vanderbilt.edu/CNVannotator/.

Tumor suppressor genes associated with drug resistance in ovarian cancer (review)

Ovarian cancer is a fatal gynecological cancer and a major cause of cancer-related mortality worldwide. The main limitation to a successful treatment for ovarian cancer is the development of drug resistance to combined chemotherapy. Tumor suppressor genes (TSGs) are wild-type alleles of genes which play regulatory roles in diverse cellular activities, and whose loss of function contributes to the development of cancer. It has been demonstrated that TSGs contribute to drug resistance in several types of solid tumors. However, an overview of the contribution of TSGs to drug resistance in ovarian cancer has not previously been reported. In this study, 15 TSGs responding to drug resistance in ovarian cancer were reviewed to determine the relationship of TSGs with ovarian cancer drug resistance. Furthermore, gene/protein-interaction and bio-association analysis were performed to demonstrate the associations of these TSGs and to mine the potential drug resistance-related genes in ovarian cancer. We observed that the 15 TSGs had close interactions with each other, suggesting that they may contribute to drug resistance in ovarian cancer as a group. Five pathways/processes consisting of DNA damage, apoptosis, cell cycle, DNA binding and methylation may be the key ways with which TSGs participate in the regulation of drug resistance. In addition, ubiquitin C (UBC) and six additional TSGs including the adenomatous polyposis coli gene (APC), death associated protein kinase gene (DAPK), pleiomorphic adenoma gene-like 1 (PLAGL1), retinoblastoma susceptibility gene (RB1), a gene encoding an apoptosis-associated speck-like protein (PYCARD/ASC) and tumor protein 63 (TP63), which had close interactions with the 15 TSGs, are potential drug resistance-related genes in ovarian cancer.

TSGene: a web resource for tumor suppressor genes

Tumor suppressor genes (TSGs) are guardian genes that play important roles in controlling cell proliferation processes such as cell-cycle checkpoints and inducing apoptosis. Identification of these genes and understanding their functions are critical for further investigation of tumorigenesis. So far, many studies have identified numerous TSGs and illustrated their functions in various types of tumors or normal samples. Furthermore, accumulating evidence has shown that non-coding RNAs can act as TSGs to prevent the tumorigenesis processes. Therefore, there is a growing demand to integrate TSGs with large-scale experimental evidence (e.g. gene expression and epigenetic signatures) to provide a comprehensive resource for further investigation of TSGs and their molecular mechanisms in cancer. To achieve this goal, we first developed a comprehensive literature-based database called TSGene (tumor suppressor gene database), freely available at http://bioinfo.mc.vanderbilt.edu/TSGene/. In the current release, TSGene contains 716 human (637 protein-coding and 79 non-coding genes), 628 mouse and 567 rat TSGs curated from UniProtKB, the Tumor Associated Gene database and 5795 PubMed abstracts. Additionally, the TSGene provides detailed annotations for each TSG, such as cancer mutations, gene expressions, methylation sites, TF regulations and protein–protein interactions.