ECGene: A Literature-Based Knowledgebase of Endometrial Cancer Genes

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

DES-Tcell is a knowledgebase for exploring immunology-related literature

T-cells are a subtype of white blood cells circulating throughout the body, searching for infected and abnormal cells. They have multifaceted functions that include scanning for and directly killing cells infected with intracellular pathogens, eradicating abnormal cells, orchestrating immune response by activating and helping other immune cells, memorizing encountered pathogens, and providing long-lasting protection upon recurrent infections. However, T-cells are also involved in immune responses that result in organ transplant rejection, autoimmune diseases, and some allergic diseases. To support T-cell research, we developed the DES-Tcell knowledgebase (KB). This KB incorporates text- and data-mined information that can expedite retrieval and exploration of T-cell relevant information from the large volume of published T-cell-related research. This KB enables exploration of data through concepts from 15 topic-specific dictionaries, including immunology-related genes, mutations, pathogens, and pathways. We developed three case studies using DES-Tcell, one of which validates effective retrieval of known associations by DES-Tcell. The second and third case studies focuses on concepts that are common to Grave’s disease (GD) and Hashimoto’s thyroiditis (HT). Several reports have shown that up to 20% of GD patients treated with antithyroid medication develop HT, thus suggesting a possible conversion or shift from GD to HT disease. DES-Tcell found miR-4442 links to both GD and HT, and that miR-4442 possibly targets the autoimmune disease risk factor CD6, which provides potential new knowledge derived through the use of DES-Tcell. According to our understanding, DES-Tcell is the first KB dedicated to exploring T-cell-relevant information via literature-mining, data-mining, and topic-specific dictionaries.

Integrative analysis of common genes and driver mutations implicated in hormone stimulation for four cancers in women

Cancer is one of the leading cause of death of women worldwide, and breast, ovarian, endometrial and cervical cancers contribute significantly to this every year. Developing early genetic-based diagnostic tools may be an effective approach to increase the chances of survival and provide more treatment opportunities. However, the current cancer genetic studies are mainly conducted independently and, hence lack of common driver genes involved in cancers in women. To explore the potential common molecular mechanism, we integrated four comprehensive literature-based databases to explore the shared implicated genetic effects. Using a total of 460 endometrial, 2,068 ovarian, 2,308 breast and 537 cervical cancer-implicated genes, we identified 52 genes which are common in all four types of cancers in women. Furthermore, we defined their potential functional role in endogenous hormonal regulation pathways within the context of four cancers in women. For example, these genes are strongly associated with hormonal stimulation, which may facilitate rapid diagnosis and treatment management decision making. Additional mutational analyses on combined the cancer genome atlas datasets consisting of 5,919 gynaecological and breast tumor samples were conducted to identify the frequently mutated genes across cancer types. For those common implicated genes for hormonal stimulants, we found that three quarter of 5,919 samples had genomic alteration with the highest frequency in MYC (22%), followed by NDRG1 (19%), ERBB2 (14%), PTEN (13%), PTGS2 (13%) and CDH1 (11%). We also identified 38 hormone related genes, eight of which are associated with the ovulation cycle. Further systems biology approach of the shared genes identified 20 novel genes, of which 12 were involved in the hormone regulation in these four cancers in women. Identification of common driver genes for hormone stimulation provided an unique angle of involving the potential of the hormone stimulants-related genes for cancer diagnosis and prognosis.

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.

Expression of epithelial-mesenchymal transition-related genes increases with copy number in multiple cancer types

Epithelial-mesenchymal transition (EMT) is a cellular process through which epithelial cells transform into mesenchymal cells. EMT-implicated genes initiate and promote cancer metastasis because mesenchymal cells have greater invasive and migration capacities than epithelial cells. In this pan-cancer analysis, we explored the relationship between gene expression changes and copy number variations (CNVs) for EMT-implicated genes. Based on curated 377 EMT-implicated genes from the literature, we identified 212 EMT-implicated genes associated with more frequent copy number gains (CNGs) than copy number losses (CNLs) using data from The Cancer Genome Atlas (TCGA). Then by correlating these CNV data with TCGA gene expression data, we identified 71 EMT-implicated genes with concordant CNGs and gene up-regulation in 20 or more tumor samples. Of those, 14 exhibited such concordance in over 110 tumor samples. These 14 genes were predominantly apoptosis regulators, which may implies that apoptosis is critical during EMT. Moreover, the 71 genes with concordant CNG and up-regulation were largely involved in cellular functions such as phosphorylation cascade signaling. This is the first observation of concordance between CNG and up-regulation of specific genes in hundreds of samples, which may indicate that somatic CNGs activate gene expression by increasing the gene dosage.

Constructing a comprehensive gene co-expression based interactome in Bos taurus

Integrating genomic information into cattle breeding is an important approach to exploring genotype-phenotype relationships for complex traits related to diary and meat production. To assist with genomic-based selection, a reference map of interactome is needed to fully understand and identify the functional relevant genes. To this end, we constructed a co-expression analysis of 92 tissues and this represents the systematic exploration of gene-gene relationship in Bos taurus. By using robust WGCNA (Weighted Gene Correlation Network Analysis), we described the gene co-expression network of 5,000 protein-coding genes with majority variations in expression across 92 tissues. Further module identifications found 55 highly organized functional clusters representing diverse cellular activities. To demonstrate the re-use of our interaction for functional genomics analysis, we extracted a sub-network associated with DNA binding genes in Bos taurus. The subnetwork was enriched within regulation of transcription from RNA polymerase II promoter representing central cellular functions. In addition, we identified 28 novel linker genes associated with more than 100 DNA binding genes. Our WGCNA-based co-expression network reconstruction will be a valuable resource for exploring the molecular mechanisms of incompletely characterized proteins and for elucidating larger-scale patterns of functional modulization in the Bos taurus genome.

Long non-coding RNA00364 represses hepatocellular carcinoma cell proliferation via modulating p-STAT3-IFIT2 signaling axis

The effects of long non-coding RNAs (lncRNAs) on hepatocellular carcinoma (HCC) remain largely unclear. In this study, we identified an interferon (IFN)-γ-induced LncRNA, LncRNA00364, in HCC by microarray. LncRNA00364 displays lower expression in HCC tumor samples compared to paired normal controls. Overexpression of LncRNA00364 inhibits cell proliferation, G1/S cell cycle progression and promotes apoptosis in HCC cell lines. Consistently, LncRNA00364 overexpression leads to decreased HCC tumor formation in vivo. Mechanistically, LncRNA00364 specifically binds with STAT3, resulting in inhibition of STAT3 phosphorylation and therefore leads to upregulation of IFIT2. In a clinical setting, LncRNA00364 shows an independent prognostic indicator for overall survival and cumulative recurrence in HCC patients, and correlates with IFIT2. Therefore, our study provides new insights into a novel therapeutic avenue targeting the LncRNA00364 signaling axis in HCC.

Copy number alteration of neuropeptides and receptors in multiple cancers

Neuropeptides are peptide hormones used as chemical signals by the neuroendocrine system to communicate between cells. Recently, neuropeptides have been recognized for their ability to act as potent cellular growth factors on many cell types, including cancer cells. However, the molecular mechanism for how this occurs is unknown. To clarify the relationship between neuropeptides and cancer, we manually curated a total of 127 human neuropeptide genes by integrating information from the literature, homologous sequences, and database searches. Using human ligand-receptor interaction data, we first identified an interactome of 226 interaction pairs between 93 neuropeptides and 133 G-protein coupled receptors. We further identified four neuropeptide-receptor functional modules with ten or more genes, all of which were highly mutated in multiple cancers. We have identified a number of neuropeptide signaling systems with both oncogenic and tumour-suppressing roles for cancer progression, such as the insulin-like growth factors. By focusing on the neuroendocrine prostate cancer mutational data, we found prevalent amplification of neuropeptide and receptors in about 72% of samples. In summary, we report the first observation of abundant copy number variations on neuropeptides and receptors, which will be valuable for the design of peptide-based cancer prognosis, diagnosis and treatment.

Meta-analysis of gene expression studies in endometrial cancer identifies gene expression profiles associated with aggressive disease and patient outcome

Although endometrioid endometrial cancer (EEC; comprising ~80% of all endometrial cancers diagnosed) is typically associated with favourable patient outcome, a significant portion (~20%) of women with this subtype will relapse. We hypothesised that gene expression predictors of the more aggressive non-endometrioid endometrial cancers (NEEC) could be used to predict EEC patients with poor prognosis. To explore this hypothesis, we performed meta-analysis of 12 gene expression microarray studies followed by validation using RNA-Seq data from The Cancer Genome Atlas (TCGA) and identified 1,253 genes differentially expressed between EEC and NEEC. Analysis found 121 genes were associated with poor outcome among EEC patients. Forward selection likelihood-based modelling identified a 9-gene signature associated with EEC outcome in our discovery RNA-Seq dataset which remained significant after adjustment for clinical covariates, but was not significant in a smaller RNA-Seq dataset. Our study demonstrates the value of employing meta-analysis to improve the power of gene expression microarray data, and highlight genes and molecular pathways of importance for endometrial cancer therapy.

REGene: a literature-based knowledgebase of animal regeneration that bridge tissue regeneration and cancer

Regeneration is a common phenomenon across multiple animal phyla. Regeneration-related genes (REGs) are critical for fundamental cellular processes such as proliferation and differentiation. Identification of REGs and elucidating their functions may help to further develop effective treatment strategies in regenerative medicine. So far, REGs have been largely identified by small-scale experimental studies and a comprehensive characterization of the diverse biological processes regulated by REGs is lacking. Therefore, there is an ever-growing need to integrate REGs at the genomics, epigenetics, and transcriptome level to provide a reference list of REGs for regeneration and regenerative medicine research. Towards achieving this, we developed the first literature-based database called REGene (REgeneration Gene database). In the current release, REGene contains 948 human (929 protein-coding and 19 non-coding genes) and 8445 homologous genes curated from gene ontology and extensive literature examination. Additionally, the REGene database provides detailed annotations for each REG, including: gene expression, methylation sites, upstream transcription factors, and protein-protein interactions. An analysis of the collected REGs reveals strong links to a variety of cancers in terms of genetic mutation, protein domains, and cellular pathways. We have prepared a web interface to share these regeneration genes, supported by refined browsing and searching functions at http://REGene.bioinfo-minzhao.org/.