Yining Liu

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.

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.

Pedican: an online gene resource for pediatric cancers with literature evidence

Pediatric cancer (PC), that is cancer occurring in children, is the leading cause of death among children worldwide, with an incidence of 175,000 per year. Elucidating the genetic abnormalities and underlying cellular mechanisms may provide less toxic curative treatments. Therefore, it is important to understand the pathology of pediatric cancer at the genetic, genomic and epigenetic level. To unveil the cellular complexity of PC, we have developed a database of pediatric cancers (Pedican), the first literature-based pediatric gene data resource by comprehensive literature curation and data integration. In the current release, Pedican contains 735 human genes, 88 gene fusion and 24 chromosome abnormal events curated from 2245 PubMed abstracts. Pedican provides detailed annotations for each gene, such as Entrez gene information, involved pathways, protein–protein interactions, mutations, gene expression, methylation sites, TF regulation, and post-translational modification. Additionally Pedican has a user-friendly web interface, which allows sophisticated text query, sequence searches, and browsing by highlighted literature evidence and hundreds of cancer types. Overall, our curated pediatric cancer-related gene list maps the genomic and cellular landscape for various pediatric cancers, providing a valuable resource for further experiment design. The Pedican is available at http://pedican.bioinfo-minzhao.org/.

A gene browser of colorectal cancer with literature evidence and pre-computed regulatory information to identify key tumor suppressors and oncogenes.

Colorectal cancer (CRC) is a cancer of growing incidence that associates with a high mortality rate worldwide. There is a poor understanding of the heterogeneity of CRC with regard to causative genetic mutations and gene regulatory mechanisms. Previous studies have identified several susceptibility genes in small-scale experiments. However, the information has not been comprehensively and systematically compiled and interpreted. In this study, we constructed the gbCRC, the first literature-based gene resource for investigating CRC-related human genes. The features of our database include: (i) manual curation of experimentally-verified genes reported in the literature; (ii) comprehensive integration of five reliable data sources; and (iii) pre-computed regulatory patterns involving transcription factors, microRNAs and long non-coding RNAs. In total, 2067 genes associating with 2819 PubMed abstracts were compiled. Comprehensive functional annotations associated with all the genes, including gene expression profiles, homologous genes in other model species, protein-protein interactions, somatic mutations, and potential methylation sites. These comprehensive annotations and this pre-computed regulatory information highlighted the importance of the gbCRC with regard to the unexplored regulatory network of CRC. This information is available in a plain text format that is free to download.

GCGene: a gene resource for gastric cancer with literature evidence.

Gastric cancer (GC) is the fifth most common cancer and third leading cause of cancer-related deaths worldwide. Its lethality primarily stems from a lack of detection strategies for early stages of GC and a lack of noninvasive detection strategies for advanced stages. The development of early diagnostic biomarkers largely depends on understanding the biological pathways and regulatory mechanisms associated with putative GC genes. Unfortunately, the GC-implicated genes that have been identified thus far are scattered among thousands of published studies, and no systematic summary is available, which hinders the development of a large-scale genetic screen. To provide a publically accessible resource tool to meet this need, we constructed a literature-based database GCGene (Gastric Cancer Gene database) with comprehensive annotations supported by a user-friendly website. In the current release, we have collected 1,815 unique human genes including 1,678 protein-coding and 137 non-coding genes curated from extensive examination of 3,142 PubMed abstracts. The resulting database has a convenient web-based interface to facilitate both textual and sequence-based searches. All curated genes in GCGene are downloadable for advanced bioinformatics data mining. Gene prioritization was performed to rank the relative relevance of these genes in GC development. The 100 top-ranked genes are highly mutated according to the cohort of published studies we reviewed. By conducting a network analysis of these top-ranked GC-associated genes in the human interactome, we were able to identify strong links between 8 highly connected genes with low expression and patient survival time. GCGene is freely available to academic users at http://gcgene.bioinfo-minzhao.org/.

Identification of novel prognosis-related genes associated with cancer using integrative network analysis

Prognosis identifies the seriousness and the chances of survival of a cancer patient. However, it remains a challenge to identify the key cancer genes in prognostic studies. In this study, we collected 2064 genes that were related to prognostic studies by using gene expression measurements curated from published literatures. Among them, 1820 genes were associated with copy number variations (CNVs). The further functional enrichment on 889 genes with frequent copy number gains (CNGs) revealed that these genes were significantly associated with cancer pathways including regulation of cell cycle, cell differentiation and mitogen-activated protein kinase (MAPK) cascade. We further conducted integrative analyses of CNV and their target genes expression using the data from matched tumour samples of The Cancer Genome Atlas (TCGA). Ultimately, 95 key prognosis-related genes were extracted, with concordant CNG events and increased up-regulation in at least 300 tumour samples. These genes, and the number of samples in which they were found, included: ACTL6A (399), ATP6V1C1 (425), EBAG9 (412), FADD (308), MTDH (377), and SENP5 (304). This study provides the first observation of CNV in prognosis-related genes across pan-cancer. The systematic concordance between CNG and up-regulation of gene expression in these novel prognosis-related genes may indicate their prognostic significance.

A pan-cancer study of copy number gain and up-regulation in human oncogenes

Aim: There has been limited research on CNVs in oncogenes and we conducted a systematic pan‐cancer analysis of CNVs and their gene expression changes. The aim of the present study was to provide an insight into the relationships between gene expression and oncogenesis. Main methods: We collected all the oncogenes from ONGene database and overlapped with CNVs TCGA tumour samples from Catalogue of Somatic Mutations in Cancer database. We further conducted an integrative analysis of CNV with gene expression using the data from the matched TCGA tumour samples. Key findings: From our analysis, we found 637 oncogenes associated with CNVs in 5900 tumour samples. There were 204 oncogenes with frequent copy number of gain (CNG). These 204 oncogenes were enriched in cancer‐related pathways including the MAPK cascade and Ras GTPases signalling pathways. By using corresponding tumour samples data to perform integrative analyses of CNVs and gene expression changes, we identified 95 oncogenes with consistent CNG occurrence and up‐regulation in the tumour samples, which may represent the recurrent driving force for oncogenesis. Surprisingly, eight oncogenes shown concordant CNG and gene up‐regulation in at least 250 tumour samples: INTS8 (355), ECT2 (326), LSM1 (310), DDHD2 (298), COPS5 (286), EIF3E (281), TPD52 (258) and ERBB2 (254). Significance: As the first report about abundant CNGs on oncogene and concordant change of gene expression, our results may be valuable for the design of CNV‐based cancer diagnostic strategy.

dbLGL: an online leukemia gene and literature database for the retrospective comparison of adult and childhood leukemia genetics with literature evidence

Abstract Leukemia is a group of cancers with increased numbers of immature or abnormal leucocytes that originated in the bone marrow and other blood-forming organs. The development of differentially diagnostic biomarkers for different subtypes largely depends on understanding the biological pathways and regulatory mechanisms associated with leukemia-implicated genes. Unfortunately, the leukemia-implicated genes that have been identified thus far are scattered among thousands of published studies, and no systematic summary of the differences between adult and childhood leukemia exists with regard to the causative genetic mutations and genetic mechanisms of the various subtypes. In this study, we performed a systematic literature review of those susceptibility genes reported in small-scale experiments and built an online gene database containing a total of 1805 leukemia-associated genes, available at http://soft.bioinfo-minzhao.org/lgl/. Our comparison of genes from the four primary subtypes and between adult and childhood cases identified a number of potential genes related to patient survival. These curated genes can satisfy a growing demand for further integrating genomics screening for leukemia-associated low-frequency mutated genes. Database URL: http://soft.bioinfo-minzhao.org/lgl/

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

BackgroundCancer 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.ResultsTo 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.ConclusionsAs 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/.

Integrative analysis to identify oncogenic gene expression changes associated with copy number variations of enhancer in ovarian cancer

Enhancers are short regulatory regions (50-1500 bp) of DNA that control the tissue-specific activation of gene expression by long distance interaction with targeting gene regions. Recently, genome-wide identification of enhancers in diverse tissues and cell lines was achieved using high-throughput sequencing. Enhancers have been associated with malfunctions in cancer development resulting from point mutations in regulatory regions. However, the potential impact of copy number variations (CNVs) on enhancer regions is unknown. To learn more about the relationship between enhancers and cancer, we integrated the CNVs data on enhancers and explored their targeting gene expression pattern in high-grade ovarian cancer. Using human enhancer-gene interaction data with 13,691 interaction pairs between 7,905 enhancers and 5,297 targeting genes, we found that the 2,910 copy number gain events of enhancer are significantly correlated with the up-regulation of targeting genes. We further identified that a number of highly mutated super-enhancers, with concordant gene expression change on their targeting genes. We also identified 18 targeting genes by super-enhancers with prognostic significance for ovarian cancer, such as the tumour suppressor CDKN1B. We are the first to report that abundant copy number variations on enhancers could change the expression of their targeting genes which would be valuable for the design of enhancer-based cancer treatment strategy.