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BACKGROUND: Microsatellite instability-high (MSI-H) is a unique genomic status in many cancers. However, its role in the genomic features and immunotherapy in cholangiocarcinoma (CCA) is unclear. This study aimed to systematically investigate the genomic characterization and immunotherapy efficacy of MSI-H patients with CCA. METHODS: We enrolled 887 patients with CCA in this study. Tumor samples were collected for next-generation sequencing. Differences in genomic alterations between the MSI-H and microsatellite stability (MSS) groups were analyzed. We also investigated the survival of PD-1 inhibitor-based immunotherapy between two groups of 139 patients with advanced CCA. RESULTS: Differential genetic alterations between the MSI-H and MSS groups included mutations in ARID1A, ACVR2A, TGFBR2, KMT2D, RNF43, and PBRM1 which were enriched in MSI-H groups. Patients with an MSI-H status have a significantly higher tumor mutation burden (TMB) (median 41.7 vs. 3.1 muts/Mb, P < 0.001) and more positive programmed death ligand 1 (PD-L1) expression (37.5% vs. 11.9%, P < 0.001) than those with an MSS status. Among patients receiving PD-1 inhibitor-based therapy, those with MSI-H had a longer median overall survival (OS, hazard ratio (HR) = 0.17, P = 0.001) and progression-free survival (PFS, HR = 0.14, P < 0.001) than patients with MSS. Integrating MSI-H and PD-L1 expression status (combined positive score ≥ 5) could distinguish the efficacy of immunotherapy. CONCLUSIONS: MSI-H status was associated with a higher TMB value and more positive PD-L1 expression in CCA tumors. Moreover, in patients with advanced CCA who received PD-1 inhibitor-based immunotherapy, MSI-H and positive PD-L1 expression were associated with improved both OS and PFS. TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov on 07/01/2017 (NCT03892577).
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Neoplasias de los Conductos Biliares , Colangiocarcinoma , Humanos , Inestabilidad de Microsatélites , Antígeno B7-H1/genética , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Colangiocarcinoma/genética , Colangiocarcinoma/terapia , Mutación , Neoplasias de los Conductos Biliares/genética , Neoplasias de los Conductos Biliares/terapia , Conductos Biliares Intrahepáticos/metabolismo , Inmunoterapia , Genómica , Biomarcadores de Tumor/genéticaRESUMEN
BACKGROUND: Diabetic nephropathy (DN) affects about 40% of diabetes mellitus (DM) patients and is the leading cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD) all over the world, especially in high- and middle-income countries. Most DN has been present for years before it is diagnosed. Currently, the treatment of DN is mainly to prevent or delay disease progression. Although many important molecules have been discovered in hypothesis-driven research over the past two decades, advances in DN management and new drug development have been very limited. Moreover, current animal/cell models could not replicate all the features of human DN, while the development of Epigenetics further demonstrates the complexity of the mechanism of DN progression. To capture the key pathways and molecules that actually affect DN progression from numerous published studies, we collected and analyzed human DN prognostic markers (independent risk factors for DN progression). METHODS: One hundred and fifty-one DN prognostic markers were collected manually by reading 2365 papers published between 01/01/2002 and 12/15/2018. One hundred and fifteen prognostic markers of other four common CKDs were also collected. GO and KEGG enrichment analysis was done using g:Profiler, and a relationship network was built based on the KEGG database. Tissue origin distribution was derived mainly from The Human Protein Atlas (HPA), and a database of these prognostic markers was constructed using PHP Version 5.5.15 and HTML5. RESULTS: Several pathways were significantly enriched corresponding to different end point events. It is shown that the TNF signaling pathway plays a role through the process of DN progression and adipocytokine signaling pathway is uniquely enriched in ESRD. Molecules, such as TNF, IL6, SOD2, etc. are very important for DN progression, among which, it seems that "AGER" plays a pivotal role in the mechanism. A database, dbPKD, was constructed containing all the collected prognostic markers. CONCLUSIONS: This study developed a database for all prognostic markers of five common CKDs, offering some bioinformatics analyses of DN prognostic markers, and providing useful insights towards understanding the fundamental mechanism of human DN progression and for identifying new therapeutic targets.
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Bases de Datos como Asunto , Nefropatías Diabéticas/epidemiología , Nefropatías Diabéticas/patología , Progresión de la Enfermedad , Insuficiencia Renal Crónica/patología , Biomarcadores/metabolismo , Diabetes Mellitus Tipo 1/genética , Diabetes Mellitus Tipo 2/genética , Determinación de Punto Final , Humanos , Pronóstico , Factores de Riesgo , Interfaz Usuario-ComputadorRESUMEN
BACKGROUND: Primary liver cancer (PLC) is the third largest contributor to cancer mortality in the world. PLC is a heterogeneous disease that encompasses several biologically distinct subtypes including hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC) and combined hepatocellular-cholangiocarcinoma (CHC). CHC is a distinct, albeit rare, subtype of PLC and is comprised of cells with histopathological features of both HCC and ICC. Several studies have focused on the mutation and expression landscapes of HCC and ICC. However, studies of CHC were rare. OBJECTIVE: The aim of the current study was to identify genetic and gene expression alterations in the carcinogenesis and development of CHC and ICC in the Chinese population. Unraveling both similar and differing patterns among these subtypes may help to identify personalized medicine approaches that could improve patient survival. METHODS: Whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-seq were performed on 10 ICC and 10 CHC samples, matched with adjacent non-tumor liver tissue specimens. Comparative analysis was performed using HCC datasets from The Cancer Genome Atlas (TCGA). RESULTS: Mutational and transcriptional landscapes of CHC and ICC were clearly delineated. TP53 and CTNNB1 were identified as exhibiting mutations in CHC. ARID1A, PBRM1, and IDH1 were frequently mutated in ICC. RYR3, FBN2, and KCNN3 are associated with cell migration and metastasis and might be driver genes in CHC. KCNN3 was identified as also exhibiting mutations in ICC. The ECM-receptor interaction pathway associated fibrogenic hepatic progenitor cell differentiation and liver fibrosis may play an important role in carcinogenesis of PLC. Chromatin remodeling and chromosome organization are key processes in carcinogenesis and development in PLC. P53 related pathways showed alterations in CHC and HCC. Inflammation may be a key factor involved in ICC carcinogenesis. CONCLUSION: CHC and ICC are different subtypes of PLC. This study discusses predominantly the molecular genetic details of PLC subtypes and highlights the need for an accurate diagnosis and treatment of specific PLC subtypes to optimize patient management.
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Neoplasias de los Conductos Biliares , Carcinoma Hepatocelular , Colangiocarcinoma , Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Genoma Humano , Neoplasias Hepáticas , Transcriptoma , Neoplasias de los Conductos Biliares/genética , Neoplasias de los Conductos Biliares/metabolismo , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/metabolismo , Colangiocarcinoma/genética , Colangiocarcinoma/metabolismo , Estudio de Asociación del Genoma Completo , Humanos , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/metabolismoRESUMEN
BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignant cancers with a poor prognosis. For decades, more and more biomarkers were found to effect on HCC prognosis, but these studies were scattered and there were no unified identifiers. Therefore, we built the database of prognostic biomarkers and models for hepatocellular carcinoma (dbPHCC). METHODS: dbPHCC focuses on biomarkers which were related to HCC prognosis by traditional experiments rather than high-throughput technology. All of the prognostic biomarkers came from literatures issued during 2002 to 2014 in PubMed and were manually selected. dbPHCC collects comprehensive information of candidate biomarkers and HCC prognosis. RESULTS: dbPHCC mainly contains 567 biomarkers: 323 proteins, 154 genes, and 90 microRNAs. For each biomarker, the reference information, experimental conditions, and prognostic information are shown. Based on two available patient cohort data sets, an exemplified prognostic model was constructed using 15 phosphotransferases in dbPHCC. The web interface does not only provide a full range of browsing and searching, but also provides online analysis tools. dbPHCC is available at http://lifecenter.sgst.cn/dbphcc/ CONCLUSIONS: dbPHCC provides a comprehensive and convenient search and analysis platform for HCC prognosis research. GENERAL SIGNIFICANCE: dbPHCC is the first database to focus on experimentally verified individual biomarkers, which are related to HCC prognosis. Prognostic markers in dbPHCC have the potential to be therapeutic drug targets and may help in designing new treatments to improve survival of HCC patients. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.
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Biomarcadores de Tumor/genética , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/patología , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/patología , Bases de Datos Factuales , Regulación Neoplásica de la Expresión Génica/genética , Humanos , MicroARNs/genética , PronósticoRESUMEN
HeLa cell line, which was derived from cervical carcinoma, provides an idea platform to study both the integration of human papillomavirus and the massive mutations occurring on the cancer cell genome. Proteogenomics is a field with the intersection of proteomics and genomics to perform gene annotation and identify gene mutation. In this work, we first identified the SNV/INDEL, structural variation (SV), and virus infection/integration events from RNA-Seq data of HeLa cell line; then, by applying proteogenomics strategy, we were able to detect some of the genomic events with the tandem mass spectrometry (MS/MS) data from the same sample. Furthermore, some of the mutated peptides were experimentally validated using multiple reaction monitoring technology. The integrated analysis of the RNA-Seq and MS/MS data not only renders the discovery of HeLa cell genome variations more credible but also illustrates a practical workflow for protein-coding mutation discovery in cancer-related studies.
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Variación Genética , Papillomaviridae/genética , Papillomaviridae/fisiología , Proteómica/métodos , Integración Viral/fisiología , Células HeLa , Humanos , Anotación de Secuencia Molecular , Mutación/genética , Análisis de Secuencia de ARN/métodos , Espectrometría de Masas en Tándem/métodosRESUMEN
Previously, the different mechanisms of HBV infection and HCV infection were studied experimentally. Multiple studies also compared the differential network between HBV induced HCC and HCV induced HCC based on gene expression data. However network level comparison combining viral-human interaction network and dysfunctional protein interaction network for HBV and HCV-HCC has rarely been done before. In this work we did some pioneer job in construction of HBV/HCV viral dysfunctional network in HCC, in hope of investigating viral infection impact on the change of genome expression and eventually, the development of HCC. We found that HBx, the main HBV viral protein, directly acted on the gene groups of cell cycle, which could perfectly explain the dominant cell proliferation effect shown in the dysfunctional network of HBV-HCC. On the other hand, multiple important HCV viral proteins including CORE, NS3 and NS5A were found to target very important cancer related proteins such as TP53 and SMAD3, but no direct targeting to major immune response or inflammation related proteins. Therefore the dominant activation of immune response and inflammation related pathways shown in dysfunctional network of HCV-HCC might not be a direct effect of HCV infection. They might have been an indirect demonstration of activated cancer promoting pathways. Similar approaches may as well be applied to other important virus infection caused human diseases to help elucidate the mechanisms of virus-host interaction, and even help with investigations on anti-virus based therapies. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology & Clinical Implications.
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Hepatitis C/genética , Interacciones Huésped-Parásitos , Mapas de Interacción de Proteínas , Proteínas Virales/genética , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/metabolismo , Regulación Viral de la Expresión Génica , Hepacivirus/genética , Hepatitis B/genética , Hepatitis B/virología , Virus de la Hepatitis B/genética , Hepatitis C/virología , Humanos , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/metabolismo , Proteínas Virales/química , Proteínas Virales/clasificaciónRESUMEN
BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most highly malignant and lethal cancers of the world. Its pathogenesis has been reported to be multi-factorial, and the molecular carcinogenesis of HCC can not be attributed to just a few individual genes. Based on the microRNA and mRNA expression profiling of normal liver tissues, pericancerous hepatocellular tissues and hepatocellular carcinoma tissues, we attempted to find prognosis related gene sets for HCC patients. RESULTS: We identified differentially expressed genes (DEG) from three comparisons: Cancer/Normal, Cancer/Pericancerous and Pericancerous/Normal. GSEA (gene set enrichment analysis) were performed. Based on the enriched gene sets of GO terms, pathways and transcription factor targets, it was found that the genome instability and cell proliferation increased while the metabolism and differentiation decreased in HCC tissues. The expression profile of DEGs in each enriched gene set was used to correlate to the postoperative survival time of HCC patients. Nine gene sets were found to prognostic correlation. Furthermore, after substituting DEG-targeting-microRNA for DEG members of each gene set, two gene sets with the microRNA expression profiles were obtained that had prognostic potential. CONCLUSIONS: The malignancy of HCC could be represented by gene sets, and pericancerous liver exhibits important characteristics of liver cancer. The expression level of gene sets not only in HCC but also in the pericancerous liver showed potential for prognosis implying an option for HCC prognosis at an early stage. Additionally, the gene-targeting-microRNA expression profiles also showed prognostic potential, demonstrating that the multi-factorial molecular pathogenesis of HCC is contributed by various genes and microRNAs.
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Biomarcadores de Tumor/genética , Carcinoma Hepatocelular/genética , Neoplasias Hepáticas/genética , Hígado/metabolismo , MicroARNs/genética , ARN Mensajero/genética , Carcinoma Hepatocelular/diagnóstico , Carcinoma Hepatocelular/cirugía , Diferenciación Celular , Cromosomas Humanos Par 1 , Perfilación de la Expresión Génica/métodos , Regulación Neoplásica de la Expresión Génica , Inestabilidad Genómica , Humanos , Neoplasias Hepáticas/diagnóstico , Neoplasias Hepáticas/cirugía , Metabolismo , PronósticoRESUMEN
The global insight into the relationships between miRNAs and their regulatory influences remains poorly understood. And most of complex diseases may be attributed to certain local areas of pathway (subpathway) instead of the entire pathway. Here, we reviewed the studies on miRNA regulations to pathways and constructed a bipartite miRNAs and subpathways network for systematic analyzing the miRNA regulatory influences to subpathways. We found that a small fraction of miRNAs were global regulators, environmental information processing pathways were preferentially regulated by miRNAs, and miRNAs had synergistic effect on regulating group of subpathways with similar function. Integrating the disease states of miRNAs, we also found that disease miRNAs regulated more subpathways than nondisease miRNAs, and for all miRNAs, the number of regulated subpathways was not in proportion to the number of the related diseases. Therefore, the study not only provided a global view on the relationships among disease, miRNA and subpathway, but also uncovered the function aspects of miRNA regulations and potential pathogenesis of complex diseases. A web server to query, visualize and download for all the data can be freely accessed at http://bioinfo.hrbmu.edu.cn/miR2Subpath.
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Algoritmos , Redes Reguladoras de Genes , MicroARNs/genética , Bases de Datos Genéticas , Humanos , Factores de Transcripción/genéticaRESUMEN
MOTIVATION: Alzheimer's disease (AD) is a severe neurodegenerative disease of the central nervous system that may be caused by perturbation of regulatory pathways rather than the dysfunction of a single gene. However, the pathology of AD has yet to be fully elucidated. RESULTS: In this study, we systematically analyzed AD-related mRNA and miRNA expression profiles as well as curated transcription factor (TF) and miRNA regulation to identify active TF and miRNA regulatory pathways in AD. By mapping differentially expressed genes and miRNAs to the curated TF and miRNA regulatory network as active seed nodes, we obtained a potential active subnetwork in AD. Next, by using the breadth-first-search technique, potential active regulatory pathways, which are the regulatory cascade of TFs, miRNAs and their target genes, were identified. Finally, based on the known AD-related genes and miRNAs, the hypergeometric test was used to identify active pathways in AD. As a result, nine pathways were found to be significantly activated in AD. A comprehensive literature review revealed that eight out of nine genes and miRNAs in these active pathways were associated with AD. In addition, we inferred that the pathway hsa-miR-146aâSTAT1âMYC, which is the source of all nine significantly active pathways, may play an important role in AD progression, which should be further validated by biological experiments. Thus, this study provides an effective approach to finding active TF and miRNA regulatory pathways in AD and can be easily applied to other complex diseases.
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Enfermedad de Alzheimer/genética , MicroARNs/genética , Factores de Transcripción/genética , Algoritmos , Enfermedad de Alzheimer/metabolismo , Perfilación de la Expresión Génica , Regulación de la Expresión Génica , Humanos , MicroARNs/metabolismo , Factores de Transcripción/metabolismoRESUMEN
MicroRNAs (miRNAs) are non-coding RNAs that play important roles in post-transcriptional regulation. Identification of miRNAs is crucial to understanding their biological mechanism. Recently, machine-learning approaches have been employed to predict miRNA precursors (pre-miRNAs). However, features used are divergent and consequently induce different performance. Thus, feature selection is critical for pre-miRNA prediction. We generated an optimized feature subset including 13 features using a hybrid of genetic algorithm and support vector machine (GA-SVM). Based on SVM, the classification performance of the optimized feature subset is much higher than that of the two feature sets used in microPred and miPred by five-fold cross-validation. Finally, we constructed the classifier miR-SF to predict the most recently identified human pre-miRNAs in miRBase (version 16). Compared with microPred and miPred, miR-SF achieved much higher classification performance. Accuracies were 93.97%, 86.21% and 64.66% for miR-SF, microPred and miPred, respectively. Thus, miR-SF is effective for identifying pre-miRNAs.
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Inteligencia Artificial , MicroARNs/genética , Precursores del ARN/genética , Análisis de Secuencia de ARN/métodos , Algoritmos , Secuencia de Bases , Biología Computacional , Bases de Datos de Ácidos Nucleicos , Humanos , Datos de Secuencia Molecular , Conformación de Ácido Nucleico , ARN Interferente Pequeño/genéticaRESUMEN
RhoA is a member of the RHO family GTPases and is associated with essential functions in gastric cancer. In this study, we identified a gastric cancer biomarker, termed the "regulation of RhoA activity panel" (RRAP). Patients with gastric cancer from The Cancer Genome Atlas database were divided into training (N=160) and validation (N=155) cohorts. A cohort of 109 Chinese gastric cancer patients was utilized as an independent validation. Patients with mutated RRAP showed significantly better overall survival than patients with wild type RRAP. We also analyzed the association between RRAP and the migration capacity, immune-related signatures, and the tumor microenvironment. RRAP-mutant tumors had a significantly lower degree of lymph node metastasis and lower activities of migration-related pathways. These tumors also showed significantly increased immune cell infiltration and cytotoxic activity. Furthermore, two independent patient cohorts who received immune checkpoint blockade therapy were assessed for RRAP mutant status. As expected, for both immunotherapy cohorts, higher response rates to immune checkpoint blockade therapy were observed in patients with RRAP-mutant tumors than in patients with wild type RRAP tumors. Overall, this study indicates that the RRAP gene set is a potential biomarker for gastric cancer prognosis and therapeutic selection.
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Carcinoma/genética , Regulación Neoplásica de la Expresión Génica/genética , Neoplasias Gástricas/genética , Microambiente Tumoral/genética , Proteína de Unión al GTP rhoA/genética , Adulto , Anciano , Anciano de 80 o más Años , Carcinoma/inmunología , Carcinoma/patología , Movimiento Celular/genética , Estudios de Cohortes , Inhibidor p27 de las Quinasas Dependientes de la Ciclina/genética , Femenino , Proteínas Activadoras de GTPasa/genética , Proteínas de Transporte de Glicina en la Membrana Plasmática/genética , Factores de Intercambio de Guanina Nucleótido/genética , Humanos , Metástasis Linfática , Masculino , Persona de Mediana Edad , Mutación , Proteínas Oncogénicas/genética , Pronóstico , Modelos de Riesgos Proporcionales , Proteínas Serina-Treonina Quinasas/genética , Proteínas Proto-Oncogénicas c-bcr/genética , Proteínas Proto-Oncogénicas c-vav/genética , Factores de Intercambio de Guanina Nucleótido Rho/genética , Neoplasias Gástricas/inmunología , Neoplasias Gástricas/patología , Microambiente Tumoral/inmunología , Proteínas Supresoras de Tumor/genética , Proteína de Unión al GTP cdc42/genética , Proteína de Unión al GTP rhoA/metabolismoRESUMEN
Dysregulation of microRNA (miRNA) is a frequent event in hepatocellular carcinoma (HCC), but little is known whether it is a bystander or an actual player on residual HCC metastasis during liver microenvironment remodeling initiated by hepatectomy. Methods: The differently expressed miRNAs and mRNAs were identified from RNA-seq data. Western blot, qRT-PCR, fluorescence in situ hybridization, immunofluorescence and immunohistochemical were used to detect the expression of miRNA and mRNA in cell lines and patient tissues. The biological functions were investigated in vitro and in vivo. Chromatin immunoprecipitation, proximity ligation and luciferase reporter assay were used to explore the specific binding of target genes. The expression of HGF/ERBB3 signaling was detected by Western blot. Results: In this study, HGF induced by hepatectomy was shown to promote metastasis of residual HCC cells. miR-17-5p and miR-20a-5p were confirmed to play inhibitory roles on HCC metastasis. And ERBB3 was found to be the common target of miR-17-5p and miR-20a-5p. HCC cells with lower levels of miR-17-5p and miR-20a-5p or higher level of ERBB3 were often more sensitive to response HGF stimuli and to facilitate metastatic colonization both in vitro and in vivo experimental systems. Furthermore, HGF reinforced ERBB3 expression by NF-κB transcriptional activity in a positive feedback loop. Of particular importance, HCC patients with lower levels of miR-17-5p and miR-20a-5p or higher level of ERBB3 had significantly shorter OS and PFS survivals after surgical resection. Conclusion: miR-17-5p and miR-20a-5p could suppress postoperative metastasis of hepatocellular carcinoma via blocking HGF/ERBB3-NF-κB positive feedback loop and offer a new probable strategy for metastasis prevention after HCC resection.
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Carcinoma Hepatocelular/metabolismo , Neoplasias Hepáticas/metabolismo , MicroARNs/fisiología , Metástasis de la Neoplasia , Transducción de Señal , Animales , Carcinoma Hepatocelular/cirugía , Línea Celular Tumoral , Movimiento Celular , Proliferación Celular , Estudios de Cohortes , Femenino , Regulación Neoplásica de la Expresión Génica , Hepatectomía , Factor de Crecimiento de Hepatocito/metabolismo , Humanos , Neoplasias Hepáticas/cirugía , Masculino , Ratones , Ratones Endogámicos BALB C , Persona de Mediana Edad , FN-kappa B/metabolismo , Receptor ErbB-3/metabolismoRESUMEN
AIM AND OBJECTIVE: Integrating multi-omics data to identify driver genes and key biological functions for tumorigenesis remains a major challenge. METHOD: A new computational pipeline was developed to identify the Driver Mutation-Differential Co-Expression (DM-DCE) modules based on dysfunctional networks across 11 TCGA cancers. RESULTS: Functional analyses provided insight into the properties of various cancers, and found common cellular signals / pathways of cancers. Furthermore, the corresponding network analysis identified conservations or interactions across different types of cancers, thus the crosstalk between the key signaling pathways, immunity and cancers was found. Clinical analysis also identified key prognostic / survival patterns. CONCLUSION: Taken together, our study sheds light on both cancer-specific and cross-cancer characteristics systematically.
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Biología Computacional , Redes Reguladoras de Genes , Neoplasias/genética , HumanosRESUMEN
OBJECTIVE: Synergistic drug combinations are promising therapies for cancer treatment. However, effective prediction of synergistic drug combinations is quite challenging as mechanisms of drug synergism are still unclear. Various features such as drug response, and target networks may contribute to prediction of synergistic drug combinations. In this study, we aimed to construct a computational model to predict synergistic drug combinations. METHODS: We designed drug physicochemical features and network features, including drug chemical structure similarity, target distance in protein-protein network and targeted pathway similarity. At the same time, we designed fifteen pharmacogenomics features using drug treated gene expression profiles based on the background of cancer-related biology network. Based on these eighteen features, we built a prediction model for Synergistic Drug combination using Random forest algorithm (SyDRa). RESULTS: Our model achieved a quite good performance with AUC value of 0.89 and Out-of-bag estimate error rate of 0.15 in training dataset. Using the random anti-cancer drug combinations which have transcriptional profile data in the Connectivity Map dataset as the testing dataset, we identified 28 potentially synergistic drug combinations, three out of which had been reported to be effective drug combinations by literatures. CONCLUSIONS: We studied eighteen features for drug combinations and built a computational model using random forest algorithm. The model was evaluated using an independent test dataset. Our model provides an efficient strategy to identify potentially synergistic drug combinations for cancer and may help reduce the search space for high-throughput synergistic drug combinations screening.
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Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Inteligencia Artificial , Biología Computacional/métodos , Neoplasias/tratamiento farmacológico , Transcriptoma/efectos de los fármacos , Protocolos de Quimioterapia Combinada Antineoplásica/efectos adversos , Simulación por Computador , Bases de Datos Genéticas , Sinergismo Farmacológico , Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Redes Reguladoras de Genes , Humanos , Neoplasias/genética , Neoplasias/metabolismo , Neoplasias/patología , Farmacogenética , Mapas de Interacción de Proteínas , Reproducibilidad de los Resultados , Transducción de Señal/efectos de los fármacosRESUMEN
Hepatocellular carcinoma (HCC) is one of the common malignant tumors. HCC gene regulatory network (HCC GRN), whose nodes consist of genes, miRNAs or TFs and whose edges consist of interaction relationships of nodes, is one of the important ways to study molecular mechanism of HCC. Based on various experimental data, types of HCC GRNs could be conducted such as TF-miRNA regulatory network. Integrating the studies of HCC GRN, TF-miRNA transcriptional regulatory network performs better in identifying core genes which play important roles in network disturbances. It is a trend that gene variations and transcriptional regulatory networks should be combined, however the corresponding research is almost blank. This review summarizes the source of HCC data sources, the classification, character, and research program of HCC GRN. Finally, according to present analysis and discussion of progress and research status of HCC GRN, we provide a useful reference for researchers.
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Carcinoma Hepatocelular/genética , Redes Reguladoras de Genes , Neoplasias Hepáticas/genética , Humanos , MicroARNs/genética , Factores de Transcripción/genéticaRESUMEN
The mechanism of cancer metastasis remains poorly understood. Using gene profiling of hepatocellular carcinoma (HCC) tissues, we have identified GOLM1 as a leading gene relating to HCC metastasis. GOLM1 expression is correlated with early recurrence, metastasis, and poor survival of HCC patients. Both gain- and loss-of-function studies determine that GOLM1 acts as a key oncogene by promoting HCC growth and metastasis. It selectively interacts with epidermal growth factor receptor (EGFR) and serves as a specific cargo adaptor to assist EGFR/RTK anchoring on the trans-Golgi network (TGN) and recycling back to the plasma membrane, leading to prolonged activation of the downstream kinases. These findings reveal the functional role of GOLM1, a Golgi-related protein, in EGFR/RTK recycling and metastatic progression of HCC.
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Carcinoma Hepatocelular/metabolismo , Receptores ErbB/metabolismo , Neoplasias Hepáticas/metabolismo , Proteínas de la Membrana/metabolismo , Adolescente , Adulto , Anciano , Animales , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/patología , Línea Celular Tumoral , Receptores ErbB/genética , Xenoinjertos , Humanos , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/patología , Masculino , Proteínas de la Membrana/biosíntesis , Proteínas de la Membrana/genética , Ratones , Ratones Endogámicos BALB C , Ratones Desnudos , Persona de Mediana Edad , Metástasis de la Neoplasia , Transfección , Regulación hacia Arriba , Adulto JovenRESUMEN
Adverse drug reactions (ADRs) are responsible for drug candidate failure during clinical trials. It is crucial to investigate biological pathways contributing to ADRs. Here, we applied a large-scale analysis to identify overrepresented ADR-pathway combinations through merging clinical phenotypic data, biological pathway data, and drug-target relations. Evaluation was performed by scientific literature review and defining a pathway-based ADR-ADR similarity measure. The results showed that our method is efficient for finding the associations between ADRs and pathways. To more systematically understand the mechanisms of ADRs, we constructed an ADR-pathway network and an ADR-ADR network. Through network analysis on biology and pharmacology, it was found that frequent ADRs were associated with more pathways than infrequent and rare ADRs. Moreover, environmental information processing pathways contributed most to the observed ADRs. Integrating the system organ class of ADRs, we found that most classes tended to interact with other classes instead of themselves. ADR classes were distributed promiscuously in all the ADR cliques. These results reflected that drug perturbation to a certain pathway can cause changes in multiple organs, rather than in one specific organ. Our work not only provides a global view of the associations between ADRs and pathways, but also is helpful to understand the mechanisms of ADRs.
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Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos/metabolismo , Modelos Biológicos , Preparaciones Farmacéuticas/metabolismo , Proteoma/metabolismo , Transducción de Señal , Simulación por Computador , HumanosRESUMEN
BACKGROUND: Traditionally top-down method was used to identify prognostic features in cancer research. That is to say, differentially expressed genes usually in cancer versus normal were identified to see if they possess survival prediction power. The problem is that prognostic features identified from one set of patient samples can rarely be transferred to other datasets. We apply bottom-up approach in this study: survival correlated or clinical stage correlated genes were selected first and prioritized by their network topology additionally, then a small set of features can be used as a prognostic signature. METHODS: Gene expression profiles of a cohort of 221 hepatocellular carcinoma (HCC) patients were used as a training set, 'bottom-up' approach was applied to discover gene-expression signatures associated with survival in both tumor and adjacent non-tumor tissues, and compared with 'top-down' approach. The results were validated in a second cohort of 82 patients which was used as a testing set. RESULTS: Two sets of gene signatures separately identified in tumor and adjacent non-tumor tissues by bottom-up approach were developed in the training cohort. These two signatures were associated with overall survival times of HCC patients and the robustness of each was validated in the testing set, and each predictive performance was better than gene expression signatures reported previously. Moreover, genes in these two prognosis signature gave some indications for drug-repositioning on HCC. Some approved drugs targeting these markers have the alternative indications on hepatocellular carcinoma. CONCLUSION: Using the bottom-up approach, we have developed two prognostic gene signatures with a limited number of genes that associated with overall survival times of patients with HCC. Furthermore, prognostic markers in these two signatures have the potential to be therapeutic targets.
Asunto(s)
Carcinoma Hepatocelular/diagnóstico , Carcinoma Hepatocelular/tratamiento farmacológico , Biología Computacional/métodos , Reposicionamiento de Medicamentos/métodos , Neoplasias Hepáticas/diagnóstico , Neoplasias Hepáticas/tratamiento farmacológico , Biomarcadores de Tumor/metabolismo , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/metabolismo , Análisis por Conglomerados , Estudios de Cohortes , Femenino , Perfilación de la Expresión Génica , Redes Reguladoras de Genes , Humanos , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/metabolismo , Masculino , Persona de Mediana Edad , Pronóstico , Mapas de Interacción de Proteínas , Análisis de SupervivenciaRESUMEN
Over the past decades, studies have reported that the combinatorial regulation of transcription factors (TFs) and microRNAs (miRNAs) is essential for the appropriate execution of biological events and developmental processes. Dysregulations of these regulators often cause diseases. However, there are no available resources on the regulatory cascades of TFs and miRNAs in the context of human diseases. To fulfill this vacancy, we established the TMREC database in this study. First, we integrated curated transcriptional and post-transcriptional regulations to construct the TF and miRNA regulatory network. Next, we identified all linear paths using the Breadth First Search traversal method. Finally, we used known disease-related genes and miRNAs to measure the strength of association between cascades and diseases. Currently, TMREC consists of 74,248 cascades and 25,194 cascade clusters, involving in 412 TFs, 266 miRNAs and 545 diseases. With the expanding of experimental support regulation data, we will regularly update the database. TMREC aims to help experimental biologists to comprehensively analyse gene expression regulation, to understand the aetiology and to predict novel therapeutic targets. TMREC is freely available at http://bioinfo.hrbmu.edu.cn/TMREC/.