• BRIP-1
• FANCI
• FANCJ
• HGSOC
• expression
• marker
• ovarian cancer

• Humans
• Neoplastic Cells, Circulating/metabolism
• Transcriptome
• DNA Copy Number Variations
• Gene Expression Profiling
• Biomarkers, Tumor

• University Grants Commission

• Chromosome segregation
• GEO
• GSEA
• LIHC

BRIP1 (Breast Cancer 1 Interacting Helicase 1) is a tumor suppressor gene that has vital function in preserving the genetic stability by repairing DNA damage though have significant associations with the onset of breast cancer (BC) if mutated or overexpressed. In this study, the prognostic value of BRIP1 gene was evaluated and validated through bioinformatics approaches utilizing transcriptomic (mRNA expression) data from several BC databases. To determine the prognostic value, the expression level of mRNA transcript was analyzed in context of comparison between breast tumor and normal tissues regarding clinical features, breast tumor subtypes, promoter methylation status, correlation level, mutation frequency, and survival of BC patients. BRIP1 expression was found to be significantly overexpressed in various BC molecular subtypes (e.g. PAM50, Sorlie’s) and clinical status (estrogen and progesterone receptor) than associated normal tissues which correlated with prognosis. Also, in promoter methylation level, its expression was observed as upregulated-hypomethylated regarding various clinicopathological features. Multiple data mining exhibited positive correlation between BRIP1 and INTS2 (Integrator Complex Subunit 2) expressions in BC. Further, mutation analysis revealed that BRIP1 gene was altered by acquiring both somatic and germline mutations. In addition, a total of 42 mutations; 24 missense, 8 fusion, 7 truncating, and 3 inframe mutations in BC patients was detected in BRIP1 protein. Moreover, higher BRIP1 expression was found to be correlated with poor disease-specific, disease metastasis-free, relapse-free, and overall survivals of BC patients. Since, overexpression of BRIP1 was identified to be associated with different clinical features, breast tumor subtypes, promoter methylation status, and survival of BC patients that may provide a risk of ensuing malignant transformation. Thus, lower expression of BRIP1 might hinder BC prognosis. We consider that this analysis will present a proof for BRIP1 gene to be a noteworthy molecular biomarker for BC prognosis.

• BRIP1
• bioinformatics
• breast cancer
• mutation
• prognostic marker
• survival analysis

• BACH1/BRIP1
• Chl1p
• Chromatin remodeling
• genomic stability
• tumorigenesis

G-quadruplexes (G4) are stacked nucleic acid structures that are stabilized by heme. In cells, they affect DNA replication and gene transcription. They are unwound by several helicases but the composition of the repair complex and its heme sensitivity are unclear. We found that the accumulation of G-quadruplexes is affected by heme oxygenase-1 (Hmox1) expression, but in a cell-type-specific manner: hematopoietic stem cells (HSCs) from Hmox1^−/− mice have upregulated expressions of G4-unwinding helicases (e.g., Brip1, Pif1) and show weaker staining for G-quadruplexes, whereas Hmox1-deficient murine induced pluripotent stem cells (iPSCs), despite the upregulation of helicases, have more G-quadruplexes, especially after exposure to exogenous heme. Using iPSCs expressing only nuclear or only cytoplasmic forms of Hmox1, we found that nuclear localization promotes G4 removal. We demonstrated that the proximity ligation assay (PLA) can detect cellular co-localization of G-quadruplexes with helicases, as well as with HMOX1, suggesting the potential role of HMOX1 in G4 modifications. However, this colocalization does not mean a direct interaction was detectable using the immunoprecipitation assay. Therefore, we concluded that HMOX1 influences G4 accumulation, but rather as one of the proteins regulating the heme availability, not as a rate-limiting factor. It is noteworthy that cellular G4–protein colocalizations can be quantitatively analyzed using PLA, even in rare cells.

• G-quadruplex
• heme
• heme oxygenase-1
• proximity ligation assay

• cancer
• genetics

• BRCA1 Protein/genetics
• BRCA2 Protein/genetics
• Breast Neoplasms/genetics
• Breast Neoplasms/pathology
• Breast Neoplasms, Male/genetics
• Breast Neoplasms, Male/pathology
• DNA Damage/genetics
• DNA Repair
• Female
• Germ-Line Mutation/genetics
• Homologous Recombination/genetics
• Humans
• Male

• Korea Health Industry Development Institute

• R01 CA225018 NCI NIH HHS
• R01 GM108648 NIGMS NIH HHS
• R01 CA247232 NCI NIH HHS
• UL1 TR001453 NCATS NIH HHS
• R01 CA233959 NCI NIH HHS
• R01 CA176166 NCI NIH HHS
• National Institutes of Health
• National Cancer Institute
• University of Connecticut

BRIP1 is a helicase that partners with BRCA1 in the homologous recombination (HR) step in the repair of DNA inter-strand cross-link lesions. It is a rare cause of hereditary ovarian cancer in patients with no mutations of BRCA1 or BRCA2. The role of the protein in other cancers such as gastrointestinal (GI) carcinomas is less well characterized but given its role in DNA repair it could be a candidate tumor suppressor similarly to the two BRCA proteins.

To analyze the role of helicase BRIP1 (FANCJ) in GI cancers pathogenesis.

Publicly available data from genomic studies of esophageal, gastric, pancreatic, cholangiocarcinomas and colorectal cancers were interrogated to unveil the role of BRIP1 in these carcinomas and to discover associations of lesions in BRIP1 with other more common molecular defects in these cancers.

Molecular lesions in BRIP1 were rare (3.6% of all samples) in GI cancers and consisted almost exclusively of mutations and amplifications. Among mutations, 40% were possibly pathogenic according to the OncoKB database. A majority of BRIP1 mutated GI cancers were hyper-mutated due to concomitant mutations in mismatch repair or polymerase ε and δ1 genes. No associations were discovered between amplifications of BRIP1 and any mutated genes. In gastroesophageal cancers BRIP1 amplification commonly co-occurs with ERBB2 amplification.

Overall BRIP1 molecular defects do not seem to play a major role in GI cancers whereas mutations frequently occur in hypermutated carcinomas and co-occur with other HR genes mutations. Despite their rarity, BRIP1 defects may present an opportunity for therapeutic interventions similar to other HR defects.

• BRIP1
• FANCJ
• BACH1
• Gastrointestinal cancers
• Mutations
• Copy number alterations

• Codon, Nonsense
• Databases, Genetic/statistics & numerical data
• Datasets as Topic
• Fanconi Anemia Complementation Group Proteins/genetics
• Fanconi Anemia Complementation Group Proteins/metabolism
• Gastrointestinal Neoplasms/genetics
• Gastrointestinal Neoplasms/mortality
• Gastrointestinal Neoplasms/pathology
• Gene Amplification
• Genetic Predisposition to Disease
• Humans
• Kaplan-Meier Estimate
• RNA Helicases/genetics
• RNA Helicases/metabolism
• Recombinational DNA Repair/genetics
• Retrospective Studies

• BRCA1
• BRCA2
• BRIP1
• DNA repair
• FANCD2
• FANCF
• FANCJ
• TP53
• gene expression
• ovarian cancer

Co-expression network analysis provides useful information for studying gene regulation in biological processes. Examining condition-specific patterns of co-expression can provide insights into the underlying cellular processes activated in a particular condition. One challenge in this type of analysis is that the sample sizes in each condition are usually small, making the statistical inference of co-expression patterns highly underpowered. A joint network construction that borrows information from related structures across conditions has the potential to improve the power of the analysis. One possible approach to constructing the co-expression network is to use the Gaussian graphical model. Though several methods are available for joint estimation of multiple graphical models, they do not fully account for the heterogeneity between samples and between co-expression patterns introduced by condition specificity. Here we develop the condition-adaptive fused graphical lasso (CFGL), a data-driven approach to incorporate condition specificity in the estimation of co-expression networks. We show that this method improves the accuracy with which networks are learned. The application of this method on a rat multi-tissue dataset and The Cancer Genome Atlas (TCGA) breast cancer dataset provides interesting biological insights. In both analyses, we identify numerous modules enriched for Gene Ontology functions and observe that the modules that are upregulated in a particular condition are often involved in condition-specific activities. Interestingly, we observe that the genes strongly associated with survival time in the TCGA dataset are less likely to be network hubs, suggesting that genes associated with cancer progression are likely to govern specific functions or execute final biological functions in pathways, rather than regulating a large number of biological processes. Additionally, we observed that the tumor-specific hub genes tend to have few shared edges with normal tissue, revealing tumor-specific regulatory mechanism.

Gene co-expression networks provide insights into the mechanism of cellular activity and gene regulation. Condition-specific mechanisms may be identified by constructing and comparing co-expression networks of multiple conditions. We propose a novel statistical method to jointly construct co-expression networks for gene expression profiles from multiple conditions. By using a data-driven approach to capture condition-specific co-expression patterns, this method is effective in identifying both co-expression patterns that are specific to a condition and that are common across conditions. The application of this method to real datasets reveals interesting biological insights.

• Antineoplastic Agents/pharmacology
• Ataxia Telangiectasia Mutated Proteins/antagonists & inhibitors
• Ataxia Telangiectasia Mutated Proteins/physiology
• Cell Cycle/drug effects
• Cell Line, Tumor
• Checkpoint Kinase 1/physiology
• Humans
• Morpholines/pharmacology
• Neoplasm Proteins/antagonists & inhibitors
• Neoplasm Proteins/physiology
• Poly(ADP-ribose) Polymerase Inhibitors/pharmacology
• Protein Stability
• Proteome
• Pyrazines/pharmacology
• Pyrones/pharmacology
• Recombinational DNA Repair/physiology
• Signal Transduction/physiology
• Sulfones/pharmacology
• Transcription, Genetic/drug effects

• R01 GM097272 NIGMS NIH HHS

• BRIP1
• biomarkers
• breast cancer
• oncogene
• overexpression

• Breast cancer brain metastases
• Copy number variations
• Pathway and network analysis
• Whole exome sequencing
• Whole transcript array profiling
• snoRNAs

• Adult
• Base Sequence
• Biomarkers, Tumor/genetics
• Brain Neoplasms/genetics
• Brain Neoplasms/secondary
• Breast Neoplasms/pathology
• Cluster Analysis
• DNA Copy Number Variations/genetics
• Female
• Gene Expression Profiling
• Gene Expression Regulation, Neoplastic
• Gene Ontology
• Gene Regulatory Networks
• Humans
• Middle Aged
• Mutation/genetics
• Principal Component Analysis
• Exome Sequencing

• AT-32-98 King Abdullah University of Science and Technology

SWItchMiner (SWIM) is a wizard-like software implementation of a procedure, previously described, able to extract information contained in complex networks. Specifically, SWIM allows unearthing the existence of a new class of hubs, called “fight-club hubs”, characterized by a marked negative correlation with their first nearest neighbors. Among them, a special subset of genes, called “switch genes”, appears to be characterized by an unusual pattern of intra- and inter-module connections that confers them a crucial topological role, interestingly mirrored by the evidence of their clinic-biological relevance. Here, we applied SWIM to a large panel of cancer datasets from The Cancer Genome Atlas, in order to highlight switch genes that could be critically associated with the drastic changes in the physiological state of cells or tissues induced by the cancer development. We discovered that switch genes are found in all cancers we studied and they encompass protein coding genes and non-coding RNAs, recovering many known key cancer players but also many new potential biomarkers not yet characterized in cancer context. Furthermore, SWIM is amenable to detect switch genes in different organisms and cell conditions, with the potential to uncover important players in biologically relevant scenarios, including but not limited to human cancer.

• Chondrocyte
• Forkhead Box O
• Growth plate
• Hypertrophic
• Redox homeostasis

• Animals
• Bone and Bones/cytology
• Bone and Bones/metabolism
• Cell Cycle Proteins
• Cell Differentiation
• Cell Proliferation
• Chondrocytes/cytology
• Chondrocytes/metabolism
• Collagen Type II/genetics
• Collagen Type II/metabolism
• Crosses, Genetic
• Female
• Forkhead Box Protein O1/deficiency
• Forkhead Box Protein O1/genetics
• Forkhead Box Protein O3/deficiency
• Forkhead Box Protein O3/genetics
• Forkhead Transcription Factors/deficiency
• Forkhead Transcription Factors/genetics
• Gene Expression Profiling
• Gene Expression Regulation, Developmental
• Integrases/genetics
• Integrases/metabolism
• Male
• Mesenchymal Stem Cells/cytology
• Mesenchymal Stem Cells/metabolism
• Mice
• Mice, Transgenic
• Osteogenesis/genetics
• Oxidoreductases/genetics
• Oxidoreductases/metabolism
• Primary Cell Culture
• Signal Transduction

• Animals
• Bystander Effect
• DNA Breaks, Double-Stranded
• DNA Repair/radiation effects
• DNA Replication/radiation effects
• Humans
• Neoplasms/radiotherapy
• Oxidative Stress
• Radiation Injuries/genetics

• C1513/A7047 Cancer Research UK
• G1100014 Medical Research Council

• ATP
• Fanconi anemia
• Mitochondria
• Reactive oxygen species
• Respiration

• E2F
• MuRF1
• MuRF2
• cardiac hypertrophy
• ubiquitin ligase

• Chromatin/genetics
• Chromatin/physiology
• Chromosomal Proteins, Non-Histone/genetics
• Chromosomal Proteins, Non-Histone/metabolism
• DNA Damage
• DNA Replication
• Fanconi Anemia/genetics
• Fanconi Anemia/metabolism
• Fanconi Anemia Complementation Group D2 Protein/genetics
• Fanconi Anemia Complementation Group D2 Protein/metabolism
• Fanconi Anemia Complementation Group F Protein/genetics
• Fanconi Anemia Complementation Group F Protein/metabolism
• Fanconi Anemia Complementation Group Proteins/genetics
• Fanconi Anemia Complementation Group Proteins/metabolism
• Genomic Instability
• HeLa Cells
• Humans
• Immunoprecipitation
• Protein Binding
• Two-Hybrid System Techniques
• Ubiquitin-Protein Ligases/metabolism
• Ubiquitination

• GGP030406 Telethon

• dna crosslinking
• mutagenesis
• crosslink repair
• dna replication forks
• chromosomal instability
• translesion synthesis
• homologous recombination repair

• Animals
• CHO Cells
• Chromosomal Instability
• Cricetinae
• Cricetulus
• DNA Damage
• DNA Repair
• DNA Replication
• Fanconi Anemia/genetics
• Fanconi Anemia Complementation Group Proteins/genetics
• Fanconi Anemia Complementation Group Proteins/physiology
• Humans
• Models, Genetic
• Mutation
• Oxidative Stress
• Sister Chromatid Exchange

• R01 CA112566 NCI NIH HHS
• R01 CA112566-03 NCI NIH HHS
• THOMPSON14@LLNL.GOV PHS HHS

• fancj
• fanconi anemia
• breast cancer
• cancer
• dna damage
• dna repair
• helicase

• Amino Acid Sequence
• Animals
• Basic-Leucine Zipper Transcription Factors/genetics
• Basic-Leucine Zipper Transcription Factors/metabolism
• DNA/metabolism
• DNA Breaks, Double-Stranded
• DNA Repair/physiology
• DNA Replication/physiology
• Fanconi Anemia/genetics
• Fanconi Anemia/metabolism
• Fanconi Anemia Complementation Group Proteins/genetics
• Fanconi Anemia Complementation Group Proteins/metabolism
• Humans
• Models, Biological
• Molecular Sequence Data
• Substrate Specificity

• Z01 AG000741-07 Intramural NIH HHS

IRF1 is a transcription factor that regulates key processes in the immune system and in tumour suppression. To gain further insight into IRF1's role in these processes, we searched for new target genes by performing chromatin immunoprecipitation coupled to a CpG island microarray (ChIP–chip). Using this approach we identified 202 new IRF1-binding sites with high confidence. Functional categorization of the target genes revealed a surprising cadre of new roles that can be linked to IRF1. One of the major functional categories was the DNA damage response pathway. In order to further validate our findings, we show that IRF1 can regulate the mRNA expression of a number of the DNA damage response genes in our list. In particular, we demonstrate that the mRNA and protein levels of the DNA repair protein BRIP1 [Fanconi anemia gene J (FANC J)] are upregulated after IRF1 over-expression. We also demonstrate that knockdown of IRF1 by siRNA results in loss of BRIP1 expression, abrogation of BRIP1 foci after DNA interstrand crosslink (ICL) damage and hypersensitivity to the DNA crosslinking agent, melphalan; a characteristic phenotype of FANC J cells. Taken together, our data provides a more complete understanding of the regulatory networks controlled by IRF1 and reveals a novel role for IRF1 in regulating the ICL DNA damage response.

• Adult
• Aged
• Antineoplastic Combined Chemotherapy Protocols/administration & dosage
• Antineoplastic Combined Chemotherapy Protocols/therapeutic use
• BRCA1 Protein/genetics
• BRCA1 Protein/metabolism
• Carcinoma, Non-Small-Cell Lung/drug therapy
• Carcinoma, Non-Small-Cell Lung/genetics
• Carcinoma, Non-Small-Cell Lung/pathology
• Deoxycytidine/administration & dosage
• Deoxycytidine/analogs & derivatives
• Docetaxel
• Female
• Gene Expression
• Humans
• Lung Neoplasms/drug therapy
• Lung Neoplasms/genetics
• Lung Neoplasms/pathology
• Male
• Middle Aged
• RNA, Messenger/metabolism
• Retrospective Studies
• Ribonucleoside Diphosphate Reductase/genetics
• Ribonucleoside Diphosphate Reductase/metabolism
• Taxoids/administration & dosage
• Tumor Suppressor Proteins/genetics
• Tumor Suppressor Proteins/metabolism
• Gemcitabine