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Small genetic variation affecting mRNA isoforms associated with marbling and meat color in beef cattle. Funct Integr Genomics 2022; 22:451-466. [PMID: 35305194 DOI: 10.1007/s10142-022-00844-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 03/04/2022] [Accepted: 03/07/2022] [Indexed: 11/04/2022]
Abstract
The aim of this study was to identify mRNA isoforms and small genetic variants that may be affecting marbling and beef color in Nellore cattle. Longissimus thoracis muscle samples from 20 bulls with different phenotypes (out of 80 bulls set) for marbling (moderate (n = 10) and low (n = 10) groups) and beef color (desirable (n = 10) and undesirable (n = 9) group) traits were used to perform transcriptomic analysis using RNA sequencing. Fourteen and 15 mRNA isoforms were detected as differentially expressed (DE) (P-value ≤ 0.001) between divergent groups for marbling and meat color traits, respectively. Some of those DE mRNA isoforms have shown sites of splicing modified by small structural variants as single nucleotide variant (SNV), insertion, and/or deletion. Enrichment analysis identified metabolic pathways, such as O2/CO2 exchange in erythrocytes, tyrosine biosynthesis, and phenylalanine degradation. The results obtained suggest potential key regulatory genes associated with these economically important traits for the beef industry and for the consumer.
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2
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Donnelly LL, Hogan TC, Lenahan SM, Nandagopal G, Eaton JG, Lebeau MA, McCann CL, Sarausky HM, Hampel KJ, Armstrong JD, Cameron MP, Sidiropoulos N, Deming P, Seward DJ. Functional assessment of somatic STK11 variants identified in primary human non-small cell lung cancers. Carcinogenesis 2021; 42:1428-1438. [PMID: 34849607 PMCID: PMC8727739 DOI: 10.1093/carcin/bgab104] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 10/13/2021] [Accepted: 10/26/2021] [Indexed: 12/31/2022] Open
Abstract
Serine/Threonine Kinase 11 (STK11) encodes an important tumor suppressor that is frequently mutated in lung adenocarcinoma. Clinical studies have shown that mutations in STK11 resulting in loss of function correlate with resistance to anti-PD-1 monoclonal antibody therapy in KRAS-driven non-small cell lung cancer (NSCLC), but the molecular mechanisms responsible remain unclear. Despite this uncertainty, STK11 functional status is emerging as a reliable biomarker for predicting non-response to anti-PD-1 therapy in NSCLC patients. The clinical utility of this biomarker ultimately depends upon accurate classification of STK11 variants. For nonsense variants occurring early in the STK11 coding region, this assessment is straightforward. However, rigorously demonstrating the functional impact of missense variants remains an unmet challenge. Here we present data characterizing four STK11 splice-site variants by analyzing tumor mRNA, and 28 STK11 missense variants using an in vitro kinase assay combined with a cell-based p53-dependent luciferase reporter assay. The variants we report were identified in primary human NSCLC biopsies in collaboration with the University of Vermont Genomic Medicine group. Additionally, we compare our experimental results with data from 22 in silico predictive algorithms. Our work highlights the power, utility and necessity of functional variant assessment and will aid STK11 variant curation, provide a platform to assess novel STK11 variants and help guide anti-PD-1 therapy utilization in KRAS-driven NSCLCs.
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Affiliation(s)
- Liam L Donnelly
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - Tyler C Hogan
- Department of Biomedical and Health Sciences, University of Vermont College of Nursing and Health Sciences, Burlington, VT, USA
| | - Sean M Lenahan
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - Gopika Nandagopal
- Department of Biomedical and Health Sciences, University of Vermont College of Nursing and Health Sciences, Burlington, VT, USA
| | - Jenna G Eaton
- Department of Biomedical and Health Sciences, University of Vermont College of Nursing and Health Sciences, Burlington, VT, USA
| | - Meagan A Lebeau
- Department of Biomedical and Health Sciences, University of Vermont College of Nursing and Health Sciences, Burlington, VT, USA
| | | | - Hailey M Sarausky
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - Kenneth J Hampel
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - Jordan D Armstrong
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - Margaret P Cameron
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - Nikoletta Sidiropoulos
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA.,University of Vermont Cancer Center, Burlington, VT, USA
| | - Paula Deming
- Department of Biomedical and Health Sciences, University of Vermont College of Nursing and Health Sciences, Burlington, VT, USA.,University of Vermont Cancer Center, Burlington, VT, USA
| | - David J Seward
- Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington, VT, USA.,University of Vermont Cancer Center, Burlington, VT, USA
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3
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Mucaki EJ, Shirley BC, Rogan PK. Expression Changes Confirm Genomic Variants Predicted to Result in Allele-Specific, Alternative mRNA Splicing. Front Genet 2020; 11:109. [PMID: 32211018 PMCID: PMC7066660 DOI: 10.3389/fgene.2020.00109] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Accepted: 01/30/2020] [Indexed: 12/11/2022] Open
Abstract
Splice isoform structure and abundance can be affected by either noncoding or masquerading coding variants that alter the structure or abundance of transcripts. When these variants are common in the population, these nonconstitutive transcripts are sufficiently frequent so as to resemble naturally occurring, alternative mRNA splicing. Prediction of the effects of such variants has been shown to be accurate using information theory-based methods. Single nucleotide polymorphisms (SNPs) predicted to significantly alter natural and/or cryptic splice site strength were shown to affect gene expression. Splicing changes for known SNP genotypes were confirmed in HapMap lymphoblastoid cell lines with gene expression microarrays and custom designed q-RT-PCR or TaqMan assays. The majority of these SNPs (15 of 22) as well as an independent set of 24 variants were then subjected to RNAseq analysis using the ValidSpliceMut web beacon (http://validsplicemut.cytognomix.com), which is based on data from the Cancer Genome Atlas and International Cancer Genome Consortium. SNPs from different genes analyzed with gene expression microarray and q-RT-PCR exhibited significant changes in affected splice site use. Thirteen SNPs directly affected exon inclusion and 10 altered cryptic site use. Homozygous SNP genotypes resulting in stronger splice sites exhibited higher levels of processed mRNA than alleles associated with weaker sites. Four SNPs exhibited variable expression among individuals with the same genotypes, masking statistically significant expression differences between alleles. Genome-wide information theory and expression analyses (RNAseq) in tumor exomes and genomes confirmed splicing effects for 7 of the HapMap SNP and 14 SNPs identified from tumor genomes. q-RT-PCR resolved rare splice isoforms with read abundance too low for statistical significance in ValidSpliceMut. Nevertheless, the web-beacon provides evidence of unanticipated splicing outcomes, for example, intron retention due to compromised recognition of constitutive splice sites. Thus, ValidSpliceMut and q-RT-PCR represent complementary resources for identification of allele-specific, alternative splicing.
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Affiliation(s)
- Eliseos J Mucaki
- Department of Biochemistry, University of Western Ontario, London, ON, Canada
| | | | - Peter K Rogan
- Department of Biochemistry, University of Western Ontario, London, ON, Canada.,CytoGnomix, London, ON, Canada.,Department of Oncology University of Western Ontario, London, ON, Canada.,Department of Computer Science, University of Western Ontario, London, ON, Canada
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4
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Tanimoto K, Muramatsu T, Inazawa J. Massive computational identification of somatic variants in exonic splicing enhancers using The Cancer Genome Atlas. Cancer Med 2019; 8:7372-7384. [PMID: 31631560 PMCID: PMC6885893 DOI: 10.1002/cam4.2619] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 10/01/2019] [Accepted: 10/02/2019] [Indexed: 12/26/2022] Open
Abstract
Owing to the development of next-generation sequencing (NGS) technologies, a large number of somatic variants have been identified in various types of cancer. However, the functional significance of most somatic variants remains unknown. Somatic variants that occur in exonic splicing enhancer (ESE) regions are thought to prevent serine and arginine-rich (SR) proteins from binding to ESE sequence motifs, which leads to exon skipping. We computationally identified somatic variants in ESEs by compiling numerous open-access datasets from The Cancer Genome Atlas (TCGA). Using somatic variants and RNA-seq data from 9635 patients across 32 TCGA projects, we identified 646 ESE-disrupting variants. The false positive rate of our method, estimated using a permutation test, was approximately 1%. Of these ESE-disrupting variants, approximately 71% were located in the binding motifs of four classical SR proteins. ESE-disrupting variants occurred in proportion to the number of somatic variants, but not necessarily in the specific genes associated with the biological processes of cancer. Existing bioinformatics tools could not predict the pathogenicity of ESE-disrupting variants identified in this study, although these variants could cause exon skipping. We demonstrated that ESE-disrupting nonsense variants tended to escape nonsense-mediated decay surveillance. Using integrated analyses of open access data, we could specifically identify ESE-disrupting variants. We have generated a powerful tool, which can handle datasets without normal samples or raw data, and thus contribute to reducing variants of uncertain significance because our statistical approach only uses the exon-junction read counts from the tumor samples.
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Affiliation(s)
- Kousuke Tanimoto
- Genome Laboratory, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.,Genomics Research Support Unit, Research Core, Tokyo Medical and Dental University (TMDU), Japan, Tokyo, Japan
| | - Tomoki Muramatsu
- Department of Molecular Cytogenetics, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
| | - Johji Inazawa
- Department of Molecular Cytogenetics, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.,Bioresource Research Center, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
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5
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Shirley BC, Mucaki EJ, Rogan PK. Pan-cancer repository of validated natural and cryptic mRNA splicing mutations. F1000Res 2019; 7:1908. [PMID: 31275557 DOI: 10.12688/f1000research.17204.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/30/2018] [Indexed: 12/26/2022] Open
Abstract
We present a major public resource of mRNA splicing mutations validated according to multiple lines of evidence of abnormal gene expression. Likely mutations present in all tumor types reported in the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) were identified based on the comparative strengths of splice sites in tumor versus normal genomes, and then validated by respectively comparing counts of splice junction spanning and abundance of transcript reads in RNA-Seq data from matched tissues and tumors lacking these mutations. The comprehensive resource features 341,486 of these validated mutations, the majority of which (69.9%) are not present in the Single Nucleotide Polymorphism Database (dbSNP 150). There are 131,347 unique mutations which weaken or abolish natural splice sites, and 222,071 mutations which strengthen cryptic splice sites (11,932 affect both simultaneously). 28,812 novel or rare flagged variants (with <1% population frequency in dbSNP) were observed in multiple tumor tissue types. An algorithm was developed to classify variants into splicing molecular phenotypes that integrates germline heterozygosity, degree of information change and impact on expression. The classification thresholds were calibrated against the ClinVar clinical database phenotypic assignments. Variants are partitioned into allele-specific alternative splicing, likely aberrant and aberrant splicing phenotypes. Single variants or chromosome ranges can be queried using a Global Alliance for Genomics and Health (GA4GH)-compliant, web-based Beacon "Validated Splicing Mutations" either separately or in aggregate alongside other Beacons through the public Beacon Network, as well as through our website. The website provides additional information, such as a visual representation of supporting RNAseq results, gene expression in the corresponding normal tissues, and splicing molecular phenotypes.
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Affiliation(s)
| | - Eliseos J Mucaki
- Biochemistry, University of Western Ontario, London, Ontario, N6A 2C1, Canada
| | - Peter K Rogan
- CytoGnomix Inc., London, Ontario, N5X 3X5, Canada.,Biochemistry, University of Western Ontario, London, Ontario, N6A 2C1, Canada.,Computer Science, University of Western Ontario, London, Ontario, N6A 2C1, Canada.,Oncology, University of Western Ontario, London, Ontario, N6A 2C1, Canada
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6
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Shirley BC, Mucaki EJ, Rogan PK. Pan-cancer repository of validated natural and cryptic mRNA splicing mutations. F1000Res 2018; 7:1908. [PMID: 31275557 PMCID: PMC6544075 DOI: 10.12688/f1000research.17204.3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/27/2019] [Indexed: 11/20/2022] Open
Abstract
We present a major public resource of mRNA splicing mutations validated according to multiple lines of evidence of abnormal gene expression. Likely mutations present in all tumor types reported in the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) were identified based on the comparative strengths of splice sites in tumor versus normal genomes, and then validated by respectively comparing counts of splice junction spanning and abundance of transcript reads in RNA-Seq data from matched tissues and tumors lacking these mutations. The comprehensive resource features 341,486 of these validated mutations, the majority of which (69.9%) are not present in the Single Nucleotide Polymorphism Database (dbSNP 150). There are 131,347 unique mutations which weaken or abolish natural splice sites, and 222,071 mutations which strengthen cryptic splice sites (11,932 affect both simultaneously). 28,812 novel or rare flagged variants (with <1% population frequency in dbSNP) were observed in multiple tumor tissue types. An algorithm was developed to classify variants into splicing molecular phenotypes that integrates germline heterozygosity, degree of information change and impact on expression. The classification thresholds were calibrated against the ClinVar clinical database phenotypic assignments. Variants are partitioned into allele-specific alternative splicing, likely aberrant and aberrant splicing phenotypes. Single variants or chromosome ranges can be queried using a Global Alliance for Genomics and Health (GA4GH)-compliant, web-based Beacon "Validated Splicing Mutations" either separately or in aggregate alongside other Beacons through the public Beacon Network, as well as through our website. The website provides additional information, such as a visual representation of supporting RNAseq results, gene expression in the corresponding normal tissues, and splicing molecular phenotypes.
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Affiliation(s)
| | - Eliseos J Mucaki
- Biochemistry, University of Western Ontario, London, Ontario, N6A 2C1, Canada
| | - Peter K Rogan
- CytoGnomix Inc., London, Ontario, N5X 3X5, Canada.,Biochemistry, University of Western Ontario, London, Ontario, N6A 2C1, Canada.,Computer Science, University of Western Ontario, London, Ontario, N6A 2C1, Canada.,Oncology, University of Western Ontario, London, Ontario, N6A 2C1, Canada
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7
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Remo A, Manfrin E, Parcesepe P, Ferrarini A, Han HS, Mickys U, Laudanna C, Simbolo M, Malanga D, Oliveira DM, Baritono E, Colangelo T, Sabatino L, Giuliani J, Molinari E, Garonzi M, Xumerle L, Delledonne M, Giordano G, Ghimenton C, Lonardo F, D'angelo F, Grillo F, Mastracci L, Viglietto G, Ceccarelli M, Colantuoni V, Scarpa A, Pancione M. Centrosome Linker-induced Tetraploid Segregation Errors Link Rhabdoid Phenotypes and Lethal Colorectal Cancers. Mol Cancer Res 2018; 16:1385-1395. [PMID: 29784668 DOI: 10.1158/1541-7786.mcr-18-0062] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 03/06/2018] [Accepted: 05/01/2018] [Indexed: 02/05/2023]
Abstract
Centrosome anomalies contribute to tumorigenesis, but it remains unclear how they are generated in lethal cancer phenotypes. Here, it is demonstrated that human microsatellite instable (MSI) and BRAFV600E-mutant colorectal cancers with a lethal rhabdoid phenotype are characterized by inactivation of centrosomal functions. A splice site mutation that causes an unbalanced dosage of rootletin (CROCC), a centrosome linker component required for centrosome cohesion and separation at the chromosome 1p36.13 locus, resulted in abnormally shaped centrosomes in rhabdoid cells from human colon tissues. Notably, deleterious deletions at 1p36.13 were recurrent in a subgroup of BRAFV600E-mutant and microsatellite stable (MSS) rhabdoid colorectal cancers, but not in classical colorectal cancer or pediatric rhabdoid tumors. Interfering with CROCC expression in near-diploid BRAFV600E-mutant/MSI colon cancer cells disrupts bipolar mitotic spindle architecture, promotes tetraploid segregation errors, resulting in a highly aggressive rhabdoid-like phenotype in vitro Restoring near-wild-type levels of CROCC in a metastatic model harboring 1p36.13 deletion results in correction of centrosome segregation errors and cell death, revealing a mechanism of tolerance to mitotic errors and tetraploidization promoted by deleterious 1p36.13 loss. Accordingly, cancer cells lacking 1p36.13 display far greater sensitivity to centrosome spindle pole stabilizing agents in vitro These data shed light on a previously unknown link between centrosome cohesion defects and lethal cancer phenotypes providing new insight into pathways underlying genome instability.Implications: Mis-segregation of chromosomes is a prominent feature of chromosome instability and intratumoral heterogeneity recurrent in metastatic tumors for which the molecular basis is unknown. This study provides insight into the mechanism by which defects in rootletin, a centrosome linker component causes tetraploid segregation errors and phenotypic transition to a clinically devastating form of malignant rhabdoid tumor. Mol Cancer Res; 16(9); 1385-95. ©2018 AACR.
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Affiliation(s)
- Andrea Remo
- Pathology Unit, "Mater Salutis" Hospital AULSS9, Legnago (Verona), Italy
| | - Erminia Manfrin
- Department of Diagnostics and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy
| | - Pietro Parcesepe
- Department of Diagnostics and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy
| | | | - Hye Seung Han
- Department of Pathology, Konkuk University School of Medicine, Seoul, Korea
| | - Ugnius Mickys
- National Center of Pathology, Affiliate of Vilnius University Hospital Santariskiu Clinics, Vilnius, Lithuania
| | - Carmelo Laudanna
- Department of Experimental and Clinical Medicine "Gaetano Salvatore", University "Magna Grecia", Catanzaro, Italy
| | - Michele Simbolo
- Department of Diagnostics and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy
| | - Donatella Malanga
- Department of Experimental and Clinical Medicine "Gaetano Salvatore", University "Magna Grecia", Catanzaro, Italy
| | - Duarte Mendes Oliveira
- Department of Experimental and Clinical Medicine "Gaetano Salvatore", University "Magna Grecia", Catanzaro, Italy
| | | | - Tommaso Colangelo
- Institute for Stem Cell Biology, Regenerative Medicine and Innovative Therapies (ISBReMIT), Casa Sollievo della Sofferenza-IRCCS, San Giovanni Rotondo, Italy
| | - Lina Sabatino
- Department of Sciences and Technologies, University of Sannio, Benevento, Italy
| | - Jacopo Giuliani
- Pathology Unit, "Mater Salutis" Hospital AULSS9, Legnago (Verona), Italy
| | - Enrico Molinari
- Pathology Unit, "Mater Salutis" Hospital AULSS9, Legnago (Verona), Italy
| | - Marianna Garonzi
- Functional Genomics Center, Department of Biotechnology, University of Verona, Verona, Italy
| | - Luciano Xumerle
- Functional Genomics Center, Department of Biotechnology, University of Verona, Verona, Italy
| | - Massimo Delledonne
- Functional Genomics Center, Department of Biotechnology, University of Verona, Verona, Italy
- Personal Genomics S.r.l., Verona, Italy
| | - Guido Giordano
- CRO Aviano National Cancer Center, Aviano, Italy
- Medical Oncology Unit, San Filippo Neri Hospital, Rome, Italy
| | - Claudio Ghimenton
- Department of Diagnostics and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy
| | - Fortunato Lonardo
- Medical Cytogenetics and Molecular Genetics Unit, AORN "Gaetano Rummo," Benevento, Italy
| | - Fulvio D'angelo
- Bioinformatics Laboratory, BIOGEM scrl, Ariano Irpino, Avellino, Italy
| | - Federica Grillo
- Department of Surgical and Diagnostic Sciences (DISC), University of Genova and S. Martino Polyclinic Hospital, Genova, Italy
| | - Luca Mastracci
- Department of Surgical and Diagnostic Sciences (DISC), University of Genova and S. Martino Polyclinic Hospital, Genova, Italy
| | - Giuseppe Viglietto
- Department of Experimental and Clinical Medicine "Gaetano Salvatore", University "Magna Grecia", Catanzaro, Italy
| | - Michele Ceccarelli
- Department of Sciences and Technologies, University of Sannio, Benevento, Italy
- Bioinformatics Laboratory, BIOGEM scrl, Ariano Irpino, Avellino, Italy
| | - Vittorio Colantuoni
- Department of Sciences and Technologies, University of Sannio, Benevento, Italy
| | - Aldo Scarpa
- Department of Diagnostics and Public Health, Section of Pathology, University and Hospital Trust of Verona, Verona, Italy.
- ARC-Net Centre for Applied Research on Cancer, University and Hospital Trust of Verona, Verona, Italy
| | - Massimo Pancione
- Department of Sciences and Technologies, University of Sannio, Benevento, Italy.
- Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, Complutense University, Madrid, Spain
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8
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Dos Santos ES, Caputo SM, Castera L, Gendrot M, Briaux A, Breault M, Krieger S, Rogan PK, Mucaki EJ, Burke LJ, Bièche I, Houdayer C, Vaur D, Stoppa-Lyonnet D, Brown MA, Lallemand F, Rouleau E. Assessment of the functional impact of germline BRCA1/2 variants located in non-coding regions in families with breast and/or ovarian cancer predisposition. Breast Cancer Res Treat 2017; 168:311-325. [PMID: 29236234 DOI: 10.1007/s10549-017-4602-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Accepted: 11/28/2017] [Indexed: 12/19/2022]
Abstract
PURPOSE The molecular mechanism of breast and/or ovarian cancer susceptibility remains unclear in the majority of patients. While germline mutations in the regulatory non-coding regions of BRCA1 and BRCA2 genes have been described, screening has generally been limited to coding regions. The aim of this study was to evaluate the contribution of BRCA1/2 non-coding variants. METHODS Four BRCA1/2 non-coding regions were screened using high-resolution melting analysis/Sanger sequencing or next-generation sequencing on DNA extracted from index cases with breast and ovarian cancer predisposition (3926 for BRCA1 and 3910 for BRCA2). The impact of a set of variants on BRCA1/2 gene regulation was evaluated by site-directed mutagenesis, transfection, followed by Luciferase gene reporter assay. RESULTS We identified a total of 117 variants and tested twelve BRCA1 and 8 BRCA2 variants mapping to promoter and intronic regions. We highlighted two neighboring BRCA1 promoter variants (c.-130del; c.-125C > T) and one BRCA2 promoter variants (c.-296C > T) inhibiting significantly the promoter activity. In the functional assays, a regulating region within the intron 12 was found with the same enhancing impact as within the intron 2. Furthermore, the variants c.81-3980A > G and c.4186-2022C > T suppress the positive effect of the introns 2 and 12, respectively, on the BRCA1 promoter activity. We also found some variants inducing the promoter activities. CONCLUSION In this study, we highlighted some variants among many, modulating negatively the promoter activity of BRCA1 or 2 and thus having a potential impact on the risk of developing cancer. This selection makes it possible to conduct future validation studies on a limited number of variants.
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Affiliation(s)
- E Santana Dos Santos
- Department of Oncology, Center for Translational Oncology, Cancer Institute of the State of São Paulo - ICESP, São Paulo, Brazil
- Service de Génétique, Institut Curie, Paris, France
- A.C.Camargo Cancer Center, São Paulo, Brazil
| | - S M Caputo
- Service de Génétique, Institut Curie, Paris, France
| | - L Castera
- Laboratoire de Biologie et de Génétique du Cancer, CLCC François Baclesse, INSERM 1079 Centre Normand de Génomique et de MédecinePersonnalisée, Caen, France
| | - M Gendrot
- Service de Génétique, Institut Curie, Paris, France
| | - A Briaux
- Service de Génétique, Institut Curie, Paris, France
| | - M Breault
- Service de Génétique, Institut Curie, Paris, France
| | - S Krieger
- Laboratoire de Biologie et de Génétique du Cancer, CLCC François Baclesse, INSERM 1079 Centre Normand de Génomique et de MédecinePersonnalisée, Caen, France
| | - P K Rogan
- Department of Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada
| | - E J Mucaki
- Department of Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada
| | - L J Burke
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
| | - I Bièche
- Service de Génétique, Institut Curie, Paris, France
- Université Paris Descartes, Paris, France
| | - C Houdayer
- Service de Génétique, Institut Curie, Paris, France
- Université Paris Descartes, Paris, France
| | - D Vaur
- Laboratoire de Biologie et de Génétique du Cancer, CLCC François Baclesse, INSERM 1079 Centre Normand de Génomique et de MédecinePersonnalisée, Caen, France
| | - D Stoppa-Lyonnet
- Service de Génétique, Institut Curie, Paris, France
- Université Paris Descartes, Paris, France
| | - M A Brown
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
| | - F Lallemand
- Service de Génétique, Institut Curie, Paris, France.
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9
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Yang XR, Devi BCR, Sung H, Guida J, Mucaki EJ, Xiao Y, Best A, Garland L, Xie Y, Hu N, Rodriguez-Herrera M, Wang C, Jones K, Luo W, Hicks B, Tang TS, Moitra K, Rogan PK, Dean M. Prevalence and spectrum of germline rare variants in BRCA1/2 and PALB2 among breast cancer cases in Sarawak, Malaysia. Breast Cancer Res Treat 2017; 165:687-697. [PMID: 28664506 DOI: 10.1007/s10549-017-4356-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2017] [Accepted: 06/23/2017] [Indexed: 12/29/2022]
Abstract
PURPOSE To characterize the spectrum of germline mutations in BRCA1, BRCA2, and PALB2 in population-based unselected breast cancer cases in an Asian population. METHODS Germline DNA from 467 breast cancer patients in Sarawak General Hospital, Malaysia, where 93% of the breast cancer patients in Sarawak are treated, was sequenced for the entire coding region of BRCA1; BRCA2; PALB2; Exons 6, 7, and 8 of TP53; and Exons 7 and 8 of PTEN. Pathogenic variants included known pathogenic variants in ClinVar, loss of function variants, and variants that disrupt splice site. RESULTS We found 27 pathogenic variants (11 BRCA1, 10 BRCA2, 4 PALB2, and 2 TP53) in 34 patients, which gave a prevalence of germline mutations of 2.8, 3.23, and 0.86% for BRCA1, BRCA2, and PALB2, respectively. Compared to mutation non-carriers, BRCA1 mutation carriers were more likely to have an earlier age at onset, triple-negative subtype, and lower body mass index, whereas BRCA2 mutation carriers were more likely to have a positive family history. Mutation carrier cases had worse survival compared to non-carriers; however, the association was mostly driven by stage and tumor subtype. We also identified 19 variants of unknown significance, and some of them were predicted to alter splicing or transcription factor binding sites. CONCLUSION Our data provide insight into the genetics of breast cancer in this understudied group and suggest the need for modifying genetic testing guidelines for this population with a much younger age at diagnosis and more limited resources compared with Caucasian populations.
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Affiliation(s)
- Xiaohong R Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA.
| | - Beena C R Devi
- Department of Radiotherapy, Oncology and Palliative Care, Sarawak General Hospital, Kuching, Sarawak, Malaysia
| | - Hyuna Sung
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA
| | - Jennifer Guida
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA
| | - Eliseos J Mucaki
- Department of Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Yanzi Xiao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA
| | - Ana Best
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA
| | - Lisa Garland
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Yi Xie
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA
| | - Nan Hu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA
| | - Maria Rodriguez-Herrera
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA
| | - Chaoyu Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA
| | - Kristine Jones
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Wen Luo
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Belynda Hicks
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Tieng Swee Tang
- Department of Radiotherapy, Oncology and Palliative Care, Sarawak General Hospital, Kuching, Sarawak, Malaysia
| | - Karobi Moitra
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA.,Department of Biology, Trinity Washington University, Washington, DC, USA
| | - Peter K Rogan
- Department of Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Michael Dean
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, NCI/NIH, Bethesda, Rockville, MD, USA
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10
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Zou WB, Wu H, Boulling A, Cooper DN, Li ZS, Liao Z, Chen JM, Férec C. In silico prioritization and further functional characterization of SPINK1 intronic variants. Hum Genomics 2017; 11:7. [PMID: 28472998 PMCID: PMC5418720 DOI: 10.1186/s40246-017-0103-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2017] [Accepted: 04/20/2017] [Indexed: 01/25/2023] Open
Abstract
Background SPINK1 (serine protease inhibitor, kazal-type, 1), which encodes human pancreatic secretory trypsin inhibitor, is one of the most extensively studied genes underlying chronic pancreatitis. Recently, based upon data from qualitative reverse transcription-PCR (RT-PCR) analyses of transfected HEK293T cells, we concluded that 24 studied SPINK1 intronic variants were not of pathological significance, the sole exceptions being two canonical splice site variants (i.e., c.87 + 1G > A and c.194 + 2T > C). Herein, we employed the splicing prediction tools included within the Alamut software suite to prioritize the ‘non-pathological’ SPINK1 intronic variants for further quantitative RT-PCR analysis. Results Although our results demonstrated the utility of in silico prediction in classifying and prioritizing intronic variants, we made two observations worth noting. First, we established that most of the prediction tools employed ignored the general rule that GC is a weaker donor splice site than the canonical GT site. This finding is potentially important because for a given disease gene, a GC variant donor splice site may be associated with a milder clinical manifestation. Second, the non-pathological c.194 + 13T > G variant was consistently predicted by different programs to generate a new and viable donor splice site, the prediction scores being comparable to those for the physiological c.194 + 2T donor splice site and even higher than those for the physiological c.87 + 1G donor splice site. We do however provide convincing in vitro evidence that the predicted donor splice site was not entirely spurious. Conclusions Our findings, taken together, serve to emphasize the importance of functional analysis in helping to establish or refute the pathogenicity of specific intronic variants. Electronic supplementary material The online version of this article (doi:10.1186/s40246-017-0103-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Wen-Bin Zou
- Department of Gastroenterology, Changhai Hospital, Second Military Medical University, Shanghai, China.,Institut National de la Santé et de la Recherche Médicale (INSERM), U1078, Brest, France.,Etablissement Français du Sang (EFS)-Bretagne, Brest, France.,Shanghai Institute of Pancreatic Diseases, Shanghai, China
| | - Hao Wu
- Department of Gastroenterology, Changhai Hospital, Second Military Medical University, Shanghai, China.,Institut National de la Santé et de la Recherche Médicale (INSERM), U1078, Brest, France.,Etablissement Français du Sang (EFS)-Bretagne, Brest, France.,Shanghai Institute of Pancreatic Diseases, Shanghai, China
| | - Arnaud Boulling
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1078, Brest, France.,Etablissement Français du Sang (EFS)-Bretagne, Brest, France
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, UK
| | - Zhao-Shen Li
- Department of Gastroenterology, Changhai Hospital, Second Military Medical University, Shanghai, China. .,Shanghai Institute of Pancreatic Diseases, Shanghai, China.
| | - Zhuan Liao
- Department of Gastroenterology, Changhai Hospital, Second Military Medical University, Shanghai, China. .,Shanghai Institute of Pancreatic Diseases, Shanghai, China.
| | - Jian-Min Chen
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1078, Brest, France. .,Etablissement Français du Sang (EFS)-Bretagne, Brest, France. .,Faculté de Médecine et des Sciences de la Santé, Université de Bretagne Occidentale (UBO), Brest, France.
| | - Claude Férec
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1078, Brest, France.,Etablissement Français du Sang (EFS)-Bretagne, Brest, France.,Faculté de Médecine et des Sciences de la Santé, Université de Bretagne Occidentale (UBO), Brest, France.,Laboratoire de Génétique Moléculaire et d'Histocompatibilité, Centre Hospitalier Universitaire (CHU) Brest, Hôpital Morvan, Brest, France
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11
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Mucaki EJ, Caminsky NG, Perri AM, Lu R, Laederach A, Halvorsen M, Knoll JHM, Rogan PK. A unified analytic framework for prioritization of non-coding variants of uncertain significance in heritable breast and ovarian cancer. BMC Med Genomics 2016; 9:19. [PMID: 27067391 PMCID: PMC4828881 DOI: 10.1186/s12920-016-0178-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2015] [Accepted: 03/15/2016] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Sequencing of both healthy and disease singletons yields many novel and low frequency variants of uncertain significance (VUS). Complete gene and genome sequencing by next generation sequencing (NGS) significantly increases the number of VUS detected. While prior studies have emphasized protein coding variants, non-coding sequence variants have also been proven to significantly contribute to high penetrance disorders, such as hereditary breast and ovarian cancer (HBOC). We present a strategy for analyzing different functional classes of non-coding variants based on information theory (IT) and prioritizing patients with large intragenic deletions. METHODS We captured and enriched for coding and non-coding variants in genes known to harbor mutations that increase HBOC risk. Custom oligonucleotide baits spanning the complete coding, non-coding, and intergenic regions 10 kb up- and downstream of ATM, BRCA1, BRCA2, CDH1, CHEK2, PALB2, and TP53 were synthesized for solution hybridization enrichment. Unique and divergent repetitive sequences were sequenced in 102 high-risk, anonymized patients without identified mutations in BRCA1/2. Aside from protein coding and copy number changes, IT-based sequence analysis was used to identify and prioritize pathogenic non-coding variants that occurred within sequence elements predicted to be recognized by proteins or protein complexes involved in mRNA splicing, transcription, and untranslated region (UTR) binding and structure. This approach was supplemented by in silico and laboratory analysis of UTR structure. RESULTS 15,311 unique variants were identified, of which 245 occurred in coding regions. With the unified IT-framework, 132 variants were identified and 87 functionally significant VUS were further prioritized. An intragenic 32.1 kb interval in BRCA2 that was likely hemizygous was detected in one patient. We also identified 4 stop-gain variants and 3 reading-frame altering exonic insertions/deletions (indels). CONCLUSIONS We have presented a strategy for complete gene sequence analysis followed by a unified framework for interpreting non-coding variants that may affect gene expression. This approach distills large numbers of variants detected by NGS to a limited set of variants prioritized as potential deleterious changes.
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Affiliation(s)
- Eliseos J Mucaki
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 2C1, Canada
| | - Natasha G Caminsky
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 2C1, Canada
| | - Ami M Perri
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 2C1, Canada
| | - Ruipeng Lu
- Department of Computer Science, Faculty of Science, Western University, London, N6A 2C1, Canada
| | - Alain Laederach
- Department of Biology, University of North Carolina, Chapel Hill, NC, 27599-3290, USA
| | - Matthew Halvorsen
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, 10032, USA
| | - Joan H M Knoll
- Department of Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, Western University, London, N6A 2C1, Canada
- Cytognomix Inc., London, Canada
| | - Peter K Rogan
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 2C1, Canada.
- Department of Computer Science, Faculty of Science, Western University, London, N6A 2C1, Canada.
- Cytognomix Inc., London, Canada.
- Department of Oncology, Schulich School of Medicine and Dentistry, Western University, London, N6A 2C1, Canada.
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12
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Caminsky NG, Mucaki EJ, Perri AM, Lu R, Knoll JHM, Rogan PK. Prioritizing Variants in Complete Hereditary Breast and Ovarian Cancer Genes in Patients Lacking Known BRCA Mutations. Hum Mutat 2016; 37:640-52. [PMID: 26898890 DOI: 10.1002/humu.22972] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Revised: 01/22/2016] [Accepted: 02/16/2016] [Indexed: 12/11/2022]
Abstract
BRCA1 and BRCA2 testing for hereditary breast and ovarian cancer (HBOC) does not identify all pathogenic variants. Sequencing of 20 complete genes in HBOC patients with uninformative test results (N = 287), including noncoding and flanking sequences of ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, EPCAM, MLH1, MRE11A, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, PTEN, RAD51B, STK11, TP53, and XRCC2, identified 38,372 unique variants. We apply information theory (IT) to predict and prioritize noncoding variants of uncertain significance in regulatory, coding, and intronic regions based on changes in binding sites in these genes. Besides mRNA splicing, IT provides a common framework to evaluate potential affinity changes in transcription factor (TFBSs), splicing regulatory (SRBSs), and RNA-binding protein (RBBSs) binding sites following mutation. We prioritized variants affecting the strengths of 10 splice sites (four natural, six cryptic), 148 SRBS, 36 TFBS, and 31 RBBS. Three variants were also prioritized based on their predicted effects on mRNA secondary (2°) structure and 17 for pseudoexon activation. Additionally, four frameshift, two in-frame deletions, and five stop-gain mutations were identified. When combined with pedigree information, complete gene sequence analysis can focus attention on a limited set of variants in a wide spectrum of functional mutation types for downstream functional and co-segregation analysis.
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Affiliation(s)
- Natasha G Caminsky
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Eliseos J Mucaki
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Ami M Perri
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Ruipeng Lu
- Department of Computer Science, Faculty of Science, Western University, London, Ontario, Canada
| | - Joan H M Knoll
- Department of Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Cytognomix Inc, London, Ontario, Canada
| | - Peter K Rogan
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Department of Computer Science, Faculty of Science, Western University, London, Ontario, Canada.,Cytognomix Inc, London, Ontario, Canada.,Department of Oncology, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
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13
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Dorman SN, Baranova K, Knoll JHM, Urquhart BL, Mariani G, Carcangiu ML, Rogan PK. Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning. Mol Oncol 2015; 10:85-100. [PMID: 26372358 DOI: 10.1016/j.molonc.2015.07.006] [Citation(s) in RCA: 87] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2015] [Accepted: 07/31/2015] [Indexed: 12/21/2022] Open
Abstract
Increasingly, the effectiveness of adjuvant chemotherapy agents for breast cancer has been related to changes in the genomic profile of tumors. We investigated correspondence between growth inhibitory concentrations of paclitaxel and gemcitabine (GI50) and gene copy number, mutation, and expression first in breast cancer cell lines and then in patients. Genes encoding direct targets of these drugs, metabolizing enzymes, transporters, and those previously associated with chemoresistance to paclitaxel (n = 31 genes) or gemcitabine (n = 18) were analyzed. A multi-factorial, principal component analysis (MFA) indicated expression was the strongest indicator of sensitivity for paclitaxel, and copy number and expression were informative for gemcitabine. The factors were combined using support vector machines (SVM). Expression of 15 genes (ABCC10, BCL2, BCL2L1, BIRC5, BMF, FGF2, FN1, MAP4, MAPT, NFKB2, SLCO1B3, TLR6, TMEM243, TWIST1, and CSAG2) predicted cell line sensitivity to paclitaxel with 82% accuracy. Copy number profiles of 3 genes (ABCC10, NT5C, TYMS) together with expression of 7 genes (ABCB1, ABCC10, CMPK1, DCTD, NME1, RRM1, RRM2B), predicted gemcitabine response with 85% accuracy. Expression and copy number studies of two independent sets of patients with known responses were then analyzed with these models. These included tumor blocks from 21 patients that were treated with both paclitaxel and gemcitabine, and 319 patients on paclitaxel and anthracycline therapy. A new paclitaxel SVM was derived from an 11-gene subset since data for 4 of the original genes was unavailable. The accuracy of this SVM was similar in cell lines and tumor blocks (70-71%). The gemcitabine SVM exhibited 62% prediction accuracy for the tumor blocks due to the presence of samples with poor nucleic acid integrity. Nevertheless, the paclitaxel SVM predicted sensitivity in 84% of patients with no or minimal residual disease.
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Affiliation(s)
- Stephanie N Dorman
- Department of Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Katherina Baranova
- Department of Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Joan H M Knoll
- Department of Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada; Molecular Diagnostics Division, Laboratory Medicine Program, London Health Sciences Centre, ON, Canada; Cytognomix Inc., London, ON, Canada
| | - Brad L Urquhart
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Gabriella Mariani
- Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Maria Luisa Carcangiu
- Department of Diagnostic and Laboratory Pathology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Peter K Rogan
- Department of Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada; Cytognomix Inc., London, ON, Canada; Department of Computer Science, University of Western Ontario, London, ON, Canada; Department of Oncology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada.
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14
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Caminsky NG, Mucaki EJ, Rogan PK. Interpretation of mRNA splicing mutations in genetic disease: review of the literature and guidelines for information-theoretical analysis. F1000Res 2015. [DOI: 10.12688/f1000research.5654.2] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The interpretation of genomic variants has become one of the paramount challenges in the post-genome sequencing era. In this review we summarize nearly 20 years of research on the applications of information theory (IT) to interpret coding and non-coding mutations that alter mRNA splicing in rare and common diseases. We compile and summarize the spectrum of published variants analyzed by IT, to provide a broad perspective of the distribution of deleterious natural and cryptic splice site variants detected, as well as those affecting splicing regulatory sequences. Results for natural splice site mutations can be interrogated dynamically with Splicing Mutation Calculator, a companion software program that computes changes in information content for any splice site substitution, linked to corresponding publications containing these mutations. The accuracy of IT-based analysis was assessed in the context of experimentally validated mutations. Because splice site information quantifies binding affinity, IT-based analyses can discern the differences between variants that account for the observed reduced (leaky) versus abolished mRNA splicing. We extend this principle by comparing predicted mutations in natural, cryptic, and regulatory splice sites with observed deleterious phenotypic and benign effects. Our analysis of 1727 variants revealed a number of general principles useful for ensuring portability of these analyses and accurate input and interpretation of mutations. We offer guidelines for optimal use of IT software for interpretation of mRNA splicing mutations.
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15
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Caminsky N, Mucaki EJ, Rogan PK. Interpretation of mRNA splicing mutations in genetic disease: review of the literature and guidelines for information-theoretical analysis. F1000Res 2014; 3:282. [PMID: 25717368 PMCID: PMC4329672 DOI: 10.12688/f1000research.5654.1] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/10/2014] [Indexed: 12/14/2022] Open
Abstract
The interpretation of genomic variants has become one of the paramount challenges in the post-genome sequencing era. In this review we summarize nearly 20 years of research on the applications of information theory (IT) to interpret coding and non-coding mutations that alter mRNA splicing in rare and common diseases. We compile and summarize the spectrum of published variants analyzed by IT, to provide a broad perspective of the distribution of deleterious natural and cryptic splice site variants detected, as well as those affecting splicing regulatory sequences. Results for natural splice site mutations can be interrogated dynamically with Splicing Mutation Calculator, a companion software program that computes changes in information content for any splice site substitution, linked to corresponding publications containing these mutations. The accuracy of IT-based analysis was assessed in the context of experimentally validated mutations. Because splice site information quantifies binding affinity, IT-based analyses can discern the differences between variants that account for the observed reduced (leaky) versus abolished mRNA splicing. We extend this principle by comparing predicted mutations in natural, cryptic, and regulatory splice sites with observed deleterious phenotypic and benign effects. Our analysis of 1727 variants revealed a number of general principles useful for ensuring portability of these analyses and accurate input and interpretation of mutations. We offer guidelines for optimal use of IT software for interpretation of mRNA splicing mutations.
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Affiliation(s)
- Natasha Caminsky
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 2C1, Canada
| | - Eliseos J Mucaki
- Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 2C1, Canada
| | - Peter K Rogan
- Departments of Biochemistry and Computer Science, Western University, London, ON, N6A 2C1, Canada
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16
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Splicing mutation analysis reveals previously unrecognized pathways in lymph node-invasive breast cancer. Sci Rep 2014; 4:7063. [PMID: 25394353 PMCID: PMC4231324 DOI: 10.1038/srep07063] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2014] [Accepted: 10/29/2014] [Indexed: 12/22/2022] Open
Abstract
Somatic mutations reported in large-scale breast cancer (BC) sequencing studies primarily consist of protein coding mutations. mRNA splicing mutation analyses have been limited in scope, despite their prevalence in Mendelian genetic disorders. We predicted splicing mutations in 442 BC tumour and matched normal exomes from The Cancer Genome Atlas Consortium (TCGA). These splicing defects were validated by abnormal expression changes in these tumours. Of the 5,206 putative mutations identified, exon skipping, leaky or cryptic splicing was confirmed for 988 variants. Pathway enrichment analysis of the mutated genes revealed mutations in 9 NCAM1-related pathways, which were significantly increased in samples with evidence of lymph node metastasis, but not in lymph node-negative tumours. We suggest that comprehensive reporting of DNA sequencing data should include non-trivial splicing analyses to avoid missing clinically-significant deleterious splicing mutations, which may reveal novel mutated pathways present in genetic disorders.
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17
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Benaglio P, San Jose PF, Avila-Fernandez A, Ascari G, Harper S, Manes G, Ayuso C, Hamel C, Berson EL, Rivolta C. Mutational screening of splicing factor genes in cases with autosomal dominant retinitis pigmentosa. Mol Vis 2014; 20:843-51. [PMID: 24959063 PMCID: PMC4063357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2014] [Accepted: 06/16/2014] [Indexed: 11/04/2022] Open
Abstract
PURPOSE Mutations in genes encoding proteins from the tri-snRNP complex of the spliceosome account for more than 12% of cases of autosomal dominant retinitis pigmentosa (adRP). Although the exact mechanism by which splicing factor defects trigger photoreceptor death is not completely clear, their role in retinitis pigmentosa has been demonstrated by several genetic and functional studies. To test for possible novel associations between splicing factors and adRP, we screened four tri-snRNP splicing factor genes (EFTUD2, PRPF4, NHP2L1, and AAR2) as candidate disease genes. METHODS We screened up to 303 patients with adRP from Europe and North America who did not carry known RP mutations. Exon-PCR and Sanger methods were used to sequence the NHP2L1 and AAR2 genes, while the sequences of EFTUD2 and PRPF4 were obtained by using long-range PCRs spanning coding and non-coding regions followed by next-generation sequencing. RESULTS We detected novel missense changes in individual patients in the sequence of the genes PRPF4 and EFTUD2, but the role of these changes in relationship to disease could not be verified. In one other patient we identified a novel nucleotide substitution in the 5' untranslated region (UTR) of NHP2L1, which did not segregate with the disease in the family. CONCLUSIONS The absence of clearly pathogenic mutations in the candidate genes screened in our cohort suggests that EFTUD2, PRPF4, NHP2L1, and AAR2 are either not involved in adRP or are associated with the disease in rare instances, at least as observed in this study in patients of European and North American origin.
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Affiliation(s)
- Paola Benaglio
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - Patricia Fernandez San Jose
- Department of Genetics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital (IIS-FJD, UAM), Madrid, Spain,Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), ISCIII, Madrid, Spain
| | - Almudena Avila-Fernandez
- Department of Genetics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital (IIS-FJD, UAM), Madrid, Spain,Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), ISCIII, Madrid, Spain
| | - Giulia Ascari
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - Shyana Harper
- The Berman-Gund Laboratory for the Study of Retinal Degenerations, Harvard Medical School, Massachusetts Eye and Ear, Boston, MA
| | - Gaël Manes
- INSERM U1051, Institut des Neurosciences de Montpellier, Hôpital Saint Eloi, Montpellier, France
| | - Carmen Ayuso
- Department of Genetics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital (IIS-FJD, UAM), Madrid, Spain,Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), ISCIII, Madrid, Spain
| | - Christian Hamel
- INSERM U1051, Institut des Neurosciences de Montpellier, Hôpital Saint Eloi, Montpellier, France
| | - Eliot L. Berson
- The Berman-Gund Laboratory for the Study of Retinal Degenerations, Harvard Medical School, Massachusetts Eye and Ear, Boston, MA
| | - Carlo Rivolta
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
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18
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Longpre KM, Kinstlinger NS, Mead EA, Wang Y, Thekkumthala AP, Carreno KA, Hot A, Keefer JM, Tully L, Katz LS, Pietrzykowski AZ. Seasonal variation of urinary microRNA expression in male goats (Capra hircus) as assessed by next generation sequencing. Gen Comp Endocrinol 2014; 199:1-15. [PMID: 24457251 DOI: 10.1016/j.ygcen.2014.01.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2013] [Revised: 12/03/2013] [Accepted: 01/08/2014] [Indexed: 01/09/2023]
Abstract
Testosterone plays a key role in preparation of a male domesticated goat (Capra hircus) to breeding season including changes in the urogenital tract of a male goat (buck). microRNAs are important regulators of cellular metabolism, differentiation and function. They are powerful intermediaries of hormonal activity in the body, including the urogenital tract. We investigated seasonal changes in expression of microRNAs in goat buck urine and their potential consequences using next generation sequencing (microRNA-Seq). We determined the location of each microRNA gene in the goat genome. Testosterone was measured by radioimmunoassay and the androgen receptor binding sites (ARBS) in the promoters of the microRNA genes were determined by MatInspector. The overall impact of regulated microRNAs on cellular physiology was assessed by mirPath. We observed high testosterone levels during the breeding season and changes in the expression of forty microRNAs. Nineteen microRNAs were upregulated, while twenty-one were downregulated. We identified several ARBS in the promoters of regulated microRNAs. Notably, the mostly inhibited microRNA, miR-1246, has a unique set of several gene copy variants associated with a cluster of androgen receptor binding sites. Concomitant changes in regulated microRNA expression could promote transcription, proliferation and differentiation of urogenital tract cells. Together, these findings indicate that in a domesticated goat (Capra hircus), there are specific changes in the microRNA expression profile in buck urine during breeding season, which could be attributable to high testosterone levels during breeding, and could help in preparation of the urogenital tract for high metabolic demands of that season.
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Affiliation(s)
- Kristy M Longpre
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA
| | - Noah S Kinstlinger
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA
| | - Edward A Mead
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA
| | - Yongping Wang
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA
| | - Austin P Thekkumthala
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA
| | - Katherine A Carreno
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA
| | - Azra Hot
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA
| | - Jennifer M Keefer
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA
| | - Luke Tully
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA
| | - Larry S Katz
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA
| | - Andrzej Z Pietrzykowski
- Rutgers University, Department of Animal Sciences, 67 Poultry Farm Lane, New Brunswick, NJ 08901, USA.
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Viner C, Dorman SN, Shirley BC, Rogan PK. Validation of predicted mRNA splicing mutations using high-throughput transcriptome data. F1000Res 2014; 3:8. [PMID: 24741438 PMCID: PMC3983938 DOI: 10.12688/f1000research.3-8.v2] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/03/2014] [Indexed: 01/20/2023] Open
Abstract
Interpretation of variants present in complete genomes or exomes reveals numerous sequence changes, only a fraction of which are likely to be pathogenic. Mutations have been traditionally inferred from allele frequencies and inheritance patterns in such data. Variants predicted to alter mRNA splicing can be validated by manual inspection of transcriptome sequencing data, however this approach is intractable for large datasets. These abnormal mRNA splicing patterns are characterized by reads demonstrating either exon skipping, cryptic splice site use, and high levels of intron inclusion, or combinations of these properties. We present, Veridical, an
in silico method for the automatic validation of DNA sequencing variants that alter mRNA splicing. Veridical performs statistically valid comparisons of the normalized read counts of abnormal RNA species in mutant versus non-mutant tissues. This leverages large numbers of control samples to corroborate the consequences of predicted splicing variants in complete genomes and exomes.
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Affiliation(s)
- Coby Viner
- Department of Computer Science, University of Western Ontario, London, Ontario, N6A 5B7, Canada
| | - Stephanie N Dorman
- Department of Biochemistry, University of Western Ontario, London, Ontario, N6A 5C1, Canada
| | | | - Peter K Rogan
- Department of Computer Science, University of Western Ontario, London, Ontario, N6A 5B7, Canada ; Department of Biochemistry, University of Western Ontario, London, Ontario, N6A 5C1, Canada ; Cytognomix, Inc., London, Ontario, N6G 4X8, Canada
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Abstract
Interpretation of variants present in complete genomes or exomes reveals numerous sequence changes, only a fraction of which are likely to be pathogenic. Mutations have been traditionally inferred from allele frequencies and inheritance patterns in such data. Variants predicted to alter mRNA splicing can be validated by manual inspection of transcriptome sequencing data, however this approach is intractable for large datasets. These abnormal mRNA splicing patterns are characterized by reads demonstrating either exon skipping, cryptic splice site use, and high levels of intron inclusion, or combinations of these properties. We present, Veridical, an in silico method for the automatic validation of DNA sequencing variants that alter mRNA splicing. Veridical performs statistically valid comparisons of the normalized read counts of abnormal RNA species in mutant versus non-mutant tissues. This leverages large numbers of control samples to corroborate the consequences of predicted splicing variants in complete genomes and exomes.
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Affiliation(s)
- Coby Viner
- Department of Computer Science, University of Western Ontario, London, Ontario, N6A 5B7, Canada
| | - Stephanie N Dorman
- Department of Biochemistry, University of Western Ontario, London, Ontario, N6A 5C1, Canada
| | | | - Peter K Rogan
- Department of Computer Science, University of Western Ontario, London, Ontario, N6A 5B7, Canada ; Department of Biochemistry, University of Western Ontario, London, Ontario, N6A 5C1, Canada ; Cytognomix, Inc., London, Ontario, N6G 4X8, Canada
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Ellard S, Patrinos GP, Oetting WS. Clinical Applications of Next-Generation Sequencing: The 2013 Human Genome Variation Society Scientific Meeting. Hum Mutat 2013; 34:1583-7. [DOI: 10.1002/humu.22400] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2013] [Accepted: 08/12/2013] [Indexed: 11/08/2022]
Affiliation(s)
- Sian Ellard
- University of Exeter Medical School; Exeter United Kingdom
| | - George P. Patrinos
- Department of Pharmacy; School of Health Sciences; University of Patras; Patras Greece
| | - William S. Oetting
- Department of Experimental and Clinical Pharmacology; University of Minnesota; Minneapolis Minnesota
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