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Iñiguez-Muñoz S, Llinàs-Arias P, Ensenyat-Mendez M, Bedoya-López AF, Orozco JIJ, Cortés J, Roy A, Forsberg-Nilsson K, DiNome ML, Marzese DM. Hidden secrets of the cancer genome: unlocking the impact of non-coding mutations in gene regulatory elements. Cell Mol Life Sci 2024; 81:274. [PMID: 38902506 PMCID: PMC11335195 DOI: 10.1007/s00018-024-05314-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 12/07/2023] [Accepted: 06/06/2024] [Indexed: 06/22/2024]
Abstract
Discoveries in the field of genomics have revealed that non-coding genomic regions are not merely "junk DNA", but rather comprise critical elements involved in gene expression. These gene regulatory elements (GREs) include enhancers, insulators, silencers, and gene promoters. Notably, new evidence shows how mutations within these regions substantially influence gene expression programs, especially in the context of cancer. Advances in high-throughput sequencing technologies have accelerated the identification of somatic and germline single nucleotide mutations in non-coding genomic regions. This review provides an overview of somatic and germline non-coding single nucleotide alterations affecting transcription factor binding sites in GREs, specifically involved in cancer biology. It also summarizes the technologies available for exploring GREs and the challenges associated with studying and characterizing non-coding single nucleotide mutations. Understanding the role of GRE alterations in cancer is essential for improving diagnostic and prognostic capabilities in the precision medicine era, leading to enhanced patient-centered clinical outcomes.
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Affiliation(s)
- Sandra Iñiguez-Muñoz
- Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d'Investigació Sanitària Illes Balears (IdISBa), Palma, Spain
| | - Pere Llinàs-Arias
- Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d'Investigació Sanitària Illes Balears (IdISBa), Palma, Spain
| | - Miquel Ensenyat-Mendez
- Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d'Investigació Sanitària Illes Balears (IdISBa), Palma, Spain
| | - Andrés F Bedoya-López
- Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d'Investigació Sanitària Illes Balears (IdISBa), Palma, Spain
| | - Javier I J Orozco
- Saint John's Cancer Institute, Providence Saint John's Health Center, Santa Monica, CA, USA
| | - Javier Cortés
- International Breast Cancer Center (IBCC), Pangaea Oncology, Quiron Group, 08017, Barcelona, Spain
- Medica Scientia Innovation Research SL (MEDSIR), 08018, Barcelona, Spain
- Faculty of Biomedical and Health Sciences, Department of Medicine, Universidad Europea de Madrid, 28670, Madrid, Spain
| | - Ananya Roy
- Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Karin Forsberg-Nilsson
- Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- University of Nottingham Biodiscovery Institute, Nottingham, UK
| | - Maggie L DiNome
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA
| | - Diego M Marzese
- Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d'Investigació Sanitària Illes Balears (IdISBa), Palma, Spain.
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA.
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2
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Mohammadi E, Dashti S, Shafizade N, Jin H, Zhang C, Lam S, Tahmoorespur M, Mardinoglu A, Sekhavati MH. Drug repositioning for immunotherapy in breast cancer using single-cell analysis. NPJ Syst Biol Appl 2024; 10:37. [PMID: 38589404 PMCID: PMC11001976 DOI: 10.1038/s41540-024-00359-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 03/13/2024] [Indexed: 04/10/2024] Open
Abstract
Immunomodulatory peptides, while exhibiting potential antimicrobial, antifungal, and/or antiviral properties, can play a role in stimulating or suppressing the immune system, especially in pathological conditions like breast cancer (BC). Thus, deregulation of these peptides may serve as an immunotherapeutic strategy to enhance the immune response. In this meta-analysis, we utilized single-cell RNA sequencing data and known therapeutic peptides to investigate the deregulation of these peptides in malignant versus normal human breast epithelial cells. We corroborated our findings at the chromatin level using ATAC-seq. Additionally, we assessed the protein levels in various BC cell lines. Moreover, our in-house drug repositioning approach was employed to identify potential drugs that could positively impact the relapse-free survival of BC patients. Considering significantly deregulated therapeutic peptides and their role in BC pathology, our approach aims to downregulate B2M and SLPI, while upregulating PIGR, DEFB1, LTF, CLU, S100A7, and SCGB2A1 in BC epithelial cells through our drug repositioning pipeline. Leveraging the LINCS L1000 database, we propose BRD-A06641369 for B2M downregulation and ST-4070043 and BRD-K97926541 for SLPI downregulation without negatively affecting the MHC complex as a significantly correlated pathway with these two genes. Furthermore, we have compiled a comprehensive list of drugs for the upregulation of other selected immunomodulatory peptides. Employing an immunotherapeutic approach by integrating our drug repositioning pipeline with single-cell analysis, we proposed potential drugs and drug targets to fortify the immune system against BC.
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Affiliation(s)
- Elyas Mohammadi
- Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
- Department of Animal Science, Ferdowsi University of Mashhad, Mashhad, Iran.
| | - Samira Dashti
- Department of Internal Medicine, Mashhad University of Medical Science, Mashhad, Iran
| | - Neda Shafizade
- Department of Internal Medicine, Mashhad University of Medical Science, Mashhad, Iran
| | - Han Jin
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, Sweden
| | - Cheng Zhang
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, Sweden
| | - Simon Lam
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | | | - Adil Mardinoglu
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, Sweden
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, UK
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3
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Leuzzi G, Vasciaveo A, Taglialatela A, Chen X, Firestone TM, Hickman AR, Mao W, Thakar T, Vaitsiankova A, Huang JW, Cuella-Martin R, Hayward SB, Kesner JS, Ghasemzadeh A, Nambiar TS, Ho P, Rialdi A, Hebrard M, Li Y, Gao J, Gopinath S, Adeleke OA, Venters BJ, Drake CG, Baer R, Izar B, Guccione E, Keogh MC, Guerois R, Sun L, Lu C, Califano A, Ciccia A. SMARCAL1 is a dual regulator of innate immune signaling and PD-L1 expression that promotes tumor immune evasion. Cell 2024; 187:861-881.e32. [PMID: 38301646 PMCID: PMC10980358 DOI: 10.1016/j.cell.2024.01.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 07/23/2023] [Accepted: 01/05/2024] [Indexed: 02/03/2024]
Abstract
Genomic instability can trigger cancer-intrinsic innate immune responses that promote tumor rejection. However, cancer cells often evade these responses by overexpressing immune checkpoint regulators, such as PD-L1. Here, we identify the SNF2-family DNA translocase SMARCAL1 as a factor that favors tumor immune evasion by a dual mechanism involving both the suppression of innate immune signaling and the induction of PD-L1-mediated immune checkpoint responses. Mechanistically, SMARCAL1 limits endogenous DNA damage, thereby suppressing cGAS-STING-dependent signaling during cancer cell growth. Simultaneously, it cooperates with the AP-1 family member JUN to maintain chromatin accessibility at a PD-L1 transcriptional regulatory element, thereby promoting PD-L1 expression in cancer cells. SMARCAL1 loss hinders the ability of tumor cells to induce PD-L1 in response to genomic instability, enhances anti-tumor immune responses and sensitizes tumors to immune checkpoint blockade in a mouse melanoma model. Collectively, these studies uncover SMARCAL1 as a promising target for cancer immunotherapy.
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Affiliation(s)
- Giuseppe Leuzzi
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Alessandro Vasciaveo
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Angelo Taglialatela
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Xiao Chen
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | | | | | - Wendy Mao
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Tanay Thakar
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Alina Vaitsiankova
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Jen-Wei Huang
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Raquel Cuella-Martin
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Samuel B Hayward
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Jordan S Kesner
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Ali Ghasemzadeh
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Tarun S Nambiar
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Patricia Ho
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Medicine, Division of Hematology and Oncology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Alexander Rialdi
- Center for OncoGenomics and Innovative Therapeutics (COGIT), Center for Therapeutics Discovery, Department of Oncological Sciences and Pharmacological Sciences, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Maxime Hebrard
- Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (ASTAR), Singapore, Singapore
| | - Yinglu Li
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Jinmei Gao
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France
| | | | | | | | - Charles G Drake
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA; Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Urology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Richard Baer
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA; Institute for Cancer Genetics, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Benjamin Izar
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA; Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Medicine, Division of Hematology and Oncology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Ernesto Guccione
- Center for OncoGenomics and Innovative Therapeutics (COGIT), Center for Therapeutics Discovery, Department of Oncological Sciences and Pharmacological Sciences, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Raphael Guerois
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France
| | - Lu Sun
- EpiCypher Inc., Durham, NC 27709, USA
| | - Chao Lu
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Andrea Califano
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Alberto Ciccia
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA; Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY 10032, USA; Institute for Cancer Genetics, Columbia University Irving Medical Center, New York, NY 10032, USA.
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Provasek VE, Kodavati M, Guo W, Wang H, Boldogh I, Van Den Bosch L, Britz G, Hegde ML. lncRNA Sequencing Reveals Neurodegeneration-Associated FUS Mutations Alter Transcriptional Landscape of iPS Cells That Persists in Motor Neurons. Cells 2023; 12:2461. [PMID: 37887305 PMCID: PMC10604943 DOI: 10.3390/cells12202461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 10/13/2023] [Accepted: 10/13/2023] [Indexed: 10/28/2023] Open
Abstract
Fused-in sarcoma (FUS) gene mutations have been implicated in amyotrophic lateral sclerosis (ALS). This study aimed to investigate the impact of FUS mutations (R521H and P525L) on the transcriptome of induced pluripotent stem cells (iPSCs) and iPSC-derived motor neurons (iMNs). Using RNA sequencing (RNA Seq), we characterized differentially expressed genes (DEGs) and differentially expressed lncRNAs (DELs) and subsequently predicted lncRNA-mRNA target pairs (TAR pairs). Our results show that FUS mutations significantly altered the expression profiles of mRNAs and lncRNAs in iPSCs. Using this large dataset, we identified and verified six key differentially regulated TAR pairs in iPSCs that were also altered in iMNs. These target transcripts included: GPR149, NR4A, LMO3, SLC15A4, ZNF404, and CRACD. These findings indicated that selected mutant FUS-induced transcriptional alterations persist from iPSCs into differentiated iMNs. Functional enrichment analyses of DEGs indicated pathways associated with neuronal development and carcinogenesis as likely altered by these FUS mutations. Furthermore, ingenuity pathway analysis (IPA) and GO network analysis of lncRNA-targeted mRNAs indicated associations between RNA metabolism, lncRNA regulation, and DNA damage repair. Our findings provide insights into potential molecular mechanisms underlying the pathophysiology of ALS-associated FUS mutations and suggest potential therapeutic targets for the treatment of ALS.
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Affiliation(s)
- Vincent E. Provasek
- Division of DNA Repair Research within the Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA; (V.E.P.); (M.K.); (H.W.)
- School of Medicine, Texas A&M University, College Station, TX 77843, USA
| | - Manohar Kodavati
- Division of DNA Repair Research within the Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA; (V.E.P.); (M.K.); (H.W.)
| | - Wenting Guo
- INSERM, UMR-S1118, Mécanismes Centraux et Périphériques de la Neurodégénérescence, Université de Strasbourg, CRBS, 67000 Strasbourg, France;
- VIB, Center for Brain & Disease Research, 3000 Leuven, Belgium
- Leuven Brain Institute (LBI), 3000 Leuven, Belgium
- Stem Cell Institute, Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium;
| | - Haibo Wang
- Division of DNA Repair Research within the Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA; (V.E.P.); (M.K.); (H.W.)
| | - Istvan Boldogh
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX 77555, USA;
| | - Ludo Van Den Bosch
- Stem Cell Institute, Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium;
| | - Gavin Britz
- Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA;
| | - Muralidhar L. Hegde
- Division of DNA Repair Research within the Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA; (V.E.P.); (M.K.); (H.W.)
- School of Medicine, Texas A&M University, College Station, TX 77843, USA
- Department of Neurosurgery, Weill Cornell Medical College, New York, NY 10065, USA
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5
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Provasek VE, Kodavati M, Guo W, Wang H, Boldogh I, Van Den Bosch L, Britz G, Hegde M. lncRNA Sequencing Reveals Neurodegeneration-associated FUS Mutations Alter Transcriptional Landscape of iPS Cells That Persists In Motor Neurons. RESEARCH SQUARE 2023:rs.3.rs-3112246. [PMID: 37461717 PMCID: PMC10350127 DOI: 10.21203/rs.3.rs-3112246/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
Fused-in Sarcoma (FUS) gene mutations have been implicated in amyotrophic lateral sclerosis (ALS). This study aimed to investigate the impact of FUS mutations (R521H and P525L) on the transcriptome of induced pluripotent stem cells (iPSCs) and iPSC-derived motor neurons (iMNs). Using RNA sequencing (RNA Seq), we characterized differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and subsequently predicted lncRNA-mRNA target pairs (TAR pairs). Our results show that FUS mutations significantly altered expression profiles of mRNAs and lncRNAs in iPSCs. We identified key differentially regulated TAR pairs, including LMO3, TMEM132D, ERMN, GPR149, CRACD, and ZNF404 in mutant FUS iPSCs. We performed reverse transcription PCR (RT-PCR) validation in iPSCs and iMNs. Validation confirmed RNA-Seq findings and suggested that mutant FUS-induced transcriptional alterations persisted from iPSCs into differentiated iMNs. Functional enrichment analyses of DEGs indicated pathways associated with neuronal development and carcinogenesis that were likely altered by FUS mutations. Ingenuity Pathway Analysis (IPA) and GO network analysis of lncRNA-targeted mRNAs indicated associations related to RNA metabolism, lncRNA regulation, and DNA damage repair. Our findings provide insights into the molecular mechanisms underlying the pathophysiology of ALS-associated FUS mutations and suggest potential therapeutic targets for the treatment of ALS.
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Affiliation(s)
- Vincent E. Provasek
- Division of DNA Repair Research within the Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA
- School of Medicine, Texas A&M University, College Station, TX 77843, USA
| | - Manohar Kodavati
- Division of DNA Repair Research within the Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Wenting Guo
- KU Leuven-Department of Neurosciences, Experimental Neurology and Leuven Brain Institute (LBI), Leuven, 3000, Belgium
- Stem Cell Institute, Department of Development and Regeneration, KU Leuven, Leuven, Belgium
| | - Haibo Wang
- Division of DNA Repair Research within the Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Istvan Boldogh
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Ludo Van Den Bosch
- KU Leuven-Department of Neurosciences, Experimental Neurology and Leuven Brain Institute (LBI), Leuven, 3000, Belgium
| | - Gavin Britz
- Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA
- Weill Cornell Medical College, New York, NY 10065, USA
| | - Muralidhar Hegde
- Division of DNA Repair Research within the Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA
- School of Medicine, Texas A&M University, College Station, TX 77843, USA
- Weill Cornell Medical College, New York, NY 10065, USA
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6
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Przanowski P, Przanowska RK, Guertin MJ. ANKLE1 cleaves mitochondrial DNA and contributes to cancer risk by promoting apoptosis resistance and metabolic dysregulation. Commun Biol 2023; 6:231. [PMID: 36859531 PMCID: PMC9977882 DOI: 10.1038/s42003-023-04611-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 02/20/2023] [Indexed: 03/03/2023] Open
Abstract
Alleles within the chr19p13.1 locus are associated with increased risk of both ovarian and breast cancer and increased expression of the ANKLE1 gene. ANKLE1 is molecularly characterized as an endonuclease that efficiently cuts branched DNA and shuttles between the nucleus and cytoplasm. However, the role of ANKLE1 in mammalian development and homeostasis remains unknown. In normal development ANKLE1 expression is limited to the erythroblast lineage and we found that ANKLE1's role is to cleave the mitochondrial genome during erythropoiesis. We show that ectopic expression of ANKLE1 in breast epithelial-derived cells leads to genome instability and mitochondrial DNA (mtDNA) cleavage. mtDNA degradation then leads to mitophagy and causes a shift from oxidative phosphorylation to glycolysis (Warburg effect). Moreover, mtDNA degradation activates STAT1 and expression of epithelial-mesenchymal transition (EMT) genes. Reduction in mitochondrial content contributes to apoptosis resistance, which may allow precancerous cells to avoid apoptotic checkpoints and proliferate. These findings provide evidence that ANKLE1 is the causal cancer susceptibility gene in the chr19p13.1 locus and describe mechanisms by which higher ANKLE1 expression promotes cancer risk.
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Affiliation(s)
- Piotr Przanowski
- Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA, USA.
- Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, VA, USA.
| | - Róża K Przanowska
- Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA, USA
- Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Michael J Guertin
- Center for Cell Analysis and Modeling, University of Connecticut, Farmington, CT, USA.
- Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT, USA.
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7
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Dawed AY, Haider E, Pearson ER. Precision Medicine in Diabetes. Handb Exp Pharmacol 2023; 280:107-129. [PMID: 35704097 DOI: 10.1007/164_2022_590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Tailoring treatment or management to groups of individuals based on specific clinical, molecular, and genomic features is the concept of precision medicine. Diabetes is highly heterogenous with respect to clinical manifestations, disease progression, development of complications, and drug response. The current practice for drug treatment is largely based on evidence from clinical trials that report average effects. However, around half of patients with type 2 diabetes do not achieve glycaemic targets despite having a high level of adherence and there are substantial differences in the incidence of adverse outcomes. Therefore, there is a need to identify predictive markers that can inform differential drug responses at the point of prescribing. Recent advances in molecular genetics and increased availability of real-world and randomised trial data have started to increase our understanding of disease heterogeneity and its impact on potential treatments for specific groups. Leveraging information from simple clinical features (age, sex, BMI, ethnicity, and co-prescribed medications) and genomic markers has a potential to identify sub-groups who are likely to benefit from a given drug with minimal adverse effects. In this chapter, we will discuss the state of current evidence in the discovery of clinical and genetic markers that have the potential to optimise drug treatment in type 2 diabetes.
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Affiliation(s)
- Adem Y Dawed
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Eram Haider
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Ewan R Pearson
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK.
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8
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Lebeau B, Zhao K, Jangal M, Zhao T, Guerra M, Greenwood CMT, Witcher M. Single base-pair resolution analysis of DNA binding motif with MoMotif reveals an oncogenic function of CTCF zinc-finger 1 mutation. Nucleic Acids Res 2022; 50:8441-8458. [PMID: 35947648 PMCID: PMC9410893 DOI: 10.1093/nar/gkac658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 07/21/2022] [Indexed: 12/24/2022] Open
Abstract
Defining the impact of missense mutations on the recognition of DNA motifs is highly dependent on bioinformatic tools that define DNA binding elements. However, classical motif analysis tools remain limited in their capacity to identify subtle changes in complex binding motifs between distinct conditions. To overcome this limitation, we developed a new tool, MoMotif, that facilitates a sensitive identification, at the single base-pair resolution, of complex, or subtle, alterations to core binding motifs, discerned from ChIP-seq data. We employed MoMotif to define the previously uncharacterized recognition motif of CTCF zinc-finger 1 (ZF1), and to further define the impact of CTCF ZF1 mutation on its association with chromatin. Mutations of CTCF ZF1 are exclusive to breast cancer and are associated with metastasis and therapeutic resistance, but the underlying mechanisms are unclear. Using MoMotif, we identified an extension of the CTCF core binding motif, necessitating a functional ZF1 to bind appropriately. Using a combination of ChIP-Seq and RNA-Seq, we discover that the inability to bind this extended motif drives an altered transcriptional program associated with the oncogenic phenotypes observed clinically. Our study demonstrates that MoMotif is a powerful new tool for comparative ChIP-seq analysis and characterising DNA-protein contacts.
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Affiliation(s)
| | | | - Maika Jangal
- Lady Davis Institute, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
| | - Tiejun Zhao
- Lady Davis Institute, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
| | - Maria Guerra
- Lady Davis Institute, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
| | - Celia M T Greenwood
- Correspondence may also be addressed to Celia Greenwood. Tel: +1 514 340 8222 (Ext 28397);
| | - Michael Witcher
- To whom correspondence should be addressed. Tel: +1 514 340 8222 (Ext 23363);
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9
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Parrish RL, Gibson GC, Epstein MP, Yang J. TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8. HGG ADVANCES 2022; 3:100068. [PMID: 35047855 PMCID: PMC8756507 DOI: 10.1016/j.xhgg.2021.100068] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 11/01/2021] [Indexed: 01/12/2023] Open
Abstract
Standard transcriptome-wide association study (TWAS) methods first train gene expression prediction models using reference transcriptomic data and then test the association between the predicted genetically regulated gene expression and phenotype of interest. Most existing TWAS tools require cumbersome preparation of genotype input files and extra coding to enable parallel computation. To improve the efficiency of TWAS tools, we developed Transcriptome-Integrated Genetic Association Resource V2 (TIGAR-V2), which directly reads Variant Call Format (VCF) files, enables parallel computation, and reduces up to 90% of computation cost (mainly due to loading genotype data) compared to the original version. TIGAR-V2 can train gene expression imputation models using either nonparametric Bayesian Dirichlet process regression (DPR) or Elastic-Net (as used by PrediXcan), perform TWASs using either individual-level or summary-level genome-wide association study (GWAS) data, and implement both burden and variance-component statistics for gene-based association tests. We trained gene expression prediction models by DPR for 49 tissues using Genotype-Tissue Expression (GTEx) V8 by TIGAR-V2 and illustrated the usefulness of these Bayesian cis-expression quantitative trait locus (eQTL) weights through TWASs of breast and ovarian cancer utilizing public GWAS summary statistics. We identified 88 and 37 risk genes, respectively, for breast and ovarian cancer, most of which are either known or near previously identified GWAS (∼95%) or TWAS (∼40%) risk genes and three novel independent TWAS risk genes with known functions in carcinogenesis. These findings suggest that TWASs can provide biological insight into the transcriptional regulation of complex diseases. The TIGAR-V2 tool, trained Bayesian cis-eQTL weights, and linkage disequilibrium (LD) information from GTEx V8 are publicly available, providing a useful resource for mapping risk genes of complex diseases.
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Affiliation(s)
- Randy L. Parrish
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Greg C. Gibson
- School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Michael P. Epstein
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
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10
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El Ghamrasni S, Quevedo R, Hawley J, Mazrooei P, Hanna Y, Cirlan I, Zhu H, Bruce JP, Oldfield LE, Yang SYC, Guilhamon P, Reimand J, Cescon DW, Done SJ, Lupien M, Pugh TJ. Mutations in Noncoding Cis-Regulatory Elements Reveal Cancer Driver Cistromes in Luminal Breast Cancer. Mol Cancer Res 2022; 20:102-113. [PMID: 34556523 PMCID: PMC9398156 DOI: 10.1158/1541-7786.mcr-21-0471] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 07/31/2021] [Accepted: 09/17/2021] [Indexed: 01/07/2023]
Abstract
Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and noncoding cancer driver plexuses from somatic mutations. However, differentiating driver from passenger events among noncoding genetic variants remains a challenge. Herein, we reveal cancer-driver cis-regulatory elements linked to transcription factors previously shown to be involved in development of luminal breast cancers by defining a tumor-enriched catalogue of approximately 100,000 unique cis-regulatory elements from 26 primary luminal estrogen receptor (ER)+ progesterone receptor (PR)+ breast tumors. Integrating this catalog with somatic mutations from 350 publicly available breast tumor whole genomes, we uncovered cancer driver cistromes, defined as the sum of binding sites for a transcription factor, for ten transcription factors in luminal breast cancer such as FOXA1 and ER, nine of which are essential for growth in breast cancer with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of noncoding mutations over cis-regulatory elements concatenated into a functional unit. IMPLICATIONS: Mapping the accessible chromatin of luminal breast cancer led to discovery of an accumulation of mutations within cistromes of transcription factors essential to luminal breast cancer. This demonstrates coopting of regulatory networks to drive cancer and provides a framework to derive insight into the noncoding space of cancer.
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Affiliation(s)
- Samah El Ghamrasni
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Rene Quevedo
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - James Hawley
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Parisa Mazrooei
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Genentech, South San Francisco, California
| | - Youstina Hanna
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Iulia Cirlan
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Helen Zhu
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Vector Institute, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Jeff P Bruce
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Leslie E Oldfield
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - S Y Cindy Yang
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Paul Guilhamon
- Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
- Arthur and Sonia Labatt Brain Tumor Research Centre, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jüri Reimand
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Dave W Cescon
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Susan J Done
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Mathieu Lupien
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Trevor J Pugh
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
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11
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Jeong J, Shin JH, Li W, Hong JY, Lim J, Hwang JY, Chung JJ, Yan Q, Liu Y, Choi J, Wysolmerski J. MAL2 mediates the formation of stable HER2 signaling complexes within lipid raft-rich membrane protrusions in breast cancer cells. Cell Rep 2021; 37:110160. [PMID: 34965434 PMCID: PMC8762588 DOI: 10.1016/j.celrep.2021.110160] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 08/16/2021] [Accepted: 12/02/2021] [Indexed: 12/18/2022] Open
Abstract
The lipid raft-resident protein, MAL2, has been implicated as contributing to the pathogenesis of several malignancies, including breast cancer, but the underlying mechanism for its effects on tumorigenesis is unknown. Here, we show that MAL2-mediated lipid raft formation leads to HER2 plasma membrane retention and enhanced HER2 signaling in breast cancer cells. We demonstrate physical interactions between HER2 and MAL2 in lipid rafts using proximity ligation assays. Super-resolution structured illumination microscopy imaging displays the structural organization of the HER2/Ezrin/NHERF1/PMCA2 protein complex. Formation of this protein complex maintains low intracellular calcium concentrations in the vicinity of the plasma membrane. HER2/MAL2 protein interactions in lipid rafts are enhanced in trastuzumab-resistant breast cancer cells. Our findings suggest that MAL2 is crucial for lipid raft formation, HER2 signaling, and HER2 membrane stability in breast cancer cells, suggesting MAL2 as a potential therapeutic target. Jeong et al. show that the formation of MAL2-mediated lipid raft-rich membrane protrusions is crucial for HER2 signaling in breast cancer cells. MAL2 is required for the formation of HER2/Ezrin/NHERF1/PMCA2 protein complexes. Formation of these protein complexes leads to a low calcium environment in the plasma membrane
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12
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Torabi Dalivandan S, Plummer J, Gayther SA. Risks and Function of Breast Cancer Susceptibility Alleles. Cancers (Basel) 2021; 13:3953. [PMID: 34439109 PMCID: PMC8393346 DOI: 10.3390/cancers13163953] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 07/30/2021] [Accepted: 07/31/2021] [Indexed: 12/22/2022] Open
Abstract
Family history remains one of the strongest risk factors for breast cancer. It is well established that women with a first-degree relative affected by breast cancer are twice as likely to develop the disease themselves. Twins studies indicate that this is most likely due to shared genetics rather than shared epidemiological/lifestyle risk factors. Linkage and targeted sequencing studies have shown that rare high- and moderate-penetrance germline variants in genes involved in the DNA damage response (DDR) including BRCA1, BRCA2, PALB2, ATM, and TP53 are responsible for a proportion of breast cancer cases. However, breast cancer is a heterogeneous disease, and there is now strong evidence that different risk alleles can predispose to different subtypes of breast cancer. Here, we review the associations between the different genes and subtype-specificity of breast cancer based on the most comprehensive genetic studies published. Genome-wide association studies (GWAS) have also been used to identify an additional hereditary component of breast cancer, and have identified hundreds of common, low-penetrance susceptibility alleles. The combination of these low penetrance risk variants, summed as a polygenic risk score (PRS), can identify individuals across the spectrum of disease risk. However, there remains a substantial bottleneck between the discovery of GWAS-risk variants and their contribution to tumorigenesis mainly because the majority of these variants map to the non-protein coding genome. A range of functional genomic approaches are needed to identify the causal risk variants and target susceptibility genes and establish their underlying role in disease biology. We discuss how the application of these multidisciplinary approaches to understand genetic risk for breast cancer can be used to identify individuals in the population that may benefit from clinical interventions including screening for early detection and prevention, and treatment strategies to reduce breast cancer-related mortalities.
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Affiliation(s)
| | | | - Simon A. Gayther
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA; (S.T.D.); (J.P.)
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13
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Sharma K, Mishra A, Singh HN, Prashar D, Alam P, Thinlas T, Mohammad G, Kukreti R, Syed MA, Pasha MAQ. High-altitude pulmonary edema is aggravated by risk-loci and associated transcription factors in HIF-prolyl hydroxylases. Hum Mol Genet 2021; 30:1734-1749. [PMID: 34007987 DOI: 10.1093/hmg/ddab139] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 05/10/2021] [Accepted: 05/11/2021] [Indexed: 11/15/2022] Open
Abstract
High-altitude (HA, > 2500 meters) hypoxic exposure evokes several physiological processes that may be abetted by differential genetic distribution in sojourners, who are susceptible to various HA disorders, such as high-altitude pulmonary edema (HAPE). The genetic variants in hypoxia-sensing genes influence the transcriptional output, however the functional role has not been investigated in HAPE. This study explored the two hypoxia-sensing genes, prolyl hydroxylase domain protein 2 (EGLN1) and factor inhibiting HIF-1α (HIF1AN) in HA adaptation and maladaptation in three well-characterized groups: highland natives, HAPE-free controls and HAPE-patients. The two genes were sequenced and subsequently validated through genotyping of significant SNPs, haplotyping and MDR. Three EGLN1 SNPs rs1538664, rs479200 and rs480902 and their haplotypes emerged significant in HAPE. Blood gene expression and protein levels also differed significantly (P < 0.05) and correlated with clinical parameters and respective alleles. The RegulomeDB annotation exercises of the loci corroborated regulatory role. Allele-specific differential expression was evidenced by luciferase assay followed by electrophoretic mobility shift assay, LC-MS/MS and supershift assays, which confirmed allele-specific transcription factor (TF) binding of FUS RNA binding protein (FUS) with rs1538664A, Rho GDP dissociation inhibitor 1 (RhoGDH1) with rs479200T and Hypoxia up-regulated protein 1 (HYOU1) with rs480902C. Docking simulation studies were in sync for the DNA-TF structural variations. There was strong networking among the TFs that revealed physiological consequences through relevant pathways. The two hydroxylases appear crucial in the regulation of hypoxia-inducible responses.
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Affiliation(s)
- Kavita Sharma
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Delhi, 110007, India.,Department of Biotechnology, Jamia Millia Islamia, New Delhi, 110025, India
| | - Aastha Mishra
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Delhi, 110007, India
| | - Himanshu N Singh
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Delhi, 110007, India
| | - Deepak Prashar
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Delhi, 110007, India
| | - Perwez Alam
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Delhi, 110007, India.,Department of Pathology and Laboratory Medicine, College of Medicine, University of Cincinnati, OH, USA
| | | | | | - Ritushree Kukreti
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Delhi, 110007, India
| | - Mansoor Ali Syed
- Department of Biotechnology, Jamia Millia Islamia, New Delhi, 110025, India
| | - M A Qadar Pasha
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Delhi, 110007, India.,Indian Council of Medical Research, New Delhi, 110029, India
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14
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Chyr J, Zhang Z, Chen X, Zhou X. PredTAD: A machine learning framework that models 3D chromatin organization alterations leading to oncogene dysregulation in breast cancer cell lines. Comput Struct Biotechnol J 2021; 19:2870-2880. [PMID: 34093998 PMCID: PMC8142020 DOI: 10.1016/j.csbj.2021.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 05/04/2021] [Accepted: 05/04/2021] [Indexed: 10/26/2022] Open
Abstract
Topologically associating domains, or TADs, play important roles in genome organization and gene regulation; however, they are often altered in diseases. High-throughput chromatin conformation capturing assays, such as Hi-C, can capture domains of increased interactions, and TADs and boundaries can be identified using well-established analytical tools. However, generating Hi-C data is expensive. In our study, we addressed the relationship between multi-omics data and higher-order chromatin structures using a newly developed machine-learning model called PredTAD. Our tool uses already-available and cost-effective datatypes such as transcription factor and histone modification ChIPseq data. Specifically, PredTAD utilizes both epigenetic and genetic features as well as neighboring information to classify the entire human genome as boundary or non-boundary regions. Our tool can predict boundary changes between normal and breast cancer genomes. Among the most important features for predicting boundary alterations were CTCF, subunits of cohesin (RAD21 and SMC3), and chromosome number, suggesting their roles in conserved and dynamic boundaries formation. Upon further analysis, we observed that genes near altered TAD boundaries were found to be involved in several important breast cancer signaling pathways such as Ras, Jak-STAT, and estrogen signaling pathways. We also discovered a TAD boundary alteration that contributes to RET oncogene overexpression. PredTAD can also successfully predict TAD boundary changes in other conditions and diseases. In conclusion, our newly developed machine learning tool allowed for a more complete understanding of the dynamic 3D chromatin structures involved in signaling pathway activation, altered gene expression, and disease state in breast cancer cells.
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Affiliation(s)
- Jacqueline Chyr
- School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX 77054, USA
| | - Zhigang Zhang
- School of Information Management and Statistics, Hubei University of Economics, Wuhan, Hubei 430205 China
| | - Xi Chen
- School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX 77054, USA
| | - Xiaobo Zhou
- School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX 77054, USA
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15
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Pappas K, Martin TC, Wolfe AL, Nguyen CB, Su T, Jin J, Hibshoosh H, Parsons R. NOTCH and EZH2 collaborate to repress PTEN expression in breast cancer. Commun Biol 2021; 4:312. [PMID: 33750924 PMCID: PMC7943788 DOI: 10.1038/s42003-021-01825-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 02/04/2021] [Indexed: 12/22/2022] Open
Abstract
Downregulation of the PTEN tumor suppressor transcript is frequent in breast cancer and associates with poor prognosis and triple-negative breast cancer (TNBC) when comparing breast cancers to one another. Here we show that in almost all cases, when comparing breast tumors to adjacent normal ducts, PTEN expression is decreased and the PRC2-associated methyltransferase EZH2 is increased. We further find that when comparing breast cancer cases in large cohorts, EZH2 inversely correlates with PTEN expression. Within the highest EZH2 expressing group, NOTCH alterations are frequent, and also associate with decreased PTEN expression. We show that repression of PTEN occurs through the combined action of NOTCH (NOTCH1 or NOTCH2) and EZH2 alterations in a subset of breast cancers. In fact, in cases harboring NOTCH1 mutation or a NOTCH2 fusion gene, NOTCH drives EZH2, HES-1, and HEY-1 expression to repress PTEN transcription at the promoter, which may contribute to poor prognosis in this subgroup. Restoration of PTEN expression can be achieved with an EZH2 inhibitor (UNC1999), a γ-secretase inhibitor (Compound E), or knockdown of EZH2 or NOTCH. These findings elucidate a mechanism of transcriptional repression of PTEN induced by NOTCH1 or NOTCH2 alterations, and identifies actionable signaling pathways responsible for driving a large subset of poor-prognosis breast cancers. Pappas et al. show that the combination of NOTCH and EZH2 alterations drive transcriptional repression of PTEN through reversible epigenetic modification of the PTEN promoter. These results suggest an actionable target for treating poor-prognosis breast cancer.
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Affiliation(s)
- Kyrie Pappas
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Pharmacology, Columbia University Medical Center, New York, NY, USA.,Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Tiphaine C Martin
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrew L Wolfe
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA
| | - Christie B Nguyen
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tao Su
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA
| | - Jian Jin
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Mount Sinai Center for Therapeutics Discovery, Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hanina Hibshoosh
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA
| | - Ramon Parsons
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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16
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MYBL2 amplification in breast cancer: Molecular mechanisms and therapeutic potential. Biochim Biophys Acta Rev Cancer 2020; 1874:188407. [DOI: 10.1016/j.bbcan.2020.188407] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/21/2020] [Accepted: 07/21/2020] [Indexed: 02/08/2023]
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17
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Chanana N, Palmo T, Newman JH, Pasha MAQ. Vascular homeostasis at high-altitude: role of genetic variants and transcription factors. Pulm Circ 2020; 10:2045894020913475. [PMID: 33282179 PMCID: PMC7682230 DOI: 10.1177/2045894020913475] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 02/14/2020] [Indexed: 12/24/2022] Open
Abstract
High-altitude pulmonary edema occurs most frequently in non-acclimatized low landers on exposure to altitude ≥2500 m. High-altitude pulmonary edema is a complex condition that involves perturbation of signaling pathways in vasoconstrictors, vasodilators, anti-diuretics, and vascular growth factors. Genetic variations are instrumental in regulating these pathways and evidence is accumulating for a role of epigenetic modification in hypoxic responses. This review focuses on the crosstalk between high-altitude pulmonary edema-associated genetic variants and transcription factors, comparing high-altitude adapted and high-altitude pulmonary edema-afflicted subjects. This approach might ultimately yield biomarker information both to understand and to design therapies for high-altitude adaptation.
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Affiliation(s)
- Neha Chanana
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Delhi, India
| | - Tsering Palmo
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Delhi, India
| | - John H Newman
- Pulmonary Circulation Center, Division of Allergy, Pulmonary and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - M A Qadar Pasha
- Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology, Delhi, India.,Indian Council of Medical Research, New Delhi, India
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18
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Das T, Deb A, Parida S, Mondal S, Khatua S, Ghosh Z. LncRBase V.2: an updated resource for multispecies lncRNAs and ClinicLSNP hosting genetic variants in lncRNAs for cancer patients. RNA Biol 2020; 18:1136-1151. [PMID: 33112702 DOI: 10.1080/15476286.2020.1833529] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The recent discovery of long non-coding RNA as a regulatory molecule in the cellular system has altered the concept of the functional aptitude of the genome. Since our publication of the first version of LncRBase in 2014, there has been an enormous increase in the number of annotated lncRNAs of multiple species other than Human and Mouse. LncRBase V.2 hosts information of 549,648 lncRNAs corresponding to six additional species besides Human and Mouse, viz. Rat, Fruitfly, Zebrafish, Chicken, Cow and C.elegans. It provides additional distinct features such as (i) Transcription Factor Binding Site (TFBS) in the lncRNA promoter region, (ii) sub-cellular localization pattern of lncRNAs (iii) lnc-pri-miRNAs (iv) Possible small open reading frames (sORFs) within lncRNA. (v) Manually curated information of interacting target molecules and disease association of lncRNA genes (vi) Distribution of lncRNAs across multiple tissues of all species. Moreover, we have hosted ClinicLSNP within LncRBase V.2. ClinicLSNP has a comprehensive catalogue of lncRNA variants present within breast, ovarian, and cervical cancer inferred from 561 RNA-Seq data corresponding to these cancers. Further, we have checked whether these lncRNA variants overlap with (i)Repeat elements,(ii)CGI, (iii)TFBS within lncRNA loci (iv)SNP localization in trait-associated Linkage Disequilibrium(LD) region, (v)predicted the potentially pathogenic variants and (vi)effect of SNP on lncRNA secondary structure. Overall, LncRBaseV.2 is a user-friendly database to survey, search and retrieve information about multi-species lncRNAs. Further, ClinicLSNP will serve as a useful resource for cancer specific lncRNA variants and their related information. The database is freely accessible and available at http://dibresources.jcbose.ac.in/zhumur/lncrbase2/.
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Affiliation(s)
- Troyee Das
- Division of Bioinformatics, Bose Institute, Kolkata, India
| | - Aritra Deb
- Division of Bioinformatics, Bose Institute, Kolkata, India
| | - Sibun Parida
- Division of Bioinformatics, Bose Institute, Kolkata, India
| | - Sudip Mondal
- Department of Computer Science and Engineering, University of Calcutta, Kolkata, India
| | - Sunirmal Khatua
- Department of Computer Science and Engineering, University of Calcutta, Kolkata, India
| | - Zhumur Ghosh
- Division of Bioinformatics, Bose Institute, Kolkata, India
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19
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Gorini F, Scala G, Di Palo G, Dellino GI, Cocozza S, Pelicci PG, Lania L, Majello B, Amente S. The genomic landscape of 8-oxodG reveals enrichment at specific inherently fragile promoters. Nucleic Acids Res 2020; 48:4309-4324. [PMID: 32198884 PMCID: PMC7192600 DOI: 10.1093/nar/gkaa175] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 03/09/2020] [Accepted: 03/11/2020] [Indexed: 12/12/2022] Open
Abstract
8-Oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG) is the most common marker of oxidative stress and its accumulation within the genome has been associated with major human health issues such as cancer, aging, cardiovascular and neurodegenerative diseases. The characterization of the different genomic sites where 8-oxodG accumulates and the mechanisms underlying its formation are still poorly understood. Using OxiDIP-seq, we recently derived the genome-wide distribution of 8-oxodG in human non-tumorigenic epithelial breast cells (MCF10A). Here, we identify a subset of human promoters that accumulate 8-oxodG under steady-state condition. 8-oxodG nucleotides co-localize with double strand breaks (DSBs) at bidirectional and CG skewed promoters and their density correlate with RNA Polymerase II co-occupancy and transcription. Furthermore, by performing OxiDIP-seq in quiescent (G0) cells, we found a strong reduction of oxidatively-generated damage in the majority of 8-oxodG-positive promoters in the absence of DNA replication. Overall, our results suggest that the accumulation of 8-oxodG at gene promoters occurs through DNA replication-dependent or -independent mechanisms, with a possible contribution to the formation of cancer-associated translocation events.
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Affiliation(s)
- Francesca Gorini
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples 'Federico II', Naples, Italy
| | - Giovanni Scala
- Department of Biology, University of Naples 'Federico II', Naples, Italy
| | - Giacomo Di Palo
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples 'Federico II', Naples, Italy
| | - Gaetano Ivan Dellino
- Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milan, Italy.,Department of Oncology and Hemato-oncology, University of Milano, Milan, Italy
| | - Sergio Cocozza
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples 'Federico II', Naples, Italy
| | - Pier Giuseppe Pelicci
- Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milan, Italy.,Department of Oncology and Hemato-oncology, University of Milano, Milan, Italy
| | - Luigi Lania
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples 'Federico II', Naples, Italy
| | - Barbara Majello
- Department of Biology, University of Naples 'Federico II', Naples, Italy
| | - Stefano Amente
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples 'Federico II', Naples, Italy
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20
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Liu L, Lu M, Gu X, Ma X, Feng J, Cao Y, Gong W, Zhao Q, Qiang F. SMADs binding site polymorphisms rs9911630 is associated with susceptibility but not prognosis of gastric cancer: a case control study. J Cancer 2020; 11:4746-4753. [PMID: 32626521 PMCID: PMC7330692 DOI: 10.7150/jca.40089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Accepted: 05/02/2020] [Indexed: 11/16/2022] Open
Abstract
Background: Single nucleotide polymorphisms (SNPs) in transcription factor binding sites (TFBS) can change their binding strength, affecting the function of transcription factors (TFs). Small mother against decapentaplegic (SMAD) proteins are known as a family of TFs involved in tumorigenesis. We performed this study to investigate whether SNPs in SMADs binding sites affect the susceptibility or prognosis of gastric cancer (GC). Methods: Using bioinformatics tools, we focused on the association between rs9911630 polymorphism and GC. We performed this case-control study in 1275 GC patients and 1426 cancer-free subjects using TaqMan allelic discrimination method. Results: We found that rs9911630 A>G polymorphism was associate to an increased risk of gastric cancer (adjusted OR for additive model = 1.16; 95% CI = 1.03-1.30). Furthermore, we assess whether rs9911630 polymorphism affected the prognosis of GC. However, no significant association was discovered between rs9911630 A>G polymorphism and overall survival time of GC patients (HR for addictive model = 1.01; 95%CI = 0.88-1.15). Conclusions: Our results suggested that rs9911630 polymorphism in SMADs target site might influence susceptibility but not prognosis of gastric cancer.
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Affiliation(s)
- Liyang Liu
- Department of General Surgery, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Ming Lu
- Department of General Surgery, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xi Gu
- Department of General Surgery, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiang Ma
- Department of General Surgery, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jiaxi Feng
- Department of General Surgery, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yang Cao
- Department of General Surgery, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Weida Gong
- Department of General Surgery, Yixing Tumor Hospital, Yixing, Jiangsu, China
| | - Qinghong Zhao
- Department of General Surgery, the Second Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Fulin Qiang
- Department of Core Laboratory, Nantong Tumor Hospital, Nantong, Jiangsu, China
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21
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Azawi S, Liehr T, Rincic M, Manferrari M. Molecular Cytogenomic Characterization of the Murine Breast Cancer Cell Lines C-127I, EMT6/P and TA3 Hauschka. Int J Mol Sci 2020; 21:ijms21134716. [PMID: 32630352 PMCID: PMC7369978 DOI: 10.3390/ijms21134716] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 06/26/2020] [Accepted: 07/01/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND To test and introduce effective and less toxic breast cancer (BC) treatment strategies, animal models, including murine BC cell lines, are considered as perfect platforms. Strikingly, the knowledge on the genetic background of applied BC cell lines is often sparse though urgently necessary for their targeted and really justified application. METHODS In this study, we performed the first molecular cytogenetic characterization for three murine BC cell lines C-127I, EMT6/P and TA3 Hauschka. Besides fluorescence in situ hybridization-banding, array comparative genomic hybridization was also applied. Thus, overall, an in silico translation for the detected imbalances and chromosomal break events in the murine cell lines to the corresponding homologous imbalances in humans could be provided. The latter enabled a comparison of the murine cell line with human BC cytogenomics. RESULTS All three BC cell lines showed a rearranged karyotype at different stages of complexity, which can be interpreted carefully as reflectance of more or less advanced tumor stages. CONCLUSIONS Accordingly, the C-127I cell line would represent the late stage BC while the cell lines EMT6/P and TA3 Hauschka would be models for the premalignant or early BC stage and an early or benign BC, respectively. With this cytogenomic information provided, these cell lines now can be applied really adequately in future research studies.
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Affiliation(s)
- Shaymaa Azawi
- Jena University Hospital, Friedrich Schiller University, Institute of Human Genetics, Am Klinikum 1, D-07747 Jena, Germany
| | - Thomas Liehr
- Jena University Hospital, Friedrich Schiller University, Institute of Human Genetics, Am Klinikum 1, D-07747 Jena, Germany
| | - Martina Rincic
- Croatian Institute for Brain Research, School of Medicine University of Zagreb, Salata 12, 10000 Zagreb, Croatia
| | - Mattia Manferrari
- Jena University Hospital, Friedrich Schiller University, Institute of Human Genetics, Am Klinikum 1, D-07747 Jena, Germany
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22
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van de Geijn B, Finucane H, Gazal S, Hormozdiari F, Amariuta T, Liu X, Gusev A, Loh PR, Reshef Y, Kichaev G, Raychauduri S, Price AL. Annotations capturing cell type-specific TF binding explain a large fraction of disease heritability. Hum Mol Genet 2020; 29:1057-1067. [PMID: 31595288 PMCID: PMC7206853 DOI: 10.1093/hmg/ddz226] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 08/12/2019] [Accepted: 09/10/2019] [Indexed: 12/21/2022] Open
Abstract
Regulatory variation plays a major role in complex disease and that cell type-specific binding of transcription factors (TF) is critical to gene regulation. However, assessing the contribution of genetic variation in TF-binding sites to disease heritability is challenging, as binding is often cell type-specific and annotations from directly measured TF binding are not currently available for most cell type-TF pairs. We investigate approaches to annotate TF binding, including directly measured chromatin data and sequence-based predictions. We find that TF-binding annotations constructed by intersecting sequence-based TF-binding predictions with cell type-specific chromatin data explain a large fraction of heritability across a broad set of diseases and corresponding cell types; this strategy of constructing annotations addresses both the limitation that identical sequences may be bound or unbound depending on surrounding chromatin context and the limitation that sequence-based predictions are generally not cell type-specific. We partitioned the heritability of 49 diseases and complex traits using stratified linkage disequilibrium (LD) score regression with the baseline-LD model (which is not cell type-specific) plus the new annotations. We determined that 100 bp windows around MotifMap sequenced-based TF-binding predictions intersected with a union of six cell type-specific chromatin marks (imputed using ChromImpute) performed best, with an 58% increase in heritability enrichment compared to the chromatin marks alone (11.6× vs. 7.3×, P = 9 × 10-14 for difference) and a 20% increase in cell type-specific signal conditional on annotations from the baseline-LD model (P = 8 × 10-11 for difference). Our results show that TF-binding annotations explain substantial disease heritability and can help refine genome-wide association signals.
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Affiliation(s)
- Bryce van de Geijn
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, MA, USA
| | - Hilary Finucane
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Steven Gazal
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, MA, USA
| | - Farhad Hormozdiari
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, MA, USA
| | - Tiffany Amariuta
- Center for Data Sciences, Harvard Medical School, Boston, MA 02215, USA
- Divisions of Genetics, Rheumatology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02215, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02215, USA
- Graduate School of Arts and Sciences, Harvard University, Boston, MA 02215, USA
| | - Xuanyao Liu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, MA, USA
| | | | - Po-Ru Loh
- Brigham and Women’s Hospital, Boston, MA 02215, USA
| | - Yakir Reshef
- Department of Computer Science, Harvard University, Cambridge, MA 02138, USA
- Harvard/MIT MD/PhD Program, Boston, MA 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
| | - Gleb Kichaev
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Soumya Raychauduri
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, MA, USA
- Center for Data Sciences, Harvard Medical School, Boston, MA 02215, USA
- Divisions of Genetics, Rheumatology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02215, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02215, USA
- Graduate School of Arts and Sciences, Harvard University, Boston, MA 02215, USA
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
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23
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Integrating genome-wide association study with regulatory SNP annotation information identified candidate genes and pathways for schizophrenia. Aging (Albany NY) 2019; 11:3704-3715. [PMID: 31175266 PMCID: PMC6594824 DOI: 10.18632/aging.102008] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2019] [Accepted: 05/29/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Schizophrenia is a complex mental disorder. The genetic mechanism of schizophrenia remains elusive now. METHODS We conducted a large-scale integrative analysis of two genome-wide association studies of schizophrenia with functional annotation datasets of regulatory single-nucleotide polymorphism (rSNP). The significant SNPs identified by the two genome-wide association studies were first annotated to obtain schizophrenia associated rSNPs and their target genes and proteins, respectively. We then compared the integrative analysis results to identify the common rSNPs and their target regulatory genes and proteins, shared by the two genome-wide association studies of schizophrenia. Finally, DAVID tool was used to conduct gene ontology and pathway enrichment analysis of the identified targets genes and proteins. RESULTS We detected 53 schizophrenia-associated target genes for rSNP, such as FOS (P value = 2.18×10-20), ATXN1 (P value = 5.22×10-21) and HLA-DQA1 (P value = 1.98×10-10). Pathway enrichment analysis identified 24 pathways for transcription factors binding regions, chromatin interacting regions, long non-coding RNAs, topologically associated domains, circular RNAs and post-translational modifications, such as hsa05034:Alcoholism (P value = 2.57×10-7) and hsa04612:Antigen processing and presentation (P value = 6.82×10-8). CONCLUSION We detected multiple candidate genes, gene ontology terms and pathways for schizophrenia, supporting the functional importance of rSNPs, and providing novel clues for understanding the genetic architecture of schizophrenia.
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24
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Ion Channel Targeting with Antibodies and Antibody Fragments for Cancer Diagnosis. Antibodies (Basel) 2019; 8:antib8020033. [PMID: 31544839 PMCID: PMC6640718 DOI: 10.3390/antib8020033] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Revised: 05/17/2019] [Accepted: 05/20/2019] [Indexed: 12/12/2022] Open
Abstract
The antibody era has greatly impacted cancer management in recent decades. Indeed, antibodies are currently applied for both cancer diagnosis and therapy. For example, monoclonal antibodies are the main constituents of several in vitro diagnostics, which are applied at many levels of cancer diagnosis. Moreover, the great improvement provided by in vivo imaging, especially for early-stage cancer diagnosis, has traced the path for the development of a complete new class of antibodies, i.e., engineered antibody fragments. The latter embody the optimal characteristics (e.g., low renal retention, rapid clearance, and small size) which make them ideal for in vivo applications. Furthermore, the present review focuses on reviewing the main applications of antibodies and antibody fragments for solid cancer diagnosis, both in vitro and in vivo. Furthermore, we review the scientific evidence showing that ion channels represent an almost unexplored class of ideal targets for both in vitro and in vivo diagnostic purposes. In particular, we review the applications, in solid cancers, of monoclonal antibodies and engineered antibody fragments targeting the voltage-dependent ion channel Kv 11.1, also known as hERG1.
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25
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Reshef YA, Finucane HK, Kelley DR, Gusev A, Kotliar D, Ulirsch JC, Hormozdiari F, Nasser J, O'Connor L, van de Geijn B, Loh PR, Grossman SR, Bhatia G, Gazal S, Palamara PF, Pinello L, Patterson N, Adams RP, Price AL. Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk. Nat Genet 2018; 50:1483-1493. [PMID: 30177862 PMCID: PMC6202062 DOI: 10.1038/s41588-018-0196-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 07/11/2018] [Indexed: 12/19/2022]
Abstract
Biological interpretation of genome-wide association study data frequently involves assessing whether SNPs linked to a biological process, for example, binding of a transcription factor, show unsigned enrichment for disease signal. However, signed annotations quantifying whether each SNP allele promotes or hinders the biological process can enable stronger statements about disease mechanism. We introduce a method, signed linkage disequilibrium profile regression, for detecting genome-wide directional effects of signed functional annotations on disease risk. We validate the method via simulations and application to molecular quantitative trait loci in blood, recovering known transcriptional regulators. We apply the method to expression quantitative trait loci in 48 Genotype-Tissue Expression tissues, identifying 651 transcription factor-tissue associations including 30 with robust evidence of tissue specificity. We apply the method to 46 diseases and complex traits (average n = 290 K), identifying 77 annotation-trait associations representing 12 independent transcription factor-trait associations, and characterize the underlying transcriptional programs using gene-set enrichment analyses. Our results implicate new causal disease genes and new disease mechanisms.
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Affiliation(s)
- Yakir A Reshef
- Department of Computer Science, Harvard University, Cambridge, MA, USA.
- Harvard/MIT MD/PhD Program, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | | | - David R Kelley
- California Life Sciences LLC, South San Francisco, CA, USA
| | | | - Dylan Kotliar
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jacob C Ulirsch
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Dana Farber Cancer Institute, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | - Farhad Hormozdiari
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Joseph Nasser
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Luke O'Connor
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA, USA
| | - Bryce van de Geijn
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Po-Ru Loh
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sharon R Grossman
- Harvard/MIT MD/PhD Program, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Gaurav Bhatia
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Steven Gazal
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Pier Francesco Palamara
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Statistics, University of Oxford, Oxford, UK
| | - Luca Pinello
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital, Charlestown, MA, USA
- Department of Pathology, Harvard Medical School, Boston, MA, USA
| | | | - Ryan P Adams
- Google Brain, New York, NY, USA
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Alkes L Price
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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26
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Rivandi M, Martens JWM, Hollestelle A. Elucidating the Underlying Functional Mechanisms of Breast Cancer Susceptibility Through Post-GWAS Analyses. Front Genet 2018; 9:280. [PMID: 30116257 PMCID: PMC6082943 DOI: 10.3389/fgene.2018.00280] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 07/09/2018] [Indexed: 12/12/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified more than 170 single nucleotide polymorphisms (SNPs) associated with the susceptibility to breast cancer. Together, these SNPs explain 18% of the familial relative risk, which is estimated to be nearly half of the total familial breast cancer risk that is collectively explained by low-risk susceptibility alleles. An important aspect of this success has been the access to large sample sizes through collaborative efforts within the Breast Cancer Association Consortium (BCAC), but also collaborations between cancer association consortia. Despite these achievements, however, understanding of each variant's underlying mechanism and how these SNPs predispose women to breast cancer remains limited and represents a major challenge in the field, particularly since the vast majority of the GWAS-identified SNPs are located in non-coding regions of the genome and are merely tags for the causal variants. In recent years, fine-scale mapping studies followed by functional evaluation of putative causal variants have begun to elucidate the biological function of several GWAS-identified variants. In this review, we discuss the findings and lessons learned from these post-GWAS analyses of 22 risk loci. Identifying the true causal variants underlying breast cancer susceptibility and their function not only provides better estimates of the explained familial relative risk thereby improving polygenetic risk scores (PRSs), it also increases our understanding of the biological mechanisms responsible for causing susceptibility to breast cancer. This will facilitate the identification of further breast cancer risk alleles and the development of preventive medicine for those women at increased risk for developing the disease.
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Affiliation(s)
- Mahdi Rivandi
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, Netherlands.,Department of Modern Sciences and Technologies, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - John W M Martens
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, Netherlands.,Cancer Genomics Centre, Utrecht, Netherlands
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27
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Parry AJ, Hoare M, Bihary D, Hänsel-Hertsch R, Smith S, Tomimatsu K, Mannion E, Smith A, D'Santos P, Russell IA, Balasubramanian S, Kimura H, Samarajiwa SA, Narita M. NOTCH-mediated non-cell autonomous regulation of chromatin structure during senescence. Nat Commun 2018; 9:1840. [PMID: 29743479 PMCID: PMC5943456 DOI: 10.1038/s41467-018-04283-9] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2017] [Accepted: 04/16/2018] [Indexed: 12/16/2022] Open
Abstract
Senescent cells interact with the surrounding microenvironment achieving diverse functional outcomes. We have recently identified that NOTCH1 can drive 'lateral induction' of a unique senescence phenotype in adjacent cells by specifically upregulating the NOTCH ligand JAG1. Here we show that NOTCH signalling can modulate chromatin structure autonomously and non-autonomously. In addition to senescence-associated heterochromatic foci (SAHF), oncogenic RAS-induced senescent (RIS) cells exhibit a massive increase in chromatin accessibility. NOTCH signalling suppresses SAHF and increased chromatin accessibility in this context. Strikingly, NOTCH-induced senescent cells, or cancer cells with high JAG1 expression, drive similar chromatin architectural changes in adjacent cells through cell-cell contact. Mechanistically, we show that NOTCH signalling represses the chromatin architectural protein HMGA1, an association found in multiple human cancers. Thus, HMGA1 is involved not only in SAHFs but also in RIS-driven chromatin accessibility. In conclusion, this study identifies that the JAG1-NOTCH-HMGA1 axis mediates the juxtacrine regulation of chromatin architecture.
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Affiliation(s)
- Aled J Parry
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
| | - Matthew Hoare
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
- Department of Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Dóra Bihary
- MRC Cancer Unit, Hutchison/MRC Research Centre, University of Cambridge, Cambridge Biomedical Campus, Cambridge, CB2 0XZ, UK
| | - Robert Hänsel-Hertsch
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
| | - Stephen Smith
- Department of Pathology, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Kosuke Tomimatsu
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
| | - Elizabeth Mannion
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
| | - Amy Smith
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
| | - Paula D'Santos
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
| | - I Alasdair Russell
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
| | - Shankar Balasubramanian
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK
| | - Hiroshi Kimura
- Cell Biology Centre, Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, 226-8503, Japan
| | - Shamith A Samarajiwa
- MRC Cancer Unit, Hutchison/MRC Research Centre, University of Cambridge, Cambridge Biomedical Campus, Cambridge, CB2 0XZ, UK.
| | - Masashi Narita
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK.
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28
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Ma L, Liang Z, Zhou H, Qu L. Applications of RNA Indexes for Precision Oncology in Breast Cancer. GENOMICS, PROTEOMICS & BIOINFORMATICS 2018; 16:108-119. [PMID: 29753129 PMCID: PMC6112337 DOI: 10.1016/j.gpb.2018.03.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2017] [Revised: 03/25/2018] [Accepted: 03/30/2018] [Indexed: 12/11/2022]
Abstract
Precision oncology aims to offer the most appropriate treatments to cancer patients mainly based on their individual genetic information. Genomics has provided numerous valuable data on driver mutations and risk loci; however, it remains a formidable challenge to transform these data into therapeutic agents. Transcriptomics describes the multifarious expression patterns of both mRNAs and non-coding RNAs (ncRNAs), which facilitates the deciphering of genomic codes. In this review, we take breast cancer as an example to demonstrate the applications of these rich RNA resources in precision medicine exploration. These include the use of mRNA profiles in triple-negative breast cancer (TNBC) subtyping to inform corresponding candidate targeted therapies; current advancements and achievements of high-throughput RNA interference (RNAi) screening technologies in breast cancer; and microRNAs as functional signatures for defining cell identities and regulating the biological activities of breast cancer cells. We summarize the benefits of transcriptomic analyses in breast cancer management and propose that unscrambling the core signaling networks of cancer may be an important task of multiple-omic data integration for precision oncology.
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Affiliation(s)
- Liming Ma
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China
| | - Zirui Liang
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China
| | - Hui Zhou
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China
| | - Lianghu Qu
- Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China.
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29
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Mechanic LE, Lindström S, Daily KM, Sieberts SK, Amos CI, Chen HS, Cox NJ, Dathe M, Feuer EJ, Guertin MJ, Hoffman J, Liu Y, Moore JH, Myers CL, Ritchie MD, Schildkraut J, Schumacher F, Witte JS, Wang W, Williams SM, Gillanders EM. Up For A Challenge (U4C): Stimulating innovation in breast cancer genetic epidemiology. PLoS Genet 2017; 13:e1006945. [PMID: 28957327 PMCID: PMC5619686 DOI: 10.1371/journal.pgen.1006945] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Affiliation(s)
- Leah E. Mechanic
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail:
| | - Sara Lindström
- Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington, United States of America
| | | | | | - Christopher I. Amos
- Department of Biomedical Data Sciences, Dartmouth College, Lebanon, New Hampshire, United States of America
| | - Huann-Sheng Chen
- Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Nancy J. Cox
- Division of Genetic Medicine, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Marina Dathe
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Eric J. Feuer
- Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Michael J. Guertin
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Joshua Hoffman
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America
| | - Yunxian Liu
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Jason H. Moore
- Division of Informatics, Department of Biostatistics and Epidemiology, Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Chad L. Myers
- Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, Minnesota, United States of America
| | - Marylyn D. Ritchie
- Department of Biochemistry and Molecular Biology, Center for Systems Genomics, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Biomedical and Translational Informatics, Geisinger Health System, Danville, Pennsylvania, United States of America
| | - Joellen Schildkraut
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Fredrick Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - John S. Witte
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America
| | - Wen Wang
- Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, Minnesota, United States of America
| | - Scott M. Williams
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | | | | | - Elizabeth M. Gillanders
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
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