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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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Li J, Lin Y, Li D, He M, Kui H, Bai J, Chen Z, Gou Y, Zhang J, Wang T, Tang Q, Kong F, Jin L, Li M. Building Haplotype-Resolved 3D Genome Maps of Chicken Skeletal Muscle. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2305706. [PMID: 38582509 PMCID: PMC11200017 DOI: 10.1002/advs.202305706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 03/07/2024] [Indexed: 04/08/2024]
Abstract
Haplotype-resolved 3D chromatin architecture related to allelic differences in avian skeletal muscle development has not been addressed so far, although chicken husbandry for meat consumption has been prevalent feature of cultures on every continent for more than thousands of years. Here, high-resolution Hi-C diploid maps (1.2-kb maximum resolution) are generated for skeletal muscle tissues in chicken across three developmental stages (embryonic day 15 to day 30 post-hatching). The sequence features governing spatial arrangement of chromosomes and characterize homolog pairing in the nucleus, are identified. Multi-scale characterization of chromatin reorganization between stages from myogenesis in the fetus to myofiber hypertrophy after hatching show concordant changes in transcriptional regulation by relevant signaling pathways. Further interrogation of parent-of-origin-specific chromatin conformation supported that genomic imprinting is absent in birds. This study also reveals promoter-enhancer interaction (PEI) differences between broiler and layer haplotypes in skeletal muscle development-related genes are related to genetic variation between breeds, however, only a minority of breed-specific variations likely contribute to phenotypic divergence in skeletal muscle potentially via allelic PEI rewiring. Beyond defining the haplotype-specific 3D chromatin architecture in chicken, this study provides a rich resource for investigating allelic regulatory divergence among chicken breeds.
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Affiliation(s)
- Jing Li
- State Key Laboratory of Swine and Poultry Breeding IndustryCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
| | - Yu Lin
- State Key Laboratory of Swine and Poultry Breeding IndustryCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
| | - Diyan Li
- School of PharmacyChengdu UniversityChengdu610106China
| | - Mengnan He
- Wildlife Conservation Research DepartmentChengdu Research Base of Giant Panda BreedingChengdu610057China
| | - Hua Kui
- State Key Laboratory of Swine and Poultry Breeding IndustryCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
| | - Jingyi Bai
- State Key Laboratory of Swine and Poultry Breeding IndustryCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
| | - Ziyu Chen
- State Key Laboratory of Swine and Poultry Breeding IndustryCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
| | - Yuwei Gou
- State Key Laboratory of Swine and Poultry Breeding IndustryCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
| | - Jiaman Zhang
- State Key Laboratory of Swine and Poultry Breeding IndustryCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
| | - Tao Wang
- School of PharmacyChengdu UniversityChengdu610106China
| | - Qianzi Tang
- State Key Laboratory of Swine and Poultry Breeding IndustryCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
| | - Fanli Kong
- College of Life ScienceSichuan Agricultural UniversityYa'an625014China
| | - Long Jin
- State Key Laboratory of Swine and Poultry Breeding IndustryCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
| | - Mingzhou Li
- State Key Laboratory of Swine and Poultry Breeding IndustryCollege of Animal Science and TechnologySichuan Agricultural UniversityChengdu611130China
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Pham TD, Sun X. Wavelet scattering networks in deep learning for discovering protein markers in a cohort of Swedish rectal cancer patients. Cancer Med 2023; 12:21502-21518. [PMID: 38014709 PMCID: PMC10726782 DOI: 10.1002/cam4.6672] [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: 08/25/2023] [Revised: 09/25/2023] [Accepted: 10/20/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Cancer biomarkers play a pivotal role in the diagnosis, prognosis, and treatment response prediction of the disease. In this study, we analyzed the expression levels of RhoB and DNp73 proteins in rectal cancer, as captured in immunohistochemical images, to predict the 5-year survival time of two patient groups: one with preoperative radiotherapy and one without. METHODS The utilization of deep convolutional neural networks in medical research, particularly in clinical cancer studies, has been gaining substantial attention. This success primarily stems from their ability to extract intricate image features that prove invaluable in machine learning. Another innovative method for extracting features at multiple levels is the wavelet-scattering network. Our study combines the strengths of these two convolution-based approaches to robustly extract image features related to protein expression. RESULTS The efficacy of our approach was evaluated across various tissue types, including tumor, biopsy, metastasis, and adjacent normal tissue. Statistical assessments demonstrated exceptional performance across a range of metrics, including prediction accuracy, classification accuracy, precision, and the area under the receiver operating characteristic curve. CONCLUSION These results underscore the potential of dual convolutional learning to assist clinical researchers in the timely validation and discovery of cancer biomarkers.
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Affiliation(s)
- Tuan D. Pham
- Barts and The London School of Medicine and Dentistry Queen MaryUniversity of London Turner StreetLondonUK
| | - Xiao‐Feng Sun
- Division of Oncology Department of Biomedical and Clinical SciencesLinkoping UniversityLinkopingSweden
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Rossini R, Oshaghi M, Nekrasov M, Bellanger A, Domaschenz R, Dijkwel Y, Abdelhalim M, Collas P, Tremethick D, Paulsen J. Multi-level 3D genome organization deteriorates during breast cancer progression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.26.568711. [PMID: 38076897 PMCID: PMC10705249 DOI: 10.1101/2023.11.26.568711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Breast cancer entails intricate alterations in genome organization and expression. However, how three-dimensional (3D) chromatin structure changes in the progression from a normal to a breast cancer malignant state remains unknown. To address this, we conducted an analysis combining Hi-C data with lamina-associated domains (LADs), epigenomic marks, and gene expression in an in vitro model of breast cancer progression. Our results reveal that while the fundamental properties of topologically associating domains (TADs) remain largely stable, significant changes occur in the organization of compartments and subcompartments. These changes are closely correlated with alterations in the expression of oncogenic genes. We also observe a restructuring of TAD-TAD interactions, coinciding with a loss of spatial compartmentalization and radial positioning of the 3D genome. Notably, we identify a previously unrecognized interchromosomal insertion event, wherein a locus on chromosome 8 housing the MYC oncogene is inserted into a highly active subcompartment on chromosome 10. This insertion leads to the formation of de novo enhancer contacts and activation of the oncogene, illustrating how structural variants can interact with the 3D genome to drive oncogenic states. In summary, our findings provide evidence for the degradation of genome organization at multiple scales during breast cancer progression revealing novel relationships between genome 3D structure and oncogenic processes.
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Affiliation(s)
- Roberto Rossini
- Department of Biosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, 0316 Oslo, Norway
| | - Mohammadsaleh Oshaghi
- Department of Biosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, 0316 Oslo, Norway
| | - Maxim Nekrasov
- Department of Genome Sciences, The John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Aurélie Bellanger
- Department of Molecular Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, 0317 Oslo, Norway
| | - Renae Domaschenz
- Department of Genome Sciences, The John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Yasmin Dijkwel
- Department of Genome Sciences, The John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Mohamed Abdelhalim
- Department of Molecular Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, 0317 Oslo, Norway
| | - Philippe Collas
- Department of Molecular Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, 0317 Oslo, Norway
- Department of Immunology and Transfusion Medicine, Oslo University Hospital, 0424 Oslo, Norway
| | - David Tremethick
- Department of Genome Sciences, The John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Jonas Paulsen
- Department of Biosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, 0316 Oslo, Norway
- Centre for Bioinformatics, Department of Informatics, University of Oslo, 0316 Oslo, Norway
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Pang B, van Weerd JH, Hamoen FL, Snyder MP. Identification of non-coding silencer elements and their regulation of gene expression. Nat Rev Mol Cell Biol 2022; 24:383-395. [DOI: 10.1038/s41580-022-00549-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/29/2022] [Indexed: 11/09/2022]
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