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Arabfard M, Behmard E, Maghsoudloo M, Dadgar E, Parvin S, Bagheri H. Identifying candidate RNA-seq biomarkers for severity discrimination in chemical injuries: A machine learning and molecular dynamics approach. Int Immunopharmacol 2025; 148:114090. [PMID: 39847951 DOI: 10.1016/j.intimp.2025.114090] [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: 11/13/2024] [Revised: 01/11/2025] [Accepted: 01/11/2025] [Indexed: 01/25/2025]
Abstract
INTRODUCTION Biomarkers play a crucial role across various fields by providing insights into biological responses to interventions. High-throughput gene expression profiling technologies facilitate the discovery of data-driven biomarkers through extensive datasets. This study focuses on identifying biomarkers in gene expression data related to chemical injuries by mustard gas, covering a spectrum from healthy individuals to severe injuries. MATERIALS AND METHODS The study utilized RNA-Seq data comprising 52 expression data samples for 54,583 gene transcripts. These samples were categorized into four classes based on the GOLD classification for chemically injured individuals: Severe (n = 14), Moderate (n = 11), Mild (n = 16), and healthy controls (n = 11). Data preparation involved examining an Excel file created in the R programming environment using MLSeq and devtools packages. Feature selection was performed using Genetic Algorithm and Simulated Annealing, with Random Forest algorithm employed for classification. Ab initio methods ensured computational efficiency and result accuracy, while molecular dynamics simulation acted as a virtual experiment bridging the gap between experimental and theoretical experiences. RESULTS A total of 12 models were created, each introducing a list of differentially expressed genes as potential biomarkers. The performance of models varied across group comparisons, with the Genetic Algorithm generally outperforming Simulated Annealing in most cases. For the Severe vs. Moderate group, GA achieved the best performance with an accuracy of 94.38%, recall of 91.64%, and specificity of 97.10%. The results highlight the effectiveness of GA in most group comparisons, while SA performed better in specific cases involving Moderate and Mild groups. These biomarkers were evaluated against the gene expression data to assess their expression changes between different groups of chemically injured individuals. Four genes were selected based on level expression for further investigation: CXCR1, EIF2B2, RAD51, and RXFP2. The expression levels of these genes were analyzed to determine their differential expression between the groups. CONCLUSION This study was designed as a computational effort to identify diagnostic biomarkers in basic biological system research. Our findings proposed a list of discriminative biomarkers capable of distinguishing between different groups of chemically injured individuals. The identification of key genes highlights the potential for biomarkers to serve as indicators of chemical injury severity, warranting further investigation to validate their clinical relevance and utility in diagnosis and treatment.
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Affiliation(s)
- Masoud Arabfard
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
| | - Esmaeil Behmard
- School of Advanced Technologies in Medicine, Fasa University of Medical Sciences, Fasa, Iran
| | - Mazaher Maghsoudloo
- Key Laboratory of Epigenetics and Oncology, The Research Center for Preclinical Medicine, Southwest Medical University, Luzhou 646000 Sichuan, China
| | - Emad Dadgar
- Students' Research Committee, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Shahram Parvin
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Hasan Bagheri
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
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Dissecting the Complexity of Early Heart Progenitor Cells. J Cardiovasc Dev Dis 2021; 9:jcdd9010005. [PMID: 35050215 PMCID: PMC8779398 DOI: 10.3390/jcdd9010005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 12/17/2021] [Accepted: 12/22/2021] [Indexed: 12/23/2022] Open
Abstract
Early heart development depends on the coordinated participation of heterogeneous cell sources. As pioneer work from Adriana C. Gittenberger-de Groot demonstrated, characterizing these distinct cell sources helps us to understand congenital heart defects. Despite decades of research on the segregation of lineages that form the primitive heart tube, we are far from understanding its full complexity. Currently, single-cell approaches are providing an unprecedented level of detail on cellular heterogeneity, offering new opportunities to decipher its functional role. In this review, we will focus on three key aspects of early heart morphogenesis: First, the segregation of myocardial and endocardial lineages, which yields an early lineage diversification in cardiac development; second, the signaling cues driving differentiation in these progenitor cells; and third, the transcriptional heterogeneity of cardiomyocyte progenitors of the primitive heart tube. Finally, we discuss how single-cell transcriptomics and epigenomics, together with live imaging and functional analyses, will likely transform the way we delve into the complexity of cardiac development and its links with congenital defects.
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Geijer ME, Zhou D, Selvam K, Steurer B, Mukherjee C, Evers B, Cugusi S, van Toorn M, van der Woude M, Janssens RC, Kok YP, Gong W, Raams A, Lo CSY, Lebbink JHG, Geverts B, Plummer DA, Bezstarosti K, Theil AF, Mitter R, Houtsmuller AB, Vermeulen W, Demmers JAA, Li S, van Vugt MATM, Lans H, Bernards R, Svejstrup JQ, Ray Chaudhuri A, Wyrick JJ, Marteijn JA. Elongation factor ELOF1 drives transcription-coupled repair and prevents genome instability. Nat Cell Biol 2021; 23:608-619. [PMID: 34108662 PMCID: PMC7611218 DOI: 10.1038/s41556-021-00692-z] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 04/29/2021] [Indexed: 02/05/2023]
Abstract
Correct transcription is crucial for life. However, DNA damage severely impedes elongating RNA polymerase II, causing transcription inhibition and transcription-replication conflicts. Cells are equipped with intricate mechanisms to counteract the severe consequence of these transcription-blocking lesions. However, the exact mechanism and factors involved remain largely unknown. Here, using a genome-wide CRISPR-Cas9 screen, we identified the elongation factor ELOF1 as an important factor in the transcription stress response following DNA damage. We show that ELOF1 has an evolutionarily conserved role in transcription-coupled nucleotide excision repair (TC-NER), where it promotes recruitment of the TC-NER factors UVSSA and TFIIH to efficiently repair transcription-blocking lesions and resume transcription. Additionally, ELOF1 modulates transcription to protect cells against transcription-mediated replication stress, thereby preserving genome stability. Thus, ELOF1 protects the transcription machinery from DNA damage via two distinct mechanisms.
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Affiliation(s)
- Marit E Geijer
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Di Zhou
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Kathiresan Selvam
- School of Molecular Biosciences, Washington State University, Pullman, WA, USA
| | - Barbara Steurer
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Chirantani Mukherjee
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Bastiaan Evers
- Oncode Institute, Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Simona Cugusi
- Mechanisms of Transcription Laboratory, The Francis Crick Institute, London, UK
| | - Marvin van Toorn
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Melanie van der Woude
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Roel C Janssens
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Yannick P Kok
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Wenzhi Gong
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, USA
| | - Anja Raams
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Calvin S Y Lo
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Joyce H G Lebbink
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Radiation Oncology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Bart Geverts
- Erasmus Optical Imaging Center, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Dalton A Plummer
- School of Molecular Biosciences, Washington State University, Pullman, WA, USA
| | - Karel Bezstarosti
- Proteomics Center, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Arjan F Theil
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Richard Mitter
- Bioinformatics and Biostatistics, The Francis Crick Institute, London, UK
| | - Adriaan B Houtsmuller
- Erasmus Optical Imaging Center, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Wim Vermeulen
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jeroen A A Demmers
- Proteomics Center, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Shisheng Li
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, USA
| | - Marcel A T M van Vugt
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Hannes Lans
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - René Bernards
- Oncode Institute, Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Jesper Q Svejstrup
- Mechanisms of Transcription Laboratory, The Francis Crick Institute, London, UK
| | - Arnab Ray Chaudhuri
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - John J Wyrick
- School of Molecular Biosciences, Washington State University, Pullman, WA, USA
| | - Jurgen A Marteijn
- Department of Molecular Genetics, Oncode Institute, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands.
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