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Chowdhury S, Ferri-Borgogno S, Yang P, Wang W, Peng J, C Mok S, Wang P. Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic data of ovarian cancer. Brief Bioinform 2025; 26:bbaf085. [PMID: 40062614 PMCID: PMC11891659 DOI: 10.1093/bib/bbaf085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2024] [Revised: 01/29/2025] [Accepted: 02/17/2025] [Indexed: 05/13/2025] Open
Abstract
To unravel the mechanism of immune activation and suppression within tumors, a critical step is to identify transcriptional signals governing cell-cell communication between tumor and immune/stromal cells in the tumor microenvironment. Central to this communication are interactions between secreted ligands and cell-surface receptors, creating a highly connected signaling network among cells. Recent advancements in in situ-omics profiling, particularly spatial transcriptomic (ST) technology, provide unique opportunities to directly characterize ligand-receptor signaling networks that power cell-cell communication. In this paper, we propose a novel statistical method, LRnetST, to characterize the ligand-receptor interaction networks between adjacent tumor and immune/stroma cells based on ST data. LRnetST utilizes a directed acyclic graph model with a novel approach to handle the zero-inflated distributions of ST data. It also leverages existing ligand-receptor regulation databases as prior information, and employs a bootstrap aggregation strategy to achieve robust network estimation. Application of LRnetST to ST data of high-grade serous ovarian tumor samples revealed both common and distinct ligand-receptor regulations across different tumors. Some of these interactions were validated through both a MERFISH dataset and a CosMx SMI dataset of independent ovarian tumor samples. These results cast light on biological processes relating to the communication between tumor and immune/stromal cells in ovarian tumors. An open-source R package of LRnetST is available on GitHub at https://github.com/jie108/LRnetST.
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Affiliation(s)
- Shrabanti Chowdhury
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1399 Park Ave, New York, NY 10029, United States
| | - Sammy Ferri-Borgogno
- Department of Gynecologic Oncology and Reproductive Medicine, Division of Surgery, The University of Texas MD Anderson Cancer Center, 1155 Pressler St., Houston, TX 77030, United States
| | - Peng Yang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, TX, United States
| | - Wenyi Wang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, TX, United States
| | - Jie Peng
- Department of Statistics, University of California Davis, 399 Crocker Ln, Davis, CA 95616, United States
| | - Samuel C Mok
- Department of Gynecologic Oncology and Reproductive Medicine, Division of Surgery, The University of Texas MD Anderson Cancer Center, 1155 Pressler St., Houston, TX 77030, United States
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1399 Park Ave, New York, NY 10029, United States
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Antonsen E, Reynolds RJ, Charvat J, Connell E, Monti A, Petersen D, Nartey N, Anton W, Abukmail A, Marotta K, Van Baalen M, Buckland DM. Causal diagramming for assessing human system risk in spaceflight. NPJ Microgravity 2024; 10:32. [PMID: 38503732 PMCID: PMC10951288 DOI: 10.1038/s41526-024-00375-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 03/04/2024] [Indexed: 03/21/2024] Open
Abstract
For over a decade, the National Aeronautics and Space Administration (NASA) has tracked and configuration-managed approximately 30 risks that affect astronaut health and performance before, during and after spaceflight. The Human System Risk Board (HSRB) at NASA Johnson Space Center is responsible for setting the official risk posture for each of the human system risks and determining-based on evaluation of the available evidence-when that risk posture changes. The ultimate purpose of tracking and researching these risks is to find ways to reduce spaceflight-induced risk to astronauts. The adverse effects of spaceflight begin at launch and continue throughout the duration of the mission, and in some cases, across the lifetime of the astronaut. Historically, research has been conducted in individual risk "silos" to characterize risk, however, astronauts are exposed to all risks simultaneously. In January of 2020, the HSRB at NASA began assessing the potential value of causal diagramming as a tool to facilitate understanding of the complex causes and effects that contribute to spaceflight-induced human system risk. Causal diagrams in the form of directed acyclic graphs (DAGs) are used to provide HSRB stakeholders with a shared mental model of the causal flow of risk. While primarily improving communication among those stakeholders, DAGs also allow a composite risk network to be created that can be tracked and configuration managed. This paper outlines the HSRB's pilot process for this effort, the lessons learned, and future goals for data-driven risk management approaches.
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Affiliation(s)
- Erik Antonsen
- Center for Space Medicine, Department of Emergency Medicine, Baylor College of Medicine, Houston, TX, USA.
| | | | | | | | | | | | | | | | | | | | | | - Daniel M Buckland
- NASA Johnson Space Center, Houston, TX, USA
- Duke University, Durham, NC, USA
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Chowdhury S, Kennedy JJ, Ivey RG, Murillo OD, Hosseini N, Song X, Petralia F, Calinawan A, Savage SR, Berry AB, Reva B, Ozbek U, Krek A, Ma W, da Veiga Leprevost F, Ji J, Yoo S, Lin C, Voytovich UJ, Huang Y, Lee SH, Bergan L, Lorentzen TD, Mesri M, Rodriguez H, Hoofnagle AN, Herbert ZT, Nesvizhskii AI, Zhang B, Whiteaker JR, Fenyo D, McKerrow W, Wang J, Schürer SC, Stathias V, Chen XS, Barcellos-Hoff MH, Starr TK, Winterhoff BJ, Nelson AC, Mok SC, Kaufmann SH, Drescher C, Cieslik M, Wang P, Birrer MJ, Paulovich AG. Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer. Cell 2023; 186:3476-3498.e35. [PMID: 37541199 PMCID: PMC10414761 DOI: 10.1016/j.cell.2023.07.004] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 03/23/2023] [Accepted: 07/05/2023] [Indexed: 08/06/2023]
Abstract
To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.
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Affiliation(s)
- Shrabanti Chowdhury
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jacob J Kennedy
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Richard G Ivey
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Oscar D Murillo
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Noshad Hosseini
- Department of Computational Medicine and Bioinformatics, Michigan Center for Translational Pathology, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Xiaoyu Song
- Tisch Cancer Institute, Department of Population Health Science and Policy, Institute for Health Care Delivery Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Francesca Petralia
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Anna Calinawan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sara R Savage
- Lester and Sue Smith Breast Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Boris Reva
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Umut Ozbek
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Azra Krek
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Weiping Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Jiayi Ji
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Chenwei Lin
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Uliana J Voytovich
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Yajue Huang
- Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Sun-Hee Lee
- Departments of Oncology and Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Lindsay Bergan
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Travis D Lorentzen
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Mehdi Mesri
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | - Henry Rodriguez
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Zachary T Herbert
- Molecular Biology Core Facilities, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Alexey I Nesvizhskii
- Department of Pathology, Department of Computational Medicine and Bioinformatics, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA
| | - Bing Zhang
- Lester and Sue Smith Breast Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jeffrey R Whiteaker
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - David Fenyo
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Wilson McKerrow
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Joshua Wang
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Stephan C Schürer
- Department of Molecular and Cellular Pharmacology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, and Institute for Data Science & Computing, University of Miami, Miami, FL 33136, USA
| | - Vasileios Stathias
- Department of Molecular and Cellular Pharmacology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, and Institute for Data Science & Computing, University of Miami, Miami, FL 33136, USA
| | - X Steven Chen
- Department of Public Health Sciences, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Mary Helen Barcellos-Hoff
- Helen Diller Family Comprehensive Cancer Center, Department of Radiation Oncology, University of California, San Francisco, San Francisco, CA 94115, USA
| | - Timothy K Starr
- Department of Obstetrics, Gynecology and Women's Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Boris J Winterhoff
- Department of Obstetrics, Gynecology and Women's Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Andrew C Nelson
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Samuel C Mok
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Scott H Kaufmann
- Departments of Oncology and Molecular Pharmacology & Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Charles Drescher
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Marcin Cieslik
- Department of Pathology, Department of Computational Medicine and Bioinformatics, Michigan Center for Translational Pathology, University of Michigan School of Medicine, Ann Arbor, MI 48109, USA.
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Michael J Birrer
- Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.
| | - Amanda G Paulovich
- Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA.
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