{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T10:14:55Z","timestamp":1780481695863,"version":"3.54.1"},"reference-count":46,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T00:00:00Z","timestamp":1741564800000},"content-version":"vor","delay-in-days":9,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"National Institute of Health and National Science Foundation","award":["U24CA271114"],"award-info":[{"award-number":["U24CA271114"]}]},{"name":"National Institute of Health and National Science Foundation","award":["U01CA271407"],"award-info":[{"award-number":["U01CA271407"]}]},{"name":"National Institute of Health and National Science Foundation","award":["U24CA210993"],"award-info":[{"award-number":["U24CA210993"]}]},{"name":"National Institute of Health and National Science Foundation","award":["U01CA214172"],"award-info":[{"award-number":["U01CA214172"]}]},{"name":"National Institute of Health and National Science Foundation","award":["U01CA294459"],"award-info":[{"award-number":["U01CA294459"]}]},{"name":"National Institute of Health and National Science Foundation","award":["R01CA268380"],"award-info":[{"award-number":["R01CA268380"]}]},{"name":"National Institute of Health and National Science Foundation","award":["1915894"],"award-info":[{"award-number":["1915894"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,3,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>To unravel the mechanism of immune activation and suppression within tumors, a critical step is to identify transcriptional signals governing cell\u2013cell 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\u2013receptor signaling networks that power cell\u2013cell communication. In this paper, we propose a novel statistical method, LRnetST, to characterize the ligand\u2013receptor 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\u2013receptor 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\u2013receptor 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.<\/jats:p>","DOI":"10.1093\/bib\/bbaf085","type":"journal-article","created":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T10:54:37Z","timestamp":1741604077000},"source":"Crossref","is-referenced-by-count":3,"title":["Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic data of ovarian cancer"],"prefix":"10.1093","volume":"26","author":[{"given":"Shrabanti","family":"Chowdhury","sequence":"first","affiliation":[{"name":"Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai , 1399 Park Ave, New York, NY 10029 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sammy","family":"Ferri-Borgogno","sequence":"additional","affiliation":[{"name":"Department of Gynecologic Oncology and Reproductive Medicine , Division of Surgery, , 1155 Pressler St., Houston, TX 77030 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