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Conventional annotation approaches often rely on proximity-driven graph construction or expression similarity, which may introduce spurious cell\u2013cell connections and lead to unstable knowledge transfer across patients. To address this limitation, we propose PathoGraph, a functionally guided graph learning framework for robust cross-patient cell-type annotation. The proposed method integrates KEGG-7-based biosemantic graph structure learning with cross-patient representation adaptation. Specifically, pathway-derived functional semantic profiles are incorporated to refine patient-specific cell graphs, encouraging biologically coherent neighborhoods and suppressing noise introduced by purely expression-based similarity. Based on the refined graphs, a cross-patient representation adaptation mechanism further aligns embeddings between labeled reference patients and unlabeled query patients to facilitate reliable annotation transfer. Experiments on three cross-patient scRNA-seq data sets, including leukemia, breast invasive carcinoma, and colorectal cancer data sets, demonstrate that PathoGraph achieves stable annotation performance across 32 directed reference-to-query transfer tasks. Across all tasks, PathoGraph obtained an average ACC of 84.28% and an F1-score of 84.08%, showing competitive and stable performance compared with representative marker-based, correlation-based, and model-based annotation methods. Ablation studies further show that removing the biosemantic graph learning module reduces the average accuracy to 83.48%, highlighting the importance of functional-guided graph refinement. In addition, post hoc functional relevance analyses in immune-cell and cancer-associated contexts suggest that the learned cell\u2013cell graphs capture biologically relevant neighborhood structures beyond expression-driven proximity. The source code and processed data are publicly available at: https:\/\/github.com\/LiYuechao1998\/PathoGraph.<\/jats:p>","DOI":"10.1021\/acs.jcim.6c01857","type":"journal-article","created":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T14:13:49Z","timestamp":1784124829000},"page":"8663-8677","source":"Crossref","is-referenced-by-count":0,"title":["Functionally Guided\nGraph Learning for Robust Cross-Patient\nCell-Type Annotation in Single-Cell RNA Sequencing"],"prefix":"10.1021","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9912-0648","authenticated-orcid":true,"given":"Yue-Chao","family":"Li","sequence":"first","affiliation":[{"name":"Northwestern Polytechnical University , , ,","place":["Shaanxi, China, 710129"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9453-7653","authenticated-orcid":true,"given":"Meng-Meng","family":"Wei","sequence":"additional","affiliation":[{"name":"China University of Mining and Technology , , ,","place":["Xuzhou, China, 221116"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0554-2936","authenticated-orcid":true,"given":"Xin-Fei","family":"Wang","sequence":"additional","affiliation":[{"name":"Jilin University , , ,","place":["Changchun, China, 130012"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Xi\u2019an University of Technology , , ,","place":["Xi\u2019an, China, 710048"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4993-298X","authenticated-orcid":true,"given":"Jie","family":"Pan","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China , , ,","place":["Suzhou, China, 215123"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0184-307X","authenticated-orcid":true,"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"China University of Mining and Technology , , ,","place":["Xuzhou, China, 221116"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu-An","family":"Huang","sequence":"additional","affiliation":[{"name":"Northwestern Polytechnical University , , ,","place":["Shaanxi, China, 710129"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhi-An","family":"Huang","sequence":"additional","affiliation":[{"name":"City University of Hong Kong (Dongguan) , , ,","place":["Dongguan, China, 523000"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhu-Hong","family":"You","sequence":"additional","affiliation":[{"name":"Northwestern Polytechnical University , , ,","place":["Shaanxi, China, 710129"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,7,15]]},"reference":[{"key":"2026072709094995800_cit1","doi-asserted-by":"publisher","first-page":"216074","DOI":"10.1016\/j.canlet.2023.216074","article-title":"Pericytes in the tumor microenvironment","volume":"556","author":"Jiang","year":"2023","journal-title":"Cancer\nLett."},{"issue":"8","key":"2026072709094995800_cit2","doi-asserted-by":"publisher","first-page":"1192","DOI":"10.1038\/s41588-022-01141-9","article-title":"Cancer cell states recur\nacross tumor types and form specific interactions\nwith the tumor microenvironment","volume":"54","author":"Barkley","year":"2022","journal-title":"Nat. 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