A Novel Exosome-Relevant Molecular Classification Uncovers Distinct Immune Escape Mechanisms and Genomic Alterations in Gastric Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35721114", "kind": "science-record", "revision": 4, "content_hash": "sha256:116a31cfebdf781ee131f88aad9a4f92281ef05a784d5b46e2f05073f6258ede", "created_at": "2026-11-01T18:14:43Z", "updated_at": "2026-11-01T22:06:49Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Novel Exosome-Relevant Molecular Classification Uncovers Distinct Immune Escape Mechanisms and Genomic Alterations in Gastric Cancer.", "doi": "10.3389/fphar.2022.884090", "pmid": "35721114", "authors": ["Yubiao Lin", "Kaida Huang", "Zhezhen Cai", "Yide Chen", "Lihua Feng", "Yingqin Gao", "Wenhui Zheng", "Xin Fan", "Guoqin Qiu", "Jianmin Zhuang", "Shuitu Feng"], "journal": "Frontiers in pharmacology", "year": 2022, "abstract": "Objective: Gastric cancer (GC) is a highly heterogeneous malignant carcinoma. This study aimed to conduct an exosome-based classification for assisting personalized therapy for GC. Methods: Based on the expression profiling of prognostic exosome-related genes, GC patients in The Cancer Genome Atlas (TCGA) cohort were classified using the unsupervised consensus clustering approach, and the reproducibility of this classification was confirmed in the GSE84437 cohort. An exosome-based gene signature was developed via Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Immunological features, responses to immune checkpoint inhibitors, and genetic alterations were evaluated via computational methods. Results: Two exosome-relevant phenotypes (A and B) were clustered, and this classification was independent of immune subtypes and TCGA subtypes. Exosome-relevant phenotype B had a poorer prognosis and an inflamed tumor microenvironment (TME) relative to phenotype A. Patients with phenotype B presented higher responses to the anti-CTLA4 inhibitor. Moreover, phenotype B occurred at a higher frequency of genetic mutation than phenotype A. The exosome-based gene signature (GPX3, RGS2, MATN3, SLC7A2, and SNCG) could independently and accurately predict GC prognosis, which was linked to stromal activation and immunosuppression. Conclusion: Our findings offer a conceptual frame to further comprehend the roles of exosomes in immune escape mechanisms and genomic alterations of GC. More work is required to evaluate the reference value of exosome-relevant phenotypes for designing immunotherapeutic regimens.", "claims": [{"id": "claim-method", "statement": "An exosome-based gene signature was developed via Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35721114", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "An exosome-based gene signature was developed via Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35721114", "locator": "sections[30] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Two exosome-relevant phenotypes (A and B) were clustered, and this classification was independent of immune subtypes and TCGA subtypes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35721114", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Two exosome-relevant phenotypes (A and B) were clustered, and this classification was independent of immune subtypes and TCGA subtypes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Two exosome-relevant phenotypes (A and B) were clustered, and this classification was independent of immune subtypes and TCGA subtypes.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35721114"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE15459"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE15459"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35721114", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fphar.2022.884090", "sha256": "sha256:ab5e2eb0cd99b3f321e075826c437d6bac680a226813dc684bcc61c451ea278d", "bytes": 57248, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fphar.2022.884090", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9204030", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE15459", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15459", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE15459", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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