Identifying changes in immune cells and constructing prognostic models using immune-related genes in post-burn immunosuppression.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35070500", "kind": "science-record", "revision": 4, "content_hash": "sha256:e4fb395578b87f3f7a1635d7c0ffcd84abc993b3902f44bf699e44d772cc30c9", "created_at": "2026-11-01T17:36:48Z", "updated_at": "2026-11-01T22:05:39Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identifying changes in immune cells and constructing prognostic models using immune-related genes in post-burn immunosuppression.", "doi": "10.7717/peerj.12680", "pmid": "35070500", "authors": ["Peng Wang", "Zexin Zhang", "Bin Yin", "Jiayuan Li", "Cheng Xialin", "Wenqin Lian", "Yingjun Su", "Chiyu Jia"], "journal": "PeerJ", "year": 2022, "abstract": "BACKGROUND: Burn patients are prone to infection as well as immunosuppression, which is a significant cause of death. Currently, there is a lack of prognostic biomarkers for immunosuppression in burn patients. This study was conducted to identify immune-related genes that are prognosis biomarkers in post-burn immunosuppression and potential targets for immunotherapy.\nMETHODS: We downloaded the gene expression profiles and clinical data of 213 burn patients and 79 healthy samples from the Gene Expression Omnibus (GEO) database. Immune infiltration analysis was used to identify the proportion of circulating immune cells. Functional enrichment analyses were carried out to identify immune-related genes that were used to build miRNA-mRNA networks to screen key genes. Next, we carried out correlation analysis between immune cells and key genes that were then used to construct logistic regression models in GSE77791 and were validated in GSE19743. Finally, we determined the expression of key genes in burn patients using quantitative reverse transcription polymerase chain reaction (qRT-PCR).\nRESULTS: A total of 745 differently expressed genes were screened out: 299 were up-regulated and 446 were down-regulated. The number of Th-cells (CD4+) decreased while neutrophils increased in burn patients. The enrichment analysis showed that down-regulated genes were enriched in the T-cell activation pathway, while up-regulated genes were enriched in neutrophil activation response in burn patients. We screened out key genes (NFATC2, RORA, and CAMK4) that could be regulated by miRNA. The expression of key genes was related to the proportion of Th-cells (CD4+) and survival, and was an excellent predictor of prognosis in burns with an area under the curve (AUC) value of 0.945. Finally, we determined that NFATC2, RORA, and CAMK4 were down-regulated in burn patients.\nCONCLUSION: We found that NFATC2, RORA, and CAMK4 were likely prognostic biomarkers in post-burn immunosuppression and potential immunotherapeutic targets to convert Th-cell dysfunction.", "claims": [{"id": "claim-method", "statement": "Then, we selected related genes to construct a logistic regression model and draw a nomogram using the training cohort GSE77791 (the logistic regression results are shown in Tables 3 and 4).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35070500", "locator": "sections[9] \"Constructing a survival-related risk regression model and validating across different gene sets\" paragraph 2", "quote": "Then, we selected related genes to construct a logistic regression model and draw a nomogram using the training cohort GSE77791 (the logistic regression results are shown in Tables 3 and 4)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The following information was supplied regarding data availability:The code is available in the Supplemental File.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35070500", "locator": "sections[28] \"Additional Information and Declarations\" paragraph 5", "quote": "The following information was supplied regarding data availability:The code is available in the Supplemental File."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The expression of key genes was related to the proportion of Th-cells (CD4+) and survival, and was an excellent predictor of prognosis in burns with an area under the curve (AUC) value of 0.945.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35070500", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The expression of key genes was related to the proportion of Th-cells (CD4+) and survival, and was an excellent predictor of prognosis in burns with an area under the curve (AUC) value of 0.945."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The expression of key genes was related to the proportion of Th-cells (CD4+) and survival, and was an excellent predictor of prognosis in burns with an area under the curve (AUC) value of 0.945.", "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:35070500"], "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:GSE19743"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "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:GSE19743"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35070500", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7717/peerj.12680", "sha256": "sha256:1c3478f13af277a749c27583139b5d647cadebcaeb01140ad0673790c0078fdf", "bytes": 43008, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.7717/peerj.12680", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8761370", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE19743", "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=GSE19743", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE19743", "version": null, "note": "The following information was supplied regarding data availability:The code is available in the Supplemental File.", 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