An Integrated Analysis of Prognostic Signature and Immune Microenvironment in Tongue Squamous Cell Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35912229", "kind": "science-record", "revision": 4, "content_hash": "sha256:7049ff70029fa004192ffa3ad462f66a5661cc0fd187bfc343d54d521df0c746", "created_at": "2026-11-01T18:15:00Z", "updated_at": "2026-11-01T22:07:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "An Integrated Analysis of Prognostic Signature and Immune Microenvironment in Tongue Squamous Cell Carcinoma.", "doi": "10.3389/fonc.2022.891716", "pmid": "35912229", "authors": ["Yi Jin", "Zhanwang Wang", "Weizhi Tang", "Muxing Liao", "Xiangwei Wu", "Hui Wang"], "journal": "Frontiers in oncology", "year": 2022, "abstract": "Tongue squamous cell carcinoma (TSCC) is a prevalent cancer of the oral cavity. Survival metrics are usually unsatisfactory, even using combined treatment with surgery, radiation, and chemotherapy. Immune checkpoint inhibitors can prolong survival, especially in patients with recurrent or metastatic disease. However, there are few effective biomarkers to provide prognosis and guide immunotherapy. Here, we utilized weighted gene co-expression network analysis to identify the co-expression module and selected the turquoise module for further scrutiny. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed the innate pathways. The findings indicated that cell junction organization, response to topologically incorrect protein, and regulation of cell adhesion pathways may be essential. Eleven crucial predictive genes (PLXNB1, N4BP3, KDELR2, INTS8, PLAU, PPFIBP2, OAF, LMF1, IL34, ZFP3, and MAP7D3) were used to establish a risk model based on Cox and LASSO analyses of The Cancer Genome Atlas and GSE65858 databases (regarding overall survival). Kaplan-Meier analysis and receiver operating characteristic curve suggested that the risk model had better prognostic effectiveness than other clinical traits. Consensus clustering was used to classify TSCC samples into two groups with significantly different survival rates. ESTIMATE and CIBERSORT were used to display the immune landscape of TSCC and indicate the stromal score; specific types of immune cells, including naïve B cells, plasma cells, CD8 T cells, CD4 memory resting and memory activated T cells, follicular helper T cells, and T regulatory cells, may influence the heterogeneous immune microenvironment in TSCC. To further identify hub genes, we downloaded GEO datasets (GSE41613 and GSE31056) and successfully validated the risk model. Two hub genes (PLAU and PPFIBP2) were strongly associated with CD4+ and CD8+ T cells and programmed cell death protein 1 (PD1) and PD-ligand 1.", "claims": [{"id": "claim-method", "statement": "LASSO Cox regression analyses were then applied to filter core genes and construct the prognostic models according to the risk score as follows:", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35912229", "locator": "sections[7] \"Establishment of the Prognostic Risk Model\" paragraph 2", "quote": "LASSO Cox regression analyses were then applied to filter core genes and construct the prognostic models according to the risk score as follows:"}], "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:35912229", "locator": "sections[25] \"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": "The risk score had better prognostic effectiveness than other clinical traits, with an area under the ROC curve of 0.657 and 0.664 at 1 and 3 years, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35912229", "locator": "sections[18] \"Construction and Evaluation of Prognostic Signature\" paragraph 2", "quote": "The ROC curve showed that the risk score had better prognostic effectiveness than other clinical traits, with an area under the ROC curve of 0.657 and 0.664 at 1 and 3 years, respectively ( Figure 3F )."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The risk score had better prognostic effectiveness than other clinical traits, with an area under the ROC curve of 0.657 and 0.664 at 1 and 3 years, respectively.", "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:35912229"], "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:GSE31056"], "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:GSE31056"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35912229", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2022.891716", "sha256": "sha256:cc500fb8d8f12af8ecf620c789e63f9916af88d99222863afc3783518244e8a6", "bytes": 48419, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2022.891716", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9326056", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE31056", "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=GSE31056", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE31056", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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Cell Culture and Transfection The Cal-27 human TSCC cell line was obtained", "ccording to the manufacturer’s protocol. The transfection efficiency was assessed by quantitative reve"], "order_basis": "paper_text_order:2571", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["liquid (Procell Company). Cal-27 cells were cultured in a humidified atmosphere containing 5% CO2 at"], "order_basis": "paper_text_order:2903", "id": "assay:2"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["in non-metastatic and metastatic tissue from immunohistochemistry. (D) Expression of PLAU in normal and cancer", "of PLAU in normal and cancer tissue based on immunohistochemistry. (E) Expression of PPFIBP2 in normal and can", "PPFIBP2 in normal and cancer tissue based on immunohistochemistry.Click here for additional data file. Supplem"], "order_basis": "paper_text_order:4431", "id": "assay:3"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["LASSO Cox regression analyses were then applied to filter core genes and construct the prognostic models according to the risk score as follows:"], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}