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pmid:37084685

Identification of novel prognostic indicators for oral squamous cell carcinoma based on proteomics and metabolomics.

Zhitao Yao · Wei An · Maimaitituxun Tuerdi · Jin Zhao

Translational oncology · 2023 doi:10.1016/j.tranon.2023.101672

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Experiment

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Data

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title
Identification of novel prognostic indicators for oral squamous cell carcinoma based on proteomics and metabolomics.
doi
10.1016/j.tranon.2023.101672
pmid
37084685
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[0]
Zhitao Yao
[1]
Wei An
[2]
Maimaitituxun Tuerdi
[3]
Jin Zhao
journal
Translational oncology
year
2023
abstract
BACKGROUND: The low 5-year survival rate of oral squamous cell carcinoma (OSCC) suggests that new prognostic indicators need to be identified to aid the clinical management of patients. METHODS: Saliva samples from OSCC patients and healthy controls were collected for proteomic and metabolomic sequencing. Gene expressed profiling was downloaded from TCGA and GEO databases. After the differential analysis, proteins with a significant impact on the prognosis of OSCC patients were screened. Correlation analysis was performed with metabolites and core proteins were identified. Cox regression analysis was utilized to stratify OSCC samples based on core proteins. The prognostic predictive ability of the core protein was then evaluated. Differences in infiltration of immune cells between the different strata were identified. RESULTS: There were 678 differentially expressed proteins (DEPs), 94 intersected DEPs among them by intersecting with differentially expressed genes in TCGA and GSE30784 dataset. Seven core proteins were identified that significantly affected OSCC patient survival and strongly correlated with differential metabolites (R2 > 0.8). The samples were divided into high- and low-risk groups according to median risk score. The risk score and core proteins were well prognostic factor in OSCC patients. Genes in high-risk group were enriched in Notch signaling pathway, epithelial mesenchymal transition (EMT), and angiogenesis. Core proteins were strongly associated with the immune status of OSCC patients. CONCLUSIONS: The results established a 7-protein signatures with the hope of early detection and the capacity for risk assessment of OSCC patient prognosis. Further providing more potential targets for the treatment of OSCC.
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A multivariate Cox regression analysis was performed based on the 7 core proteins, and a risk score was calculated.
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A multivariate Cox regression analysis was performed based on the 7 core proteins, and a risk score was calculated.
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The proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD033080. The codes used in the manuscript were provided in the supplementary file 1.
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The proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD033080. The codes used in the manuscript were provided in the supplementary file 1.
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Seven core proteins were identified that significantly affected OSCC patient survival and strongly correlated with differential metabolites (R2 > 0.8).
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Seven core proteins were identified that significantly affected OSCC patient survival and strongly correlated with differential metabolites (R2 > 0.8).
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Seven core proteins were identified that significantly affected OSCC patient survival and strongly correlated with differential metabolites (R2 > 0.8).
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Gene expression profiling of oral squamous cell carcinoma (OSCC)
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Identification of novel prognostic indicators for oral squamous cell carcinoma based on proteomics
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The proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD033080. The codes used in the manuscript were provided in the supplementary file 1.
basis
The paper names GSE30784, GSE41613, PXD033080 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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A multivariate Cox regression analysis was performed based on the 7 core proteins, and a risk score was calculated.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37084685", "kind": "science-record", "revision": 2, "content_hash": "sha256:562152628c464c194db4b0dd1445fb39fe02f534c2a5a2bd810146e092a30881", "created_at": "2026-11-01T19:01:44Z", "updated_at": "2026-11-01T21:30:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of novel prognostic indicators for oral squamous cell carcinoma based on proteomics and metabolomics.", "doi": "10.1016/j.tranon.2023.101672", "pmid": "37084685", "authors": ["Zhitao Yao", "Wei An", "Maimaitituxun Tuerdi", "Jin Zhao"], "journal": "Translational oncology", "year": 2023, "abstract": "BACKGROUND: The low 5-year survival rate of oral squamous cell carcinoma (OSCC) suggests that new prognostic indicators need to be identified to aid the clinical management of patients.\nMETHODS: Saliva samples from OSCC patients and healthy controls were collected for proteomic and metabolomic sequencing. Gene expressed profiling was downloaded from TCGA and GEO databases. After the differential analysis, proteins with a significant impact on the prognosis of OSCC patients were screened. Correlation analysis was performed with metabolites and core proteins were identified. Cox regression analysis was utilized to stratify OSCC samples based on core proteins. The prognostic predictive ability of the core protein was then evaluated. Differences in infiltration of immune cells between the different strata were identified.\nRESULTS: There were 678 differentially expressed proteins (DEPs), 94 intersected DEPs among them by intersecting with differentially expressed genes in TCGA and GSE30784 dataset. Seven core proteins were identified that significantly affected OSCC patient survival and strongly correlated with differential metabolites (R2 > 0.8). The samples were divided into high- and low-risk groups according to median risk score. The risk score and core proteins were well prognostic factor in OSCC patients. Genes in high-risk group were enriched in Notch signaling pathway, epithelial mesenchymal transition (EMT), and angiogenesis. Core proteins were strongly associated with the immune status of OSCC patients.\nCONCLUSIONS: The results established a 7-protein signatures with the hope of early detection and the capacity for risk assessment of OSCC patient prognosis. 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:37084685", "data:geo:GSE30784"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE30784"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:37:18Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 8266, "completion_tokens": 1803, "cached_tokens": 128}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:37084685", "type": "paper", "label": "pmid:37084685"}, {"id": "source:pmid:37084685", "type": "manuscript", "label": "PMID 37084685 full text"}, {"id": "data:geo:GSE30784", "type": "dataset", "label": "GEO GSE30784"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37084685", "type": "paper", "label": "pmid:37084685"}, {"id": "source:pmid:37084685", "type": "manuscript", "label": "PMID 37084685 full text"}, {"id": "data:geo:GSE30784", "type": "dataset", "label": "GEO GSE30784"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37084685", "type": "extraction", "used": ["source:pmid:37084685"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE30784", "type": "accession_resolution", "used": ["data:geo:GSE30784"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:37084685", "parent_hash": "sha256:3a3a3ae310efbba888c5fa76a414d593f114ad270b7d2b63e1b4847ffa2cf925", "fork_of": null, "generation": 1}, "gaps": ["asset:data:geo:GSE30784 licence not read", "asset:data:geo:GSE30784 not downloaded", "asset:data:geo:GSE41613 licence not read", "asset:data:geo:GSE41613 not downloaded", "asset:data:geo:PXD033080 licence not read", "asset:data:geo:PXD033080 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": ["A multivariate Cox regression analysis was performed based on the 7 core proteins, and a risk score was calculated."], "order_basis": "analysis_only", "id": "assay:1"}]}