Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival.

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The ESCC-related dataset, GSE20347, was downloaded from the Gene Expression Omnibus (GEO) database, and weighted gene co-expression network analysis was performed to identify genes that are highly correlated with ESCC. A total of 91 transcriptome expression profiles and their corresponding clinical information were obtained from The Cancer Genome Atlas database. A mitochondria-associated risk (MAR) model was constructed using the least absolute shrinkage and selection operator Cox regression analysis and validated using GSE161533. The tumor microenvironment and drug sensitivity were explored using the MAR model. Finally, in vitro experiments were performed to analyze the effects of hub genes on the proliferation and invasion abilities of ESCC cells. To confirm the predictive ability of the MAR model, we constructed a prognostic model and assessed its predictive accuracy. The MAR model revealed substantial differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk populations and a substantial correlation between the risk scores and some common immunological checkpoints. AZD1332 and AZD7762 were more effective for patients in the low-risk group, whereas Entinostat, Nilotinib, Ruxolutinib, and Wnt.c59 were more effective for patients in the high-risk group. Knockdown of TYMS significantly inhibited the proliferation and invasive ability of ESCC cells in vitro. Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.", "claims": [{"id": "claim-method", "statement": "Univariate Cox regression and LASSO regression analyses were performed to identify prognostic indicators and genes associated with survival in patients with ESCC.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38719775", "locator": "sections[7] \"Prognostic Marker Screening\" paragraph 2", "quote": "Univariate Cox regression and LASSO regression analyses were performed to identify prognostic indicators and genes associated with survival in patients with ESCC."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Supplementary data for this paper are available on-line only at http://jmb.or.kr.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38719775", "locator": "sections[32] \"Supplemental Materials\" paragraph 2", "quote": "Supplementary data for this paper are available on-line only at http://jmb.or.kr."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38719775", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.", "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:38719775"], "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": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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