A Cell Differentiation Trajectory-Related Signature for Predicting the Prognosis of Lung Adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36072012", "kind": "science-record", "revision": 3, "content_hash": "sha256:78c02e18acb7f8492903bcc5fbda59116624ba1bd077069b2adc5b76340ccf36", "created_at": "2026-11-01T18:15:17Z", "updated_at": "2026-11-01T21:28:51Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Cell Differentiation Trajectory-Related Signature for Predicting the Prognosis of Lung Adenocarcinoma.", "doi": "10.1155/2022/3483498", "pmid": "36072012", "authors": ["Fan Yang", "Yan Zhao", "Xiaohan Huang", "Jin Zhang", "Ting Zhang"], "journal": "Genetics research", "year": 2022, "abstract": "Objective: To screen the cell differentiation trajectory-related genes and build a cell differentiation trajectory-related signature for predicting the prognosis of lung adenocarcinoma (LUAD).\nMethods: LUAD single cell mRNA expression profile, TCGA-LUAD transcriptome data were obtained from GEO and TCGA databases. Single-cell RNA-seq data were used for cell clustering and pseudotime analysis after dimensionality reduction analysis, and the cell differentiation trajectory-related genes were acquired after differential expression analysis conducted between the main branches. Then, the consensus clustering analysis was carried out on TCGA-LUAD samples, and the GSEA analysis was performed, then the differences on the expression levels of immune checkpoint genes and immunotherapy response were compared among clusters. The prognostic model was constructed, and the GSE42127 dataset was used to validate. A nomogram evaluation model was used to predict prognosis.\nResults: Two subsets with distinct differentiation states were found after cell differentiation trajectory analysis. TCGA-LUAD samples were divided into two cell differentiation trajectory-related gene-based clusters, GSEA found that cluster 1 was significantly related to 20 pathways, cluster 2 was significantly enriched in three pathways, and it was also shown that clusters could better predict immune checkpoint gene expression and immunotherapy response. A six cell differentiation-related genes-based prognostic signature was constructed, and the patients in the high-risk group had poorer prognosis than those in the low-risk group. Moreover, a nomogram was constructed based on the prognostic signature and clinicopathological features, and this nomogram had strong predictive performance and high accuracy.\nConclusion: The cell differentiation-related signature and the prognostic nomogram could accurately predict survival.", "claims": [{"id": "claim-method", "statement": "The single-factor Cox proportional hazards regression analysis was performed on the marker genes in TCGA-LUAD, and the genes with the cutoff value of P < 0.05 were screened. Then, multivariate Cox analysis and stepwise regression were carried out to identify the prognosis-related genes, and after that the prognostic model was built.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36072012", "locator": "sections[9] \"2.7. Generation and Validation of a Prognostic Model\" paragraph 2", "quote": "The single-factor Cox proportional hazards regression analysis was performed on the marker genes in TCGA-LUAD, and the genes with the cutoff value of P < 0.05 were screened. Then, multivariate Cox analysis and stepwise regression were carried out to identify the prognosis-related genes, and after that the prognostic model was built."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data that support the findings of this study are available in TCGA and GEO databases.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36072012", "locator": "sections[20] \"Data Availability\" paragraph 2", "quote": "The data that support the findings of this study are available in TCGA and GEO databases."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A six cell differentiation-related genes-based prognostic signature was constructed, and the patients in the high-risk group had poorer prognosis than those in the low-risk group.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36072012", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A six cell differentiation-related genes-based prognostic signature was constructed, and the patients in the high-risk group had poorer prognosis than those in the low-risk group."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A six cell differentiation-related genes-based prognostic signature was constructed, and the patients in the high-risk group had poorer prognosis than those in the low-risk group.", "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:36072012"], "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. 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