Novel amino acid metabolism-related gene signature to predict prognosis in clear cell renal cell carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36118874", "kind": "science-record", "revision": 4, "content_hash": "sha256:6de1bbe15a0f20a6e070e3a60d6e4d81277e832ab6a4c9cde57b755fbbe2747c", "created_at": "2026-11-01T18:15:23Z", "updated_at": "2026-11-01T22:07:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Novel amino acid metabolism-related gene signature to predict prognosis in clear cell renal cell carcinoma.", "doi": "10.3389/fgene.2022.982162", "pmid": "36118874", "authors": ["Xiaofeng Cheng", "Wen Deng", "Zhicheng Zhang", "Zhenhao Zeng", "Yifu Liu", "Xiaochen Zhou", "Cheng Zhang", "Gongxian Wang"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Background: Amino acid metabolism (AAM) deregulation, an emerging metabolic hallmark of malignancy, plays an essential role in tumour proliferation, invasion, and metastasis. However, the expression of AAM-related genes and their correlation with prognosis in clear cell renal cell carcinoma (ccRCC) remain elusive. This study aims to develop a novel consensus signature based on the AAM-related genes. Methods: The RNA-seq expression data and clinical information for ccRCC were downloaded from the TCGA (KIRC as training dataset) and ArrayExpress (E-MTAB-1980 as validation dataset) databases. The AAM-related differentially expressed genes were screened via the \"limma\" package in TCGA cohorts for further analysis. The machine learning algorithms (Lasso and stepwise Cox (direction = both)) were then utilised to establish a novel consensus signature in TCGA cohorts, which was validated by the E-MTAB-1980 cohorts. The optimal cutoff value determined by the \"survminer\" package was used to categorise patients into two risk categories. The Kaplan-Meier curve, the receiver operating characteristic (ROC) curve, and multivariate Cox regression were utilised to evaluate the prognostic value. The nomogram based on the gene signature was constructed, and its performance was analysed using ROC and calibration curves. Gene Set Enrichment Analysis (GSEA) and immune cell infiltration analysis were conducted on its potential mechanisms. The relationship between the gene signature and key immune checkpoint, N6-methyladenosine (m6A)-related genes, and sensitivity to chemotherapy was assessed. Results: A novel consensus AMM-related gene signature consisting of IYD, NNMT, ACADSB, GLDC, and PSAT1 is developed to predict prognosis in TCGA cohorts. Kaplan-Meier survival shows that overall survival in the high-risk group was more dismal than in the low-risk group in the TCGA cohort, validated by the E-MTAB-1980 cohort. Multivariate regression analysis also demonstrates that the gene signature is an independent predictor of ccRCC. Immune infiltration analysis highlighted that the high-risk group indicates an immunosuppressive microenvironment. It is also closely related to the level of key immune checkpoints, m6A modification, and sensitivity to chemotherapy drugs. Conclusion: In this study, a novel consensus AAM-related gene signature is developed and validated as an independent predictor to robustly predict the overall survival from ccRCC, which would further improve the clinical outcomes.", "claims": [{"id": "claim-method", "statement": "A combination model of Lasso and stepwise Cox (direction = both) was applied in TCGA cohorts to develop a consensus AAM-related gene signature, identifying a final set of 5 AAM-related DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36118874", "locator": "sections[16] \"Development and validation of the AAM-related prognostic signature\" paragraph 2", "quote": "A combination model of Lasso and stepwise Cox (direction = both) was applied in TCGA cohorts to develop a consensus AAM-related gene signature, identifying a final set of 5 AAM-related DEGs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36118874", "locator": "sections[26] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "To evaluate the discrimination of the AAM-related prognostic signature, ROC analysis of OS is measured, and the 1-, 3-, and 5-year areas under the ROC curves (AUCs) were 0.751,0.716, and 0.747 in the TCGA cohorts (Figure 4G) and 0.701, 0.783, and 0.761 in the E-MTAB-1980 cohorts (Figure 4H), respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36118874", "locator": "sections[16] \"Development and validation of the AAM-related prognostic signature\" paragraph 3", "quote": "To evaluate the discrimination of the AAM-related prognostic signature, ROC analysis of OS is measured, and the 1-, 3-, and 5-year areas under the ROC curves (AUCs) were 0.751,0.716, and 0.747 in the TCGA cohorts (Figure 4G) and 0.701, 0.783, and 0.761 in the E-MTAB-1980 cohorts (Figure 4H), respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "To evaluate the discrimination of the AAM-related prognostic signature, ROC analysis of OS is measured, and the 1-, 3-, and 5-year areas under the ROC curves (AUCs) were 0.751,0.716, and 0.747 in the TCGA cohorts (Figure 4G) and 0.701, 0.783, and 0.761 in the E-MTAB-1980 cohorts (Figure 4H), 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:36118874"], "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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