{"document":"journal-rps/record","document_version":"1.2","document_notes":{"1.1":"Added the canonical source the journal holds and the execution evidence another application produced. The sections that were already here say what they said in 1.0.","1.2":"Added the scope of a re-execution verdict: what the run re-executed, what it did not, and how much of the registered work answered. A verdict on a check of the paper's printed figures and a verdict on a re-run protocol are now stated apart. No earlier section changed."},"generated_at":"2026-11-09T19:40:29+00:00","publisher":"Journal of Open Source Science","what_this_is":"The journal's record for one paper, as one file. It holds the paper as it was read, the readings made of it, the registered plan, the runs, the result and the ledger behind it. A reading is a reading, a run is a run, and a verdict is not an editorial decision. The runs section records Journal executions. The execution_evidence section holds analyses performed by Automated Assays, with their source versions and results.","record":{"id":"dad7120a-f8d5-4ce5-a64a-4bfab4b9ca33","title":"Development and validation of a novel 3-gene prognostic model for pancreatic adenocarcinoma based on ferroptosis-related genes.","state":"submitted","article_type":"original_research","relationship_kind":"original","revision":0,"version":1,"synthetic":false,"doi":"10.1186/s12935-021-02431-8","authors":["Jihua Yang","XiaoHong Wei","Fang Hu","Wei Dong","Liao Sun"],"abstract":"BACKGROUND: Molecular markers play an important role in predicting clinical outcomes in pancreatic adenocarcinoma (PAAD) patients. Analysis of the ferroptosis-related genes may provide novel potential targets for the prognosis and treatment of PAAD.\nMETHODS: RNA-sequence and clinical data of PAAD was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) public databases. The PAAD samples were clustered by a non-negative matrix factorization (NMF) algorithm. The differentially expressed genes (DEGs) between different subtypes were used by \"limma_3.42.2\" package. The R software package clusterProfiler was used for functional enrichment analysis. Then, a multivariate Cox proportional and LASSO regression were used to develop a ferroptosis-related gene signature for pancreatic adenocarcinoma. A nomogram and corrected curves were constructed. Finally, the expression and function of these signature genes were explored by qRT-PCR, immunohistochemistry (IHC) and proliferation, migration and invasion assays.\nRESULTS: The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed. The prognostic model showed good independent prognostic ability in PAAD. In the GSE62452 external validation set, the molecular model also showed good risk prediction. KM-curve analysis showed that there were significant differences between the high and low-risk groups, samples with a high-risk score had a worse prognosis. The predictive efficiency of the 3-gene signature-based nomogram was significantly better than that of traditional clinical features. For comparison with other models, that our model, with a reasonable number of genes, yields a more effective result. The results obtained with qPCR and IHC assays showed that ALOX5 was highly expressed, whether ALOX12 and CISD1 were expressed at low levels in tissue samples. Finally, function assays results suggested that ALOX5 may be an oncogene and ALOX12 and CISD1 may be tumor suppressor genes.\nCONCLUSIONS: We present a novel prognostic molecular model for PAAD based on ferroptosis-related genes, which serves as a potentially effective tool for prognostic differentiation in pancreatic cancer patients.","package_hash":"60ad78c9e120c056f688b6f93d8508150647e604cb36930b151cfdbb05ed6b43","plan_hash":null,"plan_version":null,"first_receipt_at":"2026-11-04T07:03:23+00:00","decided_at":null,"days_open":5,"intake":{"method":"sci_import","source_name":"Cancer cell international","source_identifier":"pmid:35033072","source_url":null,"corpus_record_id":"pmid:35033072","recorded_by":"Journal Editor","ingested_at":"2026-11-04T07:03:23+00:00"},"lineage":{"relationship":"original","parent":null,"descendants":[]}},"source_text":{"held":false,"kind":"abstract","what_the_kind_means":"only the abstract was read","characters":null,"sha256":null,"intact":null,"note":"The hash is of the text as it arrived. A null intact value means there is no text to check, and a false one means the text no longer matches the record it arrived with."},"canonical_source":[{"record_id":"pmid:35033072","revision":3,"sci_version":"1.2","schema_uri":"https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json","authority":"corpus_engine","content_hash":"sha256:0617860cdfd03dfaa70ec2d8f7168607d60fd02669cc633867d2a85d9dae09bb","document_sha256":"a8c03b4414cafd70dbb184a7ab04d4a1df0815f78ab9779b2101ca0add2efa13","imported_at":"2026-11-04T07:03:23+00:00","what_this_is":"The canonical record as it was received. The document_sha256 is the hash of the bytes as received; the content_hash is the hash the record declares over its own body, recomputed before it was stored.","document_text":"{\n \"sci_version\": \"1.2\",\n \"schema\": \"https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json\",\n \"id\": \"pmid:35033072\",\n \"kind\": \"science-record\",\n \"revision\": 3,\n \"content_hash\": \"sha256:0617860cdfd03dfaa70ec2d8f7168607d60fd02669cc633867d2a85d9dae09bb\",\n \"created_at\": \"2026-11-01T17:36:45Z\",\n \"updated_at\": \"2026-11-01T21:26:59Z\",\n \"generator\": {\n  \"name\": \"corpus-assay-engine\",\n  \"run_id\": \"reading-sci-2026-11-01\"\n },\n \"paper\": {\n  \"state\": \"complete\",\n  \"title\": \"Development and validation of a novel 3-gene prognostic model for pancreatic adenocarcinoma based on ferroptosis-related genes.\",\n  \"doi\": \"10.1186/s12935-021-02431-8\",\n  \"pmid\": \"35033072\",\n  \"authors\": [\n   \"Jihua Yang\",\n   \"XiaoHong Wei\",\n   \"Fang Hu\",\n   \"Wei Dong\",\n   \"Liao Sun\"\n  ],\n  \"journal\": \"Cancer cell international\",\n  \"year\": 2022,\n  \"abstract\": \"BACKGROUND: Molecular markers play an important role in predicting clinical outcomes in pancreatic adenocarcinoma (PAAD) patients. Analysis of the ferroptosis-related genes may provide novel potential targets for the prognosis and treatment of PAAD.\\nMETHODS: RNA-sequence and clinical data of PAAD was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) public databases. The PAAD samples were clustered by a non-negative matrix factorization (NMF) algorithm. The differentially expressed genes (DEGs) between different subtypes were used by \\\"limma_3.42.2\\\" package. The R software package clusterProfiler was used for functional enrichment analysis. Then, a multivariate Cox proportional and LASSO regression were used to develop a ferroptosis-related gene signature for pancreatic adenocarcinoma. A nomogram and corrected curves were constructed. Finally, the expression and function of these signature genes were explored by qRT-PCR, immunohistochemistry (IHC) and proliferation, migration and invasion assays.\\nRESULTS: The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed. The prognostic model showed good independent prognostic ability in PAAD. In the GSE62452 external validation set, the molecular model also showed good risk prediction. KM-curve analysis showed that there were significant differences between the high and low-risk groups, samples with a high-risk score had a worse prognosis. The predictive efficiency of the 3-gene signature-based nomogram was significantly better than that of traditional clinical features. For comparison with other models, that our model, with a reasonable number of genes, yields a more effective result. The results obtained with qPCR and IHC assays showed that ALOX5 was highly expressed, whether ALOX12 and CISD1 were expressed at low levels in tissue samples. Finally, function assays results suggested that ALOX5 may be an oncogene and ALOX12 and CISD1 may be tumor suppressor genes.\\nCONCLUSIONS: We present a novel prognostic molecular model for PAAD based on ferroptosis-related genes, which serves as a potentially effective tool for prognostic differentiation in pancreatic cancer patients.\",\n  \"claims\": [\n   {\n    \"id\": \"claim-method\",\n    \"statement\": \"Next, LASSO regression was used to further compress the 10 genes to reduce the number of genes in the risk model.\",\n    \"kind\": \"methodological\",\n    \"target\": null,\n    \"evidence\": [\n     {\n      \"asset\": \"source:pmid:35033072\",\n      \"locator\": \"sections[22] \\\"Construction of a 3-gene signature\\\" paragraph 2\",\n      \"quote\": \"Next, LASSO regression was used to further compress the 10 genes to reduce the number of genes in the risk model.\"\n     }\n    ],\n    \"state\": \"complete\"\n   },\n   {\n    \"id\": \"claim-data-access\",\n    \"statement\": \"The results shown here are in whole or part based upon data generated by TCGA (https://www.cancer.gov/tcga), KEGG (https://www.genome.jp/kegg), GO (http://geneontology.org), GEO (https://www.ncbi.nlm.nih.gov/geo).\",\n    \"kind\": \"methodological\",\n    \"target\": null,\n    \"evidence\": [\n     {\n      \"asset\": \"source:pmid:35033072\",\n      \"locator\": \"sections[33] \\\"Availability of data and materials\\\" paragraph 2\",\n      \"quote\": \"The results shown here are in whole or part based upon data generated by TCGA (https://www.cancer.gov/tcga), KEGG (https://www.genome.jp/kegg), GO (http://geneontology.org), GEO (https://www.ncbi.nlm.nih.gov/geo).\"\n     }\n    ],\n    \"state\": \"complete\"\n   },\n   {\n    \"id\": \"claim-target-result\",\n    \"statement\": \"The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed.\",\n    \"kind\": \"qualitative\",\n    \"target\": null,\n    \"evidence\": [\n     {\n      \"asset\": \"source:pmid:35033072\",\n      \"locator\": \"sections[0] \\\"Abstract\\\" paragraph 3\",\n      \"quote\": \"The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed.\"\n     }\n    ],\n    \"state\": \"complete\"\n   }\n  ],\n  \"gaps\": []\n },\n \"experiment\": {\n  \"state\": \"complete\",\n  \"objective\": \"The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed.\",\n  \"steps\": [\n   {\n    \"id\": \"read_published_estimate\",\n    \"order\": 1,\n    \"name\": \"Read the published estimate from the source\",\n    \"kind\": \"other\",\n    \"state\": \"complete\",\n    \"blocked_on\": null,\n    \"description\": \"The claim, method and evidence span published with the source article.\",\n    \"duration_hours\": null,\n    \"parameters\": {},\n    \"inputs\": [\n     \"source:pmid:35033072\"\n    ],\n    \"outputs\": [\n     \"the published estimate and its evidence\"\n    ],\n    \"instruments\": [],\n    \"reagents\": []\n   },\n   {\n    \"id\": \"obtain_source_data\",\n    \"order\": 2,\n    \"name\": \"Obtain the source data from the named repository\",\n    \"kind\": \"data-preparation\",\n    \"state\": \"complete\",\n    \"blocked_on\": null,\n    \"description\": \"The GEO series accession resolves and its sample accessions are listed. 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The results obtained with qPCR and IHC assays showed that ALOX5 was highly expresse\"\n   ],\n   \"order_basis\": \"paper_text_order:1048\",\n   \"id\": \"assay:1\"\n  },\n  {\n   \"role\": \"data_generation\",\n   \"definition_id\": \"qpcr\",\n   \"definition_version\": \"99e1195c7d6f\",\n   \"definition_digest\": null,\n   \"required_operations\": [],\n   \"support_state\": \"partial\",\n   \"source_hashes\": {\n    \"assay_lexicon\": \"99e1195c7d6f\"\n   },\n   \"confidence\": 0.93,\n   \"evidence\": [\n    \"effective result. The results obtained with qPCR and IHC assays showed that ALOX5 was highly\"\n   ],\n   \"order_basis\": \"paper_text_order:1874\",\n   \"id\": \"assay:2\"\n  },\n  {\n   \"role\": \"data_generation\",\n   \"definition_id\": \"transfection\",\n   \"definition_version\": \"99e1195c7d6f\",\n   \"definition_digest\": null,\n   \"required_operations\": [],\n   \"support_state\": \"partial\",\n   \"source_hashes\": {\n    \"assay_lexicon\": \"99e1195c7d6f\"\n   },\n   \"confidence\": 0.99,\n   \"evidence\": [\n    \"tobiliary Surgery Hospital. Cell culture and transfection The human PAAD cell line T3M4 and Panc 02.03\",\n    \"was purchased from Origene (Beijing, China). Transfection was performed using Lipofectamine 3000 reage\",\n    \"hina) according to the instructions and cell transfection efficiency was 82%.The human ALOX12 and CISD\"\n   ],\n   \"order_basis\": \"paper_text_order:3797\",\n   \"id\": \"assay:3\"\n  },\n  {\n   \"role\": \"data_generation\",\n   \"definition_id\": \"cell_culture\",\n   \"definition_version\": \"99e1195c7d6f\",\n   \"definition_digest\": null,\n   \"required_operations\": [],\n   \"support_state\": \"partial\",\n   \"source_hashes\": {\n    \"assay_lexicon\": \"99e1195c7d6f\"\n   },\n   \"confidence\": 0.99,\n   \"evidence\": [\n    \"ncer and are epithelial-like cells. The T3M4 cell lines were cultured in DMEM (Dulbecco’ modified eagle medium) (G\",\n    \"nd are epithelial-like cells. The Panc 02.03 cell lines were cultured in RPMI-1640 (Gibco, Grand Island, NY, USA)\",\n    \"thelial-like cells. The T3M4 cell lines were cultured in DMEM (Dulbecco’ modified eagle medium) (Gibc\",\n    \"l-like cells. The Panc 02.03 cell lines were cultured in RPMI-1640 (Gibco, Grand Island, NY, USA) wit\"\n   ],\n   \"order_basis\": \"paper_text_order:4080\",\n   \"id\": \"assay:4\"\n  },\n  {\n   \"role\": \"analysis\",\n   \"definition_id\": \"survival_analysis\",\n   \"definition_version\": \"f2132e96ae6c7a4e\",\n   \"definition_digest\": null,\n   \"required_operations\": [\n    \"cox_ph\"\n   ],\n   \"support_state\": \"supported\",\n   \"source_hashes\": {\n    \"dsl_catalogue\": \"f2132e96ae6c7a4e\"\n   },\n   \"confidence\": 1.0,\n   \"evidence\": [\n    \"Next, LASSO regression was used to further compress the 10 genes to reduce the number of genes in the risk model.\"\n   ],\n   \"order_basis\": \"consumes_earlier_output\",\n   \"id\": \"assay:5\"\n  }\n ]\n}\n","document":{"sci_version":"1.2","schema":"https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json","id":"pmid:35033072","kind":"science-record","revision":3,"content_hash":"sha256:0617860cdfd03dfaa70ec2d8f7168607d60fd02669cc633867d2a85d9dae09bb","created_at":"2026-11-01T17:36:45Z","updated_at":"2026-11-01T21:26:59Z","generator":{"name":"corpus-assay-engine","run_id":"reading-sci-2026-11-01"},"paper":{"state":"complete","title":"Development and validation of a novel 3-gene prognostic model for pancreatic adenocarcinoma based on ferroptosis-related genes.","doi":"10.1186/s12935-021-02431-8","pmid":"35033072","authors":["Jihua Yang","XiaoHong Wei","Fang Hu","Wei Dong","Liao Sun"],"journal":"Cancer cell international","year":2022,"abstract":"BACKGROUND: Molecular markers play an important role in predicting clinical outcomes in pancreatic adenocarcinoma (PAAD) patients. Analysis of the ferroptosis-related genes may provide novel potential targets for the prognosis and treatment of PAAD.\nMETHODS: RNA-sequence and clinical data of PAAD was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) public databases. The PAAD samples were clustered by a non-negative matrix factorization (NMF) algorithm. The differentially expressed genes (DEGs) between different subtypes were used by \"limma_3.42.2\" package. The R software package clusterProfiler was used for functional enrichment analysis. Then, a multivariate Cox proportional and LASSO regression were used to develop a ferroptosis-related gene signature for pancreatic adenocarcinoma. A nomogram and corrected curves were constructed. Finally, the expression and function of these signature genes were explored by qRT-PCR, immunohistochemistry (IHC) and proliferation, migration and invasion assays.\nRESULTS: The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed. The prognostic model showed good independent prognostic ability in PAAD. In the GSE62452 external validation set, the molecular model also showed good risk prediction. KM-curve analysis showed that there were significant differences between the high and low-risk groups, samples with a high-risk score had a worse prognosis. The predictive efficiency of the 3-gene signature-based nomogram was significantly better than that of traditional clinical features. For comparison with other models, that our model, with a reasonable number of genes, yields a more effective result. The results obtained with qPCR and IHC assays showed that ALOX5 was highly expressed, whether ALOX12 and CISD1 were expressed at low levels in tissue samples. Finally, function assays results suggested that ALOX5 may be an oncogene and ALOX12 and CISD1 may be tumor suppressor genes.\nCONCLUSIONS: We present a novel prognostic molecular model for PAAD based on ferroptosis-related genes, which serves as a potentially effective tool for prognostic differentiation in pancreatic cancer patients.","claims":[{"id":"claim-method","statement":"Next, LASSO regression was used to further compress the 10 genes to reduce the number of genes in the risk model.","kind":"methodological","target":null,"evidence":[{"asset":"source:pmid:35033072","locator":"sections[22] \"Construction of a 3-gene signature\" paragraph 2","quote":"Next, LASSO regression was used to further compress the 10 genes to reduce the number of genes in the risk model."}],"state":"complete"},{"id":"claim-data-access","statement":"The results shown here are in whole or part based upon data generated by TCGA (https://www.cancer.gov/tcga), KEGG (https://www.genome.jp/kegg), GO (http://geneontology.org), GEO (https://www.ncbi.nlm.nih.gov/geo).","kind":"methodological","target":null,"evidence":[{"asset":"source:pmid:35033072","locator":"sections[33] \"Availability of data and materials\" paragraph 2","quote":"The results shown here are in whole or part based upon data generated by TCGA (https://www.cancer.gov/tcga), KEGG (https://www.genome.jp/kegg), GO (http://geneontology.org), GEO (https://www.ncbi.nlm.nih.gov/geo)."}],"state":"complete"},{"id":"claim-target-result","statement":"The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed.","kind":"qualitative","target":null,"evidence":[{"asset":"source:pmid:35033072","locator":"sections[0] \"Abstract\" paragraph 3","quote":"The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed."}],"state":"complete"}],"gaps":[]},"experiment":{"state":"complete","objective":"The 173 samples were divided into 3 categories (C1, C2, and C3) and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed.","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:35033072"],"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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