Identification of hub genes related to radiosensitivity and prognosis in rectal cancer.

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"independent_readings", "status": "blocked", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "reason": "a quoted statement is absent from the supplied text", "raw_response": "{\n  \"target_result\": \"Four key radiosensitivity-related immune genes were identified: BMP2, COLEC10, MASP2, and GCGR.\",\n  \"work_type\": \"analysis_only_for_target\",\n  \"physical_methods\": [],\n  \"analysis_methods\": [\n    \"Differential expression analysis between complete response and incomplete response groups\",\n    \"Intersection of differentially expressed genes and immune genes\",\n    \"Gene Ontology pathway analysis\",\n    \"KEGG pathway analysis\",\n    \"Univariate Cox regression analysis\",\n    \"Multivariate Cox regression analysis\",\n    \"Nomogram development\",\n    \"Harrell's concordance index calculation\",\n    \"Receiver operating characteristic curve analysis\",\n    \"External dataset validation\",\n    \"Single-sample gene set enrichment analysis (ssGSEA)\",\n    \"Kaplan-Meier survival analysis\",\n    \"Wilcoxon test\",\n    \"Spearman correlation analysis\"\n  ],\n  \"statistical_method\": \"Cox regression analysis\",\n  \"method_evidence\": \"Cox regression analysis was used to screen out prognostic genes.\",\n  \"repositories\": [\n    {\n      \"repository\": \"Gene Expression Omnibus (GEO)\",\n      \"accession\": \"GSE133057\",\n      \"data_description\": \"Rectal cancer radiosensitivity information used to identify differentially expressed genes between complete-response and incomplete-response groups.\",\n      \"evidence\": \"GSE133057 containing RC radiosensitivity information was downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) between the complete response (CR) group and the incomplete response (iCR) group were identified.\",\n      \"publicly_downloadable\": true\n    },\n    {\n      \"repository\": \"ImmPort database\",\n      \"accession\": \"unclear\",\n      \"data_description\": \"Immune genes used, together with differentially expressed genes, to obtain radiosensitivity-related immune genes.\",\n      \"evidence\": \"Immune genes were obtained from the ImmPort database.\",\n      \"publicly_downloadable\": false\n    },\n    {\n      \"repository\": \"The Cancer Genome Atlas (TCGA)\",\n      \"accession\": \"unclear\",\n      \"data_description\": \"Transcriptomic and clinical rectal cancer data used to develop and test the risk model and nomogram.\",\n      \"evidence\": \"Transcriptomic and clinical data of RC were downloaded from The Cancer Genome Atlas (TCGA) database, and the entire cohort was randomly divided into training and testing sets at a ratio of 7:3.\",\n      \"publicly_downloadable\": true\n    },\n    {\n      \"repository\": \"Kaplan-Meier Plotter\",\n      \"accession\": \"unclear\",\n      \"data_description\": \"Expression and patient-survival data used to investigate the prognostic role of the four hub genes.\",\n      \"evidence\": \"We utilized Kaplan-Meier plotter (https://kmplot.com) to investigate the role of hub genes with respect to the prognosis of CRC patients.\",\n      \"publicly_downloadable\": false\n    }\n  ],\n  \"availability_statement\": \"GSE133057 containing RC radiosensitivity information was downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) between the complete response (CR) group and the incomplete response (iCR) group were identified. Immune genes were obtained from the ImmPort database. Radiosensitivity-related immune genes (RRIGs) were obtained by intersecting DEGs and the immune genes. Transcriptomic and clinical data of RC were downloaded from The Cancer Genome Atlas (TCGA) database, and the entire cohort was randomly divided into training and testing sets at a ratio of 7:3.\",\n  \"data_on_request\": false,\n  \"source_claims\": [\n    \"A total of 76 RRIGs were identified, and they were mainly involved in cytokine-cytokine receptor interaction, TNF signaling pathway, cAMP signaling pathway, Toll-like receptor (TLR) signaling pathway, and so on.\",\n    \"BMP2, COLEC10, MASP2, and GCGR were screened as prognostic genes after Cox regression analysis.\",\n    \"We identified four key genes: BMP2, COLEC10, MASP2, and GCGR, which play significant roles in the radiosensitivity, immune microenvironment, and prognosis of RC.\",\n    \"Four hub RRIGs (BMP2, COLEC10, MASP2, and GCGR) were identified, which showed associations with both the radiosensitivity and prognosis of RC patients.\",\n    \"The results of Kaplan-Meier plotter showed that low mRNA expression levels of BMP2, COLEC10, and MASP2 were correlated with shorter post-progression survival (PPS) (Figure 9A-9C). And a high mRNA expression level of GCGR was correlated with shorter OS (Figure 9D).\"\n  ],\n  \"missing_information\": [\n    \"The paper does not provide an accession or dataset identifier for the ImmPort data.\",\n    \"The paper does not provide an accession or dataset identifier for the TCGA rectal cancer cohort.\",\n    \"The paper does not identify the external dataset used for validation.\",\n    \"The paper does not provide a specific accession for the Kaplan-Meier Plotter cohort.\",\n    \"The supplied text does not state that any of the data are available on request.\"\n  ],\n  \"evidence_spans\": [\n    \"A total of 76 RRIGs were identified, and they were mainly involved in cytokine-cytokine receptor interaction, TNF signaling pathway, cAMP signaling pathway, Toll-like receptor (TLR) signaling pathway, and so on.\",\n    \"BMP2, COLEC10, MASP2, and GCGR were screened as prognostic genes after Cox regression analysis.\",\n    \"We identified four key genes: BMP2, COLEC10, MASP2, and GCGR, which play significant roles in the radiosensitivity, immune microenvironment, and prognosis of RC.\",\n    \"Cox regression analysis was used to screen out prognostic genes.\",\n    \"Survival analysis was performed by Kaplan-Meier method.\",\n    \"The relationship between the risk model and immune cell infiltration was analyzed by single-sample gene set enrichment analysis (ssGSEA).\",\n    \"Next, the nomogram was designed and the C-index of the nomogram was 0.84, indicating that the nomogram model had a certain predictive value (Figure 8C).\"\n  ]\n}"}, {"provider": "minimax", "model": null, "reason": "HTTP Error 429: Too Many Requests", "raw_response": null}, {"provider": "minimax_alt", "model": null, "reason": "HTTP Error 429: Too Many Requests", "raw_response": null}]}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:93d1df08205a6cc184d20cc920dd163fa64e651e87b9bc1fe35f9e0e11c09aed", "type": "sep_package", "label": "SEP v1 package for pmid:40950702"}], "activities": [{"id": "activity:conversion:pmid:40950702", "type": "conversion", "used": ["package:93d1df08205a6cc184d20cc920dd163fa64e651e87b9bc1fe35f9e0e11c09aed"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:minimax_alt", "type": "model", "label": "minimax_alt"}, {"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}], "source_run_id": "run-20261023T122449232913", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "f1955aa7-2bfe-4b30-b6f8-212231922486", "parent_hash": "93d1df08205a6cc184d20cc920dd163fa64e651e87b9bc1fe35f9e0e11c09aed", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:40950702 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:40950702' does not resolve to a declared asset", "targets"]}