Derivation and Validation of a Prognostic Model for Cancer Dependency Genes Based on CRISPR-Cas9 in Gastric Adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33732644", "kind": "science-record", "revision": 7, "content_hash": "sha256:671336bcb9fec3e957009c4482c4271b7852c994ac324e3202fbc1627d27cc69", "created_at": "2026-11-01T15:41:29Z", "updated_at": "2026-11-01T22:03:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Derivation and Validation of a Prognostic Model for Cancer Dependency Genes Based on CRISPR-Cas9 in Gastric Adenocarcinoma.", "doi": "10.3389/fonc.2021.617289", "pmid": "33732644", "authors": ["Wenjie Zhou", "Junqing Li", "Xiaofang Lu", "Fangjie Liu", "Tailai An", "Xing Xiao", "Zi Chong Kuo", "Wenhui Wu", "Yulong He"], "journal": "Frontiers in oncology", "year": 2021, "abstract": "As a CRISPR-Cas9-based tool to help scientists to investigate gene functions, Cancer Dependency Map genes (CDMs) include an enormous series of loss-of-function screens based on genome-scale RNAi. These genes participate in regulating survival and growth of tumor cells, which suggests their potential as novel therapeutic targets for malignant tumors. By far, studies on the roles of CDMs in gastric adenocarcinoma (GA) are scarce and only a small fraction of CDMs have been investigated. In the present study, datasets of the differentially expressed genes (DEGs) were extracted from the TCGA-based (The Cancer Genome Atlas) GEPIA database, from which differentially expressed CDMs were determined. Functions and prognostic significance of these verified CDMs were evaluated using a series of bioinformatics methods. In all, 246 differentially expressed CDMs were determined, with 147 upregulated and 99 downregulated. Ten CDMs (ALG8, ATRIP, CCT6A, CFDP1, CINP, MED18, METTL1, ORC1, TANGO6, and PWP2) were identified to be prognosis-related and subsequently a prognosis model based on these ten CDMs was constructed. In comparison with that of patients with low risk in TCGA training, testing and GSE84437 cohort, overall survival (OS) of patients with high risk was significantly worse. It was then subsequently demonstrated that for this prognostic model, area under the ROC (receiver operating characteristic) curve was 0.771 and 0.697 for TCGA training and testing cohort respectively, justifying its reliability in predicting survival of GA patients. With the ten identified CDMs, we then constructed a nomogram to generate a clinically practical model. The regulatory networks and functions of the ten CDMs were then explored, the results of which demonstrated that as the gene significantly associated with survival of GA patients and Hazard ratio (HR), PWP2 promoted in-vitro invasion and migration of GA cell lines through the EMT signaling pathway. Therefore, in conclusion, the present study might help understand the prognostic significance and molecular functions of CDMs in GA.", "claims": [{"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33732644", "locator": "sections[21] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. 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"sample_count": 483, "group_sizes": null, "group_sizes_basis": null, "platform": "6947", "taxon": "Homo sapiens", "title": "Molecular subtypes in gastric cancer.", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:33732644:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:f654ca1d65f5543507736b0efcc82b986078ff9048e0ff030219c427ff2c5889", "bytes": 942, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[16]/table-wrap[1]#T1", "version": null, "note": "Ten Cancer Dependency Maps (CDMs) significantly associated with overall survival in the TCGA-STAD Project.", "structure": {"pmcid": "PMC7959733", "section_index": 16, "section_title": "Prognosis-Related Hub Cancer Dependency Map Genes", "row_count": 11, "column_count": 6}, "table": {"label": "Table 1", "caption": "Ten Cancer Dependency Maps (CDMs) significantly associated with overall survival in the TCGA-STAD Project.", "rows": [["ID", "Coef", "HR", "HR.95L", "HR.95H", "P value"], ["ALG8", "-0.05107", "0.950208", "0.89973", "1.003517", "0.066669"], ["ATRIP", "-4.24778", "0.014296", "0.000171", "1.192412", "0.059837"], ["CCT6A", "0.009201", "1.009244", "1.00174", "1.016803", "0.015662"], ["CFDP1", "0.092187", "1.09657", "1.03851", "1.157876", "0.000896"], ["CINP", "0.179328", "1.196413", "0.977263", "1.464708", "0.082358"], ["MED18", "-0.16993", "0.843725", "0.747413", "0.952448", "0.006"], ["METTL1", "0.080107", "1.083403", "1.000883", "1.172728", "0.047503"], ["ORC1", "-0.14509", "0.864948", "0.720126", "1.038894", "0.120701"], ["PWP2", "0.766357", "2.151913", "1.092021", "4.240512", "0.026807"], ["TANGO6", "0.342845", "1.40895", "0.977994", "2.029809", "0.065694"]], "row_count": 11, "column_count": 6, "numeric_cells": 53, 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:33732644", "data:geo:GSE84437", "asset:table:pmid:33732644:1"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE84437"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:28:07Z", "independence": "single_reader"}, "evidence_check": {"method": "reordered", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 38647, "completion_tokens": 2247, "cached_tokens": 13064}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:33732644", "type": "paper", "label": "pmid:33732644"}, {"id": "source:pmid:33732644", "type": "manuscript", "label": "PMID 33732644 full text"}, {"id": "data:geo:GSE84437", "type": "dataset", "label": "GEO GSE84437"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:33732644", "type": "paper", "label": "pmid:33732644"}, {"id": "source:pmid:33732644", "type": "manuscript", "label": "PMID 33732644 full text"}, {"id": "data:geo:GSE84437", "type": "dataset", "label": "GEO GSE84437"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-33732644", "type": "extraction", "used": ["source:pmid:33732644"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE84437", "type": "accession_resolution", "used": ["data:geo:GSE84437"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:33732644", "parent_hash": "sha256:a1b721fe52875b731b0227d1ca5c73a3775df0efdf2c476d5e67aa448f831def", "fork_of": null, "generation": 6}, "gaps": ["asset:data:geo:GSE84437 licence not read", "asset:data:geo:GSE84437 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["c Model for Cancer Dependency Genes Based on CRISPR-Cas9 in Gastric Adenocarcinoma.", "As a CRISPR-Cas9-based tool to help scientists to invest", "ox regression models. Cell Culture and siRNA Transfection The gastric cancer cell lines used in our st", "ons with 100nm pooled siRNA and riboFECT™ CP Transfection Kit (Guangzhou RiboBio Co. Ltd., Guangzhou,"], "order_basis": "paper_text_order:40", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["terials and Methods Data Processing Relevant RNA-sequencing and clinical datasets of GA were extracted f"], "order_basis": "paper_text_order:2219", "id": "assay:2"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["hanghai, China). After being rewarmed, HGC27 cell line was cultured on dishes filled with RPMI-1640 (Shanghai XP", "chnology Co., Ltd., Beijing, China). The two cell lines were cultured at 37°C in an atmosphere filled with 5% CO2"], "order_basis": "paper_text_order:4016", "id": "assay:3"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["“the relationship between the differentially expressed CDMs and OS were assessed through the univariate Cox regression analysis and Kaplan-Meier method”"], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}