CRISPR-cas9 Screening Identified Lethal Genes Enriched in Cell Cycle Pathway and of Prognosis Significance in Breast Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33816496", "kind": "science-record", "revision": 7, "content_hash": "sha256:74d215235c2f30ba61168ed351de1099a479efc52f645464b91aacbbdedbb130", "created_at": "2026-11-01T15:41:31Z", "updated_at": "2026-11-01T22:03:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "CRISPR-cas9 Screening Identified Lethal Genes Enriched in Cell Cycle Pathway and of Prognosis Significance in Breast Cancer.", "doi": "10.3389/fcell.2021.646774", "pmid": "33816496", "authors": ["Xi Sun", "Zheng Wang", "Xiaosong Chen", "Kunwei Shen"], "journal": "Frontiers in cell and developmental biology", "year": 2021, "abstract": "BACKGROUND: Lethal genes have not been systematically analyzed in breast cancer which may have significant prognostic value. The current study aims to investigate vital genes related to cell viability by analyzing the CRISPR-cas9 screening data, which may provide novel therapeutic target for patients.\nMETHODS: Genes differentially expressed between tumor and normal tissue from the Cancer Genome Atlas (TCGA) and genes related to cell viability by CRISPR-cas9 screening from Depmap (Cancer Dependency Map) were overlapped. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis was conducted to identify which pathways of overlapped genes were enriched. GSE21653 set was randomized into training and internal validation dataset at a ratio of 3:1, and external validation was performed in GSE20685 set. The least absolute shrinkage and selection operator (LASSO) regression was used to construct a signature to predict recurrence-free survival (RFS) of breast cancer patients. Univariate and multivariate Cox regression were used to evaluate the prognostic value of this signature. Differentially expressed genes (DEGs) between high-risk and low-risk patients were then analyzed to identify the main pathways regulated by this signature. Weighted correlation network analysis (WGCNA) was conducted to recognize modules correlated with high risk. Enrichment analysis was then used to identify pathways regulated by genes shared in the overlapped genes, DEGs, and WGCNA.\nRESULTS: A total of 86 oncogenes were upregulated in TCGA database and overlapped with lethal genes in Depmap database, which were enriched in cell cycle pathway. A total of 51 genes were included in the gene signature based on LASSO regression, and the median risk score of 2.36 was used as cut-off to separate low-risk patients from high-risk patients. High-risk patients showed worse RFS compared with low-risk patients in internal training, internal validation, and external validation dataset. Time-dependent receiver operating characteristic curves of 3 and 5 years indicated that risk score was superior to tumor stage, age, and PAM50 in both entire and external validation datasets. Cell cycle was the main different pathway between the high-risk and low-risk groups. Meanwhile, cell cycle was also the main pathway enriched in the 25 genes which were shared among 86 genes, DEGs, and WGCNA.\nCONCLUSION: Cell cycle pathway, identified by CRISPR-cas9 screening, was a key pathway regulating cell viability, which has significant prognostic values and can serve as a new target for breast cancer patient treatment.", "claims": [{"id": "claim-method", "statement": "Survival analysis was evaluated using Kaplan–Meier analysis with the log-rank test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33816496", "locator": "sections[10] \"Statistical Analysis\" paragraph 2", "quote": "Survival analysis was evaluated using Kaplan–Meier analysis with the log-rank test."}], "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/s.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33816496", "locator": "sections[17] \"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/s."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:33816496"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE20685"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE20685"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33816496", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fcell.2021.646774", "sha256": 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