Systematic pan-cancer analysis identifies cGAS as an immunological and prognostic biomarker.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36819495", "kind": "science-record", "revision": 2, "content_hash": "sha256:b0bf3eb3fa41ab214d1e74d6fe5e9887301776dffa3c5ae207fc8b71b2ec2f37", "created_at": "2026-11-01T19:01:25Z", "updated_at": "2026-11-01T21:30:11Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Systematic pan-cancer analysis identifies cGAS as an immunological and prognostic biomarker.", "doi": "10.21037/atm-22-6318", "pmid": "36819495", "authors": ["Peng Chen", "Xian Yang", "Peiyuan Wang", "Hao He", "Yujie Chen", "Lingfeng Yu", "Huipeng Fang", "Feng Wang", "Zhijian Huang"], "journal": "Annals of translational medicine", "year": 2023, "abstract": "Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus causes novel coronavirus disease 2019 (COVID-19), which is characterized by pneumonia, cytokine storms, and lymphopenia. Due to immunosuppression, cancer patients may be more susceptible to SARS-CoV-2 and have more serious complications. According to recent research, cyclic GMP-AMP synthase (cGAS) could be a potential SARS-CoV-2 sensor. However, at present, no studies have been conducted on cGAS gene alterations in pan-cancer. This study aimed to discover therapeutic implications for COVID-19-infected tumor patients by performing a comprehensive analysis of cGAS in malignant tumors.\nMethods: cGAS expression matrices were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) databases, which were used to evaluate cGAS expression in various tumors, its prognostic value, and its relationship to the immune microenvironment, microsatellite instability (MSI), immune neoantigens, gene mutations, immune checkpoints, MSI, tumor mutational burden (TMB), mismatch repair (MMR) genes, and DNA methyltransferases (DNMT). We also used the cBioPortal, Human Protein Atlas (HPA), and GeneMANIA databases to explore the types of changes, gene networks and immunofluorescence localization, and protein expression of these genes.\nResults: Compared to normal tissues, cGAS was highly expressed in 13 types of cancer (e.g., lung cancer) and lowly expressed in other cancers (e.g., pancreatic cancer). cGAS expression was associated with prognosis in nine cancers, such as renal clear cell carcinoma (P<0.05). Furthermore, deep deletion was the most common type of cGAS genomic mutation. DNMT, immune infiltration levels, TMB, MSI, MMR genes, neoantigens, and immune checkpoints were all correlated with cGAS expression. Moreover, we used the GSE30589 dataset to investigate the post-SARS-CoV infection changes in cGAS expression in vitro. Finally, mithramycin, MI219, AFP464, aminoflavone, kahalide F, AT13387, doxorubicin, and other drugs increased the sensitivity of cGAS expression. According to the evidence presented above, cGAS may become an important target for cancer therapy.\nConclusions: This study discovered that SARS-CoV-2-infected cancer patients might experience changes in their tumor environment as a result of cGAS, making patients with tumors expressing high cGAS more susceptible to COVID-19 and possibly a worsening prognosis. Furthermore, cGAS may be a novel biomarker for diagnosing and treating COVID-19-infected tumor patients.", "claims": [{"id": "claim-data-access", "statement": "The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) and Genotype-Tissue Expression (GTEx) database (https://gtexportal.org/) databases were used to obtain the gene expression matrix and clinical data for both normal and tumor samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36819495", "locator": "sections[4] \"cGAS sample information and pan-cancer expression analysis\" paragraph 2", "quote": "The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) and Genotype-Tissue Expression (GTEx) database (https://gtexportal.org/) databases were used to obtain the gene expression matrix and clinical data for both normal and tumor samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Compared to normal tissues, cGAS was highly expressed in 13 types of cancer (e.g., lung cancer) and lowly expressed in other cancers (e.g., pancreatic cancer).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36819495", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Compared to normal tissues, cGAS was highly expressed in 13 types of cancer (e.g., lung cancer) and lowly expressed in other cancers (e.g., pancreatic cancer)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Compared to normal tissues, cGAS was highly expressed in 13 types of cancer (e.g., lung cancer) and lowly expressed in other cancers (e.g., pancreatic cancer).", "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:36819495"], "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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Homo sapiens", "title": "Severe acute respiratory syndrome coronavirus envelope protein regulates cell stress responses and apoptosis", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE30589 not downloaded", "asset:data:geo:GSE30589 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Kaplan-Meier"}}, {"id": "method-2", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Cox regression"}}, {"id": "method-3", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {"hazard_ratio": "values, hazard ratios (HRs), and 95% confidence i"}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["survival_km"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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