In silico analysis reveals EP300 as a panCancer inhibitor of anti-tumor immune response via metabolic modulation.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32523042", "kind": "science-record", "revision": 7, "content_hash": "sha256:51eed218241e6318b24c31e760c50abebf2dc791d95c888ae16dcbf7e5bf7c04", "created_at": "2026-11-01T15:41:03Z", "updated_at": "2026-11-01T22:01:44Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "In silico analysis reveals EP300 as a panCancer inhibitor of anti-tumor immune response via metabolic modulation.", "doi": "10.1038/s41598-020-66329-7", "pmid": "32523042", "authors": ["Rosemarie Krupar", "Christian Watermann", "Christian Idel", "Julika Ribbat-Idel", "Anne Offermann", "Helen Pasternack", "Jutta Kirfel", "Andrew G Sikora", "Sven Perner"], "journal": "Scientific reports", "year": 2020, "abstract": "The tumor immune microenvironment (TIME) of head and neck squamous cell carcinomas (HNSCC) and other solid malignancies is a key determinant of therapy response and prognosis. Among other factors, it is shaped by the tumor mutational burden and defects in DNA repair enzymes. Based on the TCGA database we aimed to define specific, altered genes associated with different TIME types, which might represent new predictive markers or targets for immuno-therapeutic approaches. The HNSCC cohort of the TCGA database was used to define 3 TIME types (immune-activated, immune-suppressed, immune-absent) according to expression of immune-related genes. Mutation frequencies were correlated to the 3 TIME types. Overall survival was best in the immune-activated group. 9 genes were significantly differentially mutated in the 3 TIME types with strongest differences for TP53 and the histone-acetyltransferase EP300. Mutations in EP300 correlated with an immune-activated TIME. In panCancer analyses anti-tumor immune activity was increased in EP300 mutated esophageal, stomach and prostate cancers. Downregulation of EP300 gene expression was associated with higher anti-tumor immunity in most solid malignancies. Since EP300 is a promoter of glycolysis, which negatively affects anti-tumor immune response, we analyzed the association of EP300 with tumor metabolism. PanCancer tumor metabolism was strongly shifted towards oxidative phosphorylation in EP300 downregulated tumors. In silico analyses of of publicly available in vitro data showed a decrease of glycolysis-associated genes after treatment with the EP300 inhibitor C646. Our study reveals associations of specific gene alterations with different TIME types. In detail, we defined EP300 as a panCancer inhibitor of the TIME most likely via metabolic modulation. In this context EP300 represents a promising predictive biomarker and an immuno-therapeutic target.", "claims": [{"id": "claim-method", "statement": "Fisher’s exact test was applied to compare gene mutation frequencies between different TIME groups.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32523042", "locator": "sections[8] \"Statistical analysis\" paragraph 2", "quote": "Fisher’s exact test was applied to compare gene mutation frequencies between different TIME groups."}], "state": "complete"}, {"id": "claim-data-access", "statement": "TCGA data bank analysis was performed on the cBioPortal for Cancer Genomics website (http://www.cbioportal.org) with access to clinical data, gene mutations and gene expression levels. 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the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7287052", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "asset:table:pmid:32523042:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:3820b84b0eafe07d8308407667df4a1a3b79284770b525fb4a3aada5970f9fb9", "bytes": 1704, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#Tab1", "version": null, "note": "Patient and tumor characteristics of the complete TCGA HNSCC cohort and the three different TIME subtypes (signifcant differences compared to underlined values are marked with bold type).", "structure": {"pmcid": "PMC7287052", "section_index": 11, "section_title": "Tumor immune microenvironment subtypes in head and neck squamous cell carcinomas are associated with specific gene mutations", "row_count": 24, "column_count": 6}, "table": {"label": "Table 1", "caption": "Patient and tumor characteristics of the complete TCGA HNSCC cohort and the three different TIME subtypes (signifcant differences compared to underlined values are marked with bold type).", "rows": [["", "TCGA HNSCC", "Immune activated", "Immune suppressed", "Immune absent", ""], ["Number", "530", "20 (4%)", "35 (7%)", "100 (19%)", "p < 0.0001"], ["Mean age (y)", "60.9", "58.55", "60.2", "61.5", "ns"], ["Male sex", "386 (73%)", "18 (90%)", "28 (80%)", "81 (81%)", "ns"], ["HPV positive", "77 (15%)", "9 (45%)", "5 (14%)", "6 (6%)", "p < 0.03"], ["Anatomical site"], ["Oropharynx", "82 (16%)", "12 (60%)", "4 (11%)", "8 (8%)", "p < 0.0001"], ["Oral cavity", "320 (60%)", "7 (35%)", "20 (57%)", "62 (62%)", "p < 0.05"], ["Hypopharynx", "10 (2%)", "0", "2 (5.7%)", "1 (1%)", "ns"], ["Larynx", "117 (22%)", "1 (5%)", "9 (26%)", "29 (29%)", "p < 0.03"], ["Stage"], ["I", "21 (4%)", "3 (15%)", "1 (3%)", "4 (4%)", "ns"], ["II", "99 (19%)", "2 (10%)", "2 (6%)", "20 (20%)", "p < 0.05"], ["III", "107 (21%)", "4 (20%)", "5 (16%)", "26 (26%)", "ns"], ["IV", "288 (56%)", "11 (55%)", "24 (75%)", "48 (48%)", "p < 0.05"], ["Differentiation"], ["G1", "64 (13%)", "0 (0%)", "2 (6%)", "9 (9%)", "ns"], ["G2", "311 (61%)", "9 (53%)", "21 (64%)", "63 (64%)", "ns"], ["G3", "125 (25%)", "7 (41%)", "10 (30%)", "25 (26%)", "ns"], ["G4", "7 (1%)", "1 (6%)", "0 (0%)", "1 (1%)", "ns"], ["Social history"], ["Smoking (pack years)", "46 (n = 299)", "27 (n = 9)", "50 (n = 18)", "48 (n = 61)", "p < 0.03"], ["Drinks/day", "3.2 (n = 222)", "2.8 (n = 8)", "3.8 (n = 11)", "3.6 (n = 45)", "ns"], ["Recurrence/Progression", "145 (36%, n = 398)", "3 (21%, n = 14)", "14 (47%, n = 30)", "32 (42%, n = 77)", "ns"]], "row_count": 24, "column_count": 6, "numeric_cells": 84, "header_rows": 1, "locator": "section[11]/table-wrap[1]#Tab1"}}], "gaps": []}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-2", "family": null, "specific": null, "label": "Fisher’s exact test", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Fisher’s exact test was applied to compare gene mutation frequencies between different TIME groups."}}], "targets": [], "gaps": ["method.reader_named_unmapped", "method.group_comparison_wilcoxon"]}, "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": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R1", "expressible": false, "required_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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