Secretory High-Mobility Group Box 1 Protein Affects Regulatory T Cell Differentiation in Neuroblastoma Microenvironment In Vitro.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30643519", "kind": "science-record", "revision": 6, "content_hash": "sha256:b3314b00d69249d6c423817494e54c49a63de75f0300c502a6a7b38eded07466", "created_at": "2026-11-01T15:40:40Z", "updated_at": "2026-11-01T21:21:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Secretory High-Mobility Group Box 1 Protein Affects Regulatory T Cell Differentiation in Neuroblastoma Microenvironment In Vitro.", "doi": "10.1155/2018/7946021", "pmid": "30643519", "authors": ["Thitinee Vanichapol", "Wararat Chiangjong", "Jirawan Panachan", "Usanarat Anurathapan", "Somchai Chutipongtanate", "Suradej Hongeng"], "journal": "Journal of oncology", "year": 2018, "abstract": "Neuroblastoma (NB) is the most common extracranial tumor of childhood with poor prognosis in a high-risk group. An obstacle in the development of treatment for solid tumors is the immunosuppressive nature of the tumor microenvironment (TME). Regulatory T cells (Tregs) represent a T cell subset with specialized function in immune suppression and maintaining self-tolerance. Tregs resident within the tumor milieu is believed to play an important role in immune escape mechanisms. The role of the NB microenvironment in promoting Treg phenotype has never been elucidated. Herein, we demonstrated that the NB microenvironment promoted T cell activation and one NB cell line, SK-N-SH, manifested an ability to induce Treg differentiation. We identified tumor-derived HMGB1 as a potential protein responsible for Treg phenotype induction. By neutralizing HMGB1, Treg differentiation was abolished. Finally, we adopted a dataset of 498 pediatric NB via the NCBI GEO database, accession GSE49711, to validate clinical relevance of HMGB1 overexpression. Up to 11% of patients had HMGB1-overexpressed tumors. Moreover, this patient subpopulation showed higher risks of tumor progression, relapse, or death. Our findings emphasize the importance of immunological signature of tumor cells for appropriate therapeutic approach. Upregulation of secretory HMGB1 may contribute to suppression of antitumor immunity through induction of Tregs in the NB microenvironment.", "claims": [{"id": "claim-method", "statement": "Associations between HMGB1 mRNA alterations and clinical outcomes (i.e., the occurrence of events and death) were determined by logistic regression and presented as the adjusted odds ratio (OR) with 95% confidence interval (CI) using R package “epiDisplay” (available via http://www.cran.r-project.org).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30643519", "locator": "sections[11] \"2.9. Statistical and Data Analysis\" paragraph 3", "quote": "Associations between HMGB1 mRNA alterations and clinical outcomes (i.e., the occurrence of events and death) were determined by logistic regression and presented as the adjusted odds ratio (OR) with 95% confidence interval (CI) using R package “epiDisplay” (available via http://www.cran.r-project.org)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The proteomic data and bioinformatic results used to support the findings of this study were included within the Supplementary Information. Clinical and RNA-seq datasets are accessible at the NCBI GEO database [28], accession GSE49711 [29].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30643519", "locator": "sections[21] \"Data Availability\" paragraph 2", "quote": "The proteomic data and bioinformatic results used to support the findings of this study were included within the Supplementary Information. Clinical and RNA-seq datasets are accessible at the NCBI GEO database [28], accession GSE49711 [29]."}], "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:30643519"], "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:GSE49711"], "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:GSE49711"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:30643519", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2018/7946021", "sha256": "sha256:73bff65e0d478cf02cc26c60982395dc3a1e505212e36433622e503c9712a5df", "bytes": 34852, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2018/7946021", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6311239", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE49711", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49711", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE49711", "version": null, "note": "The proteomic data and bioinformatic results used to support the findings of this study were included within the Supplementary Information. Clinical and RNA-seq datasets are accessible at the NCBI GEO database [28], accession GSE49711 [29].", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The proteomic data and bioinformatic results used to support the findings of this study were included within the Supplementary Information. 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"data_shapes": ["predictors_and_outcome"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Associations between HMGB1 mRNA alterations and clinical outcomes (i.e., the occurrence of events and death) were determined by logistic regression and presented as the adjusted odds ratio (OR) with 95% confidence interval (CI) using R package “epiDisplay” (available via http://www.cran.r-project.org)."}}], "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": ["glm_logit_fit"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: logistic."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE49711"], "resolved_accessions": ["GSE49711"], "statements": ["The proteomic data and bioinformatic results used to support the findings of this study were included within the Supplementary Information. Clinical and RNA-seq datasets are accessible at the NCBI GEO database [28], accession GSE49711 [29]."], "basis": "The paper names GSE49711 in NCBI Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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PBMCs were then cultured in RPMI 1640 medium with 10% fetal bovine serum", "SH (ATCC HTB-1), SK-N-AS (ATCC CRL-213), and SH-SY5Y (ATCC CRL-226), were purchased from the Amer", "oma cells with different genetic background. SH-SY5Y cells are a subline of the parental line SK-", "by proteomic analysis. We chose SK-N-AS over SH-SY5Y (a subline of SK-N-SH) since this cell line"], "order_basis": "paper_text_order:1667", "id": "assay:1"}, {"role": "data_generation", "definition_id": "flow_cytometry", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["pension cells were collected and analyzed by flow cytometry. NB cells, which were adherent cells, remain"], "order_basis": "paper_text_order:3100", "id": "assay:2"}, {"role": "data_generation", "definition_id": "mass_spectrometry", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["tween groups (Figure 2) and were analyzed by LC-MS/MS for 29 unique protein identities (Table 1 an", "s of SK-N-SH versus SK-N-AS was performed by proteomic analysis. We chose SK-N-AS over SH-SY5Y (a s"], "order_basis": "paper_text_order:3606", "id": "assay:3"}, {"role": "analysis", "definition_id": "regression_modelling", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["glm_logit_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Associations between HMGB1 mRNA alterations and clinical outcomes (i.e., the occurrence of events and death) were determined by logistic regression and presented as the adjusted odds ratio (OR) with 95% confidence interval (CI) using R package “epiDisplay” (available via http://www.cran.r-project.org)."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}