Elevated Hexose-6-Phosphate Dehydrogenase Regulated by OSMR-AS1/hsa-miR-516b-5p Axis Correlates with Poor Prognosis and Dendritic Cells Infiltration of Glioblastoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36009075", "kind": "science-record", "revision": 4, "content_hash": "sha256:143e447603e29af424f5a4402ebac0a8416d1d83d31d58368eb322b0caa36779", "created_at": "2026-11-01T18:15:10Z", "updated_at": "2026-11-01T22:49:52Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Elevated Hexose-6-Phosphate Dehydrogenase Regulated by OSMR-AS1/hsa-miR-516b-5p Axis Correlates with Poor Prognosis and Dendritic Cells Infiltration of Glioblastoma.", "doi": "10.3390/brainsci12081012", "pmid": "36009075", "authors": ["Yi-Bin Zhang", "Shu-Fa Zheng", "Lin-Jie Ma", "Peng Lin", "Huang-Cheng Shang-Guan", "Yuan-Xiang Lin", "De-Zhi Kang", "Pei-Sen Yao"], "journal": "Brain sciences", "year": 2022, "abstract": "Objective Glioblastoma (GBM), a type of malignant glioma, is the most aggressive type of brain tumor and is associated with high mortality. Hexose-6-phosphate dehydrogenase (H6PD) has been detected in multiple tumors and is involved in tumor initiation and progression. However, the specific role and mechanism of H6PD in GBM remain unclear. Methods We performed pan-cancer analysis of expression and prognosis of H6PD in GBM using the Genotype-Tissue Expression Project (GTEx) and The Cancer Genome Atlas (TCGA). Subsequently, noncoding RNAs regulating H6PD expression were obtained by comprehensive analysis, including gene expression, prognosis, correlation, and immune infiltration. Finally, tumor immune infiltrates related to H6PD and survival were performed. Results Higher expression of H6PD was statistically significantly associated with an unfavorable outcome in GBM. Downregulation of hsa-miR-124-3p and hsa-miR-516b-5p in GBM was detected from GSE90603. Subsequently, OSMR-AS1 was observed in the regulation of H6PD via hsa-miR-516b-5p. Moreover, higher H6PD expression significantly correlated with immune infiltration of dendritic cells, immune checkpoint expression, and biomarkers of dendritic cells. Conclusions The OSMR-AS1/ miR-516b-5p axis was identified as the highest-potential upstream ncRNA-related pathway of H6PD in GBM. Furthermore, the present findings demonstrated that H6PD blockading might possess antitumor roles via regulating dendritic cell infiltration and immune checkpoint expression.", "claims": [{"id": "claim-method", "statement": "We also analyzed weighted Pearson correlations and p-values using the R package “weights” (https://CRAN.R-project.org/package=weights); p-values less than 0.05 were considered statistically significant.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36009075", "locator": "sections[3] \"2.1. TCGA Data Download, Process, and Analysis\" paragraph 2", "quote": "We also analyzed weighted Pearson correlations and p-values using the R package “weights” (https://CRAN.R-project.org/package=weights); p-values less than 0.05 were considered statistically significant."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed in this study are available in the following open access repositories. TGGA: The Cancer Genome Atlas (TCGA) database (https://tcga-data.nci.nih.gov/tcga/ (accessed on 19 April 2022)). GEPIA: http://gepia.cancer-pku.cn/detail.php (accessed on 19 April 2022). ENCORI: http://starbase.sysu.edu.cn (accessed on 19 April 2022). miRNet2.0: www.mirnet.ca/miRNet/home.xhtml (accessed on 19 April 2022). The UCSC Xena database: http://xena.ucsc.edu/ (accessed on 19 April 2022). TIMER: https://cistrome.shinyapps.io/timer/ (accessed on 19 April 2022).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36009075", "locator": "sections[24] \"Data Availability Statement\" paragraph 2", "quote": "The datasets analyzed in this study are available in the following open access repositories. TGGA: The Cancer Genome Atlas (TCGA) database (https://tcga-data.nci.nih.gov/tcga/ (accessed on 19 April 2022)). GEPIA: http://gepia.cancer-pku.cn/detail.php (accessed on 19 April 2022). ENCORI: http://starbase.sysu.edu.cn (accessed on 19 April 2022). miRNet2.0: www.mirnet.ca/miRNet/home.xhtml (accessed on 19 April 2022). The UCSC Xena database: http://xena.ucsc.edu/ (accessed on 19 April 2022). TIMER: https://cistrome.shinyapps.io/timer/ (accessed on 19 April 2022)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "", "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:36009075"], "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:GSE90603"], "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:GSE90603"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36009075", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3390/brainsci12081012", "sha256": "sha256:6ebae657030495f59532e354326a9f8337cb6e618ff14b692b151d145c835afb", "bytes": 35844, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3390/brainsci12081012", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9405636", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE90603", "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=GSE90603", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE90603", "version": null, "note": "The datasets analyzed in this study are available in the following open access repositories. 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The UCSC Xena database: http://xena.ucsc.edu/ (accessed on 19 April 2022). 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