Identification of Immune-Related Genes and Small-Molecule Drugs in Interstitial Cystitis/Bladder Pain Syndrome Based on the Integrative Machine Learning Algorithms and Molecular Docking.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36619718", "kind": "science-record", "revision": 4, "content_hash": "sha256:7b23f04ee4bee7197c682066a33d42ab5a3f9a2ff5bb2356c31d128c68ddbee1", "created_at": "2026-11-01T19:01:10Z", "updated_at": "2026-11-01T22:51:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Immune-Related Genes and Small-Molecule Drugs in Interstitial Cystitis/Bladder Pain Syndrome Based on the Integrative Machine Learning Algorithms and Molecular Docking.", "doi": "10.1155/2022/2069756", "pmid": "36619718", "authors": ["Yiheng Jiang", "Xinqing Zhu", "Abdullah Y Al-Danakh", "Qiwei Chen", "Deyong Yang"], "journal": "Journal of immunology research", "year": 2022, "abstract": "Background: Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic, severely distressing clinical syndrome characterized by bladder pain and pressure perceptions. The origin and pathophysiology of IC/BPS are currently unclear, making it difficult to diagnose and formulate successful treatments. Our study is aimed at investigating the role of immune-related genes in the diagnosis, progression, and therapy of IC/BPS.\nMethod: The gene expression datasets GSE11783, GSE11839, GSE28242, and GSE57560 were retrieved from the GEO database for further analysis. Immune-related IC/BPS differentially expressed genes (DEGs) were identified by limma. Three distinct machine learning approaches, least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF), were used to find the immune-related IC characteristic genes. Nomogram and receiving operator curves (ROC) were plotted to measure characteristic effectiveness. Using the CMap database and the molecular docking approach, potential small-molecule medicines were found and verified. Consensus cluster analysis was also performed to separate the IC/BPS samples into immunological subtypes.\nResults: A total of 24 immune-related IC/BPS-DEGs were identified. When compared to the normal control group, the IC/BPS cohort had significantly more immune cell infiltration. Integrative machine learning methods discovered 5 IC/BPS characteristic genes (RASGRP1, PPBP, RBP4, CR2, and PROS2) that may predict IC/BPS diagnosis and immune cell infiltration. Furthermore, two immunological subgroups with substantial variations in immune cell infiltration across IC/BPS samples were identified, which were named cluster1 and cluster2, with the hallmark genes having greater expression in cluster2. Finally, bumetanide was shown to have the potential to be a medication for the treatment of IC/BPS, and it performed well in terms of its molecular binding with RASGRP1.\nConclusion: We found and validated 5 immune-related IC/BPS genes (RASGRP1, PPBP, RBP4, CR2, and PROS2) and 2 IC/BPS immune subtypes. In addition, bumetanide was discovered to be a potential drug for treating IC/BPS, which may provide new insight into the diagnosis and immune therapy of IC/BPS patients.", "claims": [{"id": "claim-method", "statement": "Firstly, to identify IC/BPS differentially expressed genes (DEGs), a differential analysis was performed between 37 IC/BPS samples and 20 normal control samples using the R package limma (the cutoff score was set asp < 0.05 and absolute (log 2 FC) > 1.0) and was conducted to select IC/BPS differentially expressed genes (DEGs).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36619718", "locator": "sections[4] \"2.2. Analysis of Immune-Related IC/BPS-DEGs\" paragraph 2", "quote": "Firstly, to identify IC/BPS differentially expressed genes (DEGs), a differential analysis was performed between 37 IC/BPS samples and 20 normal control samples using the R package limma (the cutoff score was set asp < 0.05 and absolute (log 2 FC) > 1.0) and was conducted to select IC/BPS differentially expressed genes (DEGs)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original data presented in this study can be found in online repositories. Contact the corresponding authors for further inquiries.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36619718", "locator": "sections[21] \"Data Availability\" paragraph 2", "quote": "The original data presented in this study can be found in online repositories. Contact the corresponding authors for further inquiries."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We found and validated 5 immune-related IC/BPS genes (RASGRP1, PPBP, RBP4, CR2, and PROS2) and 2 IC/BPS immune subtypes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36619718", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "We found and validated 5 immune-related IC/BPS genes (RASGRP1, PPBP, RBP4, CR2, and PROS2) and 2 IC/BPS immune subtypes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We found and validated 5 immune-related IC/BPS genes (RASGRP1, PPBP, RBP4, CR2, and PROS2) and 2 IC/BPS immune subtypes.", "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:36619718"], "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:GSE11783"], "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:GSE11783"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36619718", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/2069756", "sha256": "sha256:120f4c7e6253372575917d6ac43e55dfdf8974ab1e1d7bb5d28de2ecead836af", "bytes": 46262, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2022/2069756", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9812613", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE11783", "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=GSE11783", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE11783", "version": null, "note": "The original data presented in this study can be found in online repositories. Contact the corresponding authors for further inquiries.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original data presented in this study can be found in online repositories. 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Contact the corresponding authors for further inquiries.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original data presented in this study can be found in online repositories. Contact the corresponding authors for further inquiries.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM299095", "GSM299096", "GSM299097", "GSM299098", "GSM299099", "GSM299100", "GSM299101", "GSM299102", "GSM299103", "GSM299104", "GSM299105", "GSM299106"], "sample_count": 12, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Differentiation associated changes in gene expression profiles for interstitial cystitis and control urothelial cells", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE28242", "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=GSE28242", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE28242", "version": null, "note": "The original data presented in this study can be found in online repositories. Contact the corresponding authors for further inquiries.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original data presented in this study can be found in online repositories. 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