Computational insights into CRISP3 downregulation in cervical cancer and its cervical lineages pattern.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39139989", "kind": "science-record", "revision": 4, "content_hash": "sha256:ac1b8140ac8cd694fb384c75f52887079418daf6edda636a35049273bdf37bdc", "created_at": "2026-11-01T20:29:14Z", "updated_at": "2026-11-01T22:54:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Computational insights into CRISP3 downregulation in cervical cancer and its cervical lineages pattern.", "doi": "10.1093/pcmedi/pbae016", "pmid": "39139989", "authors": ["Ricardo Cesar Cintra", "Andrés Galindo Céspedes", "Mércia Patrícia Ferreira Conceição", "Maiza Vitoria Aguiar Silva Oliveira", "Alessandro Buron", "Deisiane Rodrigues das Neves", "Fabio Alves Moraes", "Olinda Maria Gamarra", "Daniel Rodrigues de Bastos"], "journal": "Precision clinical medicine", "year": 2024, "abstract": "Background: Cysteine-rich secretory protein 3 (CRISP3) emerges as a potential biomarker in the study of many cancers, including cervical cancer (CC). This study aimed to analyze the expression pattern of CRISP3 in CC patients and CC cell lineages, following treatment with the epigenetic drugs: trichostatin A (TSA) and 5-aza-2'-deoxycytidine (5-aza).\nMethods: The differentially expressed genes identified in GSE63514 were used to construct a protein-protein interaction network. CRISP3 was selected for subsequent analyses. We utilized data from the TCGA and GENT2 projects to evaluate the expression profile and clinical behavior of CRISP3. Additionally, we conducted cell culture experiments to analyze the expression profile of CRISP3 in cells.\nResults: Low levels of CRISP3 were observed in squamous cell carcinoma (SCC) and human papillomavirus (HPV)16+, along with being associated with worse overall survival (OS). MIR-1229-3p was analyzed, and its high expression was associated with worse prognostic outcomes. In CC-derived cell lines, we observed low levels of CRISP3 in SiHa, followed by SW756, C33A, HeLa, and higher levels in CaSki. All cells were treated with TSA, 5-aza, or both. In all cell lines, treatment with TSA resulted in increased transcription of CRISP3.\nConclusion: We identified a significant downregulation of CRISP3 in CC, particularly in cases with HPV16 infection and SCC, which was associated with poorer OS. Preliminary findings suggest that epigenetic treatments with TSA and 5-aza may modulate CRISP3 expression, warranting further research to elucidate its regulatory mechanisms and potential as a prognostic biomarker.", "claims": [{"id": "claim-method", "statement": "Employing GEO2R (www.ncbi.nlm.nih.gov/geo/geo2r), we screened and isolated differentially expressed genes (DEGs) based on a significance threshold, where Benjamini–Hochberg < 0.05, and |logFC|≥1.5 (normal vs. tumor). The survival analysis utilized the Kaplan–Meier (KM) method and log-rank test, employing the same 'high' and 'low' stratification. For survival analysis, the curves were performed using the KM method with comparison using the log-rank test; in addition, Cox regression was performed, and the result was demonstrated as a hazard ratio (HR) with a 95% CI.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39139989", "locator": "sections[3] \"Selection of datasets and analysis of differential genes expression\" paragraph 2", "quote": "Employing GEO2R (www.ncbi.nlm.nih.gov/geo/geo2r), we screened and isolated differentially expressed genes (DEGs) based on a significance threshold, where Benjamini–Hochberg < 0.05, and |logFC|≥1.5 (normal vs. tumor)."}, {"asset": "source:pmid:39139989", "locator": "sections[5] \"TCGA and GENT2 data analysis\" paragraph 2", "quote": "The survival analysis utilized the Kaplan–Meier (KM) method and log-rank test, employing the same 'high' and 'low' stratification."}, {"asset": "source:pmid:39139989", "locator": "sections[9] \"Statistics\" paragraph 2", "quote": "For survival analysis, the curves were performed using the KM method with comparison using the log-rank test; in addition, Cox regression was performed, and the result was demonstrated as a hazard ratio (HR) with a 95% CI."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The gene expression datasets under analysis were sourced from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Specifically focusing on datasets associated with CC, an exhaustive search was conducted within the database, and after meticulous screening, we identified the microarray dataset GSE63514 [17].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39139989", "locator": "sections[3] \"Selection of datasets and analysis of differential genes expression\" paragraph 2", "quote": "The gene expression datasets under analysis were sourced from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Specifically focusing on datasets associated with CC, an exhaustive search was conducted within the database, and after meticulous screening, we identified the microarray dataset GSE63514 [17]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We identified a significant downregulation of CRISP3 in CC, particularly in cases with HPV16 infection and SCC, which was associated with poorer OS.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39139989", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "We identified a significant downregulation of CRISP3 in CC, particularly in cases with HPV16 infection and SCC, which was associated with poorer OS."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We identified a significant downregulation of CRISP3 in CC, particularly in cases with HPV16 infection and SCC, which was associated with poorer OS.", "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:39139989"], "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:GSE63514"], "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:GSE63514"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39139989", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1093/pcmedi/pbae016", "sha256": "sha256:f66f7c9dec81d368c21ee58b59d82c3065cb39b53b8860b4b43d6104e850c0e4", "bytes": 36366, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1093/pcmedi/pbae016", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11319933", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE63514", "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=GSE63514", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE63514", "version": null, "note": "The gene expression datasets under analysis were sourced from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Specifically focusing on datasets associated with CC, an exhaustive search was conducted within the database, and after meticulous screening, we identified the microarray dataset GSE63514 [17].", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The gene expression datasets under analysis were sourced from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). 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All cells were", "2™), and CaSki (HPV16; ATCC® CRL-1550™); all cell lines were cultured in Minimum Essential Medium (MEM) (GibcoTM,", "HPV16; ATCC® CRL-1550™); all cell lines were cultured in Minimum Essential Medium (MEM) (GibcoTM, Inv", "HTB-35™), SW756 (HPV18; ATCC® CRL-10302TM), HeLa (HPV18; ATCC® CCL-2™), and CaSki (HPV16; ATC"], "order_basis": "paper_text_order:1174", "id": "assay:1"}, {"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["fter meticulous screening, we identified the microarray dataset GSE63514 [17]. Employing GEO2R (www."], "order_basis": "paper_text_order:2102", "id": "assay:2"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Employing GEO2R (www.ncbi.nlm.nih.gov/geo/geo2r), we screened and isolated differentially expressed genes (DEGs) based on a significance threshold, where Benjamini–Hochberg < 0.05, and |logFC|≥1.5 (normal vs. tumor). The survival analysis utilized the Kaplan–Meier (KM) method and log-rank test, employing the same 'high' and 'low' stratification. For survival analysis, the curves were performed using the KM method with comparison using the log-rank test; in addition, Cox regression was performed, and the result was demonstrated as a hazard ratio (HR) with a 95% CI."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}