Integrative Analysis of Shared Pathogenic Genes and Potential Mechanisms in Gardnerella vaginalis and Persistent HPV16 Infection.

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This study integrated transcriptomic data from in vitro GV infection experiments and a GEO dataset (GSE75132) of HPV16 persistence to elucidate shared pathogenic mechanisms. Differential expression analysis identified 4115 genes modulated by GV infection and 861 by HPV16 persistence, with 74 common differentially expressed genes (DEGs) displaying consistent trends. Enrichment analyses revealed that these DEGs participate in metabolic pathways, immune defense, host-pathogen interactions, and carcinogenesis. Protein-protein interaction networks and Random Forest (RF) feature selection pinpointed radical S-adenosyl methionine domain containing 2 (RSAD2) and Interferon-induced protein with tetratricopeptide repeats 1 (IFIT1) as central hub genes. Upstream transcription analysis identified the homer_AGTTTCAGTTTC_ISRE motif and established a ceRNA network involving hsa-miR-654-5p, IFIT1/RSAD2, and lncRNAs. Mendelian randomization (MR) and colocalization analyses linked RSAD2 downregulation to an increased risk of cervical carcinoma in situ (rs2595163, PPH4 = 0.62), while ROC analysis demonstrated strong diagnostic potential for the combined hub gene expression. Notably, single-cell transcriptomics revealed distinct RSAD2 and IFIT1 expression patterns in immune and epithelial cells during the progression from HPV infection to cervical cancer. Collectively, these findings support RSAD2 and IFIT1 as promising biomarkers and therapeutic targets for HPV-related cervical lesions.", "claims": [{"id": "claim-method", "statement": "The diagnostic performance of these hub genes was evaluated by constructing receiver operating characteristic (ROC) curves with the “ROCR” package, with an aAUC > 0.7 considered satisfactory. Furthermore, a multi-gene diagnostic model incorporating RSAD2 and IFIT1 was developed using logistic regression.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40510586", "locator": "sections[13] \"2.11. Expression Analysis and Diagnostic Evaluation of Hub Genes\" paragraph 2", "quote": "The diagnostic performance of these hub genes was evaluated by constructing receiver operating characteristic (ROC) curves with the “ROCR” package, with an aAUC > 0.7 considered satisfactory. Furthermore, a multi-gene diagnostic model incorporating RSAD2 and IFIT1 was developed using logistic regression."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Part of the data utilized in this study is accessible on public data platforms (see Supporting Information 1: Table S5 and Table 1 for details). 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The RNA sequencing data regarding GV infection reported in this paper are openly available in the Sequence Read Archive (SRA) at https://dataview.ncbi.nlm.nih.gov/object/PRJNA1217577, reference number PRJNA1217577."}], "state": "complete"}, {"id": "claim-target-result", "statement": "ROC analysis demonstrated that the multi-biomarker diagnostic model achieved an AUC of 0.70 in dataset GSE75132, 1.00 in the RNA-Seq dataset for GV infection, 1.00 in GSE137964, and 1.00 in GSE234836.", "kind": "quantitative", "target": {"value": 0.7, "unit": "auc", "tolerance": null, "source": "ROC analysis demonstrated that this model achieved an AUC of 0.70 in dataset GSE75132, 1.00 in the RNA-Seq dataset for GV infection, 1.00 in GSE137964, and 1.00 in GSE234836 (Figure 6e–h)."}, "evidence": [{"asset": "source:pmid:40510586", "locator": "sections[25] \"3.6. Diagnostic Potential of Hub Genes in HPV16 and GV Infections\" paragraph 2", "quote": "ROC analysis demonstrated that this model achieved an AUC of 0.70 in dataset GSE75132, 1.00 in the RNA-Seq dataset for GV infection, 1.00 in GSE137964, and 1.00 in GSE234836 (Figure 6e–h)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "ROC analysis demonstrated that the multi-biomarker diagnostic model achieved an AUC of 0.70 in dataset GSE75132, 1.00 in the RNA-Seq dataset for GV infection, 1.00 in GSE137964, and 1.00 in GSE234836.", "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:40510586"], "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. 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This study integrated transcriptomic data from in vitro GV infection experiments", "ed hub gene expression. Notably, single-cell transcriptomics revealed distinct RSAD2 and IFIT1 expression", "nificance set at p < 0.05. 2.14. Single-Cell RNA Sequencing Analysis of Hub Gene Expression This study d"], "order_basis": "paper_text_order:289", "id": "assay:1"}, {"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["r the combined hub gene expression. Notably, single-cell transcriptomics revealed distinct RSAD2 and IFIT1 expression", "tistical significance set at p < 0.05. 2.14. 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