Identification and clinical validation of key genes as the potential biomarkers in colorectal adenoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36631756", "kind": "science-record", "revision": 4, "content_hash": "sha256:1237ff854044f549b53a212207d14eaa4532758d1e522d66535c503300986f49", "created_at": "2026-11-01T19:01:11Z", "updated_at": "2026-11-01T22:51:02Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and clinical validation of key genes as the potential biomarkers in colorectal adenoma.", "doi": "10.1186/s12885-022-10422-9", "pmid": "36631756", "authors": ["Bangting Wang", "Jiting Zhang", "Xin Wang", "Lili Zhao", "Yan Wang", "Zhining Fan", "Li Liu", "Wenqing Gao"], "journal": "BMC cancer", "year": 2023, "abstract": "BACKGROUND: Colorectal cancer (CRC), ranking third in cancer prevalence and second in mortality worldwide, is mainly derived from colorectal adenoma (CRA). CRA is a common benign disease in the intestine with rapidly increasing incidence and malignant potential. Therefore, this study aimed to recognize significant biomarkers and original pathogenesis in CRA.\nMETHODS: Transcriptome data of GSE8671, GSE37364, and GSE15960 were downloaded from the Gene Expression Omnibus (GEO) datasets, and differentially expressed genes (DEGs) were screened. Functional pathways enrichment, protein-protein interaction (PPI) network, stem-correlation analysis, CIBERSORT, risk score and survival analyses were performed. RT-qPCR and immunohistochemical staining were applied to verify our results. RESULTS: Screening for significant DEGs in each dataset, we identified 230 robust DEGs, including 127 upregulated and 103 downregulated genes. Functional pathways enrichment showed that these DEGs were distinctly enriched in various tumor-associated pathways, such as growth factor activity, extracellular structure organization, neutrophil activation, and inflammatory response. We filtered out two hub genes via STRING and Modules analysis, including CA2 and HSD11B2. Stem-correlation analysis displayed that hub genes were negatively associated with stem-related genes (Olfm4, CD44, CCND1 and MYC). The CIBERSORT algorithm indicated that Macrophage2, activated mast cells, and Neutrophils promoted CRA progression through inflammation. Survival analysis showed that CA2 and HSD11B2 were positively associated with survival outcomes in CRC.\nCONCLUSION: Our study has successfully identified the critical role of two core genes in the development and oncogenesis of CRA, which provides novel insight into the underlying pathogenesis, potential biomarkers and therapeutic targets.", "claims": [{"id": "claim-method", "statement": "The “edgedR” package was applied to identify DEGs in each GEO dataset (GSE8671, GSE15960, and GSE37364) in R (version 4.1.1). These genes satisfied |log2 fold-change (FC)|> 1.00, p-adjust < 0.05 and p-value < 0.05 were taken into consideration for further statistical analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36631756", "locator": "sections[4] \"Identification of DEGs from GEO datasets\" paragraph 2", "quote": "The “edgedR” package was applied to identify DEGs in each GEO dataset (GSE8671, GSE15960, and GSE37364) in R (version 4.1.1). These genes satisfied |log2 fold-change (FC)|> 1.00, p-adjust < 0.05 and p-value < 0.05 were taken into consideration for further statistical analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets support the findings of our study are available in GEO (Gene Expression Omnibus) repository, including https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8671, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15960, and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37364.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36631756", "locator": "sections[30] \"notes\" paragraph 1", "quote": "The datasets support the findings of our study are available in GEO (Gene Expression Omnibus) repository, including https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8671, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15960, and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37364."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Screening for significant DEGs in each dataset, we identified 230 robust DEGs, including 127 upregulated and 103 downregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36631756", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Screening for significant DEGs in each dataset, we identified 230 robust DEGs, including 127 upregulated and 103 downregulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Screening for significant DEGs in each dataset, we identified 230 robust DEGs, including 127 upregulated and 103 downregulated genes.", "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:36631756"], "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": "blocked", "blocked_on": "data:accession_absent", "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": [], "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": {"fold_change": "on analysis using |log2 fold-change| > 1"}, "inputs": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36631756", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12885-022-10422-9", "sha256": "sha256:892c05649efb55eb4f1d013c9f5a7ee193077fb44c16de9cb3f64ccf21c3a6d9", "bytes": 38920, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12885-022-10422-9", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9832797", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "edger", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {"fold_change": "on analysis using |log2 fold-change| > 1"}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The “edgedR” package was applied to identify DEGs in each GEO dataset (GSE8671, GSE15960, and GSE37364) in R (version 4.1.1). These genes satisfied |log2 fold-change (FC)|> 1.00, p-adjust < 0.05 and p-value < 0.05 were taken into consideration for further statistical analysis."}}, {"id": "method-2", "family": "group_comparison", "specific": "anova", "label": "Group comparison", "dsl_operations": ["group_summary", "welch_t", "bootstrap_mean_difference", "group_comparison_anova"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "analysis of variance"}}, {"id": "method-3", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "KM"}}, {"id": "method-4", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}, {"id": "method-5", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}, {"id": "method-6", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.8, "band": "high", "quote": "ROC analysis"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "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": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: edger."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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