Low Expression of ADCY4 Predicts Worse Survival of Lung Squamous Cell Carcinoma Based on Integrated Analysis and Immunohistochemical Verification.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34178627", "kind": "science-record", "revision": 7, "content_hash": "sha256:eb4d565f6fd5ab4f3a2c990d8deae13b5e6496230bb1964533ce9eeddd689282", "created_at": "2026-11-01T15:41:40Z", "updated_at": "2026-11-01T22:04:02Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Low Expression of ADCY4 Predicts Worse Survival of Lung Squamous Cell Carcinoma Based on Integrated Analysis and Immunohistochemical Verification.", "doi": "10.3389/fonc.2021.637733", "pmid": "34178627", "authors": ["Zhicong Liu", "Lixin Ru", "Zhenchao Ma"], "journal": "Frontiers in oncology", "year": 2021, "abstract": "PURPOSE: The molecular mechanism underlying the carcinogenesis and development of lung squamous cell carcinoma (LUSC) has not been sufficiently elucidated. This analysis was performed to find pivotal genes and explore their prognostic roles in LUSC.\nMETHODS: A microarray dataset from GEO (GSE19188) and a TCGA-LUSC dataset were used to identify differentially co-expressed genes through Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. We conducted functional enrichment analyses of differentially co-expressed genes and established a protein-protein interaction (PPI) network. Then, we identified the top 10 hub genes using the Maximal Clique Centrality (MCC) algorithm. We performed overall survival (OS) analysis of these hub genes among LUSC cases. GSEA analyses of survival-related hub genes were conducted. Ultimately, the GEO and The Human Protein Atlas (THPA) databases and immunohistochemistry (IHC) results from the real world were used to verify our findings.\nRESULTS: A list of 576 differentially co-expressed genes were selected. Functional enrichment analysis indicated that regulation of vasculature development, cell-cell junctions, actin binding and PPAR signaling pathways were mainly enriched. The top 10 hub genes were selected according to the ranking of MCC scores, and 5 genes were closely correlated with OS of LUSC. Additionally, GSEA analysis showed that spliceosome and cell adhesion molecules were associated with the expression of GNG11 and ADCY4, respectively. The GSE30219 and THPA databases and IHC results from the real world indicated that although GNG11 was not detected, ADCY4 was obviously downregulated in LUSC tissues at the mRNA and protein levels.\nCONCLUSIONS: This analysis showed that survival-related hub genes are highly correlated to the tumorigenesis and development of LUSC. Additionally, ADCY4 is a candidate therapeutic and prognostic biomarker of LUSC.", "claims": [{"id": "claim-method", "statement": "To explore the prognostic roles of the top ten hub genes, we conducted Kaplan–Meier univariate survival analysis through the survival package based on the TCGA-LUSC dataset.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34178627", "locator": "sections[8] \"Overall Survival of Hub Genes\" paragraph 2", "quote": "To explore the prognostic roles of the top ten hub genes, we conducted Kaplan–Meier univariate survival analysis through the survival package based on the TCGA-LUSC dataset."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34178627", "locator": "sections[22] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:34178627"], "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:GSE19188"], "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:GSE19188"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34178627", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2021.637733", "sha256": "sha256:e485ad0fd4d5bc44146094a059af3f818dc8992ddb62a26a1ab669e65de0e5fc", "bytes": 39531, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2021.637733", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8225293", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE19188", "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=GSE19188", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE19188", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . 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{"label": "Table 2", "caption": "The detailed information of IHC results from THPA database.", "rows": [["Gene", "Normal lung tissues", "LUSC tissues"], ["", "Macrophages", "Pneumocytes", "Tumor cells"], ["", "Staining", "Intensity", "Quantity", "Location", "Staining", "Intensity", "Quantity", "Location", "Staining", "Intensity", "Quantity", "Location"], ["ADCY4", "Medium", "Moderate", "75%-25%", "Cytoplasmic/membranous", "Medium", "Moderate", "75%-25%", "Cytoplasmic/membranous", "Low", "Moderate", "<25%", "Cytoplasmic/membranous"], ["GNG11", "Not detected", "Negative", "None", "None", "Not detected", "Negative", "None", "None", "Not detected", "Negative", "None", "None"], ["FSTL3", "Low", "Moderate", "<25%", "Nuclear", "Low", "Weak", "75%-25%", "Nuclear", "Low", "Weak", "75%-25%", "Nuclear"], ["GAS6", "Low", "Weak", ">75%", "Cytoplasmic/membranous", "Not detected", "Negative", "None", "None", "Not detected", "Negative", "None", "None"], ["CHRDL1", "Medium", "Moderate", "75%-25%", "Cytoplasmic/membranous", "Low", "Weak", "75%-25%", "Cytoplasmic/membranous", "Not detected", "Negative", "None", "None"]], "row_count": 8, "column_count": 13, "numeric_cells": 10, "header_rows": 3, "locator": "section[19]/table-wrap[1]#T2"}}], "gaps": ["asset:data:geo:GSE19188 not downloaded", "asset:data:geo:GSE19188 licence not read", "asset:data:geo:GSE30219 not downloaded", "asset:data:geo:GSE30219 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "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": 1.0, "band": "verbatim", "quote": "To explore the prognostic roles of the top ten hub genes, we conducted Kaplan–Meier univariate survival analysis through the survival package based on the TCGA-LUSC dataset."}}, {"id": "method-2", "family": 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