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pmid:38911338

Integrated Analysis Reveals COL4A3 as a Novel Diagnostic and Therapeutic Target in UV-Related Skin Cutaneous Melanoma.

Zuochao Yao · Lu Lu · Qianhui Xu · Shan Hua · Hui Wang · Hua Jiang

Clinical, cosmetic and investigational dermatology · 2024 doi:10.2147/CCID.S461959

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

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title
Integrated Analysis Reveals COL4A3 as a Novel Diagnostic and Therapeutic Target in UV-Related Skin Cutaneous Melanoma.
doi
10.2147/CCID.S461959
pmid
38911338
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[0]
Zuochao Yao
[1]
Lu Lu
[2]
Qianhui Xu
[3]
Shan Hua
[4]
Hui Wang
[5]
Hua Jiang
journal
Clinical, cosmetic and investigational dermatology
year
2024
abstract
Background: High levels of UV exposure are a significant factor that can trigger the onset and progression of SKCM. Moreover, this exposure is closely linked to the malignancy of the tumor and the prognosis of patients. Our objective is to identify a tumor biomarker database associated with UV exposure, which can be utilized for prognostic analysis and diagnosis and treatment of SKCM. Methods: This study used the weighted gene co-expression network analyses (WGCNA) and gene mutation frequency analyses to screen for UV-related target genes using the GSE59455 and the cancer genome atlas databases (TCGA). The prognostic model was created using Cox regression and least absolute shrinkage and selection operator analyses (LASSCO). Furthermore, in vitro experiments further validated that the overexpression or knockdown of COL4A3 could regulate the proliferation and migration abilities of SKMEL28 and A357 melanoma cells. Results: A prognostic model was created that included six genes with a high UV-related mutation in SKCM: COL4A3, CHRM2, DSC3, GIMAP5, LAMC2, and PSG7. The model had a strong patient survival correlation (P˂0.001, hazard ratio (HR) = 1.57) and significant predictor (P˂0.001, HR = 3.050). Furthermore, the model negatively correlated with immune cells, including CD8+ T cells (Cor=-0.408, P˂0.001), and M1-type macrophages (Cor=-0.385, P˂0.001), and immune checkpoints, including programmed cell death ligand-1. Moreover, we identified COL4A3 as a molecule with significant predictive functionality. Overexpression of COL4A3 significantly inhibited the proliferation, migration, and invasion abilities of SKMEL28 and A357 melanoma cells, while knockdown of COL4A3 yielded the opposite results. And overexpression of COL4A3 enhanced the inhibitory effects of imatinib on the proliferation, migration, and invasion abilities of SKMEL28 and A357 cells. Conclusion: The efficacy of the prognostic model was validated by analyzing the prognosis, immune infiltration, and immune checkpoint profiles. COL4A3 stands out as a novel diagnostic and therapeutic target for SKCM, offering new strategies for small-molecule targeted drug therapies.
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Multifactorial Cox regression and least absolute shrinkage and selection operator (LASSO)17 analysis was used to develop prognostic models.
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Multifactorial Cox regression and least absolute shrinkage and selection operator (LASSO)17 analysis was used to develop prognostic models.
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The following information was supplied regarding data availability: The dataset of TCGA-SKCM generated and/or analyzed during the current study are available at the TCGA database (https://cancergenome.nih.gov/). The datasets generated and/or analyzed during the current study are available at GEO: GSE59455. The core code of this study has been uploaded to GitHub: https://github.com/Lizhiyongjuan/Code.git. The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. We declared that materials described in the manuscript, including all relevant raw data, will be freely available to any scientist wishing to use them for non-commercial purposes.
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The following information was supplied regarding data availability: The dataset of TCGA-SKCM generated and/or analyzed during the current study are available at the TCGA database (https://cancergenome.nih.gov/). The datasets generated and/or analyzed during the current study are available at GEO: GSE59455. The core code of this study has been uploaded to GitHub: https://github.com/Lizhiyongjuan/Code.git. The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. We declared that materials described in the manuscript, including all relevant raw data, will be freely available to any scientist wishing to use them for non-commercial purposes.
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The six-gene UV-related prognostic model was strongly associated with patient survival, with a hazard ratio of 1.57, and COL4A3 overexpression inhibited melanoma-cell proliferation, migration, and invasion while enhancing imatinib's inhibitory effects.
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The model had a strong patient survival correlation (P˂0.001, hazard ratio (HR) = 1.57) and significant predictor (P˂0.001, HR = 3.050).
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The model had a strong patient survival correlation (P˂0.001, hazard ratio (HR) = 1.57) and significant predictor (P˂0.001, HR = 3.050).
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Overexpression of COL4A3 significantly inhibited the proliferation, migration, and invasion abilities of SKMEL28 and A357 melanoma cells, while knockdown of COL4A3 yielded the opposite results.
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And overexpression of COL4A3 enhanced the inhibitory effects of imatinib on the proliferation, migration, and invasion abilities of SKMEL28 and A357 cells.
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The six-gene UV-related prognostic model was strongly associated with patient survival, with a hazard ratio of 1.57, and COL4A3 overexpression inhibited melanoma-cell proliferation, migration, and invasion while enhancing imatinib's inhibitory effects.
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The following information was supplied regarding data availability: The dataset of TCGA-SKCM generated and/or analyzed during the current study are available at the TCGA database (https://cancergenome.nih.gov/). The datasets generated and/or analyzed during the current study are available at GEO: GSE59455. The core code of this study has been uploaded to GitHub: https://github.com/Lizhiyongjuan/Code.git. The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. We declared that materials described in the manuscript, including all relevant raw data, will be freely available to any scientist wishing to use them for non-commercial purposes.
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The following information was supplied regarding data availability: The dataset of TCGA-SKCM generated and/or analyzed during the current study are available at the TCGA database (https://cancergenome.nih.gov/). The datasets generated and/or analyzed during the current study are available at GEO: GSE59455. The core code of this study has been uploaded to GitHub: https://github.com/Lizhiyongjuan/Code.git. The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. We declared that materials described in the manuscript, including all relevant raw data, will be freely available to any scientist wishing to use them for non-commercial purposes.
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further validated that the overexpression or knockdown of COL4A3 could regulate the proliferation a
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38911338", "kind": "science-record", "revision": 2, "content_hash": "sha256:fd290a5dd458b37aff2f7bd8c2b1a9c726251fc647ba5f7e0edede40fc1c707a", "created_at": "2026-11-01T20:28:59Z", "updated_at": "2026-11-01T21:33:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated Analysis Reveals COL4A3 as a Novel Diagnostic and Therapeutic Target in UV-Related Skin Cutaneous Melanoma.", "doi": "10.2147/CCID.S461959", "pmid": "38911338", "authors": ["Zuochao Yao", "Lu Lu", "Qianhui Xu", "Shan Hua", "Hui Wang", "Hua Jiang"], "journal": "Clinical, cosmetic and investigational dermatology", "year": 2024, "abstract": "Background: High levels of UV exposure are a significant factor that can trigger the onset and progression of SKCM. Moreover, this exposure is closely linked to the malignancy of the tumor and the prognosis of patients. Our objective is to identify a tumor biomarker database associated with UV exposure, which can be utilized for prognostic analysis and diagnosis and treatment of SKCM.\nMethods: This study used the weighted gene co-expression network analyses (WGCNA) and gene mutation frequency analyses to screen for UV-related target genes using the GSE59455 and the cancer genome atlas databases (TCGA). The prognostic model was created using Cox regression and least absolute shrinkage and selection operator analyses (LASSCO). Furthermore, in vitro experiments further validated that the overexpression or knockdown of COL4A3 could regulate the proliferation and migration abilities of SKMEL28 and A357 melanoma cells.\nResults: A prognostic model was created that included six genes with a high UV-related mutation in SKCM: COL4A3, CHRM2, DSC3, GIMAP5, LAMC2, and PSG7. The model had a strong patient survival correlation (P˂0.001, hazard ratio (HR) = 1.57) and significant predictor (P˂0.001, HR = 3.050). Furthermore, the model negatively correlated with immune cells, including CD8+ T cells (Cor=-0.408, P˂0.001), and M1-type macrophages (Cor=-0.385, P˂0.001), and immune checkpoints, including programmed cell death ligand-1. Moreover, we identified COL4A3 as a molecule with significant predictive functionality. Overexpression of COL4A3 significantly inhibited the proliferation, migration, and invasion abilities of SKMEL28 and A357 melanoma cells, while knockdown of COL4A3 yielded the opposite results. And overexpression of COL4A3 enhanced the inhibitory effects of imatinib on the proliferation, migration, and invasion abilities of SKMEL28 and A357 cells.\nConclusion: The efficacy of the prognostic model was validated by analyzing the prognosis, immune infiltration, and immune checkpoint profiles. COL4A3 stands out as a novel diagnostic and therapeutic target for SKCM, offering new strategies for small-molecule targeted drug therapies.", "claims": [{"id": "claim-method", "statement": "Multifactorial Cox regression and least absolute shrinkage and selection operator (LASSO)17 analysis was used to develop prognostic models.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38911338", "locator": "sections[6] \"Construction and Validation of Prognostic Models\" paragraph 2", "quote": "Multifactorial Cox regression and least absolute shrinkage and selection operator (LASSO)17 analysis was used to develop prognostic models."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The following information was supplied regarding data availability: The dataset of TCGA-SKCM generated and/or analyzed during the current study are available at the TCGA database (https://cancergenome.nih.gov/). The datasets generated and/or analyzed during the current study are available at GEO: GSE59455. The core code of this study has been uploaded to GitHub: https://github.com/Lizhiyongjuan/Code.git. The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. We declared that materials described in the manuscript, including all relevant raw data, will be freely available to any scientist wishing to use them for non-commercial purposes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38911338", "locator": "sections[28] \"Data Sharing Statement\" paragraph 2", "quote": "The following information was supplied regarding data availability: The dataset of TCGA-SKCM generated and/or analyzed during the current study are available at the TCGA database (https://cancergenome.nih.gov/). The datasets generated and/or analyzed during the current study are available at GEO: GSE59455. The core code of this study has been uploaded to GitHub: https://github.com/Lizhiyongjuan/Code.git. The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. We declared that materials described in the manuscript, including all relevant raw data, will be freely available to any scientist wishing to use them for non-commercial purposes."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The six-gene UV-related prognostic model was strongly associated with patient survival, with a hazard ratio of 1.57, and COL4A3 overexpression inhibited melanoma-cell proliferation, migration, and invasion while enhancing imatinib's inhibitory effects.", "kind": "quantitative", "target": {"value": 3.05, "unit": "hazard ratio", "tolerance": null, "source": "The model had a strong patient survival correlation (P˂0.001, hazard ratio (HR) = 1.57) and significant predictor (P˂0.001, HR = 3.050)."}, "evidence": [{"asset": "source:pmid:38911338", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The model had a strong patient survival correlation (P˂0.001, hazard ratio (HR) = 1.57) and significant predictor (P˂0.001, HR = 3.050)."}, {"asset": "source:pmid:38911338", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Overexpression of COL4A3 significantly inhibited the proliferation, migration, and invasion abilities of SKMEL28 and A357 melanoma cells, while knockdown of COL4A3 yielded the opposite results."}, {"asset": "source:pmid:38911338", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "And overexpression of COL4A3 enhanced the inhibitory effects of imatinib on the proliferation, migration, and invasion abilities of SKMEL28 and A357 cells."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The six-gene UV-related prognostic model was strongly associated with patient survival, with a hazard ratio of 1.57, and COL4A3 overexpression inhibited melanoma-cell proliferation, migration, and invasion while enhancing imatinib's inhibitory effects.", "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:38911338"], "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:GSE59455"], "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:GSE59455"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38911338", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/CCID.S461959", "sha256": "sha256:f866e0f35a55cfb5b3ea27bd1bd9491086f4ddff6c517c420142da4b9db06c03", "bytes": 56537, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/CCID.S461959", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11192641", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE59455", "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=GSE59455", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE59455", "version": null, "note": "The following information was supplied regarding data availability: The dataset of TCGA-SKCM generated and/or analyzed during the current study are available at the TCGA database (https://cancergenome.nih.gov/). The datasets generated and/or analyzed during the current study are available at GEO: GSE59455. The core code of this study has been uploaded to GitHub: https://github.com/Lizhiyongjuan/Code.git. The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. We declared that materials described in the manuscript, including all relevant raw data, will be freely available to any scientist wishing to use them for non-commercial purposes.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The following information was supplied regarding data availability: The dataset of TCGA-SKCM generated and/or analyzed during the current study are available at the TCGA database (https://cancergenome.nih.gov/). The datasets generated and/or analyzed during the current study are available at GEO: GSE59455. The core code of this study has been uploaded to GitHub: https://github.com/Lizhiyongjuan/Code.git. The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. 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