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pmid:41168787

The role of TEAD4 gene in the Hippo signaling pathway in triple-negative breast cancer and targeted therapy strategies.

Xueliang Zhang · Tao Wang · Xiaowen Lian · Changsheng Wei · Dong Yan · Yan Liang

BMC medical genomics · 2025 doi:10.1186/s12920-025-02245-x

Paper

complete

Experiment

complete

Data

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Analysis

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Execution

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title
The role of TEAD4 gene in the Hippo signaling pathway in triple-negative breast cancer and targeted therapy strategies.
doi
10.1186/s12920-025-02245-x
pmid
41168787
authors array · 6 items
[0]
Xueliang Zhang
[1]
Tao Wang
[2]
Xiaowen Lian
[3]
Changsheng Wei
[4]
Dong Yan
[5]
Yan Liang
journal
BMC medical genomics
year
2025
abstract
BACKGROUND: Triple-negative breast cancer (TNBC) is an aggressive subtype with poor prognosis and limited targeted therapies. The Hippo signaling pathway, critical in tumor progression, may harbor key genes influencing TNBC behavior. However, the specific genes and their clinical significance remain unclear. METHODS: We analyzed the GSE45827 dataset from the GEO database using differential gene expression analysis (DEG) and weighted gene co-expression network analysis (WGCNA) to identify TNBC-related genes. We enriched Hippo pathway-related genes from the MsigDB database and literature to identify candidate genes (HRGs) that may affect TNBC progression. The Boruta algorithm further screened for core genes, which were validated by immunohistochemistry in TNBC and other breast cancer tissues. Finally, we explored the biological and pharmacological significance of the target through drug prediction, molecular docking, molecular dynamics simulations, and in vitro experiments. RESULTS: DEG analysis identified 2,888 differentially expressed genes, and WGCNA yielded 276 TNBC-associated genes. Intersection analysis with 70 hypoxia-related genes (HRGs) revealed four key genes: TEAD4, WWTR1, AREG, and SOX11. TEAD4 was confirmed as the central gene influencing TNBC progression. Immunohistochemical results showed strong TEAD4 expression in TNBC tissues, with negligible expression in adjacent normal tissues or other breast cancer subtypes. Drug prediction and molecular docking identified irinotecan as a potential TEAD4-targeting agent. Molecular dynamics simulations confirmed the stable binding and favorable dynamics of the irinotecan-TEAD4 complex. Both TEAD4 knockdown and irinotecan treatment significantly suppressed TNBC cell migration and invasion. The combination of TEAD4 knockout and irinotecan produced a more pronounced inhibitory effect, underscoring the therapeutic potential of targeting TEAD4 in TNBC. CONCLUSIONS: Through comprehensive analysis, we identified TEAD4 as a key gene in TNBC with high expression specificity. Irinotecan may be a potential targeted drug for TEAD4, offering a new therapeutic strategy for TNBC and potentially improving patient outcomes. Further experimental verification is required.
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To identify genes with significant expression differences in TNBC, we performed differential gene expression analysis using the DESeq2 package (v1.38.3) in R [13].
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To identify genes with significant expression differences in TNBC, we performed differential gene expression analysis using the DESeq2 package (v1.38.3) in R [13].
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The partial datasets generated and/or analyzed during this research have been included in this published article. The remaining data can be provided by the corresponding author upon reasonable request.
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DEG analysis identified 2,888 differentially expressed genes, and WGCNA yielded 276 TNBC-associated genes.
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DEG analysis identified 2,888 differentially expressed genes.
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title
Expression profiling of breast cancer samples from Institut Curie (Maire cohort) --Affy CDF
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To identify genes with significant expression differences in TNBC, we performed differential gene expression analysis using the DESeq2 package (v1.38.3) in R [13].
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The partial datasets generated and/or analyzed during this research have been included in this published article. The remaining data can be provided by the corresponding author upon reasonable request.
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ened for core genes, which were validated by immunohistochemistry in TNBC and other breast cancer tissues. Fin
[1]
e central gene influencing TNBC progression. Immunohistochemical results showed strong TEAD4 expression in TN
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of the irinotecan-TEAD4 complex. Both TEAD4 knockdown and irinotecan treatment significantly suppr
[1]
Methods Cell culture and transfection The human TNBC cell line MDA-MB-231 was obta
[2]
with 5% CO₂. For TEAD4 knockdown, cells were transfected with a specific small interfering RNA (siRNA
[3]
UCAUUTT-3’si-NC: 5’-UUCUCCGAACGUGUCACGUTT-3’ Transfection was performed using Lipofectamine 3000 reage
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n Type Culture Collection (ATCC). Cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM, HyCl
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To identify genes with significant expression differences in TNBC, we performed differential gene expression analysis using the DESeq2 package (v1.38.3) in R [13].
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41168787", "kind": "science-record", "revision": 4, "content_hash": "sha256:adf8802adf6e97f163f1092424b00b4fe01a68316267d6bd172e976f7106525f", "created_at": "2026-11-01T20:31:12Z", "updated_at": "2026-11-01T22:57:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The role of TEAD4 gene in the Hippo signaling pathway in triple-negative breast cancer and targeted therapy strategies.", "doi": "10.1186/s12920-025-02245-x", "pmid": "41168787", "authors": ["Xueliang Zhang", "Tao Wang", "Xiaowen Lian", "Changsheng Wei", "Dong Yan", "Yan Liang"], "journal": "BMC medical genomics", "year": 2025, "abstract": "BACKGROUND: Triple-negative breast cancer (TNBC) is an aggressive subtype with poor prognosis and limited targeted therapies. The Hippo signaling pathway, critical in tumor progression, may harbor key genes influencing TNBC behavior. However, the specific genes and their clinical significance remain unclear.\nMETHODS: We analyzed the GSE45827 dataset from the GEO database using differential gene expression analysis (DEG) and weighted gene co-expression network analysis (WGCNA) to identify TNBC-related genes. We enriched Hippo pathway-related genes from the MsigDB database and literature to identify candidate genes (HRGs) that may affect TNBC progression. The Boruta algorithm further screened for core genes, which were validated by immunohistochemistry in TNBC and other breast cancer tissues. Finally, we explored the biological and pharmacological significance of the target through drug prediction, molecular docking, molecular dynamics simulations, and in vitro experiments.\nRESULTS: DEG analysis identified 2,888 differentially expressed genes, and WGCNA yielded 276 TNBC-associated genes. Intersection analysis with 70 hypoxia-related genes (HRGs) revealed four key genes: TEAD4, WWTR1, AREG, and SOX11. TEAD4 was confirmed as the central gene influencing TNBC progression. Immunohistochemical results showed strong TEAD4 expression in TNBC tissues, with negligible expression in adjacent normal tissues or other breast cancer subtypes. Drug prediction and molecular docking identified irinotecan as a potential TEAD4-targeting agent. Molecular dynamics simulations confirmed the stable binding and favorable dynamics of the irinotecan-TEAD4 complex. Both TEAD4 knockdown and irinotecan treatment significantly suppressed TNBC cell migration and invasion. The combination of TEAD4 knockout and irinotecan produced a more pronounced inhibitory effect, underscoring the therapeutic potential of targeting TEAD4 in TNBC.\nCONCLUSIONS: Through comprehensive analysis, we identified TEAD4 as a key gene in TNBC with high expression specificity. Irinotecan may be a potential targeted drug for TEAD4, offering a new therapeutic strategy for TNBC and potentially improving patient outcomes. Further experimental verification is required.", "claims": [{"id": "claim-method", "statement": "To identify genes with significant expression differences in TNBC, we performed differential gene expression analysis using the DESeq2 package (v1.38.3) in R [13].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41168787", "locator": "sections[3] \"Data source and preprocessing\" paragraph 2", "quote": "To identify genes with significant expression differences in TNBC, we performed differential gene expression analysis using the DESeq2 package (v1.38.3) in R [13]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The partial datasets generated and/or analyzed during this research have been included in this published article. The remaining data can be provided by the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41168787", "locator": "sections[36] \"notes\" paragraph 1", "quote": "The partial datasets generated and/or analyzed during this research have been included in this published article. The remaining data can be provided by the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "DEG analysis identified 2,888 differentially expressed genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41168787", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "DEG analysis identified 2,888 differentially expressed genes, and WGCNA yielded 276 TNBC-associated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "DEG analysis identified 2,888 differentially expressed 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:41168787"], "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:GSE38959"], "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:GSE38959"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41168787", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12920-025-02245-x", "sha256": "sha256:a119f9277714dcc53a249e32ca3325cfdbdc0ce643559a249e38552f58d745c7", "bytes": 45617, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12920-025-02245-x", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12573850", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE38959", "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=GSE38959", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE38959", "version": null, "note": "The partial datasets generated and/or analyzed during this research have been included in this published article. 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