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pmid:38610001

RUNX1-BMP2 promotes vasculogenic mimicry in laryngeal squamous cell carcinoma via activation of the PI3K-AKT signaling pathway.

Qingwen Zhu · Xinyu Zhang · Fei Lu · Siyu Miao · Chunyang Zhang · Zhenzhen Liu · Zejun Gao · Meihao Qi · Xiaogang An · Panling Geng · Sufang Wang · Hongbo Ren · Fugen Han · Ruyue Zhang · DingJun Zha

Cell communication and signaling : CCS · 2024 doi:10.1186/s12964-024-01605-x

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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2026-11-01T19:20:34Z
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title
RUNX1-BMP2 promotes vasculogenic mimicry in laryngeal squamous cell carcinoma via activation of the PI3K-AKT signaling pathway.
doi
10.1186/s12964-024-01605-x
pmid
38610001
authors array · 15 items
[0]
Qingwen Zhu
[1]
Xinyu Zhang
[2]
Fei Lu
[3]
Siyu Miao
[4]
Chunyang Zhang
[5]
Zhenzhen Liu
[6]
Zejun Gao
[7]
Meihao Qi
[8]
Xiaogang An
[9]
Panling Geng
[10]
Sufang Wang
[11]
Hongbo Ren
[12]
Fugen Han
[13]
Ruyue Zhang
[14]
DingJun Zha
journal
Cell communication and signaling : CCS
year
2024
abstract
BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumors of the head and neck. Vasculogenic mimicry (VM) is crucial for tumor growth and metastasis and refers to the formation of fluid channels by invasive tumor cells rather than endothelial cells. However, the regulatory mechanisms underlying VM during the malignant progression of LSCC remain largely unknown. METHODS: Gene expression and clinical data for LSCC were obtained from the TCGA and Gene GEO (GSE27020) databases. A risk prediction model associated with VM was established using LASSO and Cox regression analyses. Based on their risk scores, patients with LSCC were categorized into high- and low-risk groups. The disparities in immune infiltration, tumor mutational burden (TMB), and functional enrichment between these two groups were examined. The core genes in LSCC were identified using the machine learning (SVM-RFE) and WGCNA algorithms. Subsequently, the involvement of bone morphogenetic protein 2 (BMP2) in VM and metastasis was investigated both in vitro and in vivo. To elucidate the downstream signaling pathways regulated by BMP2, western blotting was performed. Additionally, ChIP experiments were employed to identify the key transcription factors responsible for modulating the expression of BMP2. RESULTS: We established a new precise prognostic model for LSCC related to VM based on three genes: BMP2, EPO, and AGPS. The ROC curves from both TCGA and GSE27020 validation cohorts demonstrated precision survival prediction capabilities, with the nomogram showing some net clinical benefit. Multiple algorithm analyses indicated BMP2 as a potential core gene. Further experiments suggested that BMP2 promotes VM and metastasis in LSCC. The malignant progression of LSCC is promoted by BMP2 via the activation of the PI3K-AKT signaling pathway, with the high expression of BMP2 in LSCC resulting from its transcriptional activation by runt-related transcription factor 1 (RUNX1). CONCLUSION: BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1. BMP2 may be a novel, precise, diagnostic, and therapeutic biomarker of LSCC.
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sections[5] "Construction and validation of a VM-related genes(VMRGs) prognostic model" paragraph 2
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LASSO Cox regression analysis and least absolute shrinkage were applied to 141 VMDEGs to construct a prognostic model.
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BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1.
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BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1.
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BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1.
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Identification and validation of a multigene predictor of recurrence in primary laryngeal cancer.
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etastasis was investigated both in vitro and in vivo. To elucidate the downstream signaling pathw
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stream signaling pathways regulated by BMP2, western blotting was performed. Additionally, ChIP experiment
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cinoma cell line. TU212 and TU686 cells were cultured in DMEM (Gibco, Carlsbad, CA, USA) supplemented
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LASSO Cox regression analysis and least absolute shrinkage were applied to 141 VMDEGs to construct a prognostic model.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38610001", "kind": "science-record", "revision": 3, "content_hash": "sha256:9a02d47c1212b27c8e16033f30e2711c479e1508c5dbcb5d0dd51e66184c586f", "created_at": "2026-11-01T19:20:34Z", "updated_at": "2026-11-01T22:11:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "RUNX1-BMP2 promotes vasculogenic mimicry in laryngeal squamous cell carcinoma via activation of the PI3K-AKT signaling pathway.", "doi": "10.1186/s12964-024-01605-x", "pmid": "38610001", "authors": ["Qingwen Zhu", "Xinyu Zhang", "Fei Lu", "Siyu Miao", "Chunyang Zhang", "Zhenzhen Liu", "Zejun Gao", "Meihao Qi", "Xiaogang An", "Panling Geng", "Sufang Wang", "Hongbo Ren", "Fugen Han", "Ruyue Zhang", "DingJun Zha"], "journal": "Cell communication and signaling : CCS", "year": 2024, "abstract": "BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumors of the head and neck. Vasculogenic mimicry (VM) is crucial for tumor growth and metastasis and refers to the formation of fluid channels by invasive tumor cells rather than endothelial cells. However, the regulatory mechanisms underlying VM during the malignant progression of LSCC remain largely unknown.\nMETHODS: Gene expression and clinical data for LSCC were obtained from the TCGA and Gene GEO (GSE27020) databases. A risk prediction model associated with VM was established using LASSO and Cox regression analyses. Based on their risk scores, patients with LSCC were categorized into high- and low-risk groups. The disparities in immune infiltration, tumor mutational burden (TMB), and functional enrichment between these two groups were examined. The core genes in LSCC were identified using the machine learning (SVM-RFE) and WGCNA algorithms. Subsequently, the involvement of bone morphogenetic protein 2 (BMP2) in VM and metastasis was investigated both in vitro and in vivo. To elucidate the downstream signaling pathways regulated by BMP2, western blotting was performed. Additionally, ChIP experiments were employed to identify the key transcription factors responsible for modulating the expression of BMP2.\nRESULTS: We established a new precise prognostic model for LSCC related to VM based on three genes: BMP2, EPO, and AGPS. The ROC curves from both TCGA and GSE27020 validation cohorts demonstrated precision survival prediction capabilities, with the nomogram showing some net clinical benefit. Multiple algorithm analyses indicated BMP2 as a potential core gene. Further experiments suggested that BMP2 promotes VM and metastasis in LSCC. The malignant progression of LSCC is promoted by BMP2 via the activation of the PI3K-AKT signaling pathway, with the high expression of BMP2 in LSCC resulting from its transcriptional activation by runt-related transcription factor 1 (RUNX1).\nCONCLUSION: BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1. BMP2 may be a novel, precise, diagnostic, and therapeutic biomarker of LSCC.", "claims": [{"id": "claim-method", "statement": "LASSO Cox regression analysis and least absolute shrinkage were applied to 141 VMDEGs to construct a prognostic model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38610001", "locator": "sections[5] \"Construction and validation of a VM-related genes(VMRGs) prognostic model\" paragraph 2", "quote": "LASSO Cox regression analysis and least absolute shrinkage were applied to 141 VMDEGs to construct a prognostic model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "No datasets were generated or analysed during the current study.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38610001", "locator": "sections[40] \"notes\" paragraph 1", "quote": "No datasets were generated or analysed during the current study."}], "state": "complete"}, {"id": "claim-target-result", "statement": "BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38610001", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1.", "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:38610001"], "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:GSE27020"], "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:GSE27020"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38610001", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12964-024-01605-x", "sha256": 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