Evidence map›Paper›PMID 39267668›Full record

ArticleAmerican journal of cancer research2024

Integrative analysis of autophagy-related genes reveals that CAPNS1 is a novel prognostic biomarker and promotes the malignancy of melanoma via Notch signaling pathway.

Mengru Gao, Jisong Liu, Miaomiao Yang, Xiangzhou Zhang, Yulian Zhang, Zhuliang Zhou, Jiabin Deng

Abstract read
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Article in American journal of cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mengru GaoClinical Pathology Center, The First Affiliated Hospital of Anhui Medical University Hefei 230012, Anhui, China.
Jisong LiuDepartment of Burn and Plastic Surgery, The Third People's Hospital of Bengbu Bengshan District, Bengbu 233000, Anhui, China.
Miaomiao YangClinical Pathology Center, The First Affiliated Hospital of Anhui Medical University Hefei 230012, Anhui, China.
Xiangzhou ZhangDepartment of Burn and Plastic Surgery, The Third People's Hospital of Bengbu Bengshan District, Bengbu 233000, Anhui, China.
Yulian ZhangClinical Pathology Center, The First Affiliated Hospital of Anhui Medical University Hefei 230012, Anhui, China.
Zhuliang ZhouDepartment of Burn and Plastic Surgery, The Third People's Hospital of Bengbu Bengshan District, Bengbu 233000, Anhui, China.
Jiabin DengDepartment of Burn and Plastic Surgery, The Third People's Hospital of Bengbu Bengshan District, Bengbu 233000, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skin cutaneous melanoma (SKCM) is a highly fatal form of skin cancer that develops from the malignant transformation of epidermal melanocytes. There is substantial evidence linking autophagy to cancer etiology and immunotherapy efficacy. This study aimed to conduct a comprehensive analysis of autophagy-related genes (ARGs) using TCGA datasets and further explore the potential function of critical ARGs in SKCM progression. We performed comprehensive bioinformatics analysis uses the TCGA dataset. RT-PCR was applied to examine the expression of CAPNS1 in SKCM cells. Lost-of-function experiments were performed to detect the expression of the related proteins. In this search, we screed 70 differentially expressed autophagy-related genes (DE-ARGs), including 33 up-DE-ARGs and 37 down-DE-ARGs. Enrichment assays revealed that these 70 DE-ARGs may exert influence on critical cellular processes such as autophagy, protein kinase activity, and signaling pathways, impacting cell growth, differentiation, survival, and tumor development. Then, we further explore the prognostic value of 70 DE-ARGs and confirmed 18 survival-related DE-ARGs in SKCM patients. Nearly all the 18 DE-ARGs' methylation was negatively correlated with their corresponding expression in SKCM. The 12 survival-related DE-ARGs were used to develop a unique predictive model that effectively classified SKCM patients into high- and low-risk groups with regard to overall survival. Furthermore, tumor environment analysis indicated that the risk score was associated with several immune cells. Among the 12 survival-related DE-ARGs, our attention focused on CAPNS1 which was highly expressed in SKCM patients and predicted a poor prognosis. In addition, we confirmed that knockdown of CAPNS1 distinctly suppressed the proliferation, metastasis and EMT of SKCM cells, and promoted autophagy via regulating Notch signaling pathway. Overall, this study enhances our understanding of the intricate molecular landscape of SKCM progression and presents promising avenues for future research and clinical applications.

Indexed as

autophagybiomarkerCAPNS1immune microenvironmentNotch signaling pathwayprognosis signatureSkin cutaneous melanoma

Identifiers

PMID39267668
PMCPMC11387868

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.