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Identification of novel disulfidptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of skin cutaneous melanoma patients.
Cheng, Shengrong; Wang, Xin; Yang, Shuhan; Liang, Jiahui; Song, Caiying; Zhu, Qiuxuan; Chen, Wendong; Ren, Zhiyao; Zhu, Fei.
Afiliación
  • Cheng S; Department of Plastic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Wang X; Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
  • Yang S; Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Liang J; Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Song C; Department of Breast Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Zhu Q; Department of Plastic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Chen W; Department of Plastic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Ren Z; Department of Plastic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Zhu F; Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
Skin Res Technol ; 30(7): e13814, 2024 Jul.
Article en En | MEDLINE | ID: mdl-38924611
ABSTRACT

BACKGROUND:

Skin cutaneous melanoma (SKCM) is an aggressive form of malignant melanoma with poor prognosis and high mortality rates. Disulfidptosis is a newly discovered cell death regulatory mechanism caused by the abnormal accumulation of disulfides. This unique pathway is guiding significant new research to understand cancer progression for targeted treatment. However, the correlation between disulfidptosis with long non-coding RNAs (lncRNAs) in SKCM remains unknown at present.

METHODS:

The Cancer Genome Atlas database furnished lncRNA expression data and clinical information for SKCM patients. Pearson correlation and Cox regression analyses identified disulfidptosis-related lncRNAs associated with SKCM prognosis. ROC curves and a nomogram validated the model. TME, immune infiltration, GSEA analysis, immune checkpoint gene expression profiling, and drug sensitivity were assessed in high and low-risk groups. Consistent clustering categorized SKCM patients for personalized clinical treatment guidance.

RESULTS:

A total of twelve disulfidptosis-related lncRNAs were identified for the development of prognosis prediction models. The area under the curve (AUC) values of the ROC curve and the nomogram provided reliable discrimination to evaluate the prognostic potential for SKCM patients. The TME played a crucial role in tumorigenesis, progression and prognosis, and the risk scores were closely related to immune cell infiltration. Meanwhile, the combination of chemotherapy, targeted therapy, and immunotherapy was recommended for low-risk patients based on drug sensitivity and immune efficacy analyses.

CONCLUSION:

We identified a risk model of twelve disulfidptosis-related lncRNAs that could be used to predict the prognosis of SKCM patients and help guide immunotherapy and chemotherapy for personalized treatment plans.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Cutáneas / Microambiente Tumoral / ARN Largo no Codificante / Melanoma Límite: Female / Humans / Male / Middle aged Idioma: En Revista: Skin Res Technol Asunto de la revista: DERMATOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Cutáneas / Microambiente Tumoral / ARN Largo no Codificante / Melanoma Límite: Female / Humans / Male / Middle aged Idioma: En Revista: Skin Res Technol Asunto de la revista: DERMATOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: China