| Autor: |
Yu Sheng, Jing Liu, Miao Zhang, Shuyun Zheng |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Mathematical Biosciences and Engineering, Vol 20, Iss 11, Pp 19912-19928 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1551-0018 |
| DOI: |
10.3934/mbe.2023881?viewType=HTML |
| Popis: |
Skin cutaneous melanoma (SKCM) is one of the most malignant forms of skin cancer, characterized by its high metastatic potential and low cure rate in advanced stages. Despite advancements in clinical therapies, the overall cure rate for SKCM remains low due to its resistance to conventional treatments. Inflammation is associated with the activation and regulation of inflammatory responses and plays a crucial role in the immune system. It has been implicated in various physiological and pathological processes, including cancer. However, the mechanisms of inflammasome activation in SKCM remain largely unexplored. In this study, we quantified the expression level of six inflammasome-related gene sets using transcriptomic data from SKCM patients. As a result, we found that inflammasome features were closely associated with various clinical characteristics and served as a favorable prognostic factor for patients. A functional enrichment analysis revealed the oncogenic role of inflammasome features in SKCM. Unsupervised clustering was applied to identify immune clusters and inflammatory subtypes, revealing a significant overlap between immune cluster 4 and SKCM subtype 2. The CASP1, GSDMD, NLRP3, IL1B, and IL18 features could predict immune checkpoint blockade therapy response in various SKCM cohorts. In conclusion, our study highlighted the significant association between the inflammasome and cancer treatment. Understanding the role of inflammasome signaling in SKCM pathology can help identify potential therapeutic targets and improve patient prognosis. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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