Prognostic and immune-related value of STK17B in skin cutaneous melanoma

Shi, Xueying; Zhou, Qi; Huang, Bingqian; Xia, Shilin; Jiang, Yuankuan; Fang, Shifeng; Lin, Jingrong

doi:10.1371/journal.pone.0263311

Cited by 7 publications

(5 citation statements)

References 31 publications

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“…Furthermore, we performed survival analysis using the genes in SCARP-derived GRN and found that many genes’ abnormal expressions were associated with the poor prognoses, such as TRIM69 , MITF and STK17B ( Figure 5E and Supplementary Figure 31 ). In particular, the low expression of gene STK17B , which has been shown in the literature to play an important role in immune infiltration, was associated with skin cancer, making it a key biomarker for the diagnosis of melanoma disease [ 52 ].…”

Section: Resultsmentioning

confidence: 99%

Incorporating network diffusion and peak location information for better single-cell ATAC-seq data analysis

Yu,

Leng,

Hou

et al. 2024

Briefings in Bioinformatics

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Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data provided new insights into the understanding of epigenetic heterogeneity and transcriptional regulation. With the increasing abundance of dataset resources, there is an urgent need to extract more useful information through high-quality data analysis methods specifically designed for scATAC-seq. However, analyzing scATAC-seq data poses challenges due to its near binarization, high sparsity and ultra-high dimensionality properties. Here, we proposed a novel network diffusion–based computational method to comprehensively analyze scATAC-seq data, named Single-Cell ATAC-seq Analysis via Network Refinement with Peaks Location Information (SCARP). SCARP formulates the Network Refinement diffusion method under the graph theory framework to aggregate information from different network orders, effectively compensating for missing signals in the scATAC-seq data. By incorporating distance information between adjacent peaks on the genome, SCARP also contributes to depicting the co-accessibility of peaks. These two innovations empower SCARP to obtain lower-dimensional representations for both cells and peaks more effectively. We have demonstrated through sufficient experiments that SCARP facilitated superior analyses of scATAC-seq data. Specifically, SCARP exhibited outstanding cell clustering performance, enabling better elucidation of cell heterogeneity and the discovery of new biologically significant cell subpopulations. Additionally, SCARP was also instrumental in portraying co-accessibility relationships of accessible regions and providing new insight into transcriptional regulation. Consequently, SCARP identified genes that were involved in key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to diseases and predicted reliable cis-regulatory interactions. To sum up, our studies suggested that SCARP is a promising tool to comprehensively analyze the scATAC-seq data.

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Section: Resultsmentioning

confidence: 99%

Incorporating network diffusion and peak location information for better single-cell ATAC-seq data analysis

Yu,

Leng,

Hou

et al. 2024

Briefings in Bioinformatics

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show abstract

“…26). In particular, the low expression of gene STK17B , which has been shown in the literature to play an important role in immune infiltration, was associated with skin cancer, making it a key biomarker for the diagnosis of melanoma disease [51].…”

Section: Resultsmentioning

confidence: 99%

Single-Cell ATAC-seq analysis via Network Refinement with peaks location information

Sun

Hou

et al. 2022

Preprint

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Single-cell ATAC-seq (scATAC-seq) data provided new insights into the elaboration of cellular heterogeneity and transcriptional regulation. However, scATAC-seq data posed challenges for data analysis because of its near binarization, high sparsity, and ultra-high dimensionality properties. Here we proposed a novel network diffusion-based method to comprehensively analyze scATAC-seq data, named Single-Cell ATAC-seq Analysis via Network Refinement with Peaks Location Information (SCARP). By modeling the prior probability of co-accessibility between adjacent peaks as a decreasing function of genomic distance, SCARP is the first scATAC-seq analysis method that utilizes the genomic information of peaks, which contributed to characterizing co-accessibility of peaks. SCARP used network to model the accessible relationships between cells and peaks, aggregated information with the diffusion method, and then performed dimensionality reduction to obtain low-dimensional cell embeddings as well as peak embeddings. We have demonstrated through sufficient experiments that SCARP facilitated superior analysis of scATAC-seq data. Specifically, SCARP exhibited outstanding cell clustering performance to better elucidate cell heterogeneity, and can be used to reveal new biologically significant cell subpopulations. SCARP was also instrumental in portraying co-accessibility relationships of accessible regions and providing new insight into transcriptional regulation, and those SCARP-derived genes were involved in some key KEGG pathways related to diseases. To sum up, our studies suggested that SCARP is a promising tool to comprehensively analyze the scATAC-seq data from a new perspective.

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“…Therefore, it is of great necessity to investigate the molecular signaling pathways and mechanisms of DRAK2-mediated CLL. Recent studies have shown that DRAK2 expression is down-regulated in skin cutaneous melanoma (SKCM) . Furthermore, the low expression of DRAK2 is linked to poor clinical prognosis and low survival rates in SKCM patients, but the mechanism needs further confirmation .…”

Section: The Dapk Family In Diseasesmentioning

confidence: 99%

“…168 Furthermore, the low expression of DRAK2 is linked to poor clinical prognosis and low survival rates in SKCM patients, but the mechanism needs further confirmation. 168 Notably, studies have demonstrated that nonalcoholic steatohepatitis (NASH) is an advanced stage of nonalcoholic fatty liver disease (NAFLD) and that DRAK2 is significantly upregulated in the livers of NAFLD/NASH patients and NAFLD/NASH diet-fed mice. 169 Mechanistically, DRAK2 interacts directly with serine/ arginine-rich (SR) splicing factor 6 (SRSF6) and prevents SRSF6 phosphorylation by inhibiting the interaction of SRSF6 with SRSF protein kinase 1 (SRPK1) (Table 4, Figure 2C).…”

Section: Drak2 In Diseasesmentioning

confidence: 99%

“…Recent studies have shown that DRAK2 expression is down-regulated in skin cutaneous melanoma (SKCM) . Furthermore, the low expression of DRAK2 is linked to poor clinical prognosis and low survival rates in SKCM patients, but the mechanism needs further confirmation . Notably, studies have demonstrated that nonalcoholic steatohepatitis (NASH) is an advanced stage of nonalcoholic fatty liver disease (NAFLD) and that DRAK2 is significantly upregulated in the livers of NAFLD/NASH patients and NAFLD/NASH diet-fed mice .…”

Section: The Dapk Family In Diseasesmentioning

confidence: 99%

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Targeting Death-Associated Protein Kinases for Treatment of Human Diseases: Recent Advances and Future Directions

et al. 2023

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The death-associated protein kinase (DAPK) family is a member of the calcium/calmodulin-regulated serine/threonine protein kinase family, and studies have shown that its role, as its name suggests, is mainly to regulate cell death. The DAPK family comprises five members, including DAPK1, DAPK2, DAPK3, DRAK1 and DRAK2, which show high homology in the common N-terminal kinase domain but differ in the extra-catalytic domain. Notably, previous research has suggested that the DAPK family plays an essential role in both the development and regulation of human diseases. However, only a few small-molecule inhibitors have been reported. In this Perspective, we mainly discuss the structure, biological function, and role of DAPKs in diseases and the currently discovered small-molecule inhibitors, providing valuable information for the development of the DAPK field.

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Prognostic and immune-related value of STK17B in skin cutaneous melanoma

Cited by 7 publications

References 31 publications

Incorporating network diffusion and peak location information for better single-cell ATAC-seq data analysis

Incorporating network diffusion and peak location information for better single-cell ATAC-seq data analysis

Single-Cell ATAC-seq analysis via Network Refinement with peaks location information

Targeting Death-Associated Protein Kinases for Treatment of Human Diseases: Recent Advances and Future Directions

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