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一种用于预测皮肤黑色素瘤预后的新型焦亡相关长链非编码RNA特征

A Novel Pyroptosis-Related lncRNA Signature for Predicting the Prognosis of Skin Cutaneous Melanoma.

作者信息

Xie Jiaheng, Li Haobo, Chen Liang, Cao Yuan, Hu Yiming, Zhu Zhechen, Wang Ming, Shi Jingping

机构信息

Department of Burn and Plastic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.

Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.

出版信息

Int J Gen Med. 2021 Oct 8;14:6517-6527. doi: 10.2147/IJGM.S335396. eCollection 2021.

DOI:10.2147/IJGM.S335396
PMID:34675619
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8518699/
Abstract

PURPOSE

To construct a prognosis model of melanoma based on pyroptosis related genes.

METHODS

Melanoma RNA-sequencing data was downloaded from TCGA. First, the lnRNAs related to pyroptosis were obtained through Pearson correlation analysis. Then, the prognosis model of pyroptosis related genes was constructed by Cox regression and Lasso regression. Melanoma patients were divided into high-risk and low-risk groups by risk score, and the differences in prognosis and immune microenvironment between the two groups were explored.

RESULTS

We found that the high-risk group had a significantly poorer prognosis, and different groups differed in immune infiltration, m6A methylation, and immune checkpoint.

CONCLUSION

Our prognostic model can provide a reference for the study of pyroptosis in melanoma cells and provide a new idea for melanoma treatment.

摘要

目的

构建基于焦亡相关基因的黑色素瘤预后模型。

方法

从TCGA下载黑色素瘤RNA测序数据。首先,通过Pearson相关分析获得与焦亡相关的lnRNA。然后,通过Cox回归和Lasso回归构建焦亡相关基因的预后模型。根据风险评分将黑色素瘤患者分为高风险组和低风险组,探讨两组之间预后和免疫微环境的差异。

结果

我们发现高风险组的预后明显较差,不同组在免疫浸润、m6A甲基化和免疫检查点方面存在差异。

结论

我们的预后模型可为黑色素瘤细胞焦亡的研究提供参考,并为黑色素瘤治疗提供新思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/bc41ce314e31/IJGM-14-6517-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/e42d240a08ca/IJGM-14-6517-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/2384467258a4/IJGM-14-6517-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/f89596f1798c/IJGM-14-6517-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/29984320d054/IJGM-14-6517-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/3f7865d32c58/IJGM-14-6517-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/bc41ce314e31/IJGM-14-6517-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/e42d240a08ca/IJGM-14-6517-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/2384467258a4/IJGM-14-6517-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/f89596f1798c/IJGM-14-6517-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/29984320d054/IJGM-14-6517-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/3f7865d32c58/IJGM-14-6517-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ae2/8518699/bc41ce314e31/IJGM-14-6517-g0006.jpg

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