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基于内质网应激相关基因的综合标志物预测黑色素瘤的预后和免疫治疗反应。

A comprehensive signature based on endoplasmic reticulum stress-related genes in predicting prognosis and immunotherapy response in melanoma.

机构信息

Department of Otolaryngology Head and Neck Surgery, Enshi Prefecture Ethnic Hospital, 178 Hangkong Avenue, Enshi, Hubei Province, China.

出版信息

Sci Rep. 2023 May 22;13(1):8232. doi: 10.1038/s41598-023-35031-9.

DOI:10.1038/s41598-023-35031-9
PMID:37217516
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10203260/
Abstract

Melanoma is considered as one of the most invasion types of skin cancer with high mortality rates. Although combination of immune checkpoint therapy with local surgical excision provide a novel promising therapeutic strategies, the overall prognosis of melanoma patients remains unsatisfactory. Endoplasmic reticulum (ER) stress, a process of protein misfolding and undue accumulation, has been proven to play an indispensable regulatory role in tumor progression and tumor immunity. However, whether the signature based ER genes has predictive value for the prognosis and immunotherapy of melanoma has not been systematically manifested. In this study, the LASSO regression and multivariate Cox regression were applied to construct a novel signature for predicting melanoma prognosis both in the training and testing set. Intriguingly, we found that patients endowed with high- and low-risk scores displayed differences in clinicopathologic classification, immune cell infiltration level, tumor microenvironment, and immune checkpoint treatment response. Subsequently, based on molecular biology experiments, we validated that silencing the expression of RAC1, an ERG composed of the risk signature, could restrain the proliferation and migration, promote apoptosis, as well as increase the expression of PD-1/PD-L1 and CTLA4 in melanoma cells. Taken together, the risk signature was regarded as promising predictors for melanoma prognosis and might provide prospective strategies to ameliorate patients' response to immunotherapy.

摘要

黑色素瘤被认为是最具侵袭性的皮肤癌之一,死亡率很高。虽然免疫检查点治疗联合局部手术切除为新型治疗策略提供了希望,但黑色素瘤患者的总体预后仍不理想。内质网(ER)应激是一种蛋白质错误折叠和过度积累的过程,已被证明在肿瘤进展和肿瘤免疫中发挥不可或缺的调节作用。然而,基于 ER 基因的特征是否对黑色素瘤的预后和免疫治疗具有预测价值尚未得到系统体现。在这项研究中,应用 LASSO 回归和多变量 Cox 回归构建了一种新的预测黑色素瘤预后的signature,该 signature 在训练集和测试集中均具有预测价值。有趣的是,我们发现高风险和低风险评分的患者在临床病理分类、免疫细胞浸润水平、肿瘤微环境和免疫检查点治疗反应方面存在差异。随后,通过分子生物学实验,我们验证了沉默风险 signature 中包含的 ERG 成分 RAC1 的表达可以抑制黑色素瘤细胞的增殖和迁移,促进细胞凋亡,并增加 PD-1/PD-L1 和 CTLA4 的表达。总之,该 risk signature 被认为是黑色素瘤预后的有前途的预测指标,并可能为改善患者对免疫治疗的反应提供有前景的策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/efbdaeeca230/41598_2023_35031_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/8a47777872f0/41598_2023_35031_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/4dd9a8a3d708/41598_2023_35031_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/1f4391b29bc9/41598_2023_35031_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/e20cfd069ed5/41598_2023_35031_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/c960052e6cff/41598_2023_35031_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/ee7bc158eebb/41598_2023_35031_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/62b854526749/41598_2023_35031_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/efbdaeeca230/41598_2023_35031_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/8a47777872f0/41598_2023_35031_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/4dd9a8a3d708/41598_2023_35031_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/1f4391b29bc9/41598_2023_35031_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/e20cfd069ed5/41598_2023_35031_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/c960052e6cff/41598_2023_35031_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/ee7bc158eebb/41598_2023_35031_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/62b854526749/41598_2023_35031_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17f6/10203260/efbdaeeca230/41598_2023_35031_Fig8_HTML.jpg

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