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肿瘤微环境中细胞焦亡的多组学特征及其在转移性黑色素瘤中的治疗相关性

Multiomics characterization of pyroptosis in the tumor microenvironment and therapeutic relevance in metastatic melanoma.

机构信息

The Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China.

Hunan Key Laboratory of Skin Cancer and Psoriasis, Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Changsha, China.

出版信息

BMC Med. 2024 Jan 17;22(1):24. doi: 10.1186/s12916-023-03175-0.

DOI:10.1186/s12916-023-03175-0
PMID:38229080
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10792919/
Abstract

BACKGROUND

Pyroptosis, mediated by gasdermins with the release of multiple inflammatory cytokines, has emerged as playing an important role in targeted therapy and immunotherapy due to its effectiveness at inhibiting tumor growth. Melanoma is one of the most commonly used models for immunotherapy development, though an inadequate immune response can occur. Moreover, the development of pyroptosis-related therapy and combinations with other therapeutic strategies is limited due to insufficient understanding of the role of pyroptosis in the context of different tumor immune microenvironments (TMEs).

METHODS

Here, we present a computational model (pyroptosis-related gene score, PScore) to assess the pyroptosis status. We applied PScore to 1388 melanoma samples in our in-house cohort and eight other publicly available independent cohorts and then calculated its prognostic power of and potential as a predictive marker of immunotherapy efficacy. Furthermore, we performed association analysis for PScore and the characteristics of the TME by using bulk, single-cell, and spatial transcriptomics and assessed the association of PScore with mutation status, which contributes to targeted therapy.

RESULTS

Pyroptosis-related genes (PRGs) showed distinct expression patterns and prognostic predictive ability in melanoma. Most PRGs were associated with better survival in metastatic melanoma. Our PScore model based on genes associated with prognosis exhibits robust performance in survival prediction in multiple metastatic melanoma cohorts. We also found PScore to be associated with BRAF mutation and correlate positively with multiple molecular signatures, such as KRAS signaling and the IFN gamma response pathway. Based on our data, melanoma with an immune-enriched TME had a higher PScore than melanoma with an immune-depleted or fibrotic TME. Additionally, monocytes had the highest PScore and malignant cells and fibroblasts the lowest PScore based on single-cell and spatial transcriptome analyses. Finally, a higher PScore was associated with better therapeutic efficacy of immune checkpoint blockade, suggesting the potential of pyroptosis to serve as a marker of immunotherapy response.

CONCLUSIONS

Collectively, our findings indicate that pyroptosis is a prognostic factor and is associated with the immune response in metastatic melanoma, as based on multiomics data. Our results provide a theoretical basis for drug combination and reveal potential immunotherapy response markers.

摘要

背景

细胞焦亡是由gasdermins 介导的,通过释放多种炎症细胞因子发挥作用,由于其有效抑制肿瘤生长的作用,在靶向治疗和免疫治疗中发挥着重要作用。黑色素瘤是免疫治疗发展最常用的模型之一,但可能会出现免疫反应不足的情况。此外,由于对不同肿瘤免疫微环境(TME)中细胞焦亡作用的理解不足,限制了与细胞焦亡相关的治疗方法的发展和与其他治疗策略的结合。

方法

在这里,我们提出了一种计算模型(细胞焦亡相关基因评分,PScore)来评估细胞焦亡状态。我们将 PScore 应用于我们内部队列的 1388 个黑色素瘤样本和另外八个公开的独立队列中,然后计算其预后能力和作为免疫治疗疗效预测标志物的潜力。此外,我们通过使用批量、单细胞和空间转录组学进行了 PScore 与 TME 特征的关联分析,并评估了 PScore 与突变状态的关联,这有助于靶向治疗。

结果

细胞焦亡相关基因(PRGs)在黑色素瘤中表现出不同的表达模式和预后预测能力。大多数 PRGs 与转移性黑色素瘤的更好生存相关。我们基于与预后相关的基因的 PScore 模型在多个转移性黑色素瘤队列中具有稳健的生存预测性能。我们还发现 PScore 与 BRAF 突变相关,并与多个分子特征(如 KRAS 信号通路和 IFNγ 反应途径)呈正相关。根据我们的数据,免疫富集的 TME 中的黑色素瘤比免疫耗竭或纤维化的 TME 中的黑色素瘤具有更高的 PScore。此外,基于单细胞和空间转录组分析,单核细胞的 PScore 最高,恶性细胞和成纤维细胞的 PScore 最低。最后,较高的 PScore 与免疫检查点阻断治疗的更好疗效相关,表明细胞焦亡作为免疫治疗反应的标志物的潜力。

结论

总之,我们的研究结果表明,基于多组学数据,细胞焦亡是转移性黑色素瘤的预后因素,并与免疫反应相关。我们的结果为药物联合提供了理论依据,并揭示了潜在的免疫治疗反应标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/7140f44f538d/12916_2023_3175_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/b8e2f113dd24/12916_2023_3175_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/aabb3838932d/12916_2023_3175_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/88ba9cd63b08/12916_2023_3175_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/7140f44f538d/12916_2023_3175_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/b8e2f113dd24/12916_2023_3175_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/9ef5aeae9239/12916_2023_3175_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/a640f69ea83d/12916_2023_3175_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/aabb3838932d/12916_2023_3175_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/88ba9cd63b08/12916_2023_3175_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/10792919/7140f44f538d/12916_2023_3175_Fig6_HTML.jpg

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