Identification of a pyroptosis‐based model for predicting clinical outcomes from immunotherapy in patients with metastatic melanoma

Wu, Guanghao; Chen, Biying; Jiang, Junjie; Chen, Yiran; Chen, Yanyan; Wang, Haiyong

doi:10.1002/cam4.5178

Cited by 7 publications

(3 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, we constructed the PScore model to evaluate pyroptosis status in melanoma patients, as there is as yet no applicable and quick method to estimate pyroptosis status other than electron microscopy or PCR [101][102][103]. Although some pyroptosis-related models based on RNA sequencing [104,105] have been explored to predict the clinical outcome of cutaneous melanoma patients, in-depth research is still lacking. We found that PRGs have different expression patterns in primary and metastatic tumors and that the NMF method based on PRGs can predict the prognosis of metastatic patients but not primary patients.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

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

Chen,

He,

Zhou

et al. 2024

BMC Med

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionmentioning

confidence: 99%

“…There have been several attempts thus far to establish prognostic models related to pyroptosis [19][20][21][22][23][24][25][26][27][28][29]. The majority of them have been built based on least absolute shrinkage and selection operator (LASSO) regression [30] with distinct gene sets as input.…”

Section: Introductionmentioning

confidence: 99%

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

Chen,

He,

Zhou

et al. 2024

BMC Med

View full text Add to dashboard Cite

show abstract

“…In the study by Wu and colleagues, a PYR-based model was constructed by analyzing RNA sequencing data and clinical information of melanoma patients from four immunotherapy databases, including Gide (patients receiving anti-PD1 or the combination anti-PD1 and anti-CTLA4), Lauss (patients treated with adoptive T-cell therapy), Liu (patients treated with anti-PD1) and Nathanson (patients treated with anti-CTLA4) [ 101 ]. Gide worked as the training cohort and the others as validation cohorts.…”

Section: Pyroptosis and Cancermentioning

confidence: 99%

The Therapeutic Potential of Pyroptosis in Melanoma

Zaffaroni

Beretta

2023

IJMS

View full text Add to dashboard Cite

Pyroptosis is a programmed cell death characterized by the rupture of the plasma membranes and release of cellular content leading to inflammatory reaction. Four cellular mechanisms inducing pyroptosis have been reported thus far, including the (i) caspase 1-mediated canonical, (ii) caspase 4/5/11-mediated non-canonical, (iii) caspase 3/8-mediated and (iv) caspase-independent pathways. Although discovered as a defense mechanism protecting cells from infections of intracellular pathogens, pyroptosis plays roles in tumor initiation, progression and metastasis of tumors, as well as in treatment response to antitumor drugs and, consequently, patient outcome. Pyroptosis induction following antitumor therapies has been reported in several tumor types, including lung, colorectal and gastric cancer, hepatocellular carcinoma and melanoma. This review provides an overview of the cellular pathways of pyroptosis and discusses the therapeutic potential of pyroptosis induction in cancer, particularly in melanoma.

show abstract

Identification of a pyroptosis‐based model for predicting clinical outcomes from immunotherapy in patients with metastatic melanoma

Chen

Jiang

et al. 2022

Cancer Medicine

View full text Add to dashboard Cite

Immunotherapy has greatly improved outcomes for patients with advanced melanoma, but good predictive biomarkers remain lacking in clinical practice. Although increasing evidence has revealed a vital role of pyroptosis in the tumor microenvironment (TME), it remains unclear for pyroptosis as a predictive biomarker for immunotherapy in melanoma. RNA sequencing data and annotated clinical information of melanoma patients were obtained from four published immunotherapy datasets. LASSO regression analysis was conducted to develop a pyroptosis-based model for quantifying a pyroptosis score in each tumor. Based on four clinical cohorts, we evaluated the predictive capability of the model using multiple immunotherapeutic outcomes, including clinical benefits, overall survival (OS), and progression-free survival (PFS). Furthermore, we depicted the distinctive TME features associated with pyroptosis. Compared with the group with low pyroptosis

show abstract

Identification of a pyroptosis‐based model for predicting clinical outcomes from immunotherapy in patients with metastatic melanoma

Cited by 7 publications

References 66 publications

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

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

The Therapeutic Potential of Pyroptosis in Melanoma

Identification of a pyroptosis‐based model for predicting clinical outcomes from immunotherapy in patients with metastatic melanoma

Contact Info

Product

Resources

About