Allan Scarpitta

Bio: Allan Scarpitta is an academic researcher from University of Rouen. The author has contributed to research in topics: Pyroptosis & Tumor microenvironment. The author has co-authored 1 publications.

Pyroptotic and Necroptotic Cell Death in the Tumor Microenvironment and Their Potential to Stimulate Anti-Tumor Immune Responses.

Abstract: Cancer remains the second most common cause of death worldwide affecting around 10 million patients every year. Among the therapeutic options, chemotherapeutic drugs are widely used but often associated with side effects. In addition, toxicity against immune cells may hamper anti-tumor immune responses. Some chemotherapeutic drugs, however, preserve immune functions and some can even stimulate anti-tumor immune responses through the induction of immunogenic cell death (ICD) rather than apoptosis. ICD stimulates the immune system by several mechanisms including the release of damage-associated molecular patterns (DAMPs) from dying cells. In this review, we will discuss the consequences of inducing two recently characterized forms of ICD, i.e., pyroptosis and necroptosis, in the tumor microenvironment (TME) and the perspectives they may offer to increase the immunogenicity of the so-called cold tumors and to stimulate effective anti-tumor immune responses.

A necroptosis‐related gene signature for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinoma

Abstract: Hepatocellular carcinoma (HCC) remains a growing threat to global health. Necroptosis is a newly discovered form of cell necrosis that plays a vital role in cancer development. Thus, we conducted this study to identify a predictive signature of HCC based on necroptosis‐related genes.

Ag/Au Bimetallic Nanoparticles Trigger Different Cell Death Pathways and Affect Damage Associated Molecular Pattern Release in Human Cell Lines

Abstract: Simple Summary Apoptosis is the goal of several therapeutic strategies for cancer. However, the apoptotic pathway is not always functional in many cancers and thus, alternative ways to destroy cancer cells are required. In this context, we investigated whether nanoparticles composed of a gold and silver alloy (AgAu NPs) can induce other programmed cell death pathways. These include necroptosis and pyroptosis, while their effects on the release of molecules that serve as danger signals, the damage associated molecular patterns (DAMPs) were also investigated. Our findings suggest that MDA-MB-231 cells, one of the cancer cell lines tested, experience mixed cell death (several cell death pathways are activated), while a second cell line, HCT116 cells, releases DAMPS. This is important, since necroptosis and pyroptosis have promising anticancer effects, while DAMPs trigger inflammation and current knowledge suggests a rather beneficial role in cancer. Abstract Apoptosis induction is a common therapeutic approach. However, many cancer cells are resistant to apoptotic death and alternative cell death pathways including pyroptosis and necroptosis need to be triggered. At the same time, danger signals that include HMGB1 and HSP70 can be secreted/released by damaged cancer cells that boost antitumor immunity. We studied the cytotoxic effects of AgAu NPs, Ag NPs and Au NPs with regard to the programmed cell death (apoptosis, necroptosis, pyroptosis) and the secretion/release of HSP70 and HMGB1. Cancer cell lines were incubated with 30, 40 and 50 μg/mL of AgAu NPs, Ag NPs and Au NPs. Cytotoxicity was estimated using the MTS assay, and mRNA fold change of CASP1, CASP3, BCL-2, ZPB1, HMGB1, HSP70, CXCL8, CSF1, CCL20, NLRP3, IL-1β and IL-18 was used to investigate the associated programmed cell death. Extracellular levels of HMGB1 and IL-1β were investigated using the ELISA technique. The nanoparticles showed a dose dependent toxicity. Pyroptosis was triggered for LNCaP and MDA-MB-231 cells, and necroptosis for MDA-MB-231 cells. HCT116 cells experience apoptotic death and show increased levels of extracellular HMGB1. Our results suggest that in a manner dependent of the cellular microenvironment, AgAu NPs trigger mixed programmed cell death in P53 deficient MDA-MB-231 cells, while they also trigger IL-1β release in MDA-MB-231 and LNCaP cells and release of HMGB1 in HCT116 cells.

Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic Model

Abstract: Background Necroptosis is associated with the development of many tumors but in bladder cancer the tumor microenvironment (TME) and prognosis associated with necroptosis is unclear. Methods We classified patients into different necroptosis subtypes by the expression level of NRGS (necroptosis-related genes) and analyzed the relationship between necroptosis subtypes of bladder cancer and TME, then extracted differentially expressed genes (DEGS) of necroptosis subtypes, classified patients into different gene subtypes according to DEGS, and performed univariate COX analysis on DEGS to obtain prognosis-related DEGS. All patients included in the analysis were randomized into the Train and Test groups in a 1:1 ratio, and the prognostic model was obtained using the LASSO algorithm and multivariate COX analysis with the Train group as the sample, and external validation of the model was conducted using the GSE32894. Results Two necroptosis subtypes and three gene subtypes were obtained by clustering analysis and the prognosis-related DEGS was subjected to the LASSO algorithm and multivariate COX analysis to determine six predictors to construct the prognostic model using the formula: riskScore = CERCAM × 0.0035 + POLR1H × −0.0294 + KCNJ15 × −0.0172 + GSDMB × −0.0109 + EHBP1 × 0.0295 + TRIM38 × −0.0300. The results of the survival curve, roc curve, and risk curve proved the reliability of the prognostic model by validating the model with the test group and the results of the calibration chart of the Nomogram applicable to the clinic also showed its good accuracy. Necroptosis subtype A with high immune infiltration had a higher risk score than necroptosis subtype B, gene subtype B with low immune infiltration had a lower risk score than gene subtypes A and C, CSC index was negatively correlated with the risk score and drug sensitivity prediction showed that commonly used chemotherapeutic agents were highly sensitive to the high-risk group. Conclusion Our analysis of NRGS in bladder cancer reveals their potential role in TME, immunity, and prognosis. These findings may improve our understanding of necroptosis in bladder cancer and provide some reference for predicting prognosis and developing immunotherapies.

Immune landscape and risk prediction based on pyroptosis-related molecular subtypes in triple-negative breast cancer

Abstract: The survival outcome of triple-negative breast cancer (TNBC) remains poor, with difficulties still existing in prognosis assessment and patient stratification. Pyroptosis, a newly discovered form of programmed cell death, is involved in cancer pathogenesis and progression. The role of pyroptosis in the tumor microenvironment (TME) of TNBC has not been fully elucidated. In this study, we disclosed global alterations in 58 pyroptosis-related genes at somatic mutation and transcriptional levels in TNBC samples collected from The Cancer Genome Atlas and Gene Expression Omnibus databases. Based on the expression patterns of genes related to pyroptosis, we identified two molecular subtypes that harbored different TME characteristics and survival outcomes. Then, based on differentially expressed genes between two subtypes, we established a 12-gene score with robust efficacy in predicting short- and long-term overall survival of TNBC. Patients at low risk exhibited a significantly better prognosis, more antitumor immune cell infiltration, and higher expression of immune checkpoints including PD-1, PD-L1, CTLA-4, and LAG3. The comprehensive analysis of the immune landscape in TNBC indicated that alterations in pyroptosis-related genes were closely related to the formation of the immune microenvironment and the intensity of the anticancer response. The 12-gene score provided new information on the risk stratification and immunotherapy strategy for highly heterogeneous patients with TNBC.

Identification and analysis of necroptosis-associated signatures for prognostic and immune microenvironment evaluation in hepatocellular carcinoma

Abstract: Background Hepatocellular carcinoma remains the third most common cause of cancer-related deaths worldwide. Although great achievements have been made in resection, chemical therapies and immunotherapies, the pathogenesis and mechanism of HCC initiation and progression still need further exploration. Necroptosis genes have been reported to play an important role in HCC malignant activities, thus it is of great importance to comprehensively explore necroptosis-associated genes in HCC. Methods We chose the LIHC cohort from the TCGA, ICGC and GEO databases for this study. ConsensusClusterPlus was adopted to identify the necroptosis genes-based clusters, and LASSO cox regression was applied to construct the prognostic model based on necroptosis signatures. The GSEA and CIBERSORT algorithms were applied to evaluate the immune cell infiltration level. QPCR was also applied in this study to evaluate the expression level of genes in HCC. Results We identified three clusters, C1, C2 and C3. Compared with C2 and C3, the C1 cluster had the shortest overall survival time and highest immune score. The C1 was samples were significantly enriched in cell cycle pathways, some tumor epithelial-mesenchymal transition related signaling pathways, among others. The DEGs between the 3 clusters showed that C1 was enriched in cell cycle, DNA replication, cellular senescence, and p53 signaling pathways. The LASSO cox regression identified KPNA2, SLC1A5 and RAMP3 as prognostic model hub genes. The high risk-score subgroup had an elevated expression level of immune checkpoint genes and a higher TIDE score, which suggested that the high risk-score subgroup had a lower efficiency of immunotherapies. We also validated that the necroptosis signatures-based risk-score model had powerful prognosis prediction ability. Conclusion Based on necroptosis-related genes, we classified patients into 3 clusters, among which C1 had significantly shorter overall survival times. The proposed necroptosis signatures-based prognosis prediction model provides a novel approach in HCC survival prediction and clinical evaluation.