PARP-1 improves leukemia outcomes by inducing parthanatos during chemotherapy

Silica Nanoparticles Induce SH-SY5Y Cells Death Via PARP and Caspase Signaling Pathways

A growing stream of research indicates that exposure to Silica nanoparticles (SiNPs) can cause nervous system damage, leading to the occurrence of neurodegenerative diseases such as Alzheimer's disease. However, the specific mechanism by which SiNPs cause neuroblast injury remains unclear and requires further research. This study established an in vitro experimental model of SH-SY5Y cells exposed to SiNPs and observed cell growth through an inverted fluorescence microscope. Cell viability was measured using an MTT assay. The intracellular ROS and Ca2+ levels were detected by flow cytometry. Cell apoptosis was observed using both Hoechst33342 staining and TUNEL staining. The activities of SOD and ATPase and the content of ATP in the cells were tested by biochemical methods. The genes including parp-1, aif, par, ucp2, vdac and prdx3 were explored using quantitative real-time PCR. The expressions of PARP, AIF, PAR, Caspase-3, Caspase-9 and Cyt C proteins were evaluated by Western Blot. The immunofluorescence technique was used to observe the distribution of Parthanatos-related proteins induced by SiNPs. The results showed that SiNPs reduced cell survival rate, induced excessive ROS and Ca2+ overload, decreased SOD activity, ATPase activity, intracellular and mitochondrial ATP content, increased the expression of mitochondrial function and PARP pathway related genes, as well as PARP and Caspase pathway protein expression, ultimately inducing cell apoptosis. As a further test of the roles of PARP and Caspase pathways in SiNPs induced SH-SY5Y cells death, we selected the PARP inhibitor Olaparib and Caspase inhibitor Z-VAD, and the above effects were significantly improved after treatment with the inhibitors. Conclusively, this study confirmed that SiNPs can generate excessive ROS production in SH-SY5Y cells, alter mitochondrial function, and induce cell death through Parthanatos and caspase dependent apoptotic pathways, which can coexist and interact with each other.

Parthanatos and apoptosis: unraveling their roles in cancer cell death and therapy resistance

Cell death is a fundamental process that needs to be maintained to balance cellular functions and prevent disease. There are several cell death pathways; however, apoptosis and parthanatos are the most prominent and have important roles in cancer biology. As an extremely well-regulated process, apoptosis removes damaged or abnormal cells via caspase activation and mitochondrial involvement. Unlike in the healthy cells, the loss of ability to induce apoptosis in cancer permits tumor cells to survive and multiply out of control and contribute to tumor progression and therapy resistance. On the contrary, parthanatos is a caspase-independent metabolic collapse driven by poly (ADP-ribose) polymerase 1 (PARP1) overactivation, translocation of apoptosis-inducing factor (AIF), and complete DNA damage. Several cancer models are involved with parthanatos. Deoxypodophyllotoxin (DPT) induces parthanatos in glioma cells by excessive ROS generation, PARP1 upregulation, and AIF nuclear translocation. Like in acute myeloid leukemia (AML), the cannabinoid derivative WIN-55 triggers parthanatos, and the effects can be reversed by PARP inhibitors such as olaparib. Developing cancer treatment strategies involving advanced cancer treatment strategies relies on the interplay between apoptosis and parthanatos. However, such apoptosis-based cancer therapies tend to develop resistance, so there is an urgent need to look into alternative pathways like parthanatos, which may not always trigger apoptosis. In overcoming apoptosis resistance, there is evidence that combining apoptosis-inducing agents, such as BH3 mimetics, with PARP inhibitors synergistically enhances cell death. Oxidative stress modulators have been found to promote the execution of parthanatic and apoptotic pathways and allow treatment. In this review, apoptosis and parthanatos are thoroughly compared at the molecular level, and their roles in cancer pathogenesis as related to cancer therapeutic potential are discussed. We incorporate recent findings to demonstrate that not only can parthanatos be used to manage therapy resistance and enhance cancer treatment via the combination of parthanatos and apoptosis but also that immunity and bone deposition can feasibly be employed against long-circulating cancer stem cells to treat diverse forms of metastatic cancers.

Machine learning-based bulk RNA analysis reveals a prognostic signature of 13 cell death patterns and potential therapeutic target of SMAD3 in acute myeloid leukemia

BACKGROUND

Dysregulation or abnormality of the programmed cell death (PCD) pathway is closely related to the occurrence and development of many tumors, including acute myeloid leukemia (AML). Studying the abnormal characteristics of PCD pathway-related molecular markers can provide a basis for prognosis prediction and targeted drug design in AML patients.

METHODS

A total of 1394 genes representing 13 different PCD pathways were examined in AML patients and healthy donors. The upregulated genes were analyzed for their ability to predict overall survival (OS) individually, and these prognostic genes were subsequently combined to construct a PCD-related prognostic signature via an integrated approach consisting of 101 models based on ten machine learning algorithms. RNA transcriptome and clinical data from multiple AML cohorts (TCGA-AML, GSE106291, GSE146173 and Beat AML) were obtained to develop and validate the AML prognostic model.

RESULTS

A total of 214 upregulated PCD-related genes were identified in AML patients, 39 of which were proven to be prognostic genes in the training cohort. On the basis of the average C-index and number of model genes identified from the machine learning combinations, a PCD index was developed and validated for predicting AML OS. A prognostic nomogram was then generated and validated on the basis of the PCD index, age and ELN risk stratification in the Beat AML cohort and the GSE146173 cohort, revealing satisfactory predictive power (AUC values ≥ 0.7). With different mutation patterns, a higher PCD index was associated with a worse OS. The PCD index was significantly related to higher scores for immunosuppressive cells and mature leukemia cell subtypes. As the gene most closely related to the PCD index, the expression of SMAD3 was further validated in vitro. AML cells harboring KMT2A rearrangements were more sensitive to the SMAD3 inhibitor SIS3, and the expression of the autophagy-related molecular marker LC3 was increased in KMT2A-rearranged cell lines after SIS3 monotherapy and combined treatment.

CONCLUSION

The PCD index and SMAD3 gene expression levels have potential prognostic value and can be used in targeted therapy for AML, and these findings can lead to the development of effective strategies for the combined treatment of high-risk AML patients.

Multiomics integration and machine learning reveal prognostic programmed cell death signatures in gastric cancer

Gastric cancer (GC) is characterized by notable heterogeneity and the impact of molecular subtypes on treatment and prognosis. The role of programmed cell death (PCD) in cellular processes is critical, yet its specific function in GC is underexplored. This study applied multiomics approaches, integrating transcriptomic, epigenetic, and somatic mutation data, with consensus clustering algorithms to classify GC molecular subtypes and assess their biological and immunological features. A machine learning model was developed to create the Gastric Cancer Multi-Omics Programmed Cell Death Signature (GMPS), targeting PCD-related genes. We verified the expression of the GMPS hub genes using the RT-qPCR method. The prognostic influence of GMPS on GC was then evaluated. Single-cell analysis was performed to examine the heterogeneity of PCD characteristics in GC. Findings indicate that GMPS notably correlates with patient survival rates, tumor mutational burden (TMB), and copy number variations (CNV), demonstrating substantial prognostic predictive power. Moreover, GMPS is closely associated with the tumor microenvironment (TME) and immune therapy response. This research elucidates the molecular subtypes of GC, highlighting PCD's critical role in prognosis assessment. The relationship between GMPS and immune therapy response, alongside gastric cancer's microenvironmental features, provides insights for personalized treatment.

Emerging role of immunogenic cell death in cancer immunotherapy

Cancer immunotherapy, such as immune checkpoint blockade (ICB), has emerged as a groundbreaking approach for effective cancer treatment. Despite its considerable potential, clinical studies have indicated that the current response rate to cancer immunotherapy is suboptimal, primarily attributed to low immunogenicity in certain types of malignant tumors. Immunogenic cell death (ICD) represents a form of regulated cell death (RCD) capable of enhancing tumor immunogenicity and activating tumor-specific innate and adaptive immune responses in immunocompetent hosts. Therefore, gaining a deeper understanding of ICD and its evolution is crucial for developing more effective cancer therapeutic strategies. This review focuses exclusively on both historical and recent discoveries related to ICD modes and their mechanistic insights, particularly within the context of cancer immunotherapy. Our recent findings are also highlighted, revealing a mode of ICD induction facilitated by atypical interferon (IFN)-stimulated genes (ISGs), including polo-like kinase 2 (PLK2), during hyperactive type I IFN signaling. The review concludes by discussing the therapeutic potential of ICD, with special attention to its relevance in both preclinical and clinical settings within the field of cancer immunotherapy.

lncRNA Profiling of Exosomes and Its Communication Role in Regulating Silica-Stimulated Macrophage Apoptosis and Fibroblast Activation

Long-term silica particle exposure leads to interstitial pulmonary inflammation and fibrosis, called silicosis. Silica-activated macrophages secrete a wide range of cytokines resulting in persistent inflammation. In addition, silica-stimulated activation of fibroblast is another checkpoint in the progression of silicosis. The pathogenesis after silica exposure is complex, involving intercellular communication and intracellular signaling pathway transduction, which was ignored previously. Exosomes are noteworthy because of their crucial role in intercellular communication by delivering bioactive substances, such as lncRNA. However, the expression profile of exosomal lncRNA in silicosis has not been reported yet. In this study, exosomes were isolated from the peripheral serum of silicosis patients or healthy donors. The exosomal lncRNAs were profiled using high-throughput sequencing technology. Target genes were predicted, and functional annotation was performed using differentially expressed lncRNAs. Eight aberrant expressed exosomal lncRNAs were considered to play a key role in the process of silicosis according to the OPLS-DA. Furthermore, the increased expression of lncRNA MSTRG.43085.16 was testified in vitro. Its target gene PARP1 was critical in regulating apoptosis based on bioinformatics analysis. In addition, the effects of exosomes on macrophage apoptosis and fibroblast activation were checked based on a co-cultured system. Our findings suggested that upregulation of lncRNA MSTRG.43085.16 could regulate silica-induced macrophage apoptosis through elevating PARP1 expression, and promote fibroblast activation, implying that the exosomal lncRNA MSTRG.43085.16 might have potential as a biomarker for the early diagnosis of silicosis.