Programmed Cell Death Tunes Tumor Immunity

PANoptosis in cancer, the triangle of cell death

BACKGROUND

PANoptosis is a novel form of programmed cell death (PCD) found in 2019 that is regulated by the PANoptosome. PANoptosis combines essential features of pyroptosis, apoptosis, and necroptosis, forming a "death triangle" of cells. While apoptosis, pyroptosis, and necroptosis have been extensively studied for their roles in human inflammatory diseases and many other clinical conditions, historically they were considered as independent processes. However, emerging evidence indicates that these PCDs exhibit cross talk and interactions, resulting in the development of the concept of PANoptosis.

METHODS

In this review, we offer a concise summary of the fundamental mechanisms of apoptosis, pyroptosis, and necroptosis. We subsequently introduce the notion of PANoptosis and detail the assembly mechanism of the PANoptosome complex which is responsible for inducing cell death. We also describe some regulatory networks of PANoptosis.

RESULTS

PANoptosis now has been associated with various human diseases including cancer. Although the exact function of PANoptosis in each tumor is not fully understood, it represents a prospective avenue for cancer therapy, offering promise for advancements in cancer therapy.

CONCLUSIONS

In the future, in-depth study of PANoptosis will continue to help us in understanding the fundamental processes underlying cell death and provide scientific support for cancer research.

Higher expression of programmed cell death 4 (PDCD4) in acute myeloid leukemia is associated with better prognosis after chemotherapy

Acute myeloid leukemia (AML) is a common heterogeneous malignancy. Novel molecular markers aid diagnosis, patient sub-categorization, and optimal clinical decisions. Here, we explored the prognostic implications associated with the expression of the programmed cell death (PDCD) family of molecules in AML patients. Based on the findings from the TCGA and OHSU cohorts, we observed that the mRNA abundance of PDCD4 is significantly higher compared to other molecules within the PDCD family. Furthermore, high expression of PDCD4 was associated with predicted long-term patient survival in diagnosed AML patients. In the chemotherapy group, patients with high PDCD4 expression showed a tendency toward longer overall survival (OS) (P = 0.0266) and event-free survival (EFS) (P = 0.0008). High PDCD4 levels served as a favorable independent predictor for both OS and EFS in AML patients. However, subgroup analyses in the hematopoietic stem cell transplantation (HSCT) group revealed no significant difference in OS or EFS between individuals with high and low PDCD4 expression. Furthermore, in the low PDCD4 expression group, AML patients who underwent HSCT experienced improved survival outcomes (P = 0.0015), helping to mitigate the unfavorable prognosis associated with PDCD4 downregulation. Conversely, in the high PDCD4 expression group, HSCT offered a notable short-term survival advantage, while patients with high PDCD4 expression responded favorably to long-term survival through chemotherapy. Biological function enrichment showed that the expression of PDCD4 was correlated with complement and coagulation cascades, cell receptor signaling pathways, and cholesterol metabolism. The findings from this study will aid in better categorizing heterogeneous AML patients and guiding more appropriate clinical decision-making.

The Prognosis of Cancer Depends on the Interplay of Autophagy, Apoptosis, and Anoikis within the Tumor Microenvironment

Within the tumor microenvironment, the fight between the immune system and cancer influences tumor transformation. Metastasis formation is an important stage in the progression of cancer. This process is aided by cellular detachment and resistance to anoikis, which are achieved by altering intercellular signaling. Autophagy, specifically pro-survival autophagy, aids cancer cells in developing treatment resistance. Numerous studies have shown that autophagy promotes tumor growth and resistance to anoikis. To regulate protective autophagy, cancer-related genes phosphorylate both pro- and anti-apoptotic proteins. Apoptosis, a type of controlled cell death, eliminates damaged or unwanted cells. Anoikis is a type of programmed cell death in which cells lose contact with the extracellular matrix. The dysregulation of these cellular pathways promotes tumor growth and spread. Apoptosis, anoikis, and autophagy interact meticulously and differently depending on the cellular circumstances. For instance, autophagy can protect cancer cells from apoptosis by removing cellular components that are damaged and might otherwise trigger apoptotic pathways. Similarly, anoikis dysregulation can trigger autophagy by causing cellular harm and metabolic stress. In order to prevent or treat metastatic disease, specifically, targeting these cellular mechanisms may present a promising prospect for cancer therapy. This review discourses the state of our understanding of the molecular and cellular mechanisms underlying tumor transformation and the establishment of metastatic tumors. To enhance the prognosis for cancer, we highlight and discuss potential therapeutic approaches that target these processes and genes involved in them.

LncPCD: a manually curated database of experimentally supported associations between lncRNA-mediated programmed cell death and diseases

Programmed cell death (PCD) refers to controlled cell death that is conducted to keep the internal environment stable. Long noncoding RNAs (lncRNAs) participate in the progression of PCD in a variety of diseases. However, no specialized online repository is available to collect and store the associations between lncRNA-mediated PCD and diseases. Here, we developed LncPCD, a comprehensive database that provides information on experimentally supported associations of lncRNA-mediated PCD with diseases. The current version of LncPCD documents 6666 associations between five common types of PCD (apoptosis, autophagy, ferroptosis, necroptosis and pyroptosis) and 1222 lncRNAs in 331 diseases. We also manually curated a wealth of information: (1) 7 important lncRNA regulatory mechanisms, (2) 310 PCD-associated cell types in three species, (3) detailed information on lncRNA subcellular locations and (4) clinical applications for lncRNA-mediated PCD in diseases. Additionally, 10 single-cell sequencing datasets were integrated into LncPCD to characterize the dynamics of lncRNAs in diseases. Overall, LncPCD is an extremely useful resource for understanding the functions and mechanisms of lncRNA-mediated PCD in diseases. Database URL:  http://spare4.hospital.studio:9000/lncPCD/Home.jsp.

Metabolic reprogramming involves in transition of activated/resting CD4+ memory T cells and prognosis of gastric cancer

Background

Little is known on how metabolic reprogramming potentially prompts transition of activated and resting CD4+ memory T cells infiltration in tumor microenvironment of gastric cancer (GC). The study aimed to evaluate their interactions and develop a risk model for predicting prognosis in GC.

Methods

Expression profiles were obtained from TCGA and GEO databases. An immunotherapeutic IMvigor210 cohort was also enrolled. CIBERSORT algorithm was used to evaluate the infiltration of immune cells. The ssGSEA method was performed to assess levels of 114 metabolism pathways. Prognosis and correlation analysis were conducted to identify metabolism pathways and genes correlated with activated CD4+ memory T cells ratio (AR) and prognosis. An AR-related metabolism gene (ARMG) risk model was constructed and validated in different cohorts. Flow cytometry was applied to validate the effect of all-trans retinoic acid (ATRA) on CD4+ memory T cells.

Results

Since significantly inverse prognostic value and negative correlation of resting and activated CD4+ memory T cells, high AR level was associated with favorable overall survival (OS) in GC. Meanwhile, 15 metabolism pathways including retinoic acid metabolism pathway were significantly correlated with AR and prognosis. The ARMG risk model could classify GC patients with different outcomes, treatment responses, genomic and immune landscape. The prognostic value of the model was also confirmed in the additional validation, immunotherapy and pan-cancer cohorts. Functional analyses revealed that the ARMG model was positively correlated with pro-tumorigenic pathways. In vitro experiments showed that ATRA could inhibit levels of activated CD4+ memory T cells and AR.

Conclusion

Our study showed that metabolic reprogramming including retinoic acid metabolism could contribute to transition of activated and resting CD4+ memory T cells, and affect prognosis of GC patients. The ARMG risk model could serve as a new tool for GC patients by accurately predicting prognosis and response to treatment.

Diagnostic role and immune correlates of programmed cell death-related genes in hepatocellular carcinoma

Programmed cell death (PCD) is thought to have multiple roles in tumors. Here, the roles of PCD-related genes were comprehensively analyzed to evaluate their values in hepatocellular carcinoma (HCC) diagnosis and prognosis. Gene expression and single-cell data of HCC patients, and PCD-related genes were collected from public databases. The diagnostic and prognostic roles of differentially expressed PCD-related genes in HCC were explored by univariate and multivariate Cox regression analyses. Single-cell data were further analyzed for the immune cells and expression of feature genes. Finally, we evaluated the expression of genes by quantitative real-time polymerase chain reaction and Western blot, and the proportion of immune cells was detected by flow cytometry in HCC samples. We obtained 52 differentially expressed PCD-related genes in HCC, based on which the consensus clustering analysis cluster 2 was found to have a worse prognosis than cluster 1. Then 10 feature genes were identified using LASSO analysis, and programmed cell death index (PCDI) was calculated to divided HCC patients into high-PCDI and low-PCDI groups. Worse prognosis was observed in high-PCDI group. Cox regression analysis showed that PCDI is an independent prognostic risk factor for HCC patients. Additionally, SERPINE1 and G6PD of feature genes significantly affect patient survival. Macrophages and Tregs were significantly positively correlated with PCDI. G6PD mainly expressed in macrophages, SERPINE1 mainly expressed in fibroblast. The experimental results confirmed the high expression of SERPINE1 and G6PD in HCC compared with the control, and the infiltration level of macrophages and Treg in HCC was also obviously elevated. PCDI may be a new predictor for the diagnosis of patients with HCC. The association of SERPINE1 and G6PD with the immune environment will provide new clues for HCC therapy.

A prognostic risk model for programmed cell death and revealing TRIB3 as a promising apoptosis suppressor in renal cell carcinoma

Programmed cell death (PCD), a common modality of cell death, affects tumor development and acts as a target for tumor therapeutics. Many modalities of PCD regulate genesis, progression and metastasis of cancers, thus affecting the patients' prognosis, but the comprehensive molecular mechanisms of PCD in tumors are lacking, especially in renal cancer. Here, seventeen PRPCDGs were identified from 1257 genes associated with thirteen PCD modalities, which were highly differentially expressed and significantly affected patients' prognosis. Then, LASSO regression analysis of these PRPCDGs screened the 9-gene PRPCDGs risk signature in TCGA-KIRC database. The PRPCDGs risk signature was closely associated with the patients' prognosis and presented stable prediction efficacy for 5- and 7-year overall survival (OS) in three different cohorts of renal cancer. Immune cell infiltration, immune checkpoint expression and pathway enrichment (including GO, KEGG pathway, tumor-associated pathways and metabolism-associated pathways) were significantly different in the high- or low-PRPCDGs-risk group. Finally, we illustrated that TRIB3 might be a protumor factor responsible for the elevated proliferation and invasion capacities of renal cell carcinoma (RCC) cells. In summary, the PRPCDGs risk signature was developed and showed stable prediction efficacy for the prognosis of patients and that (such as TRIB3) could be a potential target for RCC management.

Head and neck squamous cell carcinoma-specific prognostic signature and drug sensitive subtypes based on programmed cell death-related genes

Background

As a complex group of malignancies, head and neck squamous cell carcinoma (HNSC) is one of the leading causes of cancer mortality. This study aims to establish a reliable clinical classification and gene signature for HNSC prognostic prediction and precision treatments.

Methods

A consensus clustering analysis was performed to group HNSC patients in The Cancer Genome Atlas (TCGA) database based on genes linked to programmed cell death (PCD). Differentially expressed genes (DEGs) between subtypes were identified using the "limma" R package. The TCGA prognostic signature and PCD-related prognostic genes were found using a least absolute shrinkage and selection operator (LASSO) regression analysis and univariate Cox regression analysis. The robustness of the LASSO analysis was validated using datasets GSE65858 and GSE41613. A cell counting kit-8 (CCK-8) test, Western blot, and real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) were used to evaluate the expression and viability of prognostic genes.

Results

Four molecular subtypes were identified in PCD-related genes. Subtype C4 had the best prognosis and the highest immune score, while subtype C1 exhibited the most unfavorable outcomes. Three hundred shared DEGs were identified among the four subtypes, and four prognostic genes (CTLA4, CAMK2N1, PLAU and CALML5) were used to construct a TCGA-HNSC prognostic model. High-risk patients manifested poorer prognosis, more inflammatory pathway enrichment, and lower immune cell infiltration. High-risk patients were more prone to immune escape and were more likely to be resistant to Cisplatin and 5-Fluorouracil. Prognosis prediction was validated in external datasets. The expression of CTLA4, CAMK2N1, PLAU and CALML5 was enhanced in CAL-27 and SCC-25 cell lines, and CALML5 inhibited CAL-27 and SCC-25 cell viability.

Conclusion

This study shares novel insights into HNSC classification and provides a reliable PCD-related prognostic signature for prognosis prediction and treatment for patients with HNSC.

Leveraging diverse cell-death patterns to predict the prognosis, immunotherapy and drug sensitivity of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) poses clinical challenges due to its varied prognosis, tumor microenvironment attributes, and responses to immunotherapy. We established a novel Programmed Cell Death-related Signature (PRS) for ccRCC assessment, derived through the Least Absolute Shrinkage and Selection Operator (LASSO) regression method. We validated PRS using the E-MTAB-1980 dataset and created PCD-related clusters via non-negative matrix factorization (NMF). Our investigation included an in-depth analysis of immune infiltration scores using various algorithms. Additionally, we integrated data from the Cancer Immunome Atlas (TCIA) for ccRCC immunotherapy insights and leveraged the Genomics of Drug Sensitivity in Cancer (GDSC) database to assess drug sensitivity models. We complemented our findings with single-cell sequencing data and employed the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and qRT-PCR to compare gene expression profiles between cancerous and paracancerous tissues. PRS serves as a valuable tool for prognostication, immune characterization, tumor mutation burden estimation, immunotherapy response prediction, and drug sensitivity assessment in ccRCC. We identify five genes with significant roles in cancer promotion and three genes with cancer-suppressive properties, further validated by qRT-PCR and CPTAC analyses, showcasing gene expression differences in ccRCC tissues. Our study introduces an innovative PCD model that amalgamates diverse cell death patterns to provide accurate predictions for clinical outcomes, mutational profiles, and immune characteristics in ccRCC. Our findings hold promise for advancing personalized treatment strategies in ccRCC patients.

Identification of necroptosis-related features in diabetic nephropathy and analysis of their immune microenvironent and inflammatory response

Background: Diabetic nephropathy (DN) was considered a severe microvascular complication of diabetes, which was recognized as the second leading cause of end-stage renal diseases. Therefore, identifying several effective biomarkers and models to diagnosis and subtype DN is imminent. Necroptosis, a distinct form of programmed cell death, has been established to play a critical role in various inflammatory diseases. Herein, we described the novel landscape of necroptosis in DN and exploit a powerful necroptosis-mediated model for the diagnosis of DN. Methods: We obtained three datasets (GSE96804, GSE30122, and GSE30528) from the Gene Expression Omnibus (GEO) database and necroptosis-related genes (NRGs) from the GeneCards website. Via differential expression analysis and machine learning, significant NRGs were identified. And different necroptosis-related DN subtypes were divided using consensus cluster analysis. The principal component analysis (PCA) algorithm was utilized to calculate the necroptosis score. Finally, the logistic multivariate analysis were performed to construct the necroptosis-mediated diagnostic model for DN. Results: According to several public transcriptomic datasets in GEO, we obtained eight significant necroptosis-related regulators in the occurrence and progress of DN, including CFLAR, FMR1, GSDMD, IKBKB, MAP3K7, NFKBIA, PTGES3, and SFTPA1 via diversified machine learning methods. Subsequently, employing consensus cluster analysis and PCA algorithm, the DN samples in our training set were stratified into two diverse necroptosis-related subtypes based on our eight regulators' expression levels. These subtypes exhibited varying necroptosis scores. Then, we used various functional enrichment analysis and immune infiltration analysis to explore the biological background, immune landscape and inflammatory status of the above subtypes. Finally, a necroptosis-mediated diagnostic model was exploited based on the two subtypes and validated in several external verification datasets. Moreover, the expression level of our eight regulators were verified in the singe-cell level and glomerulus samples. And we further explored the relationship between the expression of eight regulators and the kidney function of DN. Conclusion: In summary, our necroptosis scoring model and necroptosis-mediated diagnostic model fill in the blank of the relationship between necroptosis and DN in the field of bioinformatics, which may provide novel diagnostic insights and therapy strategies for DN.

A novel model based on disulfidptosis-related genes to predict prognosis and therapy of bladder urothelial carcinoma

PURPOSE

Disulfidptosis is a novel type of cell death induced by disulphide stress that depends on the accumulation of cystine disulphide, causing cytotoxicity and triggering cell death. However, the direct prognostic effect and regulatory mechanism of disulfidptosis-related genes in bladder urothelial carcinoma (BLCA) remain unclear.

METHODS

To explore the role of 10 disulfidptosis-related genes, the multiomic data of 10 genes were comprehensively analysed. Next, based on seven disulfidptosis-related differentially expressed genes, a novel disulfidptosis-related gene score was developed to help predict the prognosis of BLCA. Immunohistochemistry, EDU, Real-time PCR and western blot were used to verify the model.

RESULTS

Significant functional differences were found between the high- and low-risk score groups, and samples with a higher risk score were more malignant. Furthermore, the tumour exclusion and Tumour Immune Dysfunction and Exclusion scores of the high-risk score group were higher than those of the low-risk score group. The risk score was positively correlated with the expression of immune checkpoints. Drug sensitivity analyses revealed that the low-risk score group had a higher sensitivity to cisplatin, doxorubicin, docetaxel and gemcitabine than the high-risk score group. Moreover, the expression of the TM4SF1 was positively correlated with the malignancy degree of BLCA, and the proliferation ability of BLCA cells was reduced after knockdown TM4SF1.

CONCLUSION

The present study results suggest that disulfidptosis-related genes influence the prognosis of BLCA through their involvement in immune cell infiltration. Thus, these findings indicate the role of disulfidptosis in BLCA and its potential regulatory mechanisms.

Predicting Prognosis and Immunotherapy Response in Multiple Cancers Based on the Association of PANoptosis-Related Genes with Tumor Heterogeneity

PANoptosis is a newly recognized inflammatory pathway for programmed cell death (PCD). It participates in regulating the internal environment, homeostasis, and disease process in various complex ways and plays a crucial role in tumor development, but its mechanism of action is still unclear. In this study, we comprehensively analyzed the expression of 14 PANoptosis-related genes (PANRGs) in 28 types of tumors. Most PANRGs are upregulated in tumors, including Z-DNA binding protein 1 (ZBP1), nucleotide-binding oligomerization domain (NOD)-like receptor pyrin domain-containing 3 (NLRP3), caspase (CASP) 1, CASP6, CASP8, PYCARD, FADD, MAP3K7, RNF31, and RBCK1. PANRGs are highly expressed in GBM, LGG, and PAAD, while their levels in ACC are much lower than those in normal tissues. We found that both the CNV and SNV gene sets in BLCA are closely related to survival performance. Subsequently, we conducted clustering and LASSO analysis on each tumor and found that the inhibitory and the stimulating immune checkpoints positively correlate with ZBP1, NLRP3, CASP1, CASP8, and TNFAIP3. The immune infiltration results indicated that KIRC is associated with most infiltrating immune cells. According to the six tumor dryness indicators, PANRGs in LGG show the strongest tumor dryness but have a negative correlation with RNAss. In KIRC, LIHC, and TGCT, most PANRGs play an important role in tumor heterogeneity. Additionally, we analyzed the linear relationship between PANRGs and miRNA and found that MAP3K7 correlates to many miRNAs in most cancers. Finally, we predicted the possible drugs for targeted therapy of the cancers. These data greatly enhance our understanding of the components of cancer and may lead to the discovery of new biomarkers for predicting immunotherapy response and improving the prognosis of cancer patients.

Identification of pyroptosis-related lncRNA subtype and signature predicts the prognosis in bladder cancer

Pyroptosis is a new type of programmed cell death involved in all stages of tumorigenesis. Herein, a comprehensive study was conducted to evaluate the prognostic significance of pyroptosis-related lncRNAs in bladder cancer. Consensus clustering analysis was performed to identify the subclusters of bladder cancer. The prognostic pyroptosis-related lncRNA signature was constructed using LASSO Cox regression analysis. Consensus clustering identified 2 clusters of bladder cancer. Interestingly, significant differences in the ESTIMAE score, immune cell infiltration and immune checkpoint expression were obtained between the 2 clusters. A signature consisting of 11 pyroptosis-related lncRNAs was established and it had a good performance in predicting the overall survival rate of bladder cancer, with an AUC of 0.713. Moreover, pyroptosis-related lncRNA signature acted as a risk factor in bladder cancer. Bladder cancer patients with high-risk score had a higher tumor grade and higher clinical stage. A significant correlation was obtained between the risk score and immune cell infiltration. The expression of most checkpoints was higher in bladder cancer patients with high-risk score. A novel pyroptosis-related lncRNA signature was identified with prognostic value for bladder cancer patients. Pyroptosis-related lncRNAs have a potential role in cancer immunology and may serve as prognostic or therapeutic targets in bladder cancer.

Targeting Ferroptosis in Bone-Related Diseases: Facts and Perspectives

Ferroptosis is a new cell fate decision discovered in recent years. Unlike apoptosis, autophagy or pyroptosis, ferroptosis is characterized by iron-dependent lipid peroxidation and mitochondrial morphological changes. Ferroptosis is involved in a variety of physiological and pathological processes. Since its discovery, ferroptosis has been increasingly studied concerning bone-related diseases. In this review, we focus on the latest research progress and prospects, summarize the regulatory mechanisms of ferroptosis, and discuss the role of ferroptosis in the pathogenesis of bone-related diseases, such as osteoporosis (OP), osteoarthritis (OA), rheumatoid arthritis (RA), and osteosarcoma (OS), as well as its therapeutic potential.

Machine Learning Developed a Programmed Cell Death Signature for Predicting Prognosis, Ecosystem, and Drug Sensitivity in Ovarian Cancer

Background

Ovarian cancer (OC) is the leading cause of gynecological cancer death and the fifth most common cause of cancer-related death in women in America. Programmed cell death played a vital role in tumor progression and immunotherapy response in cancer.

Methods

The prognostic cell death signature (CDS) was constructed with an integrative machine learning procedure, including 10 methods, using TCGA, GSE14764, GSE26193, GSE26712, GSE63885, and GSE140082 datasets. Several methods and single-cell analysis were used to explore the correlation between CDS and the ecosystem and therapy response of OC patients.

Results

The prognostic CDS constructed by the combination of StepCox (n = both) + Enet (alpha = 0.2) acted as an independent risk factor for the overall survival (OS) of OC patients and showed stable and powerful performance in predicting the OS rate of OC patients. Compared with tumor grade, clinical stage, and many developed signatures, the CDS had a higher C-index. OC patients with low CDS score had a higher level of CD8+ cytotoxic T, B cell, and M1-like macrophage, representing a related immunoactivated ecosystem. A low CDS score indicated a higher PD1 and CTLA4 immunophenoscore, higher tumor mutation burden score, lower tumor immune dysfunction and exclusion score, and lower tumor escape score in OC, demonstrating a better immunotherapy response. OC patients with high CDS score had a higher gene set score of cancer-related hallmarks, including angiogenesis, epithelial-mesenchymal transition, hypoxia, glycolysis, and notch signaling.

Conclusion

The current study constructed a novel CDS for OC, which could serve as an indicator for predicting the prognosis, ecosystem, and immunotherapy benefits of OC patients.

Efferocytosis Nanoinhibitors to Promote Secondary Necrosis and Potentiate the Immunogenicity of Conventional Cancer Therapies for Improved Therapeutic Benefits

Efferocytosis of apoptotic cancer cells by tumor-associated macrophages or other phagocytes is reported to promote tumor immunosuppression by preventing them from secondary necrosis, which would lead to the release of intracellular components and thus enhanced immunogenicity. Therefore, current apoptosis-inducing cancer treatments (e.g., chemotherapy and radiotherapy) are less satisfactory in eliciting antitumor immunity. Herein, a nanoparticulate inhibitor of efferocytosis is prepared by encapsulating BMS777607, a hydrophobic inhibitor of receptors in macrophages responsible for phosphatidylserine-dependent efferocytosis, with biocompatible poly(lactic-co-glycolic acid) and its amphiphilic derivatives. The yielded nano-BMS can inhibit the efferocytosis of apoptotic cancer cells, thus redirecting them to immunogenic secondary necrosis. As a result, intratumorally injected nano-BMS is capable of activating both innate and adaptive antitumor immunity to achieve greatly improved therapeutic responses, when synergized with nonimmunogenic chemotherapy by cisplatin, immunogenic chemotherapy by oxaliplatin, or radiotherapy by external beams. Moreover, we further demonstrate that the inhalation of nano-BMS could significantly promote the efficacy of cisplatin chemotherapy to suppress tumor lung metastases. Therefore, this study highlights a general strategy to potentiate the immunogenicity of different cancer treatments by suppressing efferocytosis-propelled tumor immunosuppression, showing tremendous clinical potential in rescuing existing cancer therapies for more effective treatment.

METTL3-METTL14 complex induces necroptosis and inflammation of vascular smooth muscle cells via promoting N6 methyladenosine mRNA methylation of receptor-interacting protein 3 in abdominal aortic aneurysms

Abdominal aortic aneurysms (AAA) have the highest incidence and rupture rate of all aortic aneurysms. The N6 methyladenosine (m6A) modification is closely associated with angiotensin (Ang II)-induced aortic diseases. This study aimed to identify whether the m6A writer METTL3/METTL4 regulates rip3 mRNA expression in AAA. To induce the mouse AAA model, apolipoprotein E-deficient (ApoE-/-) mice were subcutaneously infused with Ang II, and C57BL/6 mice were infused with type I elastase. Vascular smooth muscle cells (VSMCs) were induced with Ang II. Necroptosis was detected using an Annexin V-FITC/PI apoptosis detection kit, and ELISA assays measured inflammatory cytokines. The RNA immunoprecipitation-qPCR determined the methylated rip3 mRNA level. The increased expressions of inflammatory factors, aortic adventitia injury, degradation of elastin, and CD68-positive cells suggested the successful establishment of mouse AAA models. In AAA aorta wall tissues, the m6A modification level and the expression of METTL3/METTL14 were elevated. In Ang II-induced VSMCs, necroptosis and inflammatory cytokines in the supernatants were increased. RNA immunoprecipitation and co-immunoprecipitation assays confirmed the binding between the METTL3-METTL14 complex and rip3 mRNA, the interaction between YTHDF3 and rip3 mRNA, and between the METTL3-METTL14 complex and SMAD2/3. Interference with METTL3/METTL14 attenuated VSMC necroptosis, inflammatory response, and the AAA pathological process in vivo. The METTL3-METTL14 complex, which was increased by the activation of the SMAD2/3, elevated the m6A modification of rip3 mRNA by promoting the binding between YTHDF3 and rip3 mRNA, thus contributing to the progression of AAA. The activation of SMAD2/3 in VSMCs of abdominal aortic wall tissues is stimulated by Ang II. Subsequently, it promotes METTL3 METTL14 complex mediated m6A modification of rip3 mRNA. Meanwhile, the level of rip3 mRNA becomes more stable under the m6A reader of YTHDF3, which increases the protein level of RIP3 and further induces VSMC necroptosis. In addition, cell debris induces inflammatory factors in neighboring VSMCs and recruit monocytes/macrophages to the lesion.

Activation of STING by SAMHD1 Deficiency Promotes PANoptosis and Enhances Efficacy of PD-L1 Blockade in Diffuse Large B-cell Lymphoma

Genomic instability is a significant driver of cancer. As the sensor of cytosolic DNA, the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway plays a critical role in regulating anti-tumor immunity and cell death. However, the role and regulatory mechanisms of STING in diffuse large B-cell lymphoma (DLBCL) are still undefined. In this study, we reported that sterile alpha motif and HD domain-containing protein 1 (SAMHD1) deficiency induced STING expression and inhibited tumor growth in DLBCL. High level of SAMHD1 was associated with poor prognosis in DLBCL patients. Down-regulation of SAMHD1 inhibited DLBCL cell proliferation both in vitro and in vivo. Moreover, we found that SAMHD1 deficiency induced DNA damage and promoted the expression of DNA damage adaptor STING. STING overexpression promoted the formation of Caspase 8/RIPK3/ASC, further leading to MLKL phosphorylation, Caspase 3 cleavage, and GSDME cleavage. Up-regulation of necroptotic, apoptotic, and pyroptotic effectors indicated STING-mediated PANoptosis. Finally, we demonstrated that the STING agonist, DMXAA, enhanced the efficacy of a PD-L1 inhibitor in DLBCL. Our findings highlight the important role of STING-mediated PANoptosis in restricting DLBCL progression and provide a potential strategy for enhancing the efficacy of immune checkpoint inhibitor agents in DLBCL.

A novel defined risk signature of cuproptosis-related long non-coding RNA for predicting prognosis, immune infiltration, and immunotherapy response in lung adenocarcinoma

Background: Cuproptosis is a newly discovered non-apoptotic form of cell death that may be related to the development of tumors. Nonetheless, the potential role of cuproptosis-related lncRNAs in tumor immunity formation and patient-tailored treatment optimization of lung adenocarcinoma (LUAD) is still unclear. Methods: RNA sequencing and survival data of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) database for model training. The patients with LUAD in GSE29013, GSE30219, GSE31210, GSE37745, and GSE50081 were used for validation. The proofed cuproptosis-related genes were extracted from the previous studies. The Pearson correlation was applied to select cuproptosis-related lncRNAs. We chose differentially expressed cuproptosis-related lncRNAs in the tumor and normal tissues and allowed them to go to a Cox regression and a LASSO regression for a lncRNA signature that predicts the LUAD prognosis. Kaplan-Meier estimator, Cox model, ROC, tAUC, PCA, nomogram predictor, decision curve analysis, and real-time PCR were further deployed to confirm the model's accuracy. We examined this model's link to other regulated cell death forms. Applying TMB, immune-related signatures, and TIDE demonstrated the immunotherapeutic capabilities of signatures. We evaluated the relationship of our signature to anticancer drug sensitivity. GSEA, immune infiltration analysis, and function experiments further investigated the functional mechanisms of the signature and the role of immune cells in the prognostic power of the signature. Results: An eight-lncRNA signature (TSPOAP1-AS1, AC107464.3, AC006449.7, LINC00324, COLCA1, HAGLR, MIR4435-2HG, and NKILA) was built and demonstrated owning prognostic power by applied to the validation cohort. Each signature gene was confirmed differentially expressed in the real world by real-time PCR. The eight-lncRNA signature correlated with 2321/3681 (63.05%) apoptosis-related genes, 11/20 (55.00%) necroptosis-related genes, 34/50 (68.00%) pyroptosis-related genes, and 222/380 (58.42%) ferroptosis-related genes. Immunotherapy analysis suggested that our signature may have utility in predicting immunotherapy efficacy in patients with LUAD. Mast cells were identified as key players that support the predicting capacity of the eight-lncRNA signature through the immune infiltrating analysis. Conclusion: In this study, an eight-lncRNA signature linked to cuproptosis was identified, which may improve LUAD management strategies. This signature may possess the ability to predict the effect of LUAD immunotherapy. In addition, infiltrating mast cells may affect the signature's prognostic power.

Early low blood MALT1 expression levels forecast better efficacy of PD‑1 inhibitor‑based treatment in patients with metastatic colorectal cancer

Mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1) modulates colorectal cancer (CRC) malignant behaviors and tumor immune escape. The present study aimed to explore the association of MALT1 with treatment response and survival time among patients with metastatic CRC (mCRC) after programmed cell death protein-1 (PD-1) inhibitor-based treatment. MALT1 from the blood samples of 75 patients with unresectable mCRC receiving PD-1 inhibitor-based treatment at baseline and after 2-cycle treatment, as well as 20 healthy controls (HCs), was detected by reverse transcription-quantitative PCR. In the patients with mCRC, the objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS) and overall survival (OS) were calculated. MALT1 expression was elevated in patients with mCRC compared with that in HCs (P<0.001). In patients with mCRC, MALT1 expression was positively correlated with multiple (vs. single) metastasis (P=0.032) and peritoneum metastasis (P=0.029). MALT1 levels before treatment were decreased in ORR patients vs. non-ORR patients (P=0.043) and in DCR patients vs. non-DCR patients (P=0.007). Additionally, MALT1 expression was reduced after treatment compared with that before treatment (P<0.001). Meanwhile, MALT1 expression after treatment was notably decreased in ORR patients vs. non-ORR patients (P<0.001) and in DCR patients vs. non-DCR patients (P<0.001). Furthermore, a low MALT1 level before treatment was associated with longer PFS (P=0.030) and OS (P=0.025) times. Decreased MALT1 expression after treatment and a decline in MALT1 expression of >30% after treatment (ratio to MALT1 before treatment) (both P≤0.001) presented more significant associations with prolonged PFS and OS times. In conclusion, early low levels of blood MALT1 during therapy may predict an improved response to PD-1 inhibitor-based treatment and survival time in patients with mCRC.

Bridging Pyroptosis and Immunity: A Comprehensive Study of the Pyroptosis-Related Long Non-Coding RNA Signature in Breast Cancer

Breast cancer continuously poses serious clinical challenges to human health due to its intrinsic heterogenicity and evolving drug resistance. Recently, increasing evidence has shown that pyroptosis, known as a programmed and inflammatory form of cell death, participates in tumorigenesis, progression, and remodeling of the tumor immune microenvironment (TIME). However, a comprehensive insight into pyroptosis-related signatures for breast cancer remains elusive. The current study established a pyroptosis-related lncRNA signature using transcriptome data and corresponding clinical information from The Cancer Genome Atlas (TCGA). Pyroptosis-related gene clusters, the associated differential expression in breast cancer patients' subtypes, and the potential mechanisms were all discussed. This integrative analysis revealed a unique signature underpinning the dichotomy of breast cancer progression and survival outcomes. Interestingly, the pyroptosis-related lncRNA signature was revealed as closely intertwined with the TIME. A correlation was established between the pyroptosis-related LncRNA signature and the TIME, underlying the mutual effect between pyroptosis and the immune responses implicated in breast cancer. The findings in this work underline the critical role exerted by pyroptosis in breast cancer, providing new insights into disease progression, prognosis, and therapeutic potential. This work has been poised to provide new avenues for personalized, immune-based cancer therapeutics by enhancing our understanding of pyroptosis in breast cancer.

PANoptosis-related molecular subtype and prognostic model associated with the immune microenvironment and individualized therapy in pancreatic cancer

Background

PANoptosis is an inflammatory type of programmed cell death regulated by PANopotosome. Mounting evidence has shown that PANoptosis could be involved in cancer pathogenesis and the tumor immune microenvironment. Nevertheless, there have been no studies on the mechanism of PANoptosis on pancreatic cancer (PC) pathogenesis.

Methods

We downloaded the data on transcriptomic and clinical features of PC patients from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. Additionally, the data on copy number variation (CNV), methylation and somatic mutations of genes in 33 types of cancers were obtained from TCGA. Next, we identified the PANoptosis-related molecular subtype using the consensus clustering analysis, and constructed and validated the PANoptosis-related prognostic model using LASSO and Cox regression analyses. Moreover, RT-qPCR was performed to determine the expression of genes involved in the model.

Results

We obtained 66 PANoptosis-related genes (PANRGs) from published studies. Of these, 24 PC-specific prognosis-related genes were identified. Pan-cancer analysis revealed complex genetic changes, including CNV, methylation, and mutation in PANRGs were identified in various cancers. By consensus clustering analysis, PC patients were classified into two PANoptosis-related patterns: PANcluster A and B. In PANcluster A, the patient prognosis was significantly worse compared to PANcluster B. The CIBERSORT algorithm showed a significant increase in the infiltration of CD8⁺ T cells, monocytes, and naïve B cells, in patients in PANcluster B. Additionally, the infiltration of macrophages, activated mast cells, and dendritic cells were higher in patients in PANcluster A. Patients in PANcluster A were more sensitive to erlotinib, selumetinib and trametinib, whereas patients in PANcluster B were highly sensitive to irinotecan, oxaliplatin and sorafenib. Moreover, we constructed and validated the PANoptosis-related prognostic model to predict the patient's survival. Finally, the GEPIA and Human Protein Atlas databases were analyzed, and RT-qPCR was performed. Compared to normal tissues, a significant increase in CXCL10 and ITGB6 (associated with the model) expression was observed in PC tissues.

Conclusion

We first identified the PANoptosis-related molecular subtypes and established a PANoptosis-related prognostic model for predicting the survival of patients with PC. These results would aid in exploring the mechanisms of PANoptosis in PC pathogenesis.

The PANoptosis-related signature indicates the prognosis and tumor immune infiltration features of gliomas

Background

Gliomas are the most common primary tumors of the central nervous system, with high heterogeneity and highly variable survival rates. Accurate classification and prognostic assessment are key to the selection of treatment strategies. One hallmark of the tumor is resistance to cell death. PANoptosis, a novel mode of programmed cell death, has been frequently reported to be involved in the innate immunity associated with pathogen infection and played an important role in cancers. However, the intrinsic association of PANoptosis with glioma requires deeper investigation.

Methods

The genetics and expression of the 17 reported PANoptosome-related genes were analyzed in glioma. Based on these genes, patients were divided into two subtypes by consensus clustering analysis. After obtaining the differentially expressed genes between clusters, a prognostic model called PANopotic score was constructed after univariate Cox regression, LASSO regression, and multivariate Cox regression. The expression of the 5 genes included in the PANopotic score was also examined by qPCR in our cohort. The prognostic differences, clinical features, TME infiltration status, and immune characteristics between PANoptotic clusters and score groups were compared, some of which even extended to pan-cancer levels.

Results

Gene mutations, CNVs and altered gene expression of PANoptosome-related genes exist in gliomas. Two PANoptotic clusters were significantly different in prognosis, clinical features, immune characteristics, and mutation landscapes. The 5 genes included in the PANopotic score had significantly altered expression in glioma samples in our cohort. The high PANoptotic score group was inclined to show an unfavorable prognosis, lower tumor purity, worse molecular genetic signature, and distinct immune characteristics related to immunotherapy. The PANoptotic score was considered as an independent prognostic factor for glioma and showed superior prognostic assessment efficacy over several reported models. PANopotic score was included in the nomogram constructed for the potential clinical prognostic application. The associations of PANoptotic score with prognostic assessment and tumor immune characteristics were also reflected at the pan-cancer level.

Conclusion

Molecular subtypes of glioma based on PANoptosome-related genes were proposed and PANoptotic score was constructed with different clinical characteristics of anti-tumor immunity. The potential intrinsic association between PANoptosis and glioma subtypes, prognosis, and immunotherapy was revealed.

Programmed Cell Death in Asthma: Apoptosis, Autophagy, Pyroptosis, Ferroptosis, and Necroptosis

Bronchial asthma is a complex heterogeneous airway disease, which has emerged as a global health issue. A comprehensive understanding of the different molecular mechanisms of bronchial asthma may be an efficient means to improve its clinical efficacy in the future. Increasing research evidence indicates that some types of programmed cell death (PCD), including apoptosis, autophagy, pyroptosis, ferroptosis, and necroptosis, contributed to asthma pathogenesis, and may become new targets for future asthma treatment. This review briefly discusses the molecular mechanism and signaling pathway of these forms of PCD focuses on summarizing their roles in the pathogenesis and treatment strategies of asthma and offers some efficient means to improve clinical efficacy of therapeutics for asthma in the near future.

The applications of nanozymes in cancer therapy: based on regulating pyroptosis, ferroptosis and autophagy of tumor cells

Nanozymes are nanomaterials with catalytic properties similar to those of natural enzymes, and they have recently been collectively identified as a class of innovative artificial enzymes. Nanozymes are widely used in various fields, such as biomedicine, due to their high catalytic activity and stability. Nanozymes can trigger changes in reactive oxygen species (ROS) levels in cells and the activation of inflammasomes, leading to the programmed cell death (PCD), including the pyroptosis, ferroptosis, and autophagy, of tumor cells. In addition, some nanozymes consume glucose, starving cancer cells and thus accelerating tumor cell death. In addition, the electric charge of the structure and the catalytic activity of nanozymes are sensitive to external factors such as light and electric and magnetic fields. Therefore, nanozymes can be used with different therapeutic methods, such as chemodynamic therapy (CDT), photodynamic therapy (PDT) and sonodynamic therapy (SDT), to achieve highly efficient antitumor effects. Many cancer therapies induce tumor cell death via the pyroptosis, ferroptosis, and autophagy of tumor cells mediated by nanozymes. We review the mechanisms of pyroptosis, ferroptosis, and autophagy in tumor development, as well as the potential application of nanozymes to regulate pyroptosis, ferroptosis, and autophagy in tumor cells.

Exploring PANoptosis in breast cancer based on scRNA-seq and bulk-seq

Background

PANoptosis, a cell death pathway involving pyroptosis, apoptosis, and necroptosis, is pivotal in the development of malignancy. However, in the field of breast cancer, the interaction between PANoptosis and tumor cells has not been thoroughly explored.

Methods

We downloaded breast cancer data and GSE176078 single-cell sequencing dataset from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases to obtain PANoptosis-associated genes. To construct prognostic models, COX and LASSO regression was used to identify PANoptosis-associated genes with prognostic value. Finally, immune infiltration analysis and differential analysis of biological functions were performed.

Results

Risk grouping was performed according to the prognostic model constructed by COX regression and LASSO regression. The low-risk group showed a better prognosis (P < 0.05) and possessed higher levels of immune infiltration and expression of immune checkpoint-related genes. In addition, the lower the risk score, the higher the degree of microsatellite instability (MSI). Meanwhile, radixin (RDX), the gene with the highest hazard ratio (HR) value among PANoptosis prognosis-related genes, was explicitly expressed in artery Iendothelial cells (ECs) and was widely involved in signaling pathways such as immune response and cell proliferation, possessing rich biological functions.

Conclusion

We demonstrated the potential of PANoptosis-based molecular clustering and prognostic features in predicting the survival of breast cancer patients. Furthermore, this study has led to a deeper understanding of the role of PANoptosis in breast cancer and has the potential to provide new directions for immunotherapy of breast cancer.

V. J, Pal S, Nair BG, Kar R, Mishra N. Paraptosis: a unique cell death mode for targeting cancer

Programmed cell death (PCD) is the universal process that maintains cellular homeostasis and regulates all living systems' development, health and disease. Out of all, apoptosis is one of the major PCDs that was found to play a crucial role in many disease conditions, including cancer. The cancer cells acquire the ability to escape apoptotic cell death, thereby increasing their resistance towards current therapies. This issue has led to the need to search for alternate forms of programmed cell death mechanisms. Paraptosis is an alternative cell death pathway characterized by vacuolation and damage to the endoplasmic reticulum and mitochondria. Many natural compounds and metallic complexes have been reported to induce paraptosis in cancer cell lines. Since the morphological and biochemical features of paraptosis are much different from apoptosis and other alternate PCDs, it is crucial to understand the different modulators governing it. In this review, we have highlighted the factors that trigger paraptosis and the role of specific modulators in mediating this alternative cell death pathway. Recent findings include the role of paraptosis in inducing anti-tumour T-cell immunity and other immunogenic responses against cancer. A significant role played by paraptosis in cancer has also scaled its importance in knowing its mechanism. The study of paraptosis in xenograft mice, zebrafish model, 3D cultures, and novel paraptosis-based prognostic model for low-grade glioma patients have led to the broad aspect and its potential involvement in the field of cancer therapy. The co-occurrence of different modes of cell death with photodynamic therapy and other combinatorial treatments in the tumour microenvironment are also summarized here. Finally, the growth, challenges, and future perspectives of paraptosis research in cancer are discussed in this review. Understanding this unique PCD pathway would help to develop potential therapy and combat chemo-resistance in various cancer.

Identification of PANoptosis-relevant subgroups to evaluate the prognosis and immune landscape of patients with liver hepatocellular carcinoma

Liver hepatocellular carcinoma (LIHC) is one of the most common malignant tumors, which is difficult to be diagnosed at an early stage due to its poor prognosis. Despite the fact that PANoptosis is important in the occurrence and development of tumors, no bioinformatic explanation related to PANoptosis in LIHC can be found. A bioinformatics analysis on the data of LIHC patients in TCGA database was carried out on the basis of previously identified PANoptosis-related genes (PRGs). LIHC patients were divided into two PRG clusters whose gene characteristics of differentially expressed genes (DEGs) were discussed. According to DEGs, the patients were further divided into two DEG clusters, and prognostic-related DEGs (PRDEGs) were applied to risk score calculation, the latter of which turned out to be practical in identifying the relationship among risk score, patient prognosis, and immune landscape. The results suggested that PRGs and relevant clusters were bound up with the survival and immunity of patients. Moreover, the prognostic value based on two PRDEGs was evaluated, the risk scoring model was constructed, and the nomogram model for predicting the survival rate of patients was further developed. Therefore, it was found that the prognosis of the high-risk subgroup was poor. Additionally, three factors, namely, the abundance of immune cells, the expression of immune checkpoints, and immunotherapy and chemotherapy were considered to be associated with the risk score. RT-qPCR results indicated higher positive expression of CD8A and CXCL6 in both LIHC tissues and most human liver cancer cell lines. In summary, the results suggested that PANoptosis was bound up with LIHC-related survival and immunity. Two PRDEGs were identified as potential markers. Thus, the understanding of PANoptosis in LIHC was enriched, with some strategies provided for the clinical therapy of LIHC.

A Novel Defined PANoptosis-Related miRNA Signature for Predicting the Prognosis and Immune Characteristics in Clear Cell Renal Cell Carcinoma: A miRNA Signature for the Prognosis of ccRCC

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent cancers, and PANoptosis is a distinct, inflammatory-programmed cell death regulated by the PANoptosome. The essential regulators of cancer occurrence and progression are microRNAs (miRNAs). However, the potential function of PANoptosis-related microRNAs (PRMs) in ccRCC remains obscure. This study retrieved ccRCC samples from The Cancer Genome Atlas database and three Gene Expression Omnibus datasets. PRMs were recognized based on previous reports in the scientific literature. Regression analyses were used to identify the prognosis PRMs and construct a PANoptosis-related miRNA prognostic signature based on the risk score. We discovered that high-risk patients had poorer survival prognoses and were significantly linked to high-grade and advanced-stage tumors, using a variety of R software packages and web analysis tools. Furthermore, we demonstrated that the low-risk group had significant changes in their metabolic pathways. In contrast, the high-risk group was characterized by high immune cell infiltration, immune checkpoint expression, and low half-maximum inhibition concentration (IC50) values of chemotherapeutic agents. This suggests that high-risk patients may benefit more from immunotherapy and chemotherapy. In conclusion, we constructed a PANoptosis-related microRNA signature and revealed its potential significance in clinicopathological features and tumor immunity, thereby providing new precise treatment strategies.

A Pan-Cancer Analysis of Prognostic and Immunological Roles for Cell Death Genes

The dysregulation of cell death is closely associated with the development, progression, tumor microenvironment (TME), and prognosis of cancer. However, there is no study that comprehensively explores the prognostic and immunological role of cell death in human pan-cancer. We used published human pan-cancer RNA-sequencing and clinical data to explore the prognostic and immunological roles of programmed cell death, which included apoptosis, autophagy, ferroptosis, necroptosis, and pyroptosis. A total of 9925 patients were included for bioinformatic analysis, with 6949 and 2976 patients in the training cohort and validation cohort, respectively. Five-hundred and ninety-nine genes were defined as programmed-cell-death-related genes. In the training cohort, 75 genes were identified to define PAGscore by survival analysis. According to the median value of PAGscore, patients were divided into high- and low-risk groups, and subsequent analyses demonstrated that the high-risk group had a higher level of genomic mutation frequency, hypoxia score, immuneScore, expression of immune genes, activity of malignant signaling pathways, and cancer immunity cycle. Most anti-tumor and pro-tumor components of the TME showed greater activity in high-risk patients. Scores of malignant cell properties were also higher in high-risk patients. These findings were confirmed in the validation cohort and external cohort. Our study constructed a reliable gene signature to distinguish prognosis-favorable and prognosis-unfavorable patients and demonstrated that cell death was significantly associated with cancer prognosis and the TME.

Interrelation between Programmed Cell Death and Immunogenic Cell Death: Take Antitumor Nanodrug as an Example

Programmed cell death (PCD, mainly including apoptosis, necrosis, ferroptosis, pyroptosis, and autophagy) and immunogenic cell death (ICD), as important cell death mechanisms, are widely reported in cancer therapy, and understanding the relationship between the two is significant for clinical tumor treatments. Considering that vast nanodrugs are developed to induce tumor PCD and ICD simultaneously, in this review, the interrelationship between PCD and ICD is described using nanomedicines as examples. First, an overview of PCD patterns and focus on the morphological differences and interconnections among them are provided. Then the interrelationship between apoptosis and ICD in terms of endoplasmic reticulum stress is described by introducing various cancer treatments and the recent developments of nanomedicines with inducible immunogenicity. Next, the crosstalk between non-apoptotic (including necrosis, ferroptosis, pyroptosis, and autophagy) signaling pathways and ICD is introduced and their relationship through various nanomedicines as examples is further illustrated. Finally, the relationship between PCD and ICD and its application prospects in the development of new ICD nanomaterials are summarized. This review is believed to deepen the understanding of the relationship between PCD and ICD, extend the biomedical applications of various nanodrugs, and promote the progress of clinical tumor therapy.

Assessing regulated cell death modalities as an efficient tool for in vitro nanotoxicity screening: a review

Nanomedicine is a fast-growing field of nanotechnology. One of the major obstacles for a wider use of nanomaterials for medical application is the lack of standardized toxicity screening protocols for assessing the safety of newly synthesized nanomaterials. In this review, we focus on less frequently studied nanomaterials-induced regulated cell death (RCD) modalities, including eryptosis, necroptosis, pyroptosis, and ferroptosis, as a tool for in vitro nanomaterials safety evaluation. We summarize the latest insights into the mechanisms that mediate these RCDs in response to nanomaterials exposure. Comprehensive data from reviewed studies suggest that ROS (reactive oxygen species) overproduction and ROS-mediated pathways play a central role in nanomaterials-induced RCDs activation. On the other hand, studies also suggest that individual properties of nanomaterials, including size, shape, or surface charge, could determine specific toxicity pathways with consequent RCD induction as well. We anticipate that the evaluation of RCDs can become one of the mechanism-based screening methods in nanotoxicology. In addition to the toxicity assessment, evaluation of necroptosis-, pyroptosis-, and ferroptosis-promoting capacity of nanomaterials could simultaneously provide useful information for specific medical applications as could be their anti-tumor potential. Moreover, a detailed understanding of molecular mechanisms driving nanomaterials-mediated induction of immunogenic RCDs will substantially aid novel anti-tumor nanodrugs development.

Ferroptosis in lung cancer: a novel pathway regulating cell death and a promising target for drug therapy

Lung cancer is a common malignant tumor that occurs in the human body and poses a serious threat to human health and quality of life. The existing treatment methods mainly include surgical treatment, chemotherapy, and radiotherapy. However, due to the strong metastatic characteristics of lung cancer and the emergence of related drug resistance and radiation resistance, the overall survival rate of lung cancer patients is not ideal. There is an urgent need to develop new treatment strategies or new effective drugs to treat lung cancer. Ferroptosis, a novel type of programmed cell death, is different from the traditional cell death pathways such as apoptosis, necrosis, pyroptosis and so on. It is caused by the increase of iron-dependent reactive oxygen species due to intracellular iron overload, which leads to the accumulation of lipid peroxides, thus inducing cell membrane oxidative damage, affecting the normal life process of cells, and finally promoting the process of ferroptosis. The regulation of ferroptosis is closely related to the normal physiological process of cells, and it involves iron metabolism, lipid metabolism, and the balance between oxygen-free radical reaction and lipid peroxidation. A large number of studies have confirmed that ferroptosis is a result of the combined action of the cellular oxidation/antioxidant system and cell membrane damage/repair, which has great potential application in tumor therapy. Therefore, this review aims to explore potential therapeutic targets for ferroptosis in lung cancer by clarifying the regulatory pathway of ferroptosis. Based on the study of ferroptosis, the regulation mechanism of ferroptosis in lung cancer was understood and the existing chemical drugs and natural compounds targeting ferroptosis in lung cancer were summarized, with the aim of providing new ideas for the treatment of lung cancer. In addition, it also provides the basis for the discovery and clinical application of chemical drugs and natural compounds targeting ferroptosis to effectively treat lung cancer.

Single-Cell Sequencing Reveals Necroptosis-Related Prognostic Genes of Glioblastoma

Background

Glioblastoma (GBM) is one of the most malignant forms of brain cancer, with the extremely lower survival rate. Necroptosis (NCPS) is also one of the most wide types of cell death, and its clinical importance in GBM is not clear.

Methods

We first identified necroptotic genes in GBM by single-cell RNA sequencing analysis of our surgical samples and weighted coexpression network analysis (WGNCA) from TCGA GBM data. The cox regression model with least absolute shrinkage and selection operator (LASSO) was used to construct the risk model. Then, KM plot and reactive operation curve (ROC) analysis were used to assess the prediction ability of the model. At last, the infiltrated immune cells and gene mutation profiling were investigated between the high- and low-NCPS groups as well.

Result

The risk model including ten necroptosis-related genes was identified as an independent risk factor for the outcome. In addition, we found that the risk model is correlated with the infiltrated immune cells and tumor mutation burden in GBM. NDUFB2 is identified to be a risk gene in GBM with bioinformatical analysis and in vitro experiment validation.

Conclusion

This risk model of necroptosis-related genes might provide clinical evidence for GBM interventions.

Identification of an Autophagy-Related Signature for Prognosis and Immunotherapy Response Prediction in Ovarian Cancer

BACKGROUND

Ovarian cancer (OC) is one of the most malignant tumors in the female reproductive system, with a poor prognosis. Various responses to treatments including chemotherapy and immunotherapy are observed among patients due to their individual characteristics. Applicable prognostic markers could make it easier to refine risk stratification for OC patients. Autophagy is closely implicated in the occurrence and development of tumors, including OC. Whether autophagy -related genes can be used as prognostic markers for OC patients remains unclear.

METHODS

The gene transcriptome data of 374 OC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The correlation between the autophagy levels and outcomes of OC patients was identified through the single sample gene set enrichment analysis (ssGSEA). Recognized molecular markers of autophagy in different clinical specimens were detected by immunohistochemistry (IHC) assay. The gene set enrichment analysis (GSEA), ESTIMATE, and CIBERSORT analysis were applied to explore the correlation of autophagy with the tumor immune microenvironment (TIME). Single-cell RNA-sequencing (scRNA-seq) data from seven OC patients were included for characterizing cell-cell interaction patterns of autophagy-high or low tumor cells. Machine learning, Stepwise Cox regression and LASSO-Cox analysis were used to screen autophagy hub genes, which were used to establish an autophagy-related signature for prognosis evaluation. Four tumor immunotherapy cohorts were obtained from the GEO (Gene Expression Omnibus) database and the literature for autophagy risk score validation.

RESULTS

The autophagy levels were closely related to the prognosis of the OC patients. Additionally, the autophagy levels were correlated with TIME status including immune score, and immune-cell infiltration. The scRNA-seq analysis found that tumor cells with high or low autophagy levels had different interactions with immune cells, especially macrophages. Eight autophagy-hub genes (ZFYVE1, AMBRA1, LAMP2, TRAF6, PDPK1, ATG2B, DAPK1 and TP53INP2) were screened for an autophagy-related signature. According to this signature, higher risk score was correlated with poor prognosis and better immunotherapy response in the OC patients.

CONCLUSIONS

The autophagy-related signature is applicable to predict the prognosis and immune checkpoint inhibitors (ICIs) therapy efficiency in OC patients. It is possible to identify OC patients who will respond to ICIs therapy and have a favorable prognosis, although more verification is needed.

The Role of the NLRP3 Inflammasome and Programmed Cell Death in Acute Liver Injury

Acute liver injury (ALI) is a globally important public health issue that, when severe, rapidly progresses to acute liver failure, seriously compromising the life safety of patients. The pathogenesis of ALI is defined by massive cell death in the liver, which triggers a cascade of immune responses. Studies have shown that the aberrant activation of the nod-like receptor protein 3 (NLRP3) inflammasome plays an important role in various types of ALI and that the activation of the NLRP3 inflammasome causes various types of programmed cell death (PCD), and these cell death effectors can in turn regulate NLRP3 inflammasome activation. This indicates that NLRP3 inflammasome activation is inextricably linked to PCD. In this review, we summarize the role of NLRP3 inflammasome activation and PCD in various types of ALI (APAP, liver ischemia reperfusion, CCl₄, alcohol, Con A, and LPS/D-GalN induced ALI) and analyze the underlying mechanisms to provide references for future relevant studies.

Pyroptosis in urinary malignancies: a literature review

Urinary neoplasms refer to malignant tumours occurring in any part of the urinary system, including the kidney, renal pelvis, ureter, bladder, prostate, etc. The worldwide incidence of urinary system tumours has been increasing yearly. Available methods include surgical treatment, radiotherapy, chemotherapy, endocrine therapy, molecular targeted therapy, and immune therapy. In recent years, emerging evidence has demonstrated that cell pyroptosis plays an important role in the occurrence and progression of malignant urinary tumours. Pyroptosis is a new type of cell death that involves inflammatory processes regulated by gasdermins (GSDMs) and is characterized by membrane perforation, cell swelling and cell rupture. Recent studies have shown that pyroptosis can inhibit and promote the development of tumours. This manuscript reviews the role of pyroptosis in the development and progression of prostate cancer, kidney cancer and bladder cancer and introduces the latest research results in these fields to discuss the therapeutic potential of the pyroptosis pathway in urinary malignancies.

Spatiotemporal local and abscopal cell death and immune responses to histotripsy focused ultrasound tumor ablation

Introduction

Histotripsy is a novel focused ultrasound tumor ablation modality with potent immunostimulatory effects.

Methods

To measure the spatiotemporal kinetics of local andabscopal responses to histotripsy, C57BL/6 mice bearing bilateral flank B16 melanoma or Hepa1-6 hepatocellular carcinoma tumors were treated with unilateral sham or partial histotripsy. Treated and contralateral untreated (abscopal) tumors were analyzed using multicolor immunofluorescence, digital spatial profiling, RNA sequencing (RNASeq), and flow cytometry.

Results

Unilateral histotripsy triggered abscopal tumor growth inhibition. Within the ablation zone, early high mobility group box protein 1 (HMGB1) release and necroptosis were accompanied by immunogenic cell death transcriptional responses in tumor cells and innate immune activation transcriptional responses in infiltrating myeloid and natural killer (NK) cells. Delayed CD8+ T cell intratumoral infiltration was spatiotemporally aligned with cancer cell features of ferroptosis; this effect was enhanced by CTLA-4 blockade and recapitulated in vitro when tumor-draining lymph node CD8+ T cells were co-cultured with tumor cells. Inoculation with cell-free tumor fractions generated by histotripsy but not radiation or freeze/thaw conferred partial protection from tumor challenge.

Discussion

We propose that histotripsy may evoke local necroptotic immunogenic cell death, priming systemic adaptive immune responses and abscopal ferroptotic cancer cell death.

Identification and Validation of a Novel Prognostic Signature Based on Ferroptosis-Related Genes in Ovarian Cancer

BACKGROUND

Ovarian cancer is the most lethal gynecological tumor, with a poor prognosis due to the lack of early symptoms, resistance to chemotherapy, and recurrence. Ferroptosis belongs to the regulated cell death family, and is characterized by iron-dependent processes. Here, comprehensive bioinformatics analysis was applied to explore a valuable prognostic model based on ferroptosis-related genes, which was further validated in clinical OC samples.

METHODS

mRNA data of normal and ovarian tumor samples were obtained separately from the GTEx and TCGA databases. The least absolute shrinkage and selection operator (LASSO) cox regression was applied to construct the prognostic model based on ferroptosis-associated genes. Expression of ALOX12 in OC cell lines, as well as cell functions, including proliferation and migration, were examined. Finally, the prognostic efficiency of the model was assessed in the clinical tissues of OC patients.

RESULTS

A gene signature consisting of ALOX12, RB1, DNAJB6, STEAP3, and SELENOS was constructed. The signature divided TCGA, ICGC, and GEO cohorts into high-risk and low-risk groups separately. Receiver operating characteristic (ROC) curves and independent prognostic factor analysis were carried out, and the prognostic efficacy was validated. The expression levels of ALOX12 in cell lines were examined. Inhibition of ALOX12 attenuated cell proliferation and migration in HEY cells. Moreover, the prognostic value of ALOX12 expression was examined in clinical samples of OC patients.

CONCLUSION

This work constructed a novel ferroptosis-associated gene model. Furthermore, the clinical predictive role of ALOX12 was identified in OC patients, suggesting that ALOX12 might act as a potential prognostic tool and therapeutic target for OC patients.

PANoptosis: A Cell Death Characterized by Pyroptosis, Apoptosis, and Necroptosis

PANoptosis is a new cell death proposed by Malireddi et al in 2019, which is characterized by pyroptosis, apoptosis and necroptosis, but cannot be explained by any of them alone. The interaction between pyroptosis, apoptosis and necroptosis is involved in PANoptosis. In this review, from the perspective of PANoptosis, we focus on the relationship between pyroptosis, apoptosis and necroptosis, the key molecules in the process of PANoptosis and the formation of PANoptosome, as well as the role of PANoptosis in diseases. We aim to understand the mechanism of PANoptosis and provide a basis for targeted intervention of PANoptosis-related molecules to treat human diseases.

The expression pattern of pyroptosis-related genes predicts the prognosis and drug response of melanoma

Cutaneous melanoma (CM, hereafter referred to as melanoma) is a highly malignant tumor that typically undergoes early metastasis. Pyroptosis, as a special programmed cell death process that releases inflammatory factors and has been widely studied in tumors, but its role in melanoma has not been fully elucidated. In this study, we examined the relationship between pyroptosis and the prognosis of melanoma through bioinformatic analysis of RNA-sequencing data. Our results demonstrated that pyroptosis is a protective factor associated with melanoma prognosis. A higher pyroptosis score was associated with a more favorable overall survival. We used weighted gene co-expression networks analysis (WGCNA) to establish an effective prognosis model based on 12 pyroptosis-related genes. We then validated it in two independent cohorts. Furthermore, a nomogram combining clinicopathological characteristics and a pyroptosis-related gene signature (PGS) score was designed to effectively evaluate the prognosis of melanoma. Additionally, we analyzed the potential roles of pyroptosis in the tumor immune microenvironment and drug response. Interestingly, we found that the elevated infiltration of multiple immune cells, such as CD4⁺ T cells, CD8⁺ T cells, dendritic cells, and M1 macrophages, may be associated with the occurrence of pyroptosis. Pyroptosis was also related to a better response of melanoma to interferon-α, paclitaxel, cisplatin and imatinib. Through Spearman correlation analysis of the 12 pyroptosis-related genes and 135 chemotherapeutic agents in the Genomics of Drug Sensitivity in Cancer database, we identified solute carrier family 31 member 2 (SLC31A2) and collagen type 4 alpha 5 chain (COL4A5) as being associated with resistance to most of these drugs. In conclusion, this PGS is an effective and novelty prognostic indicator in melanoma, and also has an association with the melanoma immune microenvironment and melanoma treatment decision-making.

Identification of necroptosis subtypes and development of necroptosis-related risk score model for in ovarian cancer

Background: ith the ongoing development of targeted therapy, non-apoptotic cell death, including necroptosis, has become a popular topic in the field of prevention and treatment. The purpose of this study was to explore the effect of necroptosis-related genes (NRGs) on the classification of ovarian cancer (OV) subtypes and to develop a necroptosis-related risk score (NRRS) classification system. Methods: 74 NRGs were obtained from the published studies, and univariate COX regression analysis was carried out between them and OV survival. Consensus clustering analysis was performed on OV samples according to the expression of NRGs related to prognosis. Furthermore, the NRRS model was developed by combining Weighted Gene Co-Expression Network Analysis (WGCNA) with least absolute shrinkage and selection operator (Lasso)-penalized Cox regression and multivariate Cox regression analysis. And the decision tree model was constructed based on the principle of random forest screening factors principle. Results: According to the post-related NRGs, OV was divided into two necroptosis subtypes. Compared with Cluster 1 (C1), the overall survival (OS) of Cluster 2 (C2) was significantly shorter, stromal score and immune score, the infiltration level of tumor associated immune cells and the expression of 20 immune checkpoints were significantly higher. WGCNA identified the blue module most related to necroptosis subtype, and 12 genes in the module were used to construct NRRS. NRRS was an independent prognostic variable of OV. The OS of samples with lower NRRS was significantly longer, and tumor mutation burden and homologous recombination defect were more obvious. Conclusion: This study showed that necroptosis plays an important role in the classification, prognosis, immune infiltration and biological characteristics of OV subtypes. The evaluation of tumor necroptosis may provide a new perspective for OV treatment.

Construction of a Prognostic Model Based on Cuproptosis-Related lncRNA Signatures in Pancreatic Cancer

Aim

The aim of this study is to identify cuproptosis-related lncRNAs and construct a prognostic model for pancreatic cancer patients for clinical use.

Methods

The expression profile of lncRNAs was downloaded from The Cancer Genome Atlas database, and cuproptosis-related lncRNAs were identified. The prognostic cuproptosis-related lncRNAs were obtained and used to establish and validate a prognostic risk score model in pancreatic cancer.

Results

In total, 181 cuproptosis-related lncRNAs were obtained. The prognostic risk score model was constructed based on five lncRNAs (AC025257.1, TRAM2-AS1, AC091057.1, LINC01963, and MALAT1). Patients were assigned to two groups according to the median risk score. Kaplan-Meier survival curves showed that the difference in the prognosis between the high- and low-risk groups was statistically significant. Multivariate Cox analysis showed that our risk score was an independent risk factor for pancreatic cancer patients. Receiver operator characteristic curves revealed that the cuproptosis-related lncRNA model can effectively predict the prognosis of pancreatic cancer. The principal component analysis showed a difference between the high- and low-risk groups intuitively. Functional enrichment analysis showed that different genes were involved in cancer-related pathways in patients in the high- and low-risk groups.

Conclusion

The risk model based on five prognostic cuproptosis-related lncRNAs can well predict the prognosis of pancreatic cancer patients. Cuproptosis-related lncRNAs could be potential biomarkers for pancreatic cancer diagnosis and treatment.

Construction and validation model of necroptosis-related gene signature associates with immunity for osteosarcoma patients

Osteosarcoma is the most common malignant tumor in children and adolescents and its diagnosis and treatment still need to be improved. Necroptosis has been associated with many malignancies, but its significance in diagnosing and treating osteosarcoma remains unclear. The objective is to establish a predictive model of necroptosis-related genes (NRGs) in osteosarcoma for evaluating the tumor microenvironment and new targets for immunotherapy. In this study, we download the osteosarcoma data from the TARGET and GEO websites and the average muscle tissue data from GTEx. NRGs were screened by Cox regression analysis. We constructed a prediction model through nonnegative matrix factorization (NMF) clustering and the least absolute shrinkage and selection operator (LASSO) algorithm and verified it with a validation cohort. Kaplan–Meier survival time, ROC curve, tumor invasion microenvironment and CIBERSORT were assessed. In addition, we establish nomograms for clinical indicators and verify them by calibration evaluation. The underlying mechanism was explored through the functional enrichment analysis. Eight NRGs were screened for predictive model modeling. NRGs prediction model through NMF clustering and LASSO algorithm was established. The survival, ROC and tumor microenvironment scores showed significant statistical differences among subgroups (P < 0.05). The validation model further verifies it. By nomogram and calibration, we found that metastasis and risk score were independent risk factors for the poor prognosis of osteosarcoma. GO and KEGG analyses demonstrate that the genes of osteosarcoma cluster in inflammatory, apoptotic and necroptosis signaling pathways. The significant role of the correlation between necroptosis and immunity in promoting osteosarcoma may provide a novel insight into detecting molecular mechanisms and targeted therapy.

Identification of cuproptosis-related patterns and construction of a scoring system for predicting prognosis, tumor microenvironment-infiltration characteristics, and immunotherapy efficacy in breast cancer

Background

Cuproptosis, a recently discovered refreshing form of cell death, is distinct from other known mechanisms. As copper participates in cell death, the induction of cancer cell death with copper ionophores may emerge as a new avenue for cancer treatment. However, the role of cuproptosis in tumor microenvironment (TME) cell infiltration remains unknown.

Methods

We systematically evaluated the cuproptosis patterns in The Cancer Genome Atlas (TCGA) database in breast cancer (BRCA) samples based on 10 cuproptosis-related genes (CRGs), and correlated these patterns with the prognosis and characteristics of TME cell infiltration. A principal component analysis algorithm was used to construct a cuproptosis score to quantify the cuproptosis pattern in individual tumors. Further, the relationships between the cuproptosis score and transcription background, clinical features, characteristics of TME cell infiltration, drug response, and efficacy of immunotherapy were assessed.

Results

Two distinct cuproptosis patterns with distinct prognoses were identified; their TME characteristics were found to be consistent with the immune-excluded and immune-inflamed phenotypes, respectively. The cuproptosis patterns in individual patients were evaluated using the cuproptosis score based on the cuproptosis phenotype-related genes, contributing to distinguishing biological processes, clinical outcome, immune cell infiltration, genetic variation, and drug response. Univariate and multivariate Cox regression analyses verified this score as an independent prognostic predictor in BRCA. A high cuproptosis score, characterized by immune activation, suggests an inflamed tumor and immune-inflamed phenotype with poor survival and a low cuproptosis score, characterized by immune suppression, indicates a non-inflamed tumor and immune-excluded phenotype with better survival. Significant differences were observed in the IC50 between the high and low cuproptosis score groups receiving chemotherapy and targeted therapy drugs. In the two immunotherapy cohorts, patients with a higher cuproptosis score experienced considerable therapeutic advantages and clinical benefits.

Conclusions

This study is the first to elucidate the prominent role of cuproptosis in the clinical outcome and the formation of TME diversity and complexity in BRCA. Estimating cuproptosis patterns in tumors could help predict the prognosis and characteristics of TME cell infiltration and guide more effective chemotherapeutic and immunotherapeutic strategies.

The role of pyroptosis and its crosstalk with immune therapy in breast cancer

Pyroptosis is a brand-new category of programmed cell death (PCD) that is brought on by multitudinous inflammasomes, which can recognize several stimuli to pilot the cleavage of and activate inflammatory cytokines like IL-18 and IL-1β is believed to have dual effects on the development of multiple cancers including breast cancer. However, pyroptosis has different effects on cancers depending on the type of tissues and their distinct heredity. Recently, the association between pyroptosis and breast cancer has received more and more attention, and it is thought that inducing pyroptosis could be used as a cancer treatment option. In addition, a great deal of evidence accumulating over the past decades has evinced the crosstalk between pyroptosis and tumor immunological therapy. Thus, a comprehensive summary combining the function of pyroptosis in breast cancer and antitumor immunity is imperative. We portray the prevalent knowledge of the multidimensional roles of pyroptosis in cancer and summarize the pyroptosis in breast cancer principally. Moreover, we elucidate the influence of inflammasomes and pyroptosis-produced cytokines on the tumor microenvironment (TME) of breast cancer. Taken together, we aim to provide a clue to harness pyroptosis rationally and apply it to augment immunotherapy efficiency for breast cancer.

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

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.

Advancements in the Alcohol-Associated Liver Disease Model

Alcohol-associated liver disease (ALD) is an intricate disease that results in a broad spectrum of liver damage. The presentation of ALD can include simple steatosis, steatohepatitis, liver fibrosis, cirrhosis, and even hepatocellular carcinoma (HCC). Effective prevention and treatment strategies are urgently required for ALD patients. In previous decades, numerous rodent models were established to investigate the mechanisms of alcohol-associated liver disease and explore therapeutic targets. This review provides a summary of the latest developments in rodent models, including those that involve EtOH administration, which will help us to understand the characteristics and causes of ALD at different stages. In addition, we discuss the pathogenesis of ALD and summarize the existing in vitro models. We analyse the pros and cons of these models and their translational relevance and summarize the insights that have been gained regarding the mechanisms of alcoholic liver injury.