PANoptosis-based molecular subtyping and HPAN-index predicts therapeutic response and survival in hepatocellular carcinoma

Investigating the molecular mechanisms and clinical potential of APO+ endothelial cells associated with PANoptosis in the tumor microenvironment of hepatocellular carcinoma using single-cell sequencing data

INTRODUCTION

PANoptosis is a newly identified form of programmed cell death that integrates elements of pyroptosis, apoptosis, and necroptosis. It plays a pivotal role in shaping the tumor immune microenvironment. Despite its significance, the specific functions and mechanisms of PANoptosis within the tumor microenvironment (TME) of hepatocellular carcinoma (HCC) remain unclear. This study aims to investigate these mechanisms using single-cell RNA sequencing data.

METHODS

Single-cell RNA sequencing data from HCC patients were obtained from the GEO database. The AUCell algorithm was used to quantify PANoptosis activity across various cell types in the TME. Cell populations with high PANoptosis scores were further analyzed using CytoTRACE and scMetabolism to assess their differentiation states and metabolic profiles. Associations between these high-score cell subsets and patient prognosis, tumor stage, and response to immunotherapy were examined. Cell-cell communication analysis was performed to explore how PANoptosis-related APO+ endothelial cells (ECs) may influence HCC progression. Immunofluorescence staining was used to assess the spatial distribution of APO+ ECs in tumor and adjacent tissues. Finally, a CCK8 assay was conducted to evaluate the effect of APOH+ HUVECs on HCC cell proliferation.

RESULTS

A total of 16 HCC patient samples with single-cell RNA sequencing data were included in the study. By calculating the PANoptosis scores of different cell types, we found that ECs, macrophages, hepatocytes, and fibroblasts exhibited higher PANoptosis scores. The PANoptosis scores, differentiation trajectories, intercellular communication, and metabolic characteristics of these four cell subpopulations with high PANoptosis scores were visualized. Among all subpopulations, APO+ ECs demonstrated the most significant clinical relevance, showing a positive correlation with better clinical staging, prognosis, and response to immunotherapy in HCC patients. Cellular communication analysis further revealed that APO+ ECs might regulate the expression of HLA molecules, thereby influencing T cell proliferation and differentiation, potentially contributing to improved prognosis in HCC patients. Immunofluorescence staining results indicated that APO+ ECs were primarily located in the adjacent tissues of HCC patients, with lower expression in tumor tissues. The results of cellular experiments showed that APOH+ HUVECs significantly inhibited the proliferation of HCC cells.

CONCLUSIONS

This study systematically mapped the cellular landscape of the TME in HCC patients and explored the differences in differentiation trajectories, metabolic pathways, and other aspects of subpopulations with high PANoptosis scores. Additionally, the study elucidated the potential molecular mechanisms through which APO+ ECs inhibit HCC cell proliferation and improve prognosis and immunotherapeutic efficacy in HCC patients. This research provides new insights for clinical prognosis evaluation and immunotherapy strategies in HCC.

Revealing roles of PANoptosis-related genes in prognosis and molecular subtypes in lung squamous cell carcinoma by integrated bioinformatic analyses and experiments

The purpose of current study was to reveal the role of PANoptosis-associated genes in lung squamous cell carcinoma (LUSC) and their potential as prognostic biomarkers. We analyzed RNA-seq data from TCGA-LUSC and GEO datasets to identify differentially expressed genes (DEGs) between LUSC and normal samples, followed by VENN analysis to reveal PANoptosis-related DEGs. Functional enrichment analyses were performed by clusterProfiler package. Distinct LUSC subtypes were identified by consensus clustering based on PANoptosis-related DEGs. Univariate Cox and LASSO regression were utilized to identify key prognostic genes, and a prognostic model was developed based on selected genes. Immune infiltration status was evaluated by CIBERSORT and ESTIMATE algorithms. Expression of key prognostic genes was tested in three LUSC cell lines by RT-qPCR and Western blot. Roles of TLR3 in LUSC progression were determined by functional experiments. A total of 76 PANoptosis-related DEGs were identified, with significant enrichment in apoptosis pathways. The clustering analysis revealed four subtypes, in which survival and immune microenvironment were dramatically different. From the 76 genes, four key prognostic genes (CHEK2, PDK4, TLR3, and IL1B) were identified to establish prognostic risk model, which could reflect the survival status and immune cells composition variations for LUSC patients. Besides, these four genes showed significant correlations with infiltrating levels of various immune cells. TLR3 was identified as a more weighted prognostic risk gene in LUSC. Functional assays demonstrated that genes like TLR3 modulated cell proliferation, migration, and inflammatory responses in LUSC cells. This study highlighted the potential of the four key PANoptosis genes as biomarkers or targets in LUSC, and the risk model based on these four genes provided novel insights to develop personalized treatment strategy for patients with LUSC.

Screening of pivotal oncogenes modulated by DNA methylation in hepatocellular carcinoma and identification of atractylenolide I as an anti-cancer drug

This study was performed to identify crucial oncogenes modulated by DNA methylation in hepatocellular carcinoma (HCC) and look for new drugs for HCC treatment. The data of TCGA-LIHC cohort were obtained from UCSC database. Weighted gene co-expression network analysis and multiple machine learning algorithms were applied to screen the crucial prognosis-related genes in HCC. Then these genes were further screened by DNA methylation status. Ten-eleven translocation 1 (TET1) was overexpressed in HCC cell lines, and its biological functions and regulatory effects on the oncogenes were explored by qPCR, methylation-specific polymerase chain reaction, cell viability assay, Western blot, etc. Molecular docking was applied to evaluate the binding affinity between atractylenolide I (AT-I) and TET1, and the tumor-suppressive functions of AT-I were examined with both in vitro and in vivo models. In this work, 12 crucial genes related to HCC prognosis were obtained, among which six genes were with differential methylation status in HCC tissues, including AKR1B10, ALPK3, NQO1, NT5DC2, SFN, and SPP1. The expression levels of ALPK3 and NT5DC2 were positively regulated by TET1, the crucial mediator of demethylation. TET1 overexpression increased the viability and stemness of HCC cells. AT-I had good binding affinity with TET1, and repressed its activity. AT-I promoted the methylation of ALPK3 and NT5DC2 promoter regions, and reduced their expression, and repressed the growth of HCC cells. In summary, DNA methylation contributes to HCC progression, and AT-I represses the malignancy of HCC cells by inhibiting TET1-mediated abnormal DNA demethylation.

The molecular mechanisms, roles, and potential applications of PANoptosis in cancer treatment

PANoptosis, a newly identified form of programmed cell death regulated by the panoptosome complex, exhibits key characteristics of apoptosis, pyroptosis and necroptosis. It exerts a substantial influence on the initiation and progression of a spectrum of diseases, particularly in cancer, where its impact is increasingly being recognized. PANoptosis is closely related to tumorigenesis, carcinogenesis, metastasis, chemotherapy resistance, as well as the prediction of therapeutic responses and prognosis in cancer patients. In this review, we first review the discovery of PANoptosis and systematically analyze the composition of the panoptosome. Subsequently, we examine the role of PANoptosis in various types of cancer, encompassing its function within the tumor microenvironment, its role in tumor drug resistance, and its predictive role in cancer prognosis. Ultimately, we delve into strategies for targeting PANoptosis in cancer therapy, including targeting various molecules in the PANoptosis pathway, such as ZBP1, RIPK1, RIPK3, Caspases and other novel strategies like nanoinducers and viral vectors. This review aims to provide references and assistance for the research and application of PANoptosis in cancer treatment.

Investigation of PANoptosis pathway in age-related macular degeneration triggered by Aβ1-40

Our study aimed to identify PANoptosis in Aβ1-40-induced AMD, both in vivo and in vitro, and to determine if AIM2-PANoptosome mediates this process. We used transcriptomics to explore the signaling pathways and target genes linked to PANoptosis within a mouse model of AMD triggered by Aβ1-40. Optical coherence tomography (OCT), hematoxylin and eosin (H&E) staining, and electroretinography (ERG) were employed to assess retinal damage in terms of morphology and function. Morphological changes in ARPE-19 cells were observed using optical microscopy and scanning electron microscopy. Enzyme-linked immunosorbent assay (ELISA) was used to detect the levels of cytokines in cell supernatants, mouse orbital serum, and human plasma to evaluate the severity of inflammation. CO-immunoprecipitation(CoIP) and molecular docking were performed to assess the impact and expression of proteins associated with the AIM2-PANoptosome. Quantitative polymerase chain reaction (qPCR), Western blot (WB), immunofluorescence, and apoptosis detection kits were used to evaluate the expression levels of genes and proteins related to PANoptosis-like cell death. Our results showed that the Aβ1-40-induced AMD model had increased expression of apoptosis, necroptosis, and pyroptosis pathways, and AIM2-PANoptosome components. CoIP and docking confirmed increased AIM2, ZBP1, and PYRIN levels under Aβ1-40 treatment. WB and immunofluorescence showed upregulation of PANoptosis-related proteins. Inhibitors reduced Aβ-induced protein expression. ELISA showed increased inflammatory cytokines. Apoptosis assays and microscopy revealed Aβ1-40-induced ARPE-19 cell loss and morphological changes. In conclusion, the Aβ1-40-induced AMD model displayed PANoptosis-like cell death, offering insights into disease pathogenesis.

Unravelling the Role of PANoptosis in Liver Diseases: Mechanisms and Therapeutic Implications

PANoptosis is a multimodal form of cell death that involves inflammatory, apoptotic, and necroptotic pathways, playing a key role in the development of liver diseases. This article first outlines the definition and characteristics of PANoptosis, and then explores its mechanisms of action in different types of liver diseases, including acute liver injury, liver failure, metabolic dysfunction-associated fatty liver disease, and hepatocellular carcinoma. Furthermore, this article analyses the molecular regulatory network of PANoptosis and potential therapeutic targets. Finally, this article summarises the current research on PANoptosis in liver diseases and future research directions, and it reviews the role of the emerging cell death mechanism of PANoptosis in liver diseases.

Strategies for discovering novel hepatocellular carcinoma biomarkers

Liver cancer, particularly hepatocellular carcinoma (HCC), remains a significant global health challenge due to its high mortality rate and late-stage diagnosis. The discovery of reliable biomarkers is crucial for improving early detection and patient outcomes. This review provides a comprehensive overview of current and emerging biomarkers for HCC, including alpha-fetoprotein, des-gamma-carboxy prothrombin, glypican-3, Golgi protein 73, osteopontin, and microRNAs. Despite advancements, the diagnostic limitations of existing biomarkers underscore the urgent need for novel markers that can detect HCC in its early stages. The review emphasizes the importance of integrating multi-omics approaches, combining genomics, proteomics, and metabolomics, to develop more robust biomarker panels. Such integrative methods have the potential to capture the complex molecular landscape of HCC, offering insights into disease mechanisms and identifying targets for personalized therapies. The significance of large-scale validation studies, collaboration between research institutions and clinical settings, and consideration of regulatory pathways for clinical implementation is also discussed. In conclusion, while substantial progress has been made in biomarker discovery, continued research and innovation are essential to address the remaining challenges. The successful translation of these discoveries into clinical practice will require rigorous validation, standardization of protocols, and cross-disciplinary collaboration. By advancing the development and application of novel biomarkers, we can improve the early detection and management of HCC, ultimately enhancing patient survival and quality of life.

Exploring the Anti-PANoptosis Mechanism of Dachaihu Decoction Against Sepsis-Induced Acute Lung Injury: Network Pharmacology, Bioinformatics, and Experimental Validation

Background

Dachaihu decoction (DCHD) is a common Chinese medicine formula against sepsis-induced acute lung injury (SALI). PANoptosis is a novel type of programmed cell death. Nevertheless, The mechanisms of DCHD against SALI via anti-PANoptosis remains unknown.

Methods

First, we identified the intersecting targets among DCHD, SALI, and PANoptosis using relevant databases and published literature. Then, protein-protein interaction (PPI) network, molecular docking, and functional enrichment analysis were conducted. In vivo, cecal ligation and puncture (CLP) was used to construct a sepsis mouse model, and the therapeutic effects of DCHD on SALI were evaluated using hematoxylin and eosin (H&E) staining, quantitative real-time PCR (qRT-PCR), and ELISA. Finally, qRT-PCR, immunofluorescence staining, and Western blotting were used to verify the effect of DCHD-containing serum (DCHD-DS) on LPS-induced RAW 264.7 macrophages in vitro.

Results

82 intersecting targets were identified by mapping the targets of DCHD, SALI, and PANoptosis. Enrichment analysis showed that DCHD against SALI via anti-PANoptosis by modulating tumor necrosis factor (TNF), AGE-RAGE, phosphoinositide 3-kinase (PI3K)-AKT, and Toll-like receptor signaling pathways by targeting Casp3, cellular tumor antigen p53 (TP53), B-cell lymphoma 2 (Bcl2), toll-like receptor-4 (TLR4), STAT3, STAT1, RELA, NF-κB1, myeloid cell leukemia-1 (MCL1), JUN, IL-1β, HSP90AA1, Casp9, Casp8, and Bcl2l1. Molecular docking analysis revealed that the key components of DCHD have a high binding affinity to the core targets. In vivo, DCHD improved lung histopathological injury, reduced inflammatory factor expression, and alleviated oxidative stress injury in lung tissues. In vitro, DCHD-DS alleviated cell morphology changes, the release of pro-inflammatory factors, and p65 nucleus aggregation. Furthermore, we verified that DCHD-DS inhibited PANoptosis by downregulating the PI3K/AKT/NF-κB signalling pathway.

Conclusion

DCHD attenuates SALI by inhibiting PANoptosis via control of the PI3K/AKT/NF-κB pathway. Our study provides a solid foundation for investigating the mechanisms of DCHD and its clinical application in the treatment of SALI.

Caspases in PANoptosis

Recent studies prove that the three well-established cell death pathways-pyroptosis, apoptosis, and necroptosis-are not isolated but rather engage in extensive crosstalk. PANoptosis, a newly identified pathway of inflammatory regulated cell death (RCD), integrates characteristics of apoptosis, pyroptosis, and necroptosis. Caspases are a family of conserved cysteine proteases that play critical roles in pyroptosis, apoptosis, and necroptosis. Similarly, caspases also play a role in PANoptosis. In this paper, we review the molecular mechanisms of these three RCDs and the crosstalk between them. We also delineate the discovery of PANoptosis and its association with disease. Furthermore, we discuss the caspase function in PANoptosis, mainly focusing on caspase-6 and caspase-8 molecules. This review describes the key molecules, especially caspases, in the context of PANoptosis research, aiming to provide a foundation for targeted interventions in PANoptosis-associated diseases.

Exploring PANoptosis in head and neck cancer: A novel approach to cancer therapy

PANoptosis is a newly discovered complex programmed cell death (PCD) form. In the field of cancer research, PANoptosis is involved in multiple cell death pathways that affect tumor cell survival, proliferation, and response to treatment, serving as an innovative strategy for cancer therapy. Endocrine-disrupting chemicals (EDCs) impact the endocrine system, including cancer. However, research on their influence on head and neck carcinoma (HNSC) through PANoptosis genes remains limited. This study utilises transcriptomic and clinical data related to HNSC from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We developed a risk model based on PANoptosis-related genes through LASSO Cox regression analysis. Finally, we utilized a Sankey diagram to depict the relationships between EDCs and key genes, identifying DSCAM, IL-6, and SYCP2 as critical predictors of HNSC PANoptosis. These essential genes identified 214 EDCs potentially influencing HNSC, including 3 (Aroclor 1242, Pentachlorobenzene, and Propanil) previously unreported to HNSC. These findings elucidate novel relationships between PANoptosis-related genes mediated by EDCs and the pathogenesis of HNSC.

Integrating T-cell inflammation features for prognosis in hepatocellular carcinoma: a novel predictive model

Background

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death globally and accounts for 75% to 90% of primary liver cancer cases. The high mortality rate of HCC, coupled with the absence of reliable prognostic biomarkers, makes its treatment and prognosis evaluation challenging. The features of the T cell-inflamed microenvironment include active interferon (IFN)-γ signaling and the presence of cytotoxic effector molecules, antigen presentation, and T-cell activating cytokines. Although these features are closely associated with anticancer immunity, their specific roles in HCC remain unclear. This study aimed to investigate the role and prognostic significance of T-cell inflammation (TCI) in HCC patients, providing new insights for clinical diagnosis and treatment strategies.

Methods

We integrated single-sample gene set enrichment analysis (ssGSEA) and weighted gene coexpression network analysis (WGCNA) to identify the genes associated with TCI at both the single-cell and bulk-transcriptome levels. The HCC TCI-related score (HTCIRS) was developed and assessed with 10 different machine learning algorithms and their combinations, which was followed by validation of the key gene KLF2 in clinical samples and tissue microarrays (TMAs).

Results

We identified 65 genes associated with TCI, of which 36 were significantly correlated with overall survival (OS). The HTCIRS demonstrated excellent performance in prognostic prediction, revealing differences in biological functions and immune cell infiltration between different risk groups within the tumor microenvironment (TME). Furthermore, KLF2 was identified to be linked to the prognosis of patients with HCC.

Conclusions

The TCI-related score proposed in this study serves as an important tool for prognostic prediction and personalized treatment of patients with HCC, with KLF2 emerging as a potential biomarker for predicting the prognosis of patients with HCC.

PANoptosis: A new era for anti-cancer strategies

Cancer cells possess an extraordinary ability to dodge cell death through various pathways, granting them a form of immortality-a key obstacle in oncotherapy. Thus, it's vital to unravel the intricate mechanisms behind newly discovered types of cell death that drive tumor suppression, going beyond apoptosis alone. The emergence of PANoptosis, a form of cell death intertwining necroptosis, pyroptosis, and apoptosis, offers a fresh perspective, integrating these pathways into one cohesive process. When cells detect damage signals, they assemble PANoptosome complexes that disrupt their balance, trigger immune responses, and lead to their eventual collapse. PANoptosis has been associated with multiple cellular pathways, including ferroptosis. Mitochondrial dysfunction also plays a critical role in sparking and advancing PANoptosis. In this review, we map out the molecular machinery and regulatory web controlling PANoptosis. We explore cutting-edge research and future trends in PANoptosis-centered tumor therapies, spotlighting promising innovations that could amplify cancer treatment effectiveness through harnessing this multifaceted cell death pathway. The development of nanomedicines and nanomaterials provides solutions to the therapeutic challenges of clinical drugs. Developing novel tumor nano-PANoptosis inducers by leveraging the advantages of nanomedicine is of research value. Traditional Chinese medicine (TCM) treatment is characterized by multiple targets, and it has distinct advantages in triggering PANoptosis through multiple pathways. Additionally, photodynamic Therapy (PDT) may offer new insights into promoting PANoptosis in tumor cells by increasing oxidative stress and reactive oxygen species levels. These will establish a solid theoretical groundwork for the development of integrated treatment methodologies.

Integrative analysis of multi-omics data identified PLG as key gene related to Anoikis resistance and immune phenotypes in hepatocellular carcinoma

PURPOSE

The extracellular matrix (ECM) plays a pivotal role in the initiation and progression of hepatocellular carcinoma (HCC) by facilitating the proliferation of HCC cells and enabling resistance to Anoikis. ECM also provide structural support that aids in the invasion of HCC cells, thereby influencing the tumor microenvironment. Due to genetic variations and molecular heterogeneity, significant challenges exist in the treatment of HCC, particularly with immunotherapy, which frequently leads to immune tolerance and suboptimal immune responses. Therefore, there is an urgent need for a multi-omics-based classification system for HCC that clarifies the molecular mechanisms underlying the establishment of immune phenotypes and Anoikis resistance in HCC cells. In this study, we employed advanced clustering algorithms to analyze and integrate multi-omics data from HCC patients, with the objective of identifying key genes that possess prognostic potential associated with the Anoikis resistance phenotype. This methodology resulted in the development of a consensus machine learning-driven signature (CMLS), which demonstrates robust predictive capabilities by examining variations in epigenetics, transcription, and immune metabolism, as well as their effects on the core differential gene, plasminogen (PLG).

RESULTS

The integrated multi-omics approach has identified PLG as a critical node within the gene regulatory network associated with Anoikis resistance and immunometabolic phenotypes. As an independent risk factor for poor prognosis in patients with HCC, PLG facilitates Anoikis resistance and enhances the migration of HCC cells. This study provides novel insights into the molecular subtypes of HCC through the application of robust clustering algorithms based on multi-omics data. The constructed CMLS serves as a valuable tool for early prognostic prediction and for screening potential drug candidates that may enhance the efficacy of immunotherapy, thereby establishing a foundation for personalized treatment strategies in HCC.

CONCLUSIONS

Our data underscore the pivotal role of PLG in the development of Anoikis resistance and the immunometabolic phenotype in HCC cells. Furthermore, we present compelling experimental evidence that PLG functions as a significant tumor promoter, suggesting its potential as a target for the formulation of tailored therapeutic strategies for HCC.

Identification of PANoptosis-Related Genes in Community-Acquired Pneumonia Diagnosis

Background

This study aimed to identify and characterize novel PANoptosis biomarkers for community-acquired pneumonia (CAP) diagnosis.

Methods

Transcriptomic data from training set GSE196399 and validation sets GSE94916 and GSE202947 were utilized. A PANoptosis gene set was identified by intersecting DEGs linked to CAP, WGCNA hub genes, and PANoptosis-related genes. GO and KEGG analyses were conducted for enrichment analysis. PANoptosis scores were calculated via ssGSEA. Feature genes were identified using SVM-RFE, LASSO regression, and RF methods. Diagnostic performance was assessed via ROC analysis. Immune cell infiltration was evaluated using CIBERSORT. A PPI network was constructed, and a nomogram was developed for CAP prediction. Drug-gene interactions were investigated. qRT-PCR was conducted to confirm feature gene alterations in clinical samples.

Results

We identified 7555 DEGs associated with CAP from the GSE196399 dataset. Through WGCNA, a PANoptosis gene set of 39 genes was found, showing significant enrichment in pathways related to apoptosis and inflammation. CAP patients exhibited significantly reduced PANoptosis scores compared to healthy controls, with a marked upregulation in the majority of the PANoptosis gene set in high-score individuals. Four feature genes (ZNF304, AKT3, MAPK8, and ARHGAP10) were identified as potential biomarkers, exhibiting high diagnostic accuracy with AUCs generally above 0.8. These genes also showed significant correlations with M0 macrophages and neutrophils. Drug-gene interaction analysis revealed potential therapeutic agents targeting MAPK8 and AKT3. Validation in clinical samples confirmed gene expression alterations in CAP patients.

Conclusion

The identified PANoptosis feature genes demonstrate high diagnostic accuracy for CAP, serving as potential biomarkers and therapeutic targets for CAP.

Identification of PANoptosis-relevant subgroups and predicting signature to evaluate the prognosis and immune landscape of patients with biliary tract cancer

BACKGROUND

This study conducted molecular subtyping of biliary tract cancer patients based on 19 PANoptosis-related gene signatures.

METHODS

Through consensus clustering, patients were categorized into two subtypes, A and B. By integrating multi-omics data and clinical information from different cohorts, we elucidated the association between different subtypes of biliary tract cancer and patient prognosis, which correlated with the immune infiltration characteristics of patients.

RESULTS

LASSO regression analysis was performed on the 19 gene signatures, and we constructed and validated a 9-gene risk score prognostic model that accurately predicts the overall survival rate of different biliary tract cancer patients. Additionally, we developed a predictive nomogram demonstrating the clinical utility and robustness of our model. Further analysis of the risk score-based immune landscape highlighted potential associations with immune cell infiltration, chemotherapy, and immune therapy response.

CONCLUSION

Our study provides valuable insights into personalized treatment strategies for biliary tract cancer, which are crucial for improving patient prognosis and guiding treatment decisions in clinical practice.

Identification of PANoptosis-based signature for predicting the prognosis and immunotherapy response in AML

Background

In recent years, the incidence of acute myeloid leukemia (AML) has increased rapidly with a suboptimal prognosis. In AML, cell death is independent of tumorigenesis, tumor invasion, and drug resistance. PANoptosis is a newly discovered form of cell death that combines pyroptosis, apoptosis, and necroptosis. However, no studies have explored the role of PANoptosis-based signatures in AML.

Methods

We screened for PANoptosis-related genes and established a PANoptosis-risk signature using the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. We combined TCGA, bulk RNA sequencing, and single-cell sequencing to investigate the correlation between candidate genes and the AML tumor microenvironment.

Results

The PANoptosis risk signature effectively predicted prognosis with good sensitivity and specificity. The risk score emerged as an independent prognostic factor. Functional enrichment analysis of PANoptosis-related differentially expressed genes suggested that the risk score may be related to cell immunity. Patients with high-risk scores exhibited increased immune cell infiltration, implying a hot tumor immune microenvironment. The risk score was positively correlated with the immune scores and expression levels of immune checkpoints. Therefore, we identified three model factors, BIRC3, PELI1, and PRKACG, as predictors for immunotherapy efficacy. Single-cell sequencing analysis demonstrated that PELI1 and BIRC3 may participate in the regulation of the AML immune microenvironment. Finally, we performed a drug sensitivity analysis to target BIRC3 and PELI1 using molecular docking and molecular dynamics simulations.

Conclusion

Our study established and verified a PANoptosis risk signature to predict the survival and immunological treatment response in AML.

Identification of early Alzheimer's disease subclass and signature genes based on PANoptosis genes

Introduction

Alzheimer's disease (AD) is one of the most prevalent forms of dementia globally and remains an incurable condition that often leads to death. PANoptosis represents an emerging paradigm in programmed cell death, integrating three critical processes: pyroptosis, apoptosis, and necroptosis. Studies have shown that apoptosis, necroptosis, and pyroptosis play important roles in AD development. Therefore, targeting PANoptosis genes might lead to novel therapeutic targets and clinically relevant therapeutic approaches. This study aims to identify different molecular subtypes of AD and potential drugs for treating AD based on PANoptosis.

Methods

Differentially expressed PANoptosis genes associated with AD were identified via Gene Expression Omnibus (GEO) dataset GSE48350, GSE5281, and GSE122063. Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to construct a risk model linked to these PANoptosis genes. Consensus clustering analysis was conducted to define AD subtypes based on these genes. We further performed gene set variation analysis (GSVA), functional enrichment analysis, and immune cell infiltration analysis to investigate differences between the identified AD subtypes. Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and the DGIdb database was consulted to identify potential therapeutic compounds targeting these hub genes. Single-cell RNA sequencing analysis was utilized to assess differences in gene expression at the cellular level across subtypes.

Results

A total of 24 differentially expressed PANoptosis genes (APANRGs) were identified in AD, leading to the classification of two distinct AD subgroups. The results indicate that these subgroups exhibit varying disease progression states, with the early subtype primarily linked to dysfunctional synaptic signaling. Furthermore, we identified hub genes from the differentially expressed genes (DEGs) between the two clusters and predicted 38 candidate drugs and compounds for early AD treatment based on these hub genes. Single-cell RNA sequencing analysis revealed that key genes associated with the early subtype are predominantly expressed in neuronal cells, while the differential genes for the metabolic subtype are primarily found in endothelial cells and astrocytes.

Conclusion

In summary, we identified two subtypes, including the AD early synaptic abnormality subtype as well as the immune-metabolic subtype. Additionally, ten hub genes, SLC17A7, SNAP25, GAD1, SLC17A6, SLC32A1, PVALB, SYP, GRIN2A, SLC12A5, and SYN2, were identified as marker genes for the early subtype. These findings may provide valuable insights for the early diagnosis of AD and contribute to the development of innovative therapeutic strategies.

DNASE1L3-mediated PANoptosis enhances the efficacy of combination therapy for advanced hepatocellular carcinoma

Rationale: The introduction of combination therapy utilizing tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors for advanced hepatocellular carcinoma (HCC) has significantly altered the management of affected patients. However, the absence of predictive biomarkers to identify those who would derive the greatest benefit from this combination therapy underscores the necessity for further enhancements in its efficacy. Methods: In this study, we performed a proteomic analysis on surgical specimens from patients who either responded to or did not respond to combination therapy with sorafenib and programmed death-1 (PD-1) monoclonal antibody (mAb). We employed in vitro experiments, including immunocytochemistry, co-immunoprecipitation, and transmission electron microscopy, to elucidate the mechanism of DNASE1L3-induced PANoptosis. Additionally, we assessed the function of DNASE1L3 in combination therapy using a mouse liver orthotopic tumor model and clinical samples. Results: Our findings indicated that the levels of deoxyribonuclease 1 like 3 (DNASE1L3) were significantly elevated in the cohort of patients who responded to treatment, correlating with the sorafenib-induced programmed cell death (PCD) of HCC cells. Further experimentation revealed that DNASE1L3 facilitated the generation of double-strand deoxyribonucleic acid (dsDNA) breaks and activated the absent in melanoma 2 (AIM2) pathway during sorafenib-induced HCC cell death, ultimately culminating in PANoptosis. Moreover, DNASE1L3-induced PANoptosis augmented the activation of anti-tumor immunity within the tumor microenvironment (TME), thereby enhancing the efficacy of the combination therapy involving sorafenib and PD-1 mAb. Conclusion: Our findings offer valuable insights into the mechanisms underlying DNASE1L3's role in sorafenib sensitivity and position DNASE1L3 as a promising predictive biomarker and target for improving outcomes in combination therapy for HCC.

Aphthous stomatitis - computational biology suggests external biotic stimulus and immunogenic cell death involved

BACKGROUND

The exact cause of recurrent aphthous stomatitis is still unknown, making it a challenge to develop effective treatments. This study employs computational biology to investigate the molecular basis of recurrent aphthous stomatitis, aiming to identify the nature of the stimuli triggering these ulcers and the type of cell death involved.

METHODS

To understand the molecular underpinnings of recurrent aphthous stomatitis, we used the Génie tool for gene identification, targeting those associated with cell death in recurrent aphthous stomatitis. The ToppGene Suite was employed for functional enrichment analysis. We also used Reactome and InteractiVenn for protein integration and prioritization against a PANoptosis gene list, enabling the construction of a protein-protein interaction network to pinpoint key proteins in recurrent aphthous stomatitis pathogenesis.

RESULTS

The study's computational approach identified 1,375 protein-coding genes linked to recurrent aphthous stomatitis. Critical among these were proteins responsive to bacterial stimuli, especially high mobility group protein B1 (HMGB1), toll-like receptor 2 (TLR2), and toll-like receptor 4 (TLR4). The enrichment analysis suggested an external biotic factor, likely bacterial, as a triggering agent in recurrent aphthous stomatitis. The protein interaction network highlighted the roles of tumor necrosis factor (TNF), NF-kappa-B essential modulator (IKBKG), and tumor necrosis factor receptor superfamily member 1A (TNFRSF1A), indicating an immunogenic cell death mechanism, potentially PANoptosis, in recurrent aphthous stomatitis.

CONCLUSION

The findings propose that bacterial stimuli could trigger recurrent aphthous stomatitis through a PANoptosis-related cell death pathway. This new understanding of recurrent aphthous stomatitis pathogenesis underscores the significance of oral microbiota in the condition. Future experimental validation and therapeutic strategy development based on these findings are necessary.

Molecular characterization analysis of PANoptosis-related genes in colorectal cancer based on bioinformatic analysis

Colorectal cancer (CRC) ranks as the third most prevalent cancer globally and stands as the second principal contributor to cancer-related fatalities. Recently, emerging research has emphasized the role of pan apoptosis (PANoptosis) in tumor development and anti-tumor therapy. In the course of this investigation, we meticulously identified and conducted a correlation analysis between differentially expressed genes associated with PANoptosis in CRC (CPAN_DEGs) and the proportion of immune cells. Subsequently, we formulated a prognostic score based on the CPAN_DEGs. Further our analysis revealed a noteworthy reduction in UNC5D mRNA expression within HCT116, HT29 and SW480 cells, as validated by qRT-PCR assay. Furthermore, scrutinizing the TCGA database unveiled a distinctive trend wherein individuals with the low UNC5D expression exhibited significantly reduced overall survival compared to their counterparts with the high UNC5D levels. The drug susceptibility analysis of UNC5D was further performed, which showed that UNC5D was corassociated with the sensitivity of CRC to 6-Thioguanine. The outcomes of our investigation underscore the mechanisms by which PANoptosis influences immune dysregulation as well as prognostic outcome in CRC.

Gene signature developed based on programmed cell death to predict the therapeutic response and prognosis for liver hepatocellular carcinoma

Background

The prognosis and therapeutic response of patients with liver hepatocellular carcinoma (LIHC) can be predicted based on programmed cell death (PCD) as PCD plays a crucial role during tumor progression. We developed a PCD-related gene signature to evaluate the therapeutic response and prognosis for patients with LIHC.

Methods

Molecular subtypes of LIHC were classified using ConsensusClusterPlus according to the gene biomarkers related to PCD. To predict the prognosis of high- and low-risk LIHC patients, a risk model was established by LASSO regression analysis based on the prognostic genes. Functional enrichment analysis was conducted using clusterProfiler package, and relative abundance of immune cells was quantified applying CIBERSORT package. Finally, to determine drug sensitivity, oncoPredict package was employed.

Results

PCD was correlated with the clinicopathologic features of LIHC. Then, we defined four molecular subtypes (C1-C4) of LIHC using PCD-related prognostic genes. Specifically, subtype C1 had the worst prognosis with enriched T cells regulatory (Tregs) and Macrophage_M0 and higher expression of T cell exhaustion markers, meanwhile, C1 also had a relatively higher TIDE score and metastasis potential. A risk model was established using 5 prognostic genes. High-risk patients tended to have higher expression of T cell exhaustion markers and TIDE score and unfavorable outcomes, and they were more sensitive to small molecule drug 5.Fluorouracil.

Conclusion

A PCD-related gene signature was developed and verified to be able to accurately predict the prognosis and drug sensitivity of LIHC patients.

PANoptosis: bridging apoptosis, pyroptosis, and necroptosis in cancer progression and treatment

This comprehensive review explores the intricate mechanisms of PANoptosis and its implications in cancer. PANoptosis, a convergence of apoptosis, pyroptosis, and necroptosis, plays a crucial role in cell death and immune response regulation. The study delves into the molecular pathways of each cell death mechanism and their crosstalk within PANoptosis, emphasizing the shared components like caspases and the PANoptosome complex. It highlights the significant role of PANoptosis in various cancers, including respiratory, digestive, genitourinary, gliomas, and breast cancers, showing its impact on tumorigenesis and patient survival rates. We further discuss the interwoven relationship between PANoptosis and the tumor microenvironment (TME), illustrating how PANoptosis influences immune cell behavior and tumor progression. It underscores the dynamic interplay between tumors and their microenvironments, focusing on the roles of different immune cells and their interactions with cancer cells. Moreover, the review presents new breakthroughs in cancer therapy, emphasizing the potential of targeting PANoptosis to enhance anti-tumor immunity. It outlines various strategies to manipulate PANoptosis pathways for therapeutic purposes, such as targeting key signaling molecules like caspases, NLRP3, RIPK1, and RIPK3. The potential of novel treatments like immunogenic PANoptosis-initiated therapies and nanoparticle-based strategies is also explored.

Identification and Analysis of PANoptosis-Related Genes in Sepsis-Induced Lung Injury by Bioinformatics and Experimental Verification

Purpose

Sepsis-induced lung injury (SLI) is a serious complication of sepsis. PANoptosis, a novel form of inflammatory programmed cell death that is not yet to be fully investigated in SLI. Our research aims to screen and validate the signature genes of PANoptosis in SLI by bioinformatics and in vivo experiment.

Methods

SLI-related datasets were downloaded from NCBI Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) of SLI were identified and intersected with the PANoptosis gene set to obtain DEGs related to PANoptosis (SPAN_DEGs). Then, Protein-Protein Interaction (PPI) network and functional enrichment analysis were conducted based on SPAN_DEGs. SVM-REF, LASSO and RandomForest three algorithms were combined to identify the signature genes. The Nomogram and ROC curves were performed to predict diagnostic value. Immune infiltration analysis, correlation analysis and differential expression analysis were used to explore the immunological characterization, correlation and expression levels of the signature genes. Finally, H&E staining and qRT-PCR were conducted for further verification in vivo experiment.

Results

Twenty-four SPAN_DEGs were identified by intersecting 675 DEGs with the 277 PANoptosis genes. Four signature genes (CD14, GSDMD, IL1β, and FAS) were identified by three machine learning algorithms, which were highly expressed in the SLI group, and had high diagnostic value in the diagnostic model. Moreover, immune infiltration analysis showed that most immune cells and immune-related functions were higher in the SLI group than those in the control group and were closely associated with the signature genes. Finally, it was confirmed that the cecum ligation and puncture (CLP) group mice showed significant pathological damage in lung tissues, and the mRNA expression levels of CD14, IL1β, and FAS were significantly higher than the sham group.

Conclusion

CD14, FAS, and IL1β may be the signature genes in PANoptosis to drive the progression of SLI and involved in regulating immune processes.

PANoptosis, an indicator of COVID-19 severity and outcomes

Coronavirus disease 2019 (COVID-19) has been wreaking havoc for 3 years. PANoptosis, a distinct and physiologically relevant inflammatory programmed cell death, perpetuates cytokine storm and multi-organ injuries in COVID-19. Although PANoptosis performs indispensable roles in host defense, further investigation is needed to elucidate the exact processes through which PANoptosis modulates immunological responses and prognosis in COVID-19. This study conducted a bioinformatics analysis of online single-cell RNA sequence (scRNA-seq) and bulk RNA-seq datasets to explore the potential of PANoptosis as an indicator of COVID-19 severity. The degree of PANoptosis in bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells (PBMC) indicated the severity of COVID-19. Single-cell transcriptomics identified pro-inflammatory monocytes as one of the primary sites of PANoptosis in COVID-19. The study subsequently demonstrated the immune and metabolic characteristics of this group of pro-inflammatory monocytes. In addition, the analysis illustrated that dexamethasone was likely to alleviate inflammation in COVID-19 by mitigating PANoptosis. Finally, the study showed that the PANoptosis-related genes could predict the intensive care unit admission (ICU) and outcomes of COVID-19 patients who are hospitalized.

A PANoptosis pattern to predict prognosis and immunotherapy response in head and neck squamous cell carcinoma

Individuals diagnosed with head and neck squamous cell carcinoma (HNSCC) experience a significant occurrence rate and are susceptible to premature spreading, resulting in a bleak outlook. Therapeutic approaches, such as chemotherapy, targeted therapy, and immunotherapy, may exhibit primary and acquired resistance during the advanced phases of HNSCC. There is currently no viable solution to tackle this issue. PANoptosis-a type of non-apoptotic cell death-is a recently identified mechanism of cellular demise that entails communication and synchronization among thermal apoptosis, apoptosis, and necrosis mechanisms. However, the extent to which PANoptosis-associated genes (PRG) contribute to the forecast and immune reaction of HNSCC remains mostly undisclosed. The present study aimed to thoroughly analyze the potential importance of PRG in HNSCC and report our discoveries. We systematically analyzed 19 PRG from previous studies and clinical data from HNSCC patients to establish a PAN-related signature and assess its prognostic, predictive potential. Afterward, the patient information was separated into two gene patterns that corresponded to each other, and the analysis focused on the connection between patient prognosis, immune status, and cancer immunotherapy. The PAN score was found to correlate with survival rates, immune systems, and cancer-related pathways. We then validated the malignant role of CD27 among them in HNSCC. In summary, we demonstrated the effectiveness of PAN.Score-based molecular clustering and prognostic features in predicting the outcome of HNSCC. The discovery we made could enhance our comprehension of the significance of PAN.Score in HNSCC and facilitate the development of more effective treatment approaches.

A novel PANoptosis-related long non-coding RNA index to predict prognosis, immune microenvironment and personalised treatment in hepatocellular carcinoma

BACKGROUND

PANoptosis is involved in the interaction of apoptosis, necroptosis and pyroptosis, playing a role in programmed cell death. Moreover, long non-coding RNAs (lncRNAs) regulate the PCD. This work aims to explore the role of PANoptosis-associated lncRNAs in hepatocellular carcinoma (HCC).

METHODS

Co-expression analysis identified PANoptosis-associated lncRNAs in HCC. Cox and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms were utilised to filter lncRNAs and establish a PANoptosis-related lncRNA index (PANRI). Additionally, Cox, Kaplan-Meier and receiver operating characteristic (ROC) curves were utilised to systematically evaluate the PANRI. Furthermore, Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE), single sample gene set enrichment analysis (ssGSEA) and immune checkpoints were performed to analyse the potential of the PANRI in differentiating different tumour immune microenvironment (TIME) populations. The consensus clustering algorithm was used to distinguish individuals with HCC having different TIME subtypes. Finally, HCC cell lines HepG2 were utilised for further validation in in vitro experiments.

RESULTS

The PANRI differentiates patients according to risk. Notably, ESTIMATE and ssGSEA algorithms revealed a high immune infiltration status in high-risk patients. Additionally, consensus clustering divided the patients into three clusters to identify different subtypes of TIME. Moreover, in vitro results showed that siRNA-mediated silencing of AL049840.4 inhibited the viability and migration of HepG2 cells and promoted apoptosis.

CONCLUSIONS

This is the first PANoptosis-related, lncRNA-based risk index in HCC to assess patient prognosis, TIME and response to immunotherapy. This study offers novel perspectives on the role of PANoptosis-associated lncRNAs in HCC.

Multidimensional Analysis of PANoptosis-Related Molecule CASP8: Prognostic Significance, Immune Microenvironment Effect, and Therapeutic Implications in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) presents significant challenges in diagnosis and treatment. Understanding the role of PANoptosis-related molecules in HCC is crucial for advancing therapeutic strategies.

Methods

We conducted a comprehensive analysis using public data from the Cancer Genome Atlas, Human Protein Atlas, Tumor Immune Single Cell Hub, and STRING databases. Techniques included Kaplan-Meier survival curves, Cox regression, LASSO analysis, and various computational methods for understanding the tumor microenvironment. We also employed ClueGO, gene set enrichment analysis, and other algorithms for biological enrichment analysis.

Results

CASP8 emerged as a significant molecule in HCC, correlated with poor survival outcomes. Its expression was predominant in the nucleoplasm and cytosol and varied across different cancer types. Biological enrichment analysis revealed CASP8's association with critical cellular activities and immune responses. In the tumor microenvironment, CASP8 showed correlations with various immune cell types. A nomogram plot was developed for better clinical prognostication. Mutation analysis indicated a higher frequency of TP53 mutations in patients with elevated CASP8 expression. In addition, CASP8 was found to regulate YEATS2 in HCC, highlighting a potential pathway in tumor progression.

Conclusions

Our study underscores the multifaceted role of CASP8 in HCC, emphasizing its prognostic and therapeutic significance. The regulatory relationship between CASP8 and YEATS2 opens new avenues for understanding HCC pathogenesis and treatment strategies.

Preclinical liver cancer models in the context of immunoprecision therapy: Application and perspectives

Hepatocellular carcinoma (HCC), ranking as the third leading cause of cancer-related mortality globally, continues to pose challenges in achieving optimal treatment outcomes. The complex nature of HCC, characterized by high spatiotemporal heterogeneity, invasive potential, and drug resistance, presents difficulties in its research. Consequently, an in-depth understanding and accurate simulation of the immune microenvironment of HCC are of paramount importance. This article comprehensively explores the application of preclinical models in HCC research, encompassing cell line models, patient-derived xenograft mouse models, genetically engineered mouse models, chemically induced models, humanized mouse models, organoid models, and microfluidic chip-based patient derived organotypic spheroids models. Each model possesses its distinct advantages and limitations in replicating the biological behavior and immune microenvironment of HCC. By scrutinizing the limitations of existing models, this paper aims to propel the development of next-generation cancer models, enabling more precise emulation of HCC characteristics. This will, in turn, facilitate the optimization of treatment strategies, drug efficacy prediction, and safety assessments, ultimately contributing to the realization of personalized and precision therapies. Additionally, this article also provides insights into future trends and challenges in the fields of tumor biology and preclinical research.

The emerging role of PANoptosis in cancer treatment

Programmed cell death (PCD) is a key mechanism for the study of anticancer drugs and has a significant impact on the development and management of cancer. A growing amount of data indicates that different kinds of PCD, particularly pyroptosis, apoptosis, and necroptosis, interact closely. Recent research has revealed the existence of the distinct inflammatory PCD modality known as PANoptosis, which is controlled by complex PANoptosome complexes built by combining elements from different PCD pathways. No single PCD route is sufficient to explain all of the physiologic effects seen in PANoptosis. Numerous studies have demonstrated that PANoptosis can successfully stop cancer cells from growing, proliferating, and developing drug resistance. As a result, it has changed the focus of targeted anticancer therapy. In this review, we outlined the molecular processes of PANoptosis activation and modulation as well as the mechanisms of innate immune cell death. In order to provide a theoretical foundation for the development of drugs targeting PANoptosis as an anti-cancer target, we also highlight the PANoptosomes discovered to date and give an overview of the implications of PANoptosis in cancer treatment.