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.


Introduction
Liver cancer, particularly hepatocellular carcinoma (HCC), represents one of the most lethal malignancies worldwide, posing a signifcant public health challenge [1].Te incidence and mortality rates of this cancer are on a continuous rise globally, with a pronounced prevalence in Asia and Africa [2].Te high incidence of liver cancer is closely associated with factors such as hepatitis virus infection, alcohol consumption, obesity, and environmental contributors [3].Te prognosis for patients with liver cancer is generally poor, primarily due to the advanced stage of the disease at diagnosis and the cancer's poor response to traditional chemotherapy and radiotherapy [4].Tese challenges have spurred extensive research into more efective treatment modalities for liver cancer, particularly in the realm of molecular targeted therapy [5].Signifcant advancements have been made in molecular targeted therapies in recent years.Tis therapeutic approach is predicated on a deep understanding of the biological characteristics of tumor cells and aims to develop drugs that target specifc molecular markers [6].For instance, targeted therapies developed against common signaling pathway aberrations in liver cancer cells, such as the PI3K/AKT/mTOR and RAS/RAF/ MEK/ERK pathways, have shown promising therapeutic potential [7,8].In addition, immunotherapy, especially the use of immune checkpoint inhibitors, has demonstrated unprecedented potential in the treatment of liver cancer [9].However, further research is needed to determine which patients will beneft from these therapies and how to combine these treatments to enhance efcacy.Consequently, research on liver cancer is focusing on improving early diagnostic methods, understanding the molecular biological mechanisms of the tumor, and developing more efective personalized treatment strategies.
PANoptosis represents a comprehensive concept encompassing various forms of programmed cell death, including but not limited to classical apoptosis, necroptosis, ferroptosis, and pyroptosis [10].Tis notion is crucial for understanding the diversity and complexity of cell death, especially in disease states.In the feld of oncology, research into PANoptosis ofers novel insights into the mechanisms of survival and death of tumor cells, with particular emphasis on HCC [11].HCC, a highly aggressive tumor, often exhibits dysregulation in its cell death pathways, which are intricately linked to the tumor's development, progression, and resistance to treatment [12].Current research in HCC focuses on exploring how tumor cells evade programmed cell death and utilizing this knowledge to develop novel therapeutic strategies.For instance, studies have shown that HCC cells evade apoptosis by altering specifc apoptotic signaling pathways, such as the expression of Bcl-2 family proteins, thus afecting tumor growth and spread [13].Targeted therapies against these pathways could ofer new avenues for HCC treatment.In addition, understanding the unique mechanisms of PANoptosis in HCC is vital for predicting treatment responses and developing personalized treatment plans.Given the central role of PANoptosis in the pathogenesis of HCC, in-depth research in this area is crucial for the development of new diagnostic biomarkers and therapeutic targets [14].Tis will not only help elucidate the pathophysiological mechanisms of HCC but may also lead to more efective treatment modalities, thereby improving clinical outcomes for patients.
Our study conducted a thorough investigation of CASP8 in HCC.We identifed CASP8 as a crucial molecule through analyses of PANoptosis-related molecules, ClueGO, and protein-protein interaction networks.High CASP8 expression was linked to poor patient survival, suggesting its prognostic importance.Immunofuorescence images confrmed CASP8's presence in the nucleoplasm and cytosol.A pan-cancer analysis and single-cell techniques revealed its varied expression and distribution across diferent cancer types and cell types, respectively.Biological enrichment analysis showed CASP8's association with various biological pathways, and its correlation with diverse immune cell types indicated a signifcant role in the HCC immune landscape.In addition, we developed a nomogram for better clinical prognosis, analyzed CASP8's infuence on immunotherapy and chemotherapy, and investigated its relationship with TP53 mutations.Te study also explored CASP8's regulatory efect on YEATS2, further understanding its biological signifcance in HCC.Tis research underscores the potential of CASP8 as a key prognostic marker and therapeutic target in HCC.

Downloading and Preprocessing Public Data for HCC.
Initially, the clinical data, expression profles, and mutation data were acquired from Te Cancer Genome Atlas (TCGA) database [15].Te format of the expression profles was STAR-Counts, which was subsequently converted into the TPM format using the author's R code.Te clinical data were formatted in bcr-xml.Prior to data analysis, the expression profle data underwent preprocessing, including normalization, to ensure data quality and reproducibility.Representative cell fuorescence images were sourced from the Human Protein Atlas (HPA) database [16].In addition, single-cell data were downloaded from the Tumor Immune Single Cell Hub (TISCH) project [17], a comprehensive database that provides detailed single-cell expression profles to facilitate the study of tumor immunology and the tumor microenvironment across various cancer types [18][19][20][21][22][23].Te data of protein interaction were obtained from the STRING database.

Prognosis Analysis.
Te prognosis analysis of our study focuses on evaluating the survival outcomes of patients using Kaplan-Meier (KM) survival curves and univariate Cox regression analysis.Te KM survival curves are employed to graphically represent the survival probability over time, allowing us to visually compare the survival experiences of diferent patient cohorts.Tis method is instrumental in estimating survival functions and median survival times.On the other hand, univariate Cox regression analysis is used to assess the impact of individual variables on survival.To further improve the clinical potential of CASP8 in HCC, we develop a nomogram.Tis graphical tool integrates multiple prognostic variables, identifed as signifcant in the Cox regression analysis, into a single model.LASSO regression analysis is a penalized regression method efective in handling high-dimensional data and in selecting the most relevant prognostic factors while controlling for overftting.

Biological Enrichment Analysis. We employ both
ClueGO and gene set enrichment analysis (GSEA) to elucidate the biological contexts and pathways [24].ClueGO, a Cytoscape plugin, is utilized for deciphering functionally grouped gene ontology and pathway annotation networks [25].In addition, GSEA is performed to identify whether a predefned set of genes shows statistically signifcant, concordant diferences between two biological states.It helps in understanding gene expression data at the level of gene sets, based on their distribution within ranked gene lists, thereby ofering a more comprehensive view of the biological pathways and processes involved.

Tumor Microenvironment and Immune Function
Analysis.Our study integrates a suite of sophisticated computational methods to characterize the cellular composition and immune landscape within the tumor milieu.We utilize CIBERSORT, an algorithm that applies a deconvolution method to estimate the cell type proportions in bulk tissue gene expression data, providing insights into the immune cell composition [26].EPIC is employed for quantifying the abundance of stromal and immune cells in tumor samples [27].MCPcounter is used for the robust quantifcation of the presence of specifc immune 2 Genetics Research and stromal cell populations [28].QUANTISEQ, an algorithm designed for immune profling, is applied to dissect the tumor immune contexture [29].TIMER, another critical tool in our analysis, is utilized for the systematic evaluation of tumor-infltrating immune cells and their clinical implications [30].xCell, a gene signature-based method, aids in the comprehensive profling of the tumor microenvironment, encompassing a wide variety of immune and stromal cell types [31].Te immune function status was quantifed using the single-sample GSEA (ssGSEA) algorithm [32].

Statistical Analysis.
We apply a rigorous and systematic approach, ensuring the validity and reliability of our fndings, with all statistical analyses and graph creation conducted using the R programming language.Initially, we assess the normality of data

Identifcation of PANoptosis-Related Molecule CASP8 in HCC.
In our study, we began by compiling a comprehensive list of molecules associated with PANoptosis, guided by extensive previous research in this feld (Figure 1(a)).To further explore their biological signifcance, we employed ClueGO analysis, revealing that these molecules predominantly contribute to various biological processes.Tese include the positive regulation of interleukin-1 beta production, enhancement of cysteinetype endopeptidase activity, and the promotion of interleukin-1 production.In addition, they are involved in pyroptosis and the activation of cysteine-type endopeptidase activity in apoptotic processes (Figure 1(b)).To understand the intricate interactions among these molecules, we constructed a protein-protein interaction (PPI) network.Tis network highlighted the complex interplay and revealed the top ten central nodes as TNF, RIPK3, CASP8, CASP1, RIPK1, CASP9, CASP2, FADD, MLKL, and CASP3 (Figures 1(c)-1(d)).Following this, we applied univariate Cox regression analysis to discern the prognostic signifcance of these molecules in HCC (Figure 1(e)).Tis analysis identifed several molecules as potential risk factors, including CASP2, GSDMC, CASP8, NLRC4, and others, while NLRP6 emerged as a protective factor.Our focused attention then shifted to CASP8, which is singled out for its prominent role in the PPI network and its statistical signifcance in the Cox regression analysis.We discovered that high expression levels of CASP8 in HCC patients correlated with poorer survival outcomes, as depicted in the KM survival curve (Figure 1(f )).In addition, our observations suggested a potential link between elevated CASP8 levels and worsened histological grades, although no signifcant correlation with clinical staging was observed (Figures 1(g)-1(h)).

Expression Pattern of CASP8 in HCC.
Utilizing representative immunofuorescence images from the HPA database, our investigation revealed the cellular localization of CASP8.Te images clearly showed that CASP8 is primarily located in the nucleoplasm and cytosol, which suggests a signifcant role for CASP8 in these specifc cellular regions (Figure 2(a)).Delving further into the expression profle of CASP8, we extended our research to a pan-cancer analysis.Tis comprehensive examination indicated that CASP8 exhibits varied expression levels across multiple cancer types, highlighting its potential importance in the pathogenesis of a diverse range of cancers (Figure 2(b)).To gain a more detailed understanding of CASP8 distribution, we employed single-cell analysis techniques.Te results of this intricate examination revealed that CASP8 is extensively distributed across a wide array of cell types (Figures 2(c)-2(f )).Tis widespread presence emphasizes the versatility of CASP8 in cellular processes, potentially afecting various aspects of cancer biology.

Biological Enrichment Analysis.
GSEA provided signifcant insights into the biological pathways and processes associated with CASP8.We found that CASP8 expression positively correlates with several key cellular activities.Tese include the E2F target activity, processes related to the mitotic spindle and G2M checkpoint, infammatory responses, spermatogenesis, Hedgehog signaling pathways, apical junction mechanisms, and the epithelialmesenchymal transition (EMT).Conversely, CASP8 showed a negative correlation with activities such as myogenesis, MYC target processes, DNA repair, xenobiotic metabolism, adipogenesis, oxidative phosphorylation, and fatty acid metabolism (Figure 3(a)).In terms of Gene Ontology (GO) terms, our GSEA revealed that patients with high CASP8 expression demonstrated increased activity in several biological processes.Notably, there was heightened activity in the T cell receptor complex, female meiotic nuclear division, and regulation of transposition.On the other hand, these patients exhibited reduced activity in areas such as ribosomal subunits, cytosolic ribosomes, and ribosomes in general (Figures 3(b)-3(c)).For Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, GSEA further highlighted that high CASP8 expression in patients was linked to increased activity in axon guidance, extracellular matrix (ECM) receptor interactions, and pathways relevant to small cell lung cancer.In contrast, there was a notable decrease in activities related to the ribosome, oxidative phosphorylation, and pathways associated with Parkinson's disease (Figures 3(d)-3(e)).).In addition, the analysis indicated that patients with high CASP8 expression might have elevated levels of major histocompatibility complex class I (MHC class I), juxtaposed with lower cytolytic activity (Figure 4(c)).Tis suggests a complex interaction between CASP8 expression and the immune response within the TME of HCC.

Nomogram Plot, Drug Sensitivity, and Mutation Analysis.
To enhance the clinical prognostic capabilities associated with CASP8, a nomogram plot was developed based on the expression values of CASP8 (Figure 5(a)).Calibration graphs further validated the accuracy of this nomogram, demonstrating a strong correlation between the predicted survival outcomes and the actual observed survival rates (Figure 5(b)).With the increasing relevance of immunotherapy in treating liver cancer, we focused on assessing the impact of CASP8 on the efcacy of such treatments.Our fndings revealed that various immune checkpoints exhibited diferent expression patterns in patients with varying levels of CASP8 expression (Figure 5(c)).Tis suggests a potential role for CASP8 in modulating the response to immunotherapeutic approaches.Drug sensitivity analysis provided additional insights, indicating that patients with a higher CASP8 expression might exhibit increased sensitivity to certain chemotherapeutic agents, specifcally vorinostat and doxorubicin (Figure 5(d)).We also explored the gene mutation landscape of CASP8 in HCC patients (Figures 6(a) and 6(b)).While there was no signifcant correlation found between CASP8 expression and tumor mutational burden (TMB) or microsatellite instability (MSI) scores (Figures 6(c) and 6(d)), an interesting pattern emerged regarding TP53 mutations.Patients with elevated CASP8 expression tended to have a higher frequency of TP53 mutations (Figure 6(e)).Tis observation might provide a new perspective on the genetic alterations associated with CASP8 expression in liver cancer.

CASP8 Can Regulate the YEATS2 in HCC.
Our analysis has taken initial steps to uncover the potential role of CASP8 in HCC.A key focus was to identify downstream regulatory genes of CASP8.To this end, we frst pinpointed the top 200 molecules that showed signifcant correlation with CASP8 expression (Figure 7(a)).Following this, univariate Cox regression analysis was utilized to determine which of these molecules had a signifcant correlation with patient survival (Supplementary fle 1).Subsequently, we employed LASSO regression analysis to refne our data and optimize the variables for further study (Figures 7(b) and 7(c)).Tis was an essential step in ensuring the robustness of our fndings.Te subsequent multivariate Cox regression analysis highlighted YEATS2 as the only molecule signifcantly and independently correlated with patient survival (Figure 7(d)).Interestingly, a substantial positive correlation between CASP8 and YEATS2 in HCC tissue was observed (Figure 7(e), R � 0.683 and P < 0.001).Tis fnding indicates a potential interaction or pathway involving these two molecules that could be pivotal in the progression of HCC.Furthermore, our analysis suggested that patients with high CASP8 expression might have a poorer survival outcome compared to those with lower expression levels (Figure 7(f )).

Biological Enrichment and Expression Pattern of CASP8 in HCC.
Delving into the biological role of YEATS2 in HCC, GSEA was conducted.Te results indicated that patients with high expression of YEATS2 tended to exhibit enhanced activity in several critical biological processes.Notably, there was an increase in activities related to EMT, early estrogen response, TNF-α signaling via the NFKB pathway, E2F targets, and mitotic spindle functions.Conversely, a decrease in activities related to cholesterol homeostasis, heme metabolism, the reactive oxygen species pathway, oxidative phosphorylation, xenobiotic metabolism, and adipogenesis was observed (Figure 7(g)).In addition to the GSEA, singlecell expression analysis was employed to examine the distribution of YEATS2 in HCC.Tis analysis revealed that YEATS2 is widely distributed across various cell types within HCC, indicating its pervasive infuence and potential role in multiple aspects of tumor biology and microenvironment interactions (Figures 8(a)-8(f )).Te whole fowchart is shown in Figure S1.

Discussion
Liver cancer, one of the most common malignant tumors globally, is witnessing an increasing trend in both incidence and mortality rates [33].Tis malignancy is mainly classifed into primary and secondary types, with HCC being the most prevalent form of primary liver cancer.Te development of liver cancer is linked to a variety of factors, including chronic viral hepatitis, alcoholic liver disease, nonalcoholic fatty liver disease, and a range of environmental and genetic contributors [34].Among the various treatment options, such as surgical resection, radiotherapy, and chemotherapy, targeted therapy emerges as a particularly promising approach [35].It ofers a more precise treatment modality by specifcally targeting cancer cells while sparing normal tissues, thereby potentially reducing side efects and improving treatment outcomes.However, the often asymptomatic early stages of liver cancer lead to late diagnoses, challenging the efectiveness of these treatments [36].Tus, a pivotal focus of future research lies in advancing early detection methods and prevention strategies, alongside enhancing the efcacy and scope of targeted therapies in liver cancer management.
Our study presents a comprehensive analysis of the role of CASP8 in HCC.Initially, we compiled an extensive list of PANoptosis-related molecules and identifed CASP8 as a key   (c)       positive correlations with processes such as E2F target activity and infammatory responses and negative correlations with processes such as myogenesis.In examining the tumor microenvironment, CASP8 showed signifcant correlations with various immune cell types, suggesting its infuence on the immune landscape in HCC.Furthermore, we developed a nomogram plot for better clinical prognostication and investigated CASP8's impact on the efcacy of immunotherapy and chemotherapeutic agents.Mutation analysis revealed a pattern in TP53 mutations among patients with high CASP8 expression.Te study also explored the regulatory role of CASP8 on YEATS2 in HCC, fnding a strong positive correlation between these molecules.GSEA and single-cell expression analysis of YEATS2 further elucidated its biological role and widespread infuence in HCC.Overall, our study provides a detailed insight into the multifaceted role of CASP8 in HCC, emphasizing its potential as a prognostic marker and therapeutic target.
CASP8 is a crucial protein in the human body, playing a pivotal role in the process of apoptosis or programmed cell death [37].Tis protein is especially signifcant as it aids in maintaining the normal life cycle of cells and is vital in eliminating damaged or abnormal cells.In various diseases, the functionality of CASP8 becomes particularly important [38].For instance, in cancer, aberrant expression or malfunction of CASP8 can lead to tumor cells evading apoptosis, thereby afecting the development and spread of cancer [39].In addition, CASP8 has shown its signifcance in certain autoimmune diseases and neurodegenerative disorders, where it may be involved in regulating infammatory responses or afecting the survival of neuronal cells.Terefore, CASP8 is not only a key element in cellular biology but also a critical target in disease research and potential therapeutic strategies.
YEATS2 is increasingly recognized for its critical role in cellular processes such as gene expression regulation and chromatin structure maintenance [40].Tis protein's function is the key in understanding various disease mechanisms, particularly in oncology.For instance, in cancer, dysregulation or mutations of YEATS2 can lead to aberrant gene expression and chromatin modifcations, contributing to the oncogenic processes [41].Tis involvement in cancer progression underscores the importance of YEATS2 as a potential biomarker for cancer prognosis and a target for therapeutic intervention.Fox example, Zeng et al. indicated that YEATS2 is an underlying biological target for pancreatic cancer and could signifcantly promote the proliferation and migration ability of cancer cells [42].Mi et al. found that the YEATS2 is a marker of tumorigenesis for nonsmall cell lung cancer (NSCLC) [43].Also, YEATS2 is found to be a target for certain drugs.Lan et al. noticed that cinobufacini could delay progression of pancreatic adenocarcinoma by targeting the YEATS2/ TAK1/NF-κB axis [44].
An essential aspect of this study involves the data sourced from TCGA patients.It is crucial to acknowledge that a signifcant proportion of these patients are of Caucasian descent.Tis demographic skew has potential implications for our fndings, as the results may not be wholly representative of diverse populations.Terefore, the conclusions drawn must be cautiously generalized, keeping in mind the racial homogeneity of our primary data source.In addition, the utilization of bioinformatics algorithms in our study warrants careful consideration.While these computational tools are useful in deciphering complex biological data, they are not infallible in capturing the full spectrum of biological signifcance.Te algorithms employed ofer an interpretation based on mathematical and statistical principles, which might not always align perfectly with the underlying biological phenomena.Hence, the insights provided by these bioinformatics analyses should be regarded as indicative rather than defnitive.Tey serve as a valuable reference point, guiding further empirical research rather than conclusively delineating biological realities.In summary, while our study ofers signifcant insights, the potential racial bias due to the predominance of Caucasian data in TCGA and the inherent limitations of bioinformatics algorithms as interpretative tools must be considered when applying our fndings to broader contexts.
Analysis.Delving into the infuence of CASP8 on the tumor microenvironment of HCC, our research uncovered signifcant correlations with

Figure 3 :
Figure 3: Biological enrichment of CASP8.(a) GSEA of CASP8 in HCC based on the hallmark gene set; (b) the top three upregulated GO terms of CASP8 based on GSEA; (c) the top three downregulated GO terms of CASP8 based on GSEA; (d) the top three upregulated KEGG terms of CASP8 based on GSEA; (e) the top three downregulated KEGG terms of CASP8 based on GSEA.

Figure 4 :Figure 5 :
Figure 4: Immune analysis of CASP8.(a-b) Correlation between CASP8 and the cell components in HCC quantifed by multiple algorithms and (c) diference of immune terms quantifed by ssGSEA algorithms in patients with high and low CASP8 expression.

Figure 6 :
Figure 6: Mutation landscape of CASP8 in HCC.(a) the mutation of CASP8 in the HCC genome; (b) the mutational landscape of HCC; (c-d) correlation between CASP8 and TMB, as well as MSI; (e) patients with high CASP8 expression tend to have more TP53 mutation.

Figure 7 :
Figure 7: Identifcation of the CASP8/YEATS2 axis.(a) Top 200 molecules signifcantly correlated with CASP8; (b-c) LASSO regression analysis based on the molecules signifcantly correlated with patients survival; (d) multivariate Cox regression analysis of the molecules identifed by LASSO regression analysis; (e) correlation between CASP8 and YEATS2; (f ) KM survival curves of YEATS2; (g) GSEA of YEATS2 based on the hallmark gene set.

Figure 8 :
Figure 8: Single-cell analysis of YEATS2 in the HCC microenvironment.(a-f ) Expression level of YEATS2 in the HCC microenvironment at the single-cell level.