Caspase 4 Overexpression as a Prognostic Marker in Clear Cell Renal Cell Carcinoma: A Study Based on the Cancer Genome Atlas Data Mining

Caspase-4 promotes metastasis and interferon-γ-induced pyroptosis in lung adenocarcinoma

Caspase-4 (CASP4) is a member of the inflammatory caspase subfamily and promotes inflammation. Here, we report that CASP4 in lung adenocarcinoma cells contributes to both tumor progression via angiogenesis and tumor hyperkinesis and tumor cell killing in response to high interferon (IFN)-γ levels. We observe that elevated CASP4 expression in the primary tumor is associated with cancer progression in patients with lung adenocarcinoma. Further, CASP4 knockout attenuates tumor angiogenesis and metastasis in subcutaneous tumor mouse models. CASP4 enhances the expression of genes associated with angiogenesis and cell migration in lung adenocarcinoma cell lines through nuclear factor kappa-light chain-enhancer of activated B cell signaling without stimulation by lipopolysaccharide or tumor necrosis factor. CASP4 is induced by endoplasmic reticulum stress or IFN-γ via signal transducer and activator of transcription 1. Most notably, lung adenocarcinoma cells with high CASP4 expression are more prone to IFN-γ-induced pyroptosis than those with low CASP4 expression. Our findings indicate that the CASP4 level in primary lung adenocarcinoma can predict metastasis and responsiveness to high-dose IFN-γ therapy due to cancer cell pyroptosis.

Advances in Genomic Data and Biomarkers: Revolutionizing NSCLC Diagnosis and Treatment

Non-small cell lung cancer (NSCLC) is a significant public health concern with high mortality rates. Recent advancements in genomic data, bioinformatics tools, and the utilization of biomarkers have improved the possibilities for early diagnosis, effective treatment, and follow-up in NSCLC. Biomarkers play a crucial role in precision medicine by providing measurable indicators of disease characteristics, enabling tailored treatment strategies. The integration of big data and artificial intelligence (AI) further enhances the potential for personalized medicine through advanced biomarker analysis. However, challenges remain in the impact of new biomarkers on mortality and treatment efficacy due to limited evidence. Data analysis, interpretation, and the adoption of precision medicine approaches in clinical practice pose additional challenges and emphasize the integration of biomarkers with advanced technologies such as genomic data analysis and artificial intelligence (AI), which enhance the potential of precision medicine in NSCLC. Despite these obstacles, the integration of biomarkers into precision medicine has shown promising results in NSCLC, improving patient outcomes and enabling targeted therapies. Continued research and advancements in biomarker discovery, utilization, and evidence generation are necessary to overcome these challenges and further enhance the efficacy of precision medicine. Addressing these obstacles will contribute to the continued improvement of patient outcomes in non-small cell lung cancer.

Genetic polymorphisms in genes regulating cell death and prognosis of patients with rectal cancer receiving postoperative chemoradiotherapy

OBJECTIVE

The identification of biomarkers for predicting chemoradiotherapy efficacy is essential to optimize personalized treatment. This study determined the effects of genetic variations in genes involved in apoptosis, pyroptosis, and ferroptosis on the prognosis of patients with locally advanced rectal cancer receiving postoperative chemoradiotherapy (CRT).

METHODS

The Sequenom MassARRAY was used to detect 217 genetic variations in 40 genes from 300 patients with rectal cancer who received postoperative CRT. The associations between genetic variations and overall survival (OS) were evaluated using hazard ratios (HRs) and 95% confidence intervals (CIs) computed using a Cox proportional regression model. Functional experiments were performed to determine the functions of the arachidonate 5-lipoxygenase (ALOX5) gene and the ALOX5 rs702365 variant.

RESULTS

We detected 16 genetic polymorphisms in CASP3, CASP7, TRAILR2, GSDME, CASP4, HO-1, ALOX5, GPX4, and NRF2 that were significantly associated with OS in the additive model (P < 0.05). There was a substantial cumulative effect of three genetic polymorphisms (CASP4 rs571407, ALOX5 rs2242332, and HO-1 rs17883419) on OS. Genetic variations in the CASP4 and ALOX5 gene haplotypes were associated with a higher OS. We demonstrated, for the first time, that rs702365 [G] > [C] represses ALOX5 transcription and corollary experiments suggested that ALOX5 may promote colon cancer cell growth by mediating an inflammatory response.

CONCLUSIONS

Polymorphisms in genes regulating cell death may play essential roles in the prognosis of patients with rectal cancer who are treated with postoperative CRT and may serve as potential genetic biomarkers for individualized treatment.

Dissection of pyroptosis-related prognostic signature and CASP6-mediated regulation in pancreatic adenocarcinoma: new sights to clinical decision-making

Recent studies have indicated that pyroptosis may participate in the regulation of tumorigenesis and immune microenvironment. However, the role of pyroptosis-related genes (PRGs) in pancreatic adenocarcinoma (PAAD) remains unclear. Through multiple bioinformatics analysis, we constructed a prognostic gene model and competing endogenous RNA network. The correlation between PRGs and prognosis, immune infiltration, immune checkpoints, and tumor mutational burden was analyzed by Kaplan-Meier curve, univariate Cox, multivariate regression, and Spearman's analysis in PAAD patients. The qRT-PCR, Western blotting, CCK-8, Wound healing, and Transwell assay were applied to examine the role of CASP6 in PANC-1 cell. Thirty-one PRGs were upregulated in PAAD. Functional enrichment analysis revealed that the PRGs were mainly involved in pyroptosis, NOD-like receptor signaling pathway, and response to bacteria. We established a novel 4-gene signature related to PRGs for evaluating the prognosis of PAAD patients. Patients with PAAD in the low-risk group had a better prognosis than those in the high-risk group. The nomogram suggested that the 1-, 3-, and 5-years survival probability exhibited robust predictive performance. Significant correlation was observed between prognostic PRGs and immune infiltration, immune checkpoints, and tumor mutational burden. We first identified the potential competing endogenous RNA regulatory axis in PAAD: lncRNA PVT1/hsa-miR-16-5p/CASP6/CASP8. Moreover, knockdown of CASP6 dramatically inhibited the proliferation, migration, and invasion ability of PANC-1 cell in vitro. In conclusion, CASP6 could be a potential biomarker, promoting the occurrence and progression in PAAD. The lncRNA PVT1/hsa-miR-16-5p/CASP6/CASP8 regulatory axis plays an vital role in regulating the anti-tumor immune responses for PAAD.

Systematic Analysis of a Pyroptosis-Related Signature to Predict the Prognosis and Immune Microenvironment of Lower-Grade Glioma

Current treatments for lower-grade glioma (LGG) do not effectively improve life expectancy rates, and this is a major global health concern. Improving our knowledge of this disease will ultimately help to improve prevention, accurate prognosis, and treatment strategies. Pyroptosis is an inflammatory form of regulated cell death, which plays an important role in tumor progression and occurrence. There is still a lack of effective markers to evaluate the prognosis of LGG patients. We collected paraffin-embedded tissue samples and prognostic information from 85 patients with low-grade gliomas and fabricated them into a tissue microarray. Combining data from public databases, we explored the relationship between pyroptosis-related genes (PRGs) and the prognoses of patients with LGG and investigated their correlations with the tumor microenvironment (TME) by means of machine learning, single-cell, immunohistochemical, nomogram, GSEA, and Cox regression analyses. We developed a six-gene PRG-based prognostic model, and the results have identified CASP4 as an effective marker for LGG prognosis predictions. Furthermore, the effects on immune cell infiltration may also provide guidance for future immunotherapy strategies.

A Predictive Model Based on Pyroptosis-Related Gene Features Can Effectively Predict Clear Cell Renal Cell Carcinoma Prognosis and May Be an Underlying Target for Immunotherapy

Methods

The clinical information and RNA-seq data of ccRCC patients were collected from the TCGA dataset to first explore differential pyroptosis-related genes (PRGs). Univariate Cox regression and consensus clustering were applied to identify ccRCC subtypes. The prognostic PRGs were subjected to LASSO regression analysis to establish a prognostic model and to investigate its value and function. Finally, the relationship of the model immunity checkpoints and immunity infiltration was assessed.

Results

The receiver operating characteristic (ROC) showed that the 1-year, 3-year, and 5-year prediction rates of the prognostic model were 0.715, 0.693, and 0.732, respectively. The high-risk group had lower overall survival and higher stage than the low-risk group. Functional enrichment analysis showed that PRGs were significantly enriched mainly in the PPAR pathway, inflammatory pathway, and immune activity. ccRCC patient prognosis correlates with immune components in the microenvironment, and immune checkpoint molecules are significantly expressed in the high-risk group. Immunotherapy may be effective in the high-risk group.

Conclusion

Pyroptosis-related gene has an important impact on the progression of ccRCC and can be used as an independent predictor of patient prognosis. In addition, immune checkpoint molecules are significantly upregulated in high-risk populations, which may be a potential target for immunotherapy.

Pyroptosis-related genes regulate proliferation and invasion of pancreatic cancer and serve as the prognostic signature for modeling patient survival

OBJECTIVE

Pancreatic ductal adenocarcinoma (PDAC) has high mortality and poor prognosis. Pyroptosis can influence the prognosis of patients by regulating the proliferation, invasion, and metastasis of cancer cells. However, the role of pyroptosis-related genes (PRGs) in PDAC remains unclear.

METHODS

In this study, based on the Cancer Genome Atlas (TCGA) cohort of PDAC samples, univariate Cox analysis and LASSO regression analysis were used to screen the prognostic PRGs and establish the gene signature. To further evaluate the functional significance of CASP4 and NLRP1 in PDAC, we also conducted an in vitro study to explore the mechanism of CASP4 and NLRP1 regulating the occurrence and development of PDAC. Finally, we investigated the relationship between CASP4 and NLRP1 expression levels and drug sensitivity in pancreatic cancer cells.

RESULTS

A risk prediction model based on CASP4 and NLRP1 was established, which can distinguish high-risk patients from low-risk patients (P < 0.001). Both internal validation and external GEO data sets validation demonstrate good predictive capability of the model (AUC = 0.732, AUC = 0.802, AUC = 0.632, P < 0.05). In vitro, CCK8 and Transwell assay suggested that CASP4 may accelerate the progression of PDAC by promoting proliferation and migration of pancreatic cancer cells, while NLRP1 has been found to have tumor suppressive effect. It should be noted that knockdown of CASP4 reduced the level of coke death, the expression levels of acetyl-CoA carboxylase, FASN, SREBP-1 and SREBP-2 were decreased, and the number of lipid droplets was also significantly reduced. Moreover, the enrichment of signaling pathways showed that NLRP1 was significantly correlated with MAPK and RAS/ERK signaling pathways, and knocking down NLRP1 could indeed up-regulate p-ERK expression. Finally, high expression of CASP4 and low expression of NLRP1 increased the sensitivity of pancreatic cancer cells to ERK inhibitors.

CONCLUSIONS

In especial, CASP4 can promote tumor progression by promoting the synthesis and accumulation of fatty acids, while NLRP1 acts on RAS/ERK signaling pathway. Both of genes play an important role in the diagnosis and treatment of PDAC, which may also affect the inhibitors of MAPK/ERK efficiency.

A Pyroptosis-Related Gene Signature Associated with Prognosis and Tumor Immune Microenvironment in Gliomas

Background

Pyroptosis is a novel form of cell death that plays a significant role in cancer, while the prognostic values of pyroptosis-related genes in gliomas have not been revealed.

Methods

We analyzed the RNA-seq and clinical data of gliomas from the University of California Santa Cruz (UCSC) Xena database to determine differentially expressed pyroptosis-related genes. Based on these genes, a pyroptosis genes signature was constructed after univariate Cox analysis and Lasso Cox analyses. The sensitivity and specificity of pyroptosis genes signature were verified by the Chinese Glioma Genome Atlas (CGGA) dataset. Finally, we explored the association of risk signatures with tumor microenvironment and immune cell infiltration.

Results

Of 15 differentially expressed pyroptosis-related genes, three genes of BCL2 associated X (BAX), caspase 3 (CASP3), and caspase 4 (CASP4) were used to construct the risk signature. The effectiveness of risk signature for predicting survival at 1, 3, 5 years was performed by the receiver operating characteristic curve (ROC), and the area under curves (AUC) was 0.739, 0.817, and 0.800, respectively. Functional enrichment results showed signal transduction, cell adhesion, immune response, and inflammatory response were enriched. The immune analysis revealed that pyroptosis had a remarkable effect on the immune microenvironment.

Conclusion

In this study, we constructed a pyroptosis-related gene signature, which can serve as a potential biomarker for predicting the survival of glioma patients. Additionally, we suggested that pyroptosis may promote gliomas development by inducing chronic inflammation microenvironment.

Identification of a Pyroptosis-Related Gene Signature and Effect of Silencing the CHMP4C and CASP4 in Pancreatic Adenocarcinoma

Background

Pancreatic adenocarcinoma (PAAD) is a highly malignant tumor with an extremely poor prognosis. Pyroptosis has been demonstrated to play an important role in tumor prognosis. However, the expression of pyroptosis-related genes in PAAD and their correlations with prognosis remains unclear.

Methods

In this study, the 36 pyroptosis-related genes that were differentially expressed between normal pancreatic tissues and PAAD tissues were identified via the “limma” R package. Based on these differentially expressed genes (DEGs), a five-gene signature was established by applying the least absolute shrinkage and selection operator Cox regression in the TCGA cohort and was validated in the GEO cohort. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of DEGs based on the risk model indicated that immune-associated biological processes and pathways were enriched. In vivo, we detected the expressions of CASP4 and CHMP4C by immunohistochemistry in tumor tissues and adjacent normal tissues. In vitro, we silenced CASP4 and CHMP4C to explore their effects on pancreatic cancer cells.

Results

PAAD patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group. The expressions of CASP4 and CHMP4C in tumor tissue were higher than those in the adjacent normal tissues in vivo. The knockdown of CASP4 significantly inhibited the invasion and migration but not the proliferation of PANC-1 cells. The knockdown of CHMP4C obviously inhibited the proliferation, migration, and invasion of PANC-1 cells.

Conclusion

Pyroptosis-related genes play important roles in predicting the prognosis of PAAD, and CASP4 and CHMP4C affect the metastasis of PAAD.

Effect of MUC16 mutations on tumor mutation burden and its potential prognostic significance for cutaneous melanoma

OBJECTIVES

MUC16, a mucin marker with a high mutation probability, is closely related to the occurrence, development, response to treatment, and prognosis of melanoma. As melanoma has high immunogenicity, immunotherapy has become a routine treatment. Tumor mutation burden (TMB) is the most common indicator for determining appropriate immunotherapy. The relationship between the mutation and expression of MUC16 and the prognosis, TMB, level of immune infiltration, and drug sensitivity in melanoma was investigated in this study.

METHODS

Melanoma data were downloaded from the Cancer Genome Atlas and the International Cancer Genome Consortium database, and the "GenVisR" package was used to visualize the gene mutation types and frequencies. Intersections of the top 30 genes with the highest mutation frequencies were determined. Thereafter, we investigated the effects of MUC16 mutations on overall survival (OS) and TMB of melanoma patients by multivariate Cox regression and multivariate logistic analyses. Related pathways that were enriched by MUC16 and BRAF were investigated using gene-set enrichment analysis and gene-set variation analysis. The CIBERSORT calculation method was used to analyze the proportion of tumor-infiltrating immune subsets. The relationship between MUC16 expression and drug sensitivity was also discussed.

RESULTS

Twenty-two genes with high mutation frequencies were identified in both datasets. MUC16 and ADGRV1 mutations were associated with higher TMB and good clinical prognosis (P<0.05). Multivariate Cox regression analysis showed that age, clinical stage, and MUC16 mutations were independent prognostic factors affecting OS of melanoma patients. Multivariate logistic analysis showed that gender and MUC16 mutations were independent prognostic factors affecting the TMB. MUC16 mutations and high-expression groups were primarily enriched in immune-related pathways. Furthermore, T-cell CD4 memory activation and T-cell CD8 were positively correlated with MUC16 expression and activated dendritic cells were significantly enriched in the MUC16 mutant group. Abnormal MUC16 expression may be related to abnormal methylation and drug resistance.

CONCLUSION

MUC16 was found to have a higher mutation frequency in melanoma patients, which is associated with a higher TMB. The mutation and/or expression of MUC16 may affect immune-related pathways and tumor-infiltrating immune cell subsets, which may improve the prognosis for melanoma patients.

Identification of Prognostic Metabolism-Related Genes in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a cancer with abnormal metabolism. The purpose of this study was to investigate the effect of metabolism-related genes on the prognosis of ccRCC patients.

Methods

The data of ccRCC patients were downloaded from the TCGA and the GEO databases and clustered using the nonnegative matrix factorization method. The limma software package was used to analyze differences in gene expression. A random forest model was used to screen for important genes. A novel Riskscore model was established using multivariate regression. The model was evaluated based on the metabolic pathway, immune infiltration, immune checkpoint, and clinical characteristics.

Results

According to metabolism-related genes, kidney clear cell carcinoma (KIRC) datasets downloaded from TCGA were clustered into two groups and showed significant differences in prognosis and immune infiltration. There were 667 differentially expressed genes between the two clusters, of which 408 were screened by univariate analysis. Finally, 12 differentially expressed genes (MDK, SLC1A1, SGCB, C4orf3, MALAT1, PILRB, IGHG1, FZD1, IFITM1, MUC20, KRT80, and SALL1) were filtered out using the random forest model. The model of Riskscore was obtained by multiplying the expression levels of these 12 genes with the corresponding coefficients of the multivariate regression. We found that the Riskscore correlated with the expression of these 12 genes; the high Riskscore matched the low survival rate verified in the verification set. The analysis found that the Riskscore model was associated with most of the metabolic processes, immune infiltration of cells such as plasma cells, immune checkpoints such as PD-1, and clinical characteristics such as M stage.

Conclusion

We established a new Riskscore model for the prognosis of ccRCC based on metabolism. The genes in the model provided several novel targets for the study of ccRCC.

A Pyroptosis-Related Gene Signature for Predicting Survival in Glioblastoma

Background

In this study, a prognostic model based on pyroptosis-related genes was established to predict overall survival (OS) in patients with glioblastoma (GBM).

Methods

The gene expression data and clinical information of GBM patients were obtained from The Cancer Genome Atlas (TCGA), and bioinformatics analysis of differentially expressed genes was performed. LASSO Cox regression model was used to construct a three-pyroptosis-related gene signature, and validation was performed using an experimental cohort.

Results

A total of three pyroptosis-related genes (CASP4, CASP9, and NOD2) were used to construct a survival prognostic model, and experimental validation was performed using an experimental cohort. Receiver operating characteristic (ROC) analysis was performed, and the area under the ROC curves (AUC) was 0.921, 0.840, and 0.905 at 1, 3, and 5 years, respectively. Functional analysis revealed that T-cell activation, regulation of T-cell activation, leukocyte cell-cell adhesion, and positive regulation of cell adhesion among other immune-related functions were enriched, and immune-related processes were different between the two risk groups.

Conclusion

In this study, a novel prognostic model based on three pyroptosis-related genes is constructed and used to predict the prognosis of GBM patients. The model can accurately and conveniently predict the 1-, 3-, and 5-year OS of GBM patients.