Pyroptosis Regulators and Tumor Microenvironment Infiltration Characterization in Clear Cell Renal Cell Carcinoma

Identification of a novel PANoptosis-related gene signature for predicting the prognosis in clear cell renal cell carcinoma

PANoptosis has been shown to play an important role in tumorigenesis and gain more attention. Yet, the prognostic significance of PANoptosis-related genes has not been investigated more in clear cell renal cell carcinoma (ccRCC). The aim of this research was designed to identify and create a signature of PANoptosis-related genes which was expected to predict prognosis of ccRCC more effectively. The transcriptome data and clinical information were collected from The Cancer Genome Atlas database and the Gene Expression Omnibus database. Optimal differentially expressed PANoptosis-related genes, which were closely associated with prognosis and employed to construct a risk score, were extracted by univariate Cox analysis, least absolute shrinkage and selection operator Cox regression and multivariate Cox analysis. We performed Kaplan-Meier survival analysis and time-dependent receiver operating characteristic curves to complete this process. By adopting univariate and multivariate analysis, the constructed risk score was assessed to verify whether it could be taken as an independent contributor for prognosis. Moreover, we created a nomogram in order to predict overall survival (OS) of ccRCC. Five differentially expressed PANoptosis-related genes were screened out and used to construct a risk score. Our results showed that ccRCC patients with high risk score had a poor prognosis and shorter OS. The results of Kaplan-Meier curves and the area under the receiver operating characteristic curves of 1-, 3-, and 5-year OS indicated that the prediction performance was satisfactory. Additionally, the risk model could be taken as an independent prognostic factor in training and validation cohorts. The nomogram exhibited excellent reliability in predicting OS, which was validated by calibration curves. We identified 5 PANoptosis-related genes, which were used to construct a risk score and a nomogram for prognostic prediction with reliable predictive capability. The present study may provide new potential therapeutic targets and precise treatment strategies for ccRCC.

Exploiting branched-chain amino acid metabolism and NOTCH3 expression to predict and target colorectal cancer progression

Background

The interplay between colon adenocarcinoma (COAD) and branched-chain amino acid (BCAA) metabolism is not fully understood, presenting a crucial area for investigation.

Methods

We developed a prognostic model based on BCAA metabolism using the least absolute shrinkage and selection operator (LASSO) regression algorithm. We employed qRT-PCR and Western blot analyses to examine NOTCH3 expression in COAD tissues versus adjacent non-cancerous tissues and various cell lines. We also investigated the impact of NOTCH3 on COAD cell proliferation, invasion, and migration through in vitro and in vivo experiments.

Results

Our BCAA metabolism-related signature (BRS) distinguished between different immune features, tumor mutation burdens, responses to immunotherapy, and drug sensitivity among COAD patients. NOTCH3 was found to be overexpressed in COAD, promoting tumor growth as verified through various assays. The model effectively predicted COAD prognosis and patient responses to treatments, underscoring the potential of BCAA pathways as therapeutic targets.

Conclusion

The BRS is instrumental in predicting the prognosis and therapeutic response in COAD, with NOTCH3 playing a significant role in the proliferation, invasion and migration of COAD. These findings suggest that targeting BCAA metabolism and NOTCH3 could advance COAD treatment strategies.

Immune checkpoint gene signature assesses immune infiltration profiles in bladder cancer and identifies KRT23 as an immunotherapeutic target

BACKGROUND

In the past few decades, researchers have made promising progress, including the development of immune checkpoint inhibitors (ICIs) in the therapy of bladder cancer (BLCA). Existing studies mainly focus on single immune checkpoint inhibitors but lack relevant studies on the gene expression profiles of multiple immune checkpoints.

METHODS

RNA-sequencing profiling data and clinical information of BLCA patients and normal human bladder samples were acquired from the Cancer Genome Atlas and Gene Expression Omnibus databases and analyzed to identify different expression profiles of immune checkpoint genes (ICGs) after consensus clustering analysis. Based on the 526 intersecting differentially expressed genes, the LASSO Cox regression analysis was utilized to construct the ICG signature.

RESULTS

According to the expression of ICGs, BLCA patients were divided into three subtypes with different phenotypic and mechanistic characteristics. Furthermore, the developed ICG signature were independent predictors of outcome in BLCA patients, and was correlated with the immune infiltration, the expression of ICGs and chemotherapeutic effect.

CONCLUSIONS

This study systematically and comprehensively analyzed the expression profile of immune checkpoint genes, and established the ICG signature to investigate the differences in ICGs expression and tumor immune microenvironment, which will help risk stratification and accelerate precision medicine. Finally, we identified KRT23 as the most critical model gene, and highlighted KRT23 as a potential target to enhance immunotherapy against BLCA.

Prognostic impact and immunotherapeutic implications of NETosis-related prognostic model in clear cell renal cell carcinoma

BACKGROUND

The ramifications of necroptosis on the prognostication of clear cell renal cell carcinoma (ccRCC) remain inadequately expounded.

METHODS

A prognostic model delineating the facets of necroptosis in ccRCC was constructed, employing a compendium of algorithms. External validation was effectuated using the E-MTAB-1980 dataset. The exploration of immune infiltration scores was undertaken through the exploitation of multiple algorithms. Single-cell RNA sequencing data were procured from the GSE171306 dataset. Real-time quantitative PCR (RT-qPCR) was engaged to scrutinize the differential expression of SLC25A37 across cancer and paracancer tissues, as well as diverse cell lines. Assessments of proliferative and metastatic alterations in 769-P and 786-O cells were accomplished through Cell Counting Kit-8 (CCK8) and wound healing assays.

RESULTS

The necroptosis-related signature (NRS) emerges as a discerning metric, delineating patients' immune attributes, tumor mutation burden, immunotherapy response, and drug susceptibility. Single-cell RNA sequencing analysis unveils the marked enrichment of SLC25A37 in tumor cells. Concurrently, RT-qPCR discloses the overexpression of SLC25A37 in both ccRCC tissues and cell lines. SLC25A37 knockdown mitigates the proliferative and metastatic propensities of 769-P and 786-O cells, as evidenced by CCK8 and wound healing assays.

CONCLUSION

The NRS assumes a pivotal role in ascertaining the prognosis, tumor mutation burden, immunotherapy response, drug susceptibility, and immune cell infiltration features of ccRCC patients. SLC25A37 emerges as a putative player in immunosuppressive microenvironments, thereby providing a prospective avenue for the design of innovative immunotherapeutic targets for ccRCC.

The roles of pyroptosis in genitourinary diseases

Pyroptosis, a form of programmed cell death distinct from apoptosis and necrosis, is thought to be closely associated with the pathogenesis of diseases. Recently, the association between pyroptosis and urinary diseases has attracted considerable attention, and a comprehensive review focusing on this issue is not available. In this study, we reviewed the role of pyroptosis in the development and progression of benign urinary diseases and urinary malignancies. Based on this, pyroptosis has been implicated in the development of urinary diseases. In summary, this review sheds light on future research directions and provides novel ideas for using pyroptosis as a powerful tool to fight urinary diseases.

Development and validation of a pyroptosis-related prognostic signature associated with osteosarcoma metastasis and immune infiltration

Pyroptosis is a programmed cell death, which has garnered increasing attention because it relates to the immune and therapy response. However, few studies focus on the application of pyroptosis-related genes (PRGs) in predicting osteosarcoma (OS) patients' prognoses. In this study, the gene expression and clinical information of OS patients were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Based on these PRGs and unsupervised clustering analysis, all OS samples can be classified into 2 clusters. The 8 key differential expressions for PRGs (LAG3, ITGAM, CCL2, TLR4, IL2RA, PTPRC, FCGR2B, and CD5) were established through the univariate Cox regression and utilized to calculate the risk score of all samples. According to the 8-gene signature, OS samples can be divided into high and low-risk groups and correlation analysis can be performed using immune cell infiltration and immune checkpoints. Finally, we developed a nomogram to improve the PRG-predictive model in clinical application. We verified the predictive performance using receiver operating characteristic (ROC) and calibration curves. There were significant differences in survival, immune cell infiltration and immune checkpoints between the low and high-risk groups. A nomogram was developed with clinical indicators and the risk scores were effective in predicting the prognosis of patients with OS. In this study, a prognostic model was constructed based on 8 PRGs were proved to be independent prognostic factors of OS and associated with tumor immune microenvironment. These 8 prognostic genes were involved in OS development and may serve as new targets for developing therapeutic drugs.

Development and implementation of a prognostic model for clear cell renal cell carcinoma based on heterogeneous TLR4 expression

Objective

Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cell carcinomas and has the worst prognosis, originating from renal tubular epithelial cells. Toll-like receptor 4 (TLR4) plays a crucial role in ccRCC proliferation, infiltration, and metastasis. The aim of this study was to construct a prognostic scoring model for ccRCC based on TLR4 expression heterogeneity and to explore its association with immune infiltration, thereby providing insights for the treatment and prognostic evaluation of ccRCC.

Methods

Using R software, a differential analysis was conducted on normal samples and ccRCC samples, and in conjunction with the KEGG database, a correlation analysis for the clear cell renal cell carcinoma pathway (hsa05211) was carried out. We observed the expression heterogeneity of TLR4 in the TCGA-KIRC cohort and identified its related differential genes (TRGs). Based on the expression levels of TRGs, consensus clustering was employed to identify TLR4-related subtypes, and further clustering heatmaps, principal component, and single-sample gene set enrichment analyses were conducted. Overlapping differential genes (ODEGs) between subtypes were analysed, and combined with survival data, univariate Cox regression, LASSO, and multivariate Cox regression were used to establish a prognostic risk model for ccRCC. This model was subsequently evaluated through ROC analysis, risk factor correlation analysis, independent prognostic factor analysis, and intergroup differential analysis. The ssGSEA model was employed to explore immune heterogeneity in ccRCC, and the performance of the model in predicting patient prognosis was evaluated using box plots and the oncoPredict software package.

Results

In the TCGA-KIRC cohort, TLR4 expression was notably elevated in ccRCC samples compared to normal samples, correlating with improved survival in the high-expression group. The study identified distinct TLR4-related differential genes and categorized ccRCC into three subtypes with varied survival outcomes. A risk prognosis model based on overlapping differential genes was established, showing significant associations with immune cell infiltration and key immune checkpoints (PD-1, PD-L1, CTLA4). Additionally, drug sensitivity differences were observed between risk groups.

Conclusion

In the TCGA-KIRC cohort, the expression of TLR4 in ccRCC samples exhibited significant heterogeneity. Through clustering analysis, we identified that the primary immune cells across subtypes are myeloid-derived suppressor cells, central memory CD4 T cells, and regulatory T cells. Furthermore, we successfully constructed a prognostic risk model for ccRCC composed of 17 genes. This model provides valuable references for the prognosis prediction and treatment of ccRCC patients.

Non-coding RNAs are involved in tumor cell death and affect tumorigenesis, progression, and treatment: a systematic review

Cell death is ubiquitous during development and throughout life and is a genetically determined active and ordered process that plays a crucial role in regulating homeostasis. Cell death includes regulated cell death and non-programmed cell death, and the common types of regulatory cell death are necrosis, apoptosis, necroptosis, autophagy, ferroptosis, and pyroptosis. Apoptosis, Necrosis and necroptosis are more common than autophagy, ferroptosis and pyroptosis among cell death. Non-coding RNAs are regulatory RNA molecules that do not encode proteins and include mainly microRNAs, long non-coding RNAs, and circular RNAs. Non-coding RNAs can act as oncogenes and tumor suppressor genes, with significant effects on tumor occurrence and development, and they can also regulate tumor cell autophagy, ferroptosis, and pyroptosis at the transcriptional or post-transcriptional level. This paper reviews the recent research progress on the effects of the non-coding RNAs involved in autophagy, ferroptosis, and pyroptosis on tumorigenesis, tumor development, and treatment, and looks forward to the future direction of this field, which will help to elucidate the molecular mechanisms of tumorigenesis and tumor development, as well as provide a new vision for the treatment of tumors.

Integrated single-cell and bulk characterization of branched chain amino acid metabolism-related key gene BCAT1 and association with prognosis and immunogenicity of clear cell renal cell carcinoma

BACKGROUND

The relationship between clear cell renal cell carcinoma (ccRCC) and branched-chain amino acids (BCAA) metabolism has yet to be thoroughly explored.

METHODS

The BCAA metabolism-related clusters were constructed using non-negative matrix factorization (NMF). The features of BCAA metabolism in ccRCC were evaluated by building a prognostic model using least absolute shrinkage and selection operator (LASSO) regression algorithm. Real-time quantitative PCR (RT-qPCR) was employed to analyze differential expression of branched-chain amino acid transaminase 1 (BCAT1) between cancer and paracancer tissues and between different cell lines. Cell counting kit-8, wound healing and Transwell chamber assays were conducted to determine changes in proliferative and metastatic abilities of A498 and 786-O cells.

RESULTS

Two BCAA metabolism-related clusters with distinct prognostic and immune infiltration characteristics were identified in ccRCC. The BCAA metabolic signature (BMS) was capable of distinguishing immune features, tumor mutation burden, responses to immunotherapy, and drug sensitivity among ccRCC patients. RT-qPCR revealed overexpression of BCAT1 in ccRCC tissues and cell lines. Additionally, single-gene RNA sequencing analysis demonstrated significant enrichment of BCAT1 in macrophages and tumor cells. BCAT1 played tumor-promoting role in ccRCC and was closely associated with immunosuppressive cells and checkpoints. BCAT1 promoted ccRCC cell proliferation and metastasis.

CONCLUSIONS

The BMS played a crucial role in determining the prognosis, tumor mutation burden, responses to immunotherapy and drug sensitivity of ccRCC patients, as well as the immune cell infiltration features. BCAT1 was linked to immunosuppressive microenvironments and may offer new sights into ccRCC immunotherapeutic targets.

Identification and validation of prognostic and tumor microenvironment characteristics of necroptosis index and BIRC3 in clear cell renal cell carcinoma

Background

Necroptosis is a form of programmed cell death; it has an important role in tumorigenesis and metastasis. However, details of the regulation and function of necroptosis in clear cell renal cell carcinoma (ccRCC) remain unclear. It is necessary to explore the significance of necroptosis in ccRCC.

Methods

Necroptosis-related clusters were discerned through the application of Consensus Clustering. Based on the TCGA and GEO databases, we identified prognostic necroptosis-related genes (NRGs) with univariate COX regression analysis. The necroptosis-related model was constructed through the utilization of LASSO regression analysis, and the immune properties, tumor mutation burden, and immunotherapy characteristics of the model were assessed using multiple algorithms and datasets. Furthermore, we conducted comprehensive GO, KEGG, and GSVA analyses to probe into the functional aspects of biological pathways. To explore the expression and of hub gene (BIRC3) in different ccRCC cell types and cell lines, single-cell sequencing data was analysed and we performed Quantitative Real-time PCR to detect the expression of BIRC3 in ccRCC cell lines. Function of BIRC3 in ccRCC was assessed through Cell Counting Kit-8 (CCK8) assay (for proliferation), transwell and wound healing assays (for migration and invasion).

Results

Distinct necroptosis-related clusters exhibiting varying prognostic implications, and enrichment pathways were identified in ccRCC. A robust necroptosis-related model formulated based on the expression of six prognostic NRGs, presented substantial predictive capabilities of overall survival and was shown to be related with patients' immune profiles, tumor mutation burden, and response to immunotherapy. Notably, the hub gene BIRC3 was markedly upregulated in both ccRCC tissues and cell lines, and showed significant correlations with immunosuppressive cells, immune checkpoints, and oncogenic pathways. Downregulation of BIRC3 demonstrated a negative regulatory effect on ccRCC cell proliferation migration and invasion.

Conclusion

The necroptosis-related model assumed a pivotal role in determining the prognosis, tumor mutation burden, immunotherapy response, and immune cell infiltration characteristics among ccRCC patients. BIRC3 exhibited significant correlations with the immunosuppressive microenvironment, which highlighted its potential for informing the design of innovative immunotherapies for ccRCC patients.

Identification of Crotonylation Metabolism Signature Predicting Overall Survival for Clear Cell Renal Cell Carcinoma

Background

Immunotherapy shows promise in treating cancer by leveraging the immune system to combat cancer cells. However, the influence of crotonylation metabolism on the prognosis and tumor environment in ccRCC patients is not fully understood.

Methods

We conducted various systematic analyses, including prognosis and cluster analyses, to investigate the role of KAT2A in immunotherapy. We used qRT-PCR to compare KAT2A expression in cancer and adjacent tissues and among different cell lines. Additionally, we employed Cell Counting Kit-8, wound healing, and Transwell chamber assays to assess changes in the proliferative and metastatic ability of A498 and 786-O cells.

Results

We identified three clusters related to crotonylation metabolism, each with distinct prognosis and immune characteristics in ccRCC. We categorized CT1 as immune-inflamed, CT2 as immune-excluded, and CR3 as immune-desert. A new system, CRS, emerged as an effective predictor of patient outcomes with differing immune characteristics. Moreover, qRT-PCR revealed elevated KAT2A levels in ccRCC tissues and cell lines. KAT2A was found to promote ccRCC and correlate significantly with immunosuppressive elements and checkpoints. Reducing KAT2A expression hindered ccRCC cell growth and metastasis.

Conclusion

Our study highlights the critical role of crotonylation metabolism in cancer development and progression, particularly its link to poor prognosis. CRS proves to be an accurate predictor of patient outcomes and immune features in ccRCC. KAT2A shows strong associations with clinical factors and the immunosuppressive environment, suggesting potential for innovative immunotherapies in ccRCC treatment.

Pyroptosis in urinary malignancies: a literature review

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

Crosstalk of necroptosis and pyroptosis defines tumor microenvironment characterization and predicts prognosis in clear cell renal carcinoma

Pyroptosis and necroptosis are two recently identified forms of immunogenic cell death in the tumor microenvironment (TME), indicating a crucial involvement in tumor metastasis. However, the characteristics of necroptosis and pyroptosis that define tumor microenvironment and prognosis in ccRCC patients remain unknown. We systematically investigated the transcriptional variation and expression patterns of Necroptosis and Pyroptosis related genes (NPRGs). After screening the necroptosis-pyroptosis clusters, the potential functional annotation for clusters was explored by GSVA enrichment analysis. The Necroptosis-Pyroptosis Genes (NPG) scores were used for the prognosis model construction and validation. Then, the correlations of NPG score with clinical features, cancer stem cell (CSC) index, tumor mutation burden (TMB), TME, and Immune Checkpoint Genes (ICGs) were also individually explored to evaluate the prognosis predictive values in ccRCC. Microarray screenings identified 27 upregulated and 1 downregulated NPRGs. Ten overall survival associated NPRGs were filtered to construct the NPG prognostic model indicating a better prognostic signature for ccRCC patients with lower NPG scores (P< 0.001), which was verified using the external cohort. Univariate and multivariate analyses along with Kaplan-Meier survival analysis demonstrated that NPG score prognostic model could be applied as an independent prognostic factor, and AUC values of nomogram from 1- to 5- year overall survival with good agreement in calibration plots suggested that the proposed prognostic signature possessed good predictive capabilities in ccRCC. A high-/sNPG score is proven to be connected with tumor growth and immune-related biological processes, according to enriched GO, KEGG, and GSEA analyses. Comparing patients with a high-NPG score to those with a low-NPG score revealed significant differences in clinical characteristics, growth and recurrence of malignancies (CSC index), TME cell infiltration, and immunotherapeutic response (P< 0.005), potentially making the NPG score multifunctional in the clinical therapeutic setting. Furthermore, AIM2, CASP4, GSDMB, NOD2, and RBCK1 were also found to be highly expressed in ccRCC cell lines and tumor tissues, and GASP4 and GSDMB promote ccRCC cells’ proliferation, migration, and invasion. This study firstly suggests that targeting the NPG score feature for TME characterization may lend novel insights into its clinical applications in the prognostic prediction of ccRCC.

Identification of N6-methylandenosine related lncRNA signatures for predicting the prognosis and therapy response in colorectal cancer patients

Despite recent advances in surgical and multimodal therapies, the overall survival (OS) of advanced colorectal cancer (CRC) patients remains low. Thus, discerning sensitive prognostic biomarkers to give the optimistic treatment for CRC patients is extremely critical. N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) play an important role in CRC progression. Nonetheless, few studies have focused on the impact of m6A-related lncRNAs on the prognosis, tumor microenvironment (TME) and treatment of CRC. In this study, 1707 m6A-related lncRNAs were identified through Pearson correlation analysis and Weighted co-expression network analysis (WGCNA) using The Cancer Genome Atlas (TCGA) cohort. Then, 28 m6A-related prognostic lncRNAs were screened by univariate Cox regression analysis, followed by identifying two clusters by consensus clustering analysis. A prognostic model consisted of 8 lncRNA signatures was constructed by the least absolute shrinkage and selection operator (LASSO). Kaplan–Meier curve analysis and a nomogram were performed to investigate the prognostic ability of this model. The risk score of prognostic model act as an independent risk factor for OS rate. Functional enrichment analysis indicated that lncRNA signatures related tumor immunity. The low-risk group characterized by increased microsatellite instability-high (MSI-H), mutation burden, and immunity activation, indicated favorable odds of OS. Moreover, the lncRNA signatures were significantly associated with the cancer stem cell (CSC) index and drug sensitivity. In addition, 3 common immune genes shared by the lncRNA signatures were screened out. We found that these immune genes were widely distributed in 2 cell types of TME. Finally, a ceRNA network was constructed to identify ZEB1-AS1 regulatory axis in CRC. We found that ZEB1-AS1 was significantly overexpressed in tumor tissues, and was related to the metastasis of EMT and the chemoresistance of 5-Fu in CRC. Therefore, our study demonstrated the important role of m6A-related lncRNAs in TME remodeling. Moreover, these results illustrated the levels of ZEB1-AS1 might be valuable for predicting the progression and prognosis of CRC, and further provided a new target for the diagnosis and treatment of CRC patients.

Identification of immune subtypes to guide immunotherapy and targeted therapy in clear cell renal cell carcinoma

Accumulating pieces of evidence suggested that immunotypes may indicate the overall immune landscape in the tumor microenvironment, which were closely related to therapeutic response. The purpose of this study was to classify and define the immune subtypes of clear cell renal cell carcinoma (ccRCC), so as to authenticate the potential immune subtypes that respond to immunotherapy. Transcriptome expression profile and mutation profile data of ccRCC, as well as clinical characteristics used in this study were obtained from TCGA database. There were significant differences in the infiltration of immune cells, immune checkpoints, and antigens between ccRCC and para-cancerous tissues. According to immune components, patients with ccRCC were divided into three immune subtypes, with different clinical and molecular characteristics. Compared with other subtypes, IS2 showed cold immune phenotype, and was associated with better survival. IS1 represented complex immune populations and was associated with poor overall survival (OS) and progression free survival (PFS). Further analysis indicated that expression of immune checkpoints also differed among the three subtypes, and was abnormally up-regulated in IS3. Pathway enrichment analysis indicated that the mTOR signaling pathway was abnormally enriched in IS3, while the TGF_BETA, ANGIOGENESIS and receptor tyrosine kinase signaling pathways were abnormally enriched in IS2. Furthermore, there was an abnormal enrichment of the epithelial-to-mesenchymal transition (EMT) signaling pathway in IS1, which may be associated with a higher rate of metastasis. Finally, SCG2 was screened as a specific antigen of ccRCC, which was not only related to poor prognosis, but also significantly associated with immune cells and immune checkpoints. In conclusion, the immune subtypes of ccRCC may provide new insights into the tumor biology and the precise clinical management of this disease.

A novel inflammation‑associated prognostic signature for clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) are typically situated in a complex inflammatory and immune microenvironment, which has been reported to contribute to the unfavorable prognosis of patients with ccRCC. There would be beneficial clinical implications for elucidating the roles of its molecular characteristics in the inflammatory microenvironment. This is because it would facilitate the development of reliable biomarkers for pre-stratification prior to the designation of individualized treatment strategies. In the present study, RNA-sequencing data from 607 patients were retrospectively analyzed to elucidate the profile of inflammatory molecules. Based on this, an inflammatory prognostic signature (IPS) was developed and further validated using clinical ccRCC samples. Subsequently, the associated mechanisms in terms of the immune microenvironment and molecular pathways were then investigated. This proposed IPS was found to exhibit superior accuracy compared with the criterion of a good prognostic model for the prediction of patient prognosis from ccRCC [area under the receiver operating characteristic curve (AUC)=0.811] in addition to being an independent factor for prognostic risk stratification [hazard ratio: 11.73 (95% CI, 26.98-5.10); log-rank test, P<0.001]. Pathologically, ccRCC cells identified as high-risk according to their IPS presented with a more malignant tumor structure, including voluminous eosinophilic cytoplasm, acinar/lamellar/tubular growth patterns and atypic nuclei. High-risk ccRCC also exhibited higher infiltration levels by four types of immune cells, including T regulatory cells, but lower infiltration levels by mast cells. Pathways associated with immune-inflammation interaction, including the IL-17 pathway, were found to be upregulated in IPS-identified high-risk ccRCC. Furthermore, by combining the IPS with clinical factors, an integrated prognostic index was developed and validated for increasing the accuracy of patient risk-stratification for ccRCC (AUC=0.911). In conclusion, the complex regulatory mechanisms and molecular characteristics involved in ccRCC-inflammation interaction, coupled with their prognostic potential, were systematically elucidated in the present study. This may have important implications in furthering the understanding into the molecular mechanisms underlying this ccRCC-inflammation interaction, which can in turn be exploited for identifying high-risk patients with ccRCC prior to designing their clinical treatment strategy.

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.

Analysis of Pyroptosis-Related Immune Signatures and Identification of Pyroptosis-Related LncRNA Prognostic Signature in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common urinary system malignant tumor with a high incidence and recurrence rate. Pyroptosis is a kind of programmed cell death caused by inflammasomes. More and more evidence had confirmed that pyroptosis plays a very significant part in cancer, and it is controversial whether pyroptosis promotes or inhibits tumors. Consistently, its potential role in ccRCC treatment efficacy and prognosis remains unclear. In this study, we systematically investigated the role of pyroptosis in the ccRCC samples from The Cancer Genome Atlas (TCGA) database. Based on the differentially expressed pyroptosis-related genes (DEPRGs), we identified three pyroptosis subtypes with different clinical outcomes, immune signatures, and responses to immunotherapy. Gene set variation analysis (GSVA), Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that pyroptosis activation meant infiltration of more immune cells that is conducive to tumor progression. To further investigate the immunomodulatory effect of pyroptosis in ccRCC, we constructed a pyroptosis-score based on the common differential prognostic genes of the three pyroptosis subtypes. It was found that patients with high pyroptosis-score were in an unfavorable immune environment and the prognosis was worse. Gene set enrichment analysis suggested that immune-related biological processes were activated in the high pyroptosis-score group. Then, the least absolute shrinkage and selection operator (LASSO) Cox regression was implemented for constructing a prognostic model of eight pyroptosis-related long noncoding RNAs (PRlncRNAs) in the TCGA dataset, and the outcomes revealed that, compared with the low-risk group, the model-based high-risk group was intently associated with poor overall survival (OS). We further explored the relationship between high- and low-risk groups with tumor microenvironment (TME), immune infiltration, and drug therapy. Finally, we constructed and confirmed a robust and reliable PRlncRNA pairs prediction model of ccRCC, identified PRlncRNA, and verified it by experiments. Our findings suggested the potential role of pyroptosis in ccRCC, offering new insights into the prognosis of ccRCC and guiding effectual targeted therapy and immunotherapy.

Identification of Ferroptosis-Related Prognostic Signature and Subtypes Related to the Immune Microenvironment for Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

Purpose

To identify molecular clusters associated with ferroptosis and to develop a ferroptosis-related signature for providing novel potential targets for the recurrence-free survival and treatment of breast cancer.

Methods

Ferroptosis-related gene (FRG) signature was constructed by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO). Receiver operating characteristic curves, Kaplan-Meier survival analysis, principal component analysis, and univariate and multivariate Cox regression analyses in the training and test cohorts were used to evaluate the application of this signature. Quantitative reverse transcriptase-PCR (qRT-PCR) was employed to detect the expression of FRGs in the model. Furthermore, the correlations between the signature and immune microenvironment, somatic mutation, and chemotherapeutic drugs sensitivity were explored.

Results

Internal and external validations affirmed that relapse-free survival differed significantly between the high-risk and low-risk groups. Univariate and multivariate Cox regression analyses indicated that the riskScore was an independent prognostic factor for BRCA. The areas under the curve (AUCs) for predicting 1-, 2-, and 3-year survival in the training and test cohorts were satisfactory. Significant differences were also found in the immune microenvironment and IC50 of chemotherapeutic drugs between different risk groups. Furthermore, we divided patients into three clusters based on 18 FRGs to ameliorate the situation of immunotherapy failure in BRCA.

Conclusions

The FRG signature functions as a robust prognostic predictor of the immune microenvironment and therapeutic response, with great potential to guide individualized treatment strategies in the future.