A pyroptosis-related lncRNA signature predicts prognosis and immune microenvironment in head and neck squamous cell carcinoma

Prognostic and chemotherapeutic implications of a novel four-gene pyroptosis model in head and neck squamous cell carcinoma

Background

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers. Chemotherapy remains one dominant therapeutic strategy, while a substantial proportion of patients may develop chemotherapeutic resistance; therefore, it is particularly significant to identify the patients who could achieve maximum benefits from chemotherapy. Presently, four pyroptosis genes are reported to correlate with the chemotherapeutic response or prognosis of HNSCC, while no study has assessed the combinatorial predicting efficacy of these four genes. Hence, this study aims to evaluate the predictive value of a multi-gene pyroptosis model regarding the prognosis and chemotherapeutic responsiveness in HNSCC.

Methods

By utilizing RNA-sequencing data from The Cancer Genome Atlas database and the Gene Expression Omnibus database, the pyroptosis-related gene score (PRGscore) was computed for each HNSCC sample by performing a Gene Set Variation Analysis (GSVA) based on four genes (Caspase-1, Caspase-3, Gasdermin D, Gasdermin E). The prognostic significance of the PRGscore was assessed through Cox regression and Kaplan-Meier survival analyses. Additionally, chemotherapy sensitivity stratified by high and low PRGscore was examined to determine the potential association between pyroptosis activity and chemosensitivity. Furthermore, chemotherapy sensitivity assays were conducted in HNSCC cell lines in vitro.

Results

As a result, our study successfully formulated a PRGscore reflective of pyroptotic activity in HNSCC. Higher PRGscore correlates with worse prognosis. However, patients with higher PRGscore were remarkably more responsive to chemotherapy. In agreement, chemotherapy sensitivity tests on HNSCC cell lines indicated a positive association between overall pyroptosis levels and chemosensitivity to cisplatin and 5-fluorouracil; in addition, patients with higher PRGscore may benefit from the immunotherapy. Overall, our study suggests that HNSCC patients with higher PRGscore, though may have a less favorable prognosis, chemotherapy and immunotherapy may exhibit better benefits in this population.

Development of a novel head and neck squamous cell carcinoma prognostic signature by bulk/single-cell sequencing data integration

BACKGROUND

Identifying cell subpopulations conferring unfavorable prognosis in cancer holds clinical significance. Here, we sought to identify prognostic cell subsets and develop a novel, prognostic signature for head neck squamous cell carcinoma (HNSCC).

METHODS

Highly prognostic cell subpopulations in HNSCC were identified by integrating single-cell and bulk transcriptomic datasets. The prognostic signature and nomogram were developed by least absolute shrinkage and selection operator and multivariate Cox regression analyses based on significantly upregulated genes in this specific cell subpopulation, respectively. The qRT-PCR experiments were utilized for independent validation in our patient cohort.

RESULTS

A specific cancer cell subset associated with unfavorable prognoses was identified. Functional dissections revealed that its transcriptional programs were significantly enriched in E2F, epithelial-to-mesenchymal transition, and glycolysis. A novel prognostic signature comprising six genes was developed and further validated. Risk scores based on qRT-PCR data robustly stratified patients into subgroups with distinct prognoses. A nomogram integrated from this signature and clinical stage had superior performance.

CONCLUSION

Our model derived from integrative analyses of single-cell and bulk RNA-sequencing is a novel, robust prognostic biomarker for HNSCC.

A pyroptosis-related gene expression signature predicts immune microenvironment and prognosis in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous and aggressive malignancy with a poor prognosis. Pyroptosis triggered by gasdermins family proteins is reported vital for tumor microenvironment and cancer progression. However, pyroptosis-related gene expression and its relationship with immune infiltration and prognosis of HNSCC have not been fully defined.

MATERIAL AND METHODS

RNA-sequencing data of HNSCC patients were acquired from The Cancer Genome Atlas (TCGA) database. A pyroptosis-related gene expression signature and infiltrated immune cells were analyzed. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression and nomogram analyses were used to construct a clinical-molecular risk model for survival prognosis.

RESULTS

HNSCC was classified into three different molecular subtypes based on the expression information of pyroptosis-related genes. Immune cell infiltration was demonstrated to be distinct between the three subtypes. The segregation of patients into the high-risk group and low-risk group, were carried out using the signature of differential expression genes (DEGs) signature among the three molecular subtypes. The precision of this signature was corroborated by Receiver operating characteristic curve (ROC) analysis with the 3-year area under time-dependent ROC curve (AUC) reaching 0.711. The risk model was validated in another dataset from the Gene Expression Omnibus (GEO) database. Subsequently we established a clinical-molecular nomogram which combined the risk score with age and stage. The calibration plots for predicting the overall survival rate of 1-, 3-, and 5-years indicated that the nomogram performs well.

CONCLUSION

The expression signature that encompasses pyroptosis-related genes could be used as molecular classification for HNSCC and pyroptosis might be a promising therapeutic target in HNSCC.

Exploring the frontiers: tumor immune microenvironment and immunotherapy in head and neck squamous cell carcinoma

The global prevalence of head and neck malignancies positions them as the sixth most common form of cancer, with the head and neck squamous cell carcinoma (HNSCC) representing the predominant histological subtype. Despite advancements in multidisciplinary approaches and molecular targeted therapies, the therapeutic outcomes for HNSCC have only marginally improved, particularly in cases of recurrent or metastatic HNSCC (R/MHNSCC). This situation underscores the critical necessity for the development of innovative therapeutic strategies. Such strategies are essential not only to enhance the efficacy of HNSCC treatment but also to minimize the incidence of associated complications, thus improving overall patient prognosis. Cancer immunotherapy represents a cutting-edge cancer treatment that leverages the immune system for targeting and destroying cancer cells. It's applied to multiple cancers, including melanoma and lung cancer, offering precision, adaptability, and the potential for long-lasting remission through immune memory. It is observed that while HNSCC patients responsive to immunotherapy often experience prolonged therapeutic benefits, only a limited subset demonstrates such responsiveness. Additionally, significant clinical challenges remain, including the development of resistance to immunotherapy. The biological characteristics, dynamic inhibitory changes, and heterogeneity of the tumor microenvironment (TME) in HNSCC play critical roles in its pathogenesis, immune evasion, and therapeutic resistance. This review aims to elucidate the functions and mechanisms of anti-tumor immune cells and extracellular components within the HNSCC TME. It also introduces several immunosuppressive agents commonly utilized in HNSCC immunotherapy, examines factors influencing the effectiveness of these treatments, and provides a comprehensive summary of immunotherapeutic strategies relevant to HNSCC.

A comprehensive prognostic score for head and neck squamous cancer driver genes and phenotype traits

BACKGROUND

Head and neck squamous cancer (HNSCC) presents variable phenotype and progression features. Clinically applicable, high-accuracy multifactorial prognostic models for HNSCC survival outcomes are warranted and an active area of research. This study aimed to construct a comprehensive prognostic tool for HNSCC overall survival by integrating cancer driver genes with tumor clinical and phenotype information.

METHODS

Key overall survival-related cancer driver genes were screened from among main effector and reciprocal gene pairs using TCGA data using univariate Cox proportional hazard regression analysis. Independent validation was performed using the GSE41613 dataset. The main effector genes among these were selected using LASSO regression and transcriptome score modeling was performed using multivariate Cox regression followed by validation analysis of the prognostic score. Next, multivariate Cox regression analysis was performed using the transcriptome score combined with age, grade, gender, and stage. An 'Accurate Prediction Model of HNSCC Overall Survival Score' (APMHO) was computed and validated. Enriched functional pathways, gene mutational landscape, immune cell infiltration, and immunotherapy sensitivity markers associated with high and low APMHO scores were analyzed.

RESULTS

Screening 107 overall survival-related cancer genes and 402 interacting gene pairs, 6 genes: CRLF2, HSP90AA1, MAP2K1, PAFAH1B2, MYCL and SET genes, were identified and a transcriptional score was obtained. Age, stage and transcriptional score were found to be significant predictors in Cox regression analysis and used to construct a final APMHO model showing an AUC > 0.65 and validated. Transcriptional score, age, pathologic_N, pathologic_T, stage, and TCGA_subtype were significantly different in distribution between high and low APMHO groups. High APMHO samples showed significantly higher mutation rate, enriched tumor-related pathways including Hypoxia, unfold_protein_response, Glycolysis, and mTORC1 signaling, along with differences in immune cell infiltration and immune checkpoint, interferon-γ pathway and m6A regulator expression patterns.

CONCLUSION

The APMHO score combining transcriptional and clinical variables showed good prognostic ability for HNSCC overall survival outcomes and was associated with different patterns of phenotypical features, immune and mutational landscape, and immunotherapy sensitivity marker expression. Future studies should validate this score in independent clinical cohorts.

LncRNA AOC4P impacts the differentiation of macrophages and T-lymphocyte by regulating the NF-κB pathways of KGN cells: Potential pathogenesis of polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome (PCOS) is a multifactorial endocrine disease, which is an important cause of female infertility worldwide. PCOS patients are in a state of chronic low-grade inflammation, and immune imbalance is considered as a potential cause of its pathogenesis.

METHODS

The expression of AOC4P in PCOS and normal ovarian granulosa cells (GCs) was detected by real-time quantitative PCR. KGN cells were induced by dihydrotestosterone at 500 ng/mL to construct the PCOS model. After lentivirus-infected, KGN cells were constructed with AOC4P overexpression cell lines, the proliferation and apoptosis levels of KGN cells in AOC4P and NC groups were detected. Human monocyte cell line (THP-1)-derived macrophages and peripheral blood mononuclear cells (PBMC) were co-cultured with KGN cells for 48 h, respectively, and the differentiation of macrophages and CD4+ T cells were detected by flow cytometry.

RESULTS

Decreased AOC4P expression was found in PCOS patients. After constructing the PCOS cell model, we observed that overexpression of AOC4P promoted KGN cell proliferation and inhibited apoptosis. After co-culture with AOC4P overexpressed KGN cells, M1 macrophages decreased, M2 macrophages increased, T helper cells type 1 (Th1)/Th2 ratio increased, and regulatory T cell (Treg) cells increased. Finally, we found that AOC4P inhibited the activation of the nuclear factor κ B (NF-κB) pathway in KGN cells.

CONCLUSIONS

In this study, we found that AOC4P regulated the NF-κB signaling pathway by inhibiting the phosphorylation of P65, thereby affecting the proliferation and apoptosis of GCs, altering the differentiation of macrophages and T cells, thus contributing to the pathogenesis of PCOS.

Construction of PANoptosis signature: Novel target discovery for prostate cancer immunotherapy

PANoptosis pathway gene sets encompassing pyroptosis, apoptosis, and necroptosis were identified from the MSigDB database. We analyzed the perturbations and crosstalk in the PANoptosis pathway in prostate adenocarcinoma (PRAD), including gene mutation, transcription, methylation, and clinical features. By constructing a PANoptosis signature, we accurately predicted the prognosis and immunotherapeutic response of PRAD patients. We further explored the molecular features and immunological roles of the signature, dividing patients into high- and low-score groups. Notably, the high-score group correlated with better survival outcomes and immunotherapeutic responses, as well as a higher mutation frequency and enrichment score in the PANoptosis and HALLMARK pathways. The PANoptosis signature also enhanced overall antitumor immunity, promoted immune cell infiltration, upregulated immune checkpoint regulators, and revealed the cold tumor characteristics of PRAD. We also identified potential drug targets based on the PANoptosis signature. These findings lead the way in identifying novel prognostic markers and therapeutic targets for patients with PRAD.

PI3K/Akt signalling pathway-associated long noncoding RNA signature predicts the prognosis of laryngeal cancer patients

The PI3K/Akt signalling pathway is associated with the occurrence and development of tumours and significantly affects the prognosis of patients. We established a predictive signature based on the PI3K/Akt pathway to predict the prognosis of patients. The RNA-seq and clinical data of laryngeal cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database. Three lncRNAs (MNX1-AS1, LINC00330, LSAMP-AS1) were selected through univariate, multivariate Cox and log-rank test analysis to establish a prognostic signature. The patients were then divided into high-risk and low-risk groups based on their risk score. In the TCGA training set, the survival time of the high-risk group was shorter than that of the low-risk group (P < 0.01). Follicular helper T cells were lower in the high-risk group (P = 0.022), and CCR, inflammation promotion, parainflammation, and type I IFN immune function were suppressed. The results of the drug sensitivity analysis suggest that the high-risk group is sensitive to AKT inhibitors. The establishment of the signature was also verified based on the clinical data. Three lncRNAs can facilitate the migration, invasion, and vitality of cancer cells in vitro, and vice versa. Moreover, p-AKT (Ser473) and p-PI3K were highly activated in the cells overexpressing the abovementioned three lncRNAs. The PI3K/Akt signalling pathway-associated prognosis signature has a good predictive effect.

CTLA-4 blockade induces tumor pyroptosis via CD8+ T cells in head and neck squamous cell carcinoma

Immune checkpoint blockade (ICB) treatment has demonstrated excellent medical effects in oncology, and it is one of the most sought after immunotherapies for tumors. However, there are several issues with ICB therapy, including low response rates and a lack of effective efficacy predictors. Gasdermin-mediated pyroptosis is a typical inflammatory death mode. We discovered that increased expression of gasdermin protein was linked to a favorable tumor immune microenvironment and prognosis in head and neck squamous cell carcinoma (HNSCC). We used the mouse HNSCC cell lines 4MOSC1 (responsive to CTLA-4 blockade) and 4MOSC2 (resistant to CTLA-4 blockade) orthotopic models and demonstrated that CTLA-4 blockade treatment induced gasdermin-mediated pyroptosis of tumor cells, and gasdermin expression positively correlated to the effectiveness of CTLA-4 blockade treatment. We found that CTLA-4 blockade activated CD8+ T cells and increased the levels of interferon γ (IFN-γ) and tumor necrosis factor α (TNF-α) cytokines in the tumor microenvironment. These cytokines synergistically activated the STAT1/IRF1 axis to trigger tumor cell pyroptosis and the release of large amounts of inflammatory substances and chemokines. Collectively, our findings revealed that CTLA-4 blockade triggered tumor cells pyroptosis via the release of IFN-γ and TNF-α from activated CD8+ T cells, providing a new perspective of ICB.

Pyroptosis-related lncRNA prognostic signatures for cutaneous melanoma and tumor microenvironment status

Aims: To explore whether the expression of pyroptosis-related lncRNAs makes a difference in the prognosis and antitumor immunity of cutaneous melanoma (CM) patients. Methods: A series of analyses were conducted to establish a prognostic risk model and validate its accuracy. Immune-related analyses were performed to further assess the associations among immune status, tumor microenvironment and the prognostic risk model. Results: Eight pyroptosis-related lncRNAs relevant to prognosis were ascertained and applied to establish the prognostic risk model. The low-risk group had a higher overall survival rate. Conclusion: The established prognostic risk model presents better prediction ability for the prognosis of CM patients and provides new possible therapeutic targets for CM.

LncRNAs and regulated cell death in tumor cells

Regulated Cell Death (RCD) is a mode of cell death that occurs through drug or genetic intervention. The regulation of RCDs is one of the significant reasons for the long survival time of tumor cells and poor prognosis of patients. Long non-coding RNAs (lncRNAs) which are involved in the regulation of tumor biological processes, including RCDs occurring on tumor cells, are closely related to tumor progression. In this review, we describe the mechanisms of eight different RCDs which contain apoptosis, necroptosis, pyroptosis, NETosis, entosis, ferroptosis, autosis and cuproptosis. Meanwhile, their respective roles in the tumor are aggregated. In addition, we outline the literature that is related to the regulatory relationships between lncRNAs and RCDs in tumor cells, which is expected to provide new ideas for tumor diagnosis and treatment.

The Role of Different Immunocompetent Cell Populations in the Pathogenesis of Head and Neck Cancer-Regulatory Mechanisms of Pro- and Anti-Cancer Activity and Their Impact on Immunotherapy

Head and neck squamous cell carcinoma (HNSCC) is one of the most aggressive and heterogeneous groups of human neoplasms. HNSCC is characterized by high morbidity, accounting for 3% of all cancers, and high mortality with ~1.5% of all cancer deaths. It was the most common cancer worldwide in 2020, according to the latest GLOBOCAN data, representing the seventh most prevalent human malignancy. Despite great advances in surgical techniques and the application of modern combinations and cytotoxic therapies, HNSCC remains a leading cause of death worldwide with a low overall survival rate not exceeding 40-60% of the patient population. The most common causes of death in patients are its frequent nodal metastases and local neoplastic recurrences, as well as the relatively low response to treatment and severe drug resistance. Much evidence suggests that the tumour microenvironment (TME), tumour infiltrating lymphocytes (TILs) and circulating various subpopulations of immunocompetent cells, such regulatory T cells (CD4+CD25+Foxp3+Tregs), cytotoxic CD3+CD8+ T cells (CTLs) and CD3+CD4+ T helper type 1/2/9/17 (Th1/Th2/Th9/Th17) lymphocytes, T follicular helper cells (Tfh) and CD56dim/CD16bright activated natural killer cells (NK), carcinoma-associated fibroblasts (CAFs), myeloid-derived suppressor cells (MDSCs), tumour-associated neutrophils (N1/N2 TANs), as well as tumour-associated macrophages (M1/M2 phenotype TAMs) can affect initiation, progression and spread of HNSCC and determine the response to immunotherapy. Rapid advances in the field of immuno-oncology and the constantly growing knowledge of the immunosuppressive mechanisms and effects of tumour cancer have allowed for the use of effective and personalized immunotherapy as a first-line therapeutic procedure or an essential component of a combination therapy for primary, relapsed and metastatic HNSCC. This review presents the latest reports and molecular studies regarding the anti-tumour role of selected subpopulations of immunocompetent cells in the pathogenesis of HNSCC, including HPV+ve (HPV+) and HPV-ve (HPV-) tumours. The article focuses on the crucial regulatory mechanisms of pro- and anti-tumour activity, key genetic or epigenetic changes that favour tumour immune escape, and the strategies that the tumour employs to avoid recognition by immunocompetent cells, as well as resistance mechanisms to T and NK cell-based immunotherapy in HNSCC. The present review also provides an overview of the pre- and clinical early trials (I/II phase) and phase-III clinical trials published in this arena, which highlight the unprecedented effectiveness and limitations of immunotherapy in HNSCC, and the emerging issues facing the field of HNSCC immuno-oncology.

Immunity-related long noncoding RNA WDFY3-AS2 inhibited cell proliferation and metastasis through Wnt/β-catenin signaling in oral squamous cell carcinoma

OBJECTIVE

Long noncoding RNA WDFY3-AS2 has been shown to play dual roles in the modulation of cancer progression. This study aimed at clarifying the biological role of WDFY3-AS2 as well as the association between WDFY3-AS2 expression, β-catenin expression, and OSCC immunity in oral squamous cell carcinoma (OSCC).

DESIGN

Bioinformatics analyses, CCK8, EdU, wound healing, transwell, RT-qPCR, western blot, immunofluorescence, in situ hybridization, and immunohistochemistry assays were adopted for exploring the role of WDFY3-AS2 in OSCC.

RESULTS

Bioinformatics analyses showed that WDFY3-AS2 conferred a poor prognosis for OSCC patients. Further analyses identified WDFY3-AS2 as an independent prognostic indicator for OSCC. Moreover, silencing WDFY3-AS2 inhibits OSCC cell proliferation, migration and invasion. Gene set enrichment analysis indicated that WDFY3-AS2 participated in the regulation of Wnt signaling. In addition, WDFY3-AS2 expression was positively associated with β-catenin mRNA levels, the key component of Wnt signaling. Interestingly, WDFY3-AS2 knockdown inhibited β-catenin expression and nuclear translocation, thus suppressing OSCC progression through Wnt signaling. Furthermore, WDFY3-AS2 expression correlated with an immunosuppressive phenotype in the tumor immune microenvironment. In situ hybridization and immunohistochemistry verified that WDFY3-AS2 was positively associated with total and nuclear β-catenin protein levels and negatively associated with CD4 expression.

CONCLUSIONS

This study demonstrates that the immunity-associated WDFY3-AS2 augments OSCC proliferation and metastasis through Wnt/β-catenin signaling and may serve as a novel treatment target and a new prognostic factor for OSCC.

Construction of a pyroptosis-related lncRNAs signature for predicting prognosis and immunotherapy response in glioma

Recent studies have proved that pyroptosis-related long non-coding RNAs (PRlncRNAs) are closely linked to tumor progression, prognosis, and immunity. Here, we systematically evaluated the correlation of PRlncRNAs with glioma prognosis. This study included 3 glioma cohorts (The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and Gravendeel). Through Pearson correlation analysis, PRlncRNAs were screened from these 3 cohorts. Univariate Cox regression analysis was then carried out to determine the prognostic PRlncRNAs. A pyroptosis-related lncRNAs signature (PRLS) was then built by least absolute shrinkage and selection operator and multivariate Cox analyses. We systematically evaluated the correlation of the PRLS with the prognosis, immune features, and tumor mutation burden in glioma. A total of 14 prognostic PRlncRNAs overlapped in all cohorts and were selected as candidate lncRNAs. Based on The Cancer Genome Atlas cohort, a PRLS containing 7 PRlncRNAs was built. In all cohorts, the PRLS was proved to be a good predictor of glioma prognosis, with a higher risk score related to a poorer prognosis. We observed obvious differences in the immune microenvironment, immune cell infiltration level, and immune checkpoint expression in low- and high-risk subgroups. Compared with low-risk cases, high-risk cases had lower Tumor Immune Dysfunction and Exclusion scores and greater tumor mutation burden, indicating that high-risk cases can be more sensitive to immunotherapy. A nomogram combining PRLS and clinical parameters was constructed, which showed more robust and accurate predictive power. In conclusion, the PRLS is a potentially useful indicator for predicting prognosis and response to immunotherapy in glioma. Our findings may provide a useful insight into clinically individualized treatment strategies for patients.

Identification and validation of an m6A-related gene signature to predict prognosis and evaluate immune features of breast cancer

Breast cancer is the most prevalent cancer, and it is accompanied by high heterogeneity. N6-methyladenosine (m6A) modification significantly contributes to breast cancer tumorigenesis and progression. However, how m6A-related genes affect the clinical outcomes and tumor immune microenvironment (TIME) of breast cancer is largely unknown. Our study developed an m6A-related gene signature on the basis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The m6A-related gene signature was constructed using univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. Breast cancer patients were classified into low- and high-risk groups depending on the median risk score. The reliability and efficiency of the signature were validated using Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and principal component analysis (PCA). The risk score was validated as an independent indicator associated with overall survival, and a nomogram model was created to estimate the overall survival of patients with breast cancer. Functional annotation suggested that the risk score had a strong relationship with immune-related pathways. Different proportions of immune cell infiltration between the two groups were evaluated using various algorithms. The high-risk group had higher immune checkpoint expression levels. We discovered that one of the 6 prognostic genes, TMEM71, was downregulated in breast cancer tissues. In vitro experiments indicated that overexpression of TMEM71 suppressed breast cancer cell proliferation and migration. In conclusion, the m6A-related gene signature may be a sensitive biomarker for overall survival prediction and guide the individualized treatment for breast cancer patients.

Integrated Analysis of a Competing Endogenous RNA Network Reveals a Ferroptosis-related 6-LncRNA Prognostic Signature in Clear Cell Renal Cell Carcinoma.. [DOI: 10.21203/rs.3.rs-2294111/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background: This study set out to elucidate the biological functions and prognostic role of ferroptosis-related lncRNAs based on a synthetic analysis of competing endogenous RNA (ceRNA) networks in clear cell renal cell carcinoma (ccRCC). Methods: Ferroptosis-related genes were obtained from the FerrDb database. The expression data and matched clinical information of lncRNAs, miRNAs, and mRNAs from The Cancer Genome Atlas (TCGA) database were obtained to identify differentially expressed RNAs (DERNAs). The lncRNA-miRNA-mRNA ceRNA network was established utilizing the common miRNAs that were predicted in the RNAHybrid, StarBase, and TargetScan databases. Then, by progressive univariate Cox regression, LASSO,and multivariate Cox regression analysis of gene expression data and clinical information, a ferroptosis-related lncRNA prognosis signature was constructed based on the lncRNAs in ceRNA. Finally, the influence of independent lncRNAs on ccRCC was explored through a series of functional and unsupervised cluster analysis. Results: A total of 35 ferroptosis-related DEmRNAs, 356 DElncRNAs, and 132 DEmiRNAs were sorted out from the KIRC cohort of TCGA database. Overlapping DElncRNA-DEmiRNA and DEmiRNA-DEmRNA interactions among the RNAHybrid, StarBase, and TargetScan databases were constructed and identified, then a ceRNA network with 77 axes related to ferroptosis was established utilizing mutual DEmiRNAs in two interaction networks as nodes. Through synthetic analysis of the expression data and clinical information of 27 lncRNAs in the ceRNA network, a 6-ferroptosis-lncRNA signature including PVT1, CYTOR, MIAT, SNHG17, LINC00265, and LINC00894 was identified in the training set. Kaplan-Meier, PCA, t-SNE analysis, risk score curve, and ROC curve were performed to confirm the validity of the signature in the training set and secondly verified in the validation set. Finally, ssGSEA and ESTIMATE analysis showed that the signature was related with immune cell infiltration and could predict immune-related phenotypes. Conclusions: Our research underlines the role of the 6-ferroptosis-lncRNA signature as a predictor of prognosis and a therapeutic alternative for KIRC.

The noncoding RNAs regulating pyroptosis in colon adenocarcinoma were derived from the construction of a ceRNA network and used to develop a prognostic model

Background

Noncoding RNAs (ncRNAs), pyroptosis and tumours are all hot topics in current research, but there are very limited studies on pyroptosis and its regulated ncRNAs in colon adenocarcinoma (COAD).

Methods

The COAD transcription profile dataset from TCGA was used for differential expression analysis. Pyroptosis-related genes (PRGs), the top 200 long noncoding RNAs (lncRNAs) and circular RNA (circRNAs) were selected from the results to construct an endogenous competitive RNA (ceRNA) network. Moreover, the expression of the ceRNAs was used for consensus cluster analysis of COAD and developing a risk model after combining clinical follow-up data by the least absolute shrinkage and selection operator method. The stability and independent prognostic ability of the risk model were evaluated. Finally, gene set enrichment analysis (GSEA) and immune score comparisons between the high-risk and low-risk groups were performed.

Results

There were 87 PRGs with significant differences, among which casp3/8, NLRP1/3, and IL-1α/1β were at the core of the interactions. The ceRNA network consisted of 58 lncRNAs, 6 circRNAs, 25 PRGs, and 55 microRNAs. We speculated that KCNQ1OT1-miRNAs-SQSTM1 and HSA_CIRC_0001495-miRNAs-PTEN have great potential and value in the pyroptosis mechanism of COAD. Nine RNAs were involved in the risk score, which had excellent independent prognostic ability. Survival analyses were significant between the high-risk (HR) and low-risk (LR) groups (training cohort: P < 0.001; test cohort: P = 0.037). GSEA was mainly enriched in tumour proliferation and metastasis related pathways, while differences in immune activity showed a bipolar distribution between the HR and LR groups.

Conclusions

The overall mechanism of pyroptosis in COAD was revealed. CeRNAs most closely related to the pyroptosis mechanism of COAD were selected and used to develop a prognostic model. The results may present new regulatory sites and potential targets for COAD pyroptosis mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01359-w.

Predicting the Immune Microenvironment and Prognosis with a NETosis-Related lncRNA Signature in Head and Neck Squamous Cell Carcinoma

Background. The mechanistic aspects of the involvement of long noncoding RNAs (lncRNAs) in NETosis, the process of neutrophil extracellular trap (NET) formation in head and neck squamous cell carcinoma (HNSCC), lack comprehensive elucidation. The involvement of these molecules in the immune microenvironment and plausible HNSCC prognosis remain to see the light of the day. The plausible functioning of NETosis-related lncRNAs with their plausible prognostic impact in HNSCC was probed in this work. Methods. The scrutiny of lncRNAs linked to NETosis entailed the probing of twenty-four genes associated with the process employing Pearson’s correlation analysis on HNSCC patients’ RNA sequencing data from The Cancer Genome Atlas (TCGA) database. The application of univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses yielded a NETosis-related lncRNA signature that was subjected to probing for its suitability in prognosis employing survival and nomogram analyses. Results. The NETosis-related lncRNA signature inclusive of five lncRNAs facilitated patients to be segregated as high-risk and low-risk groups with the former documenting a poor prognosis. Regression unearthed that the risk score was an independent factor for prognosis. The receiver operating characteristic (ROC) or receiver operating characteristic curve analysis documented a one-year area under time-dependent ROC curve (AUC) value of 0.711 that is corroborative of the accuracy of this signature. Additional probing documented an evident enriching of immune-linked pathways in the low-risk patients, while the high-risk patients documented an immunologically “cold” profile as per the infiltration of immune cells. We verified lncRNA expression from our NETosis-related lncRNA signature in vitro, which reflects the reliability of our model to a certain extent. Moreover, we also verified the function of the lncRNA. We found that LINC00426 contributes to the innate immune cGAS-STING signaling pathway, which explain to some extent the role of our prognostic model in predicting “hot” and “cold” tumors. Conclusions. The plausible prognostic relevance of the NETosis-related lncRNA signature (with five lncRNAs) emerges that is suggestive of its promise in targeting HNSCC.

A novel pyroptosis-regulated gene signature for predicting prognosis and immunotherapy response in hepatocellular carcinoma

Background: Pyroptosis, a newly discovered type of programmed cell death, has both anti-tumor and tumor-promoting effects on carcinogenesis. In hepatocellular carcinoma (HCC), however, the associations between pyroptosis-regulated genes and prognosis, immune microenvironment, and immunotherapy response remain unclear. Samples and methods: Sequencing data were collected from The Cancer Genome Atlas database, The International Cancer Genome Consortium (ICGC), and The Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB). First, we investigated the expression levels and copy number variations (CNVs) of 56 pyroptosis genes in HCC and pan-cancer. Next, we identified 614 genes related to 56 pyroptosis-associated genes at the expression, mutation, and CNVs levels. Pathway enrichment analysis of 614 genes in the Hallmark, KEGG, and Reactome databases yielded a total of 253 significant signaling pathways. The pyroptosis-regulated genes (PRGs) comprised 108 genes that were derived from the top 20 signaling pathways, of which 57 genes had prognostic value in HCC. The least absolute shrinkage and selection operator (LASSO) analysis was performed to screen for PRGs with prognostic values. Ultimately, we constructed a risk score model with seven PRGs to predict HCC prognosis and validated its predictive value in three independent HCC cohorts. Risk scores were used to illustrate receiver operating characteristic (ROC) curves predicting 1, 3, and 5-years overall survival (OS). Single-sample gene set enrichment analysis (ssGSEA), was performed to study 28 types of immune cells infiltrated in HCC. The relationship between the risk signature and six immune checkpoint genes and immunotherapy was analyzed. Results: A total of seven PRGs were obtained following multiple screening steps. The risk score model containing seven PRGs was found to correlate significantly with the HCC prognosis of the training group. In addition, we validated the risk score model in two additional HCC cohorts. The risk score significantly correlated with infiltrating immune cells (i. e. CD4+ T cells, etc.), ICB key molecules (i. e. HAVCR2, etc.), and ICB response. Conclusions: This study demonstrated a vital role of PRGs in predicting the prognosis and immunotherapy response of HCC patients. The risk model could pave the way for drugs targeting pyroptosis and immune checkpoints in HCC.

Cuproptosis-Related lncRNAs are Biomarkers of Prognosis and Immune Microenvironment in Head and Neck Squamous Cell Carcinoma

Background: Cuproptosis is a new type of cell death that induces protein toxic stress and eventually leads to cell death. Hence, regulating cuproptosis in tumor cells is a new therapeutic approach. However, studies on cuproptosis-related long noncoding RNA (lncRNA) in head and neck squamous cell carcinoma (HNSC) have not been found. This study aimed to explore the cuproptosis-related lncRNAs prognostic marker and their relationship to immune microenvironment in HNSC by using bioinformatics methods.

Methods: RNA sequencing, genomic mutations, and clinical data of TCGA_HNSC were downloaded from The Cancer Genome Atlas. HNSC patients were randomly assigned to either a training group or a validation cohort. The least absolute shrinkage and selection operator Cox regression and multivariate Cox regression models were used to determine the prognostic model in the training cohort, and its independent prognostic effect was further confirmed in the validation and entire cohorts.

Results: Based on previous literature, we collected 19 genes associated with cuproptosis. Afterward, 783 cuproptosis-related lncRNAs were obtained through coexpression. Cox model revealed and constructed eight cuproptosis-related lncRNAs prognostic marker (AL132800.1, AC090587.1, AC079160.1, AC011462.4, AL157888.1, GRHL3-AS1, SNHG16, and AC021148.2). Patients were divided into high- and low-risk groups based on the median risk score. The Kaplan–Meier survival curve revealed that the overall survival between the high- and low-risk groups was statistically significant. The receiver operating characteristic curve and principal component analysis demonstrated the accurate prognostic ability of the model. Univariate and multivariate Cox regression analysis showed that risk score was an independent prognostic factor. In addition, we used multivariate Cox regression to establish a nomogram of the predictive power of prognostic markers. The tumor mutation burden showed significant differences between the high- and low-risk groups. HNSC patients in the high-risk group responded better to immunotherapy than those in the low-risk group. We also found that risk scores were significantly associated with drug sensitivity in HNSC.

Conclusion: In summary, our study identified eight cuprotosis-related lncRNAs signature of HNSC as the prognostic predictor, which may be promising biomarkers for predicting the benefit of HNSC immunotherapy as well as drug sensitivity.

Comprehensive Analysis of the Correlation Between Pyroptosis-Related LncRNAs and Tumor Microenvironment, Prognosis, and Immune Infiltration in Hepatocellular Carcinoma

Background: Accumulating evidence shows that pyroptosis plays a crucial role in hepatocellular carcinoma (HCC). However, the relationship between pyroptosis-related long non-coding RNAs (lncRNAs) and HCC tumor characteristics remains enigmatic. We aimed to explore the predictive effect of pyroptosis-related lncRNAs (PRLs) in the prognosis of HCC.

Methods: We comprehensively analyzed the role of the PRLs in the tumor microenvironment and HCC prognosis by integrating genomic data from patients of HCC. Consensus clustering analysis of PRLs was applied to identify HCC subtypes. A prognostic model was then established with a training cohort from The Cancer Genome Atlas (TCGA) using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Further, we evaluated the accuracy of this predictive model using a validation set. We predicted IC50s of commonly used chemotherapeutic and targeted drugs through the R package pRRophetic.

Results: Based on pyroptosis-related lncRNAs, a prognostic risk signature composed of seven PRLs (MKLN1AS, AL031985.3, SNHG4, GHRLOS, AC005479.2, AC099850.4, and AC026412.3) was established. For long-term prognosis of HCC patients, our model shows excellent accuracy to forecast overall survival of HCC individuals both in training set and testing set. We found a significant correlation between clinical features and the risk score. Patients in the high-risk group had tumor characteristics associated with progression such as aggressive pathological grade and stage. Besides that, gene set enrichment analysis (GSEA) showed that cell cycle and focal adhesion were significantly enriched in the high-risk group.

Conclusion: The association of the risk model constituted by these seven pyroptosis-related lncRNAs with clinical prognosis, tumor microenvironment, chemotherapy and small molecule drugs was evaluated. Our study provides strong evidence for individualized prediction of prognosis, shedding light on immunotherapy in HCC patients.

A Novel Pyroptotic and Inflammatory Gene Signature Predicts the Prognosis of Cutaneous Melanoma and the Effect of Anticancer Therapies

Purpose

The purpose of this study was to construct a gene signature comprising genes related to both inflammation and pyroptosis (GRIPs) to predict the prognosis of patients with cutaneous melanoma patients and the efficacy of immunotherapy, chemotherapy, and targeted therapy in these patients.

Methods

Gene expression profiles were collected from The Cancer Genome Atlas. Weighted gene co-expression network analysis was performed to identify GRIPs. Univariable Cox regression and Lasso regression further selected key prognostic genes. Multivariable Cox regression was used to construct a risk score, which stratified patients into high- and low-risk groups. Areas under the ROC curves (AUCs) were calculated, and Kaplan-Meier analyses were performed for the two groups, following validation in an external cohort from Gene Expression Omnibus (GEO). A nomogram including the GRIP signature and clinicopathological characteristics was developed for clinical use. Gene set enrichment analysis illustrated differentially enriched pathways. Differences in the tumor microenvironment (TME) between the two groups were assessed. The efficacies of immune checkpoint inhibitors (ICIs), chemotherapeutic agents, and targeted agents were predicted for both groups. Immunohistochemical analyses of the GRIPs between the normal and CM tissues were performed using the Human Protein Atlas data. The qRT-PCR experiments validated the expression of genes in CM cell lines, Hacat, and PIG1 cell lines.

Results

A total of 185 GRIPs were identified. A novel gene signature comprising eight GRIPs (TLR1, CCL8, EMP3, IFNGR2, CCL25, IL15, RTP4, and NLRP6) was constructed. The signature had AUCs of 0.714 and 0.659 for predicting 3-year overall survival (OS) in the TCGA entire and GEO validation cohorts, respectively. Kaplan-Meier analyses revealed that the high-risk group had a poorer prognosis. Multivariable Cox regression showed that the GRIP signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The nomogram showed good accuracy and reliability in predicting 3-year OS (AUC = 0.810). GSEA and TME analyses showed that the high-risk group had lower levels of pyroptosis, inflammation, and immune response, such as lower levels of CD8+ T-cell infiltration, CD4+ memory-activated T-cell infiltration, and ICI. In addition, low-risk patients whose disease expressed PD-1 or CTLA-4 were likely to respond better to ICIs, and several chemotherapeutic and targeted agents. Immunohistochemical analysis confirmed the distinct expression of five out of the eight GRIPs between normal and CM tissues.

Conclusion

Our novel 8-GRIP signature can accurately predict the prognosis of patients with CM and the efficacies of multiple anticancer therapies. These GRIPs might be potential prognostic biomarkers and therapeutic targets for CM.

Prognosis Risk Model Based on Pyroptosis-Related lncRNAs for Bladder Cancer

Objective. Bladder cancer (BC) is the most common malignancy in the urinary system and is prone to recurrence and metastasis. Pyroptosis is a kind of cell necrosis that is triggered by the gasdermin protein family. lncRNAs are noncoding RNAs that are more than 200 nucleotides long. Both pyroptosis and lncRNAs are associated with tumor development and progression. This study is aimed at exploring and establishing a prognostic signature of BC based on pyroptosis-related lncRNAs. Methods. In this study, The Cancer Genome Atlas (TCGA) database provided us with the RNA sequencing transcriptome data of bladder cancer patients, and we identified differentially expressed pyroptosis-related lncRNAs in bladder cancer. Then, the prognostic significance of these lncRNAs was assessed using univariate Cox regression analysis and LASSO regression analysis. Subsequently, 4 pyroptosis-related lncRNAs, namely, AL121652.1, AL161729.4, AC007128.1, and AC124312.3, were identified by multivariate Cox regression analysis, thus constructing the prognostic risk model. Then, we compared the levels of immune infiltration, differences in cell function, immune checkpoints, and m6A-related gene expression levels between the high- and low-risk groups. Result. Patients were divided into low-risk or high-risk groups based on the median risk score. Kaplan–Meier survival analysis indicated that the overall survival of bladder cancer patients in the low-risk group was substantially superior to that in the high-risk group ( $p<0.001$ ). The receiver operating characteristic (ROC) curve further confirmed the credibility of our model. Moreover, gene set enrichment analysis (GSEA) indicated that these were different signal pathways significantly enriched between the two groups. Immune infiltration, immune checkpoint, and N6-methyladenosine-related gene analysis also reflected that there were notable differences between the two groups. Conclusion. Therefore, this prognostic risk model is based on the level of pyroptotic lncRNAs, which is conducive to individualized assessment of the risk of patients and provides a reference for clinical treatment. This will also help provide insights into the prognosis and treatment of bladder cancer.

A Novel Pyroptosis-Related Prognostic Signature for Cervical Squamous Cell Carcinoma

Purpose

Pyroptosis has vital roles in tumorigenesis and cancer development; however, its relationship with cervical squamous cell cancer (CSCC) remains unexplored. In this study, we aimed to develop a CSCC prediction signature related to pyroptosis.

Patients and Methods

Consensus clustering analysis was conducted to detect pyroptosis-related subclusters for CSCC. Next, differentially expressed genes (DEGs) between subclusters were identified. Univariate, least absolute shrinkage and selection operator, and stepwise multivariate Cox regression analyses were applied to establish a prognostic model and a nomogram drawn. Additionally, functional enrichment analysis, tumor mutation burden, and immune characteristics associated with this signature were investigated.

Results

We constructed a seven-gene signature that functions as an independent predictor of prognosis in CSCC using data from The Cancer Genome Atlas. Patients with CSCC were divided into two groups based on median risk score, and patients in the low-risk group had significantly longer survival time than those in the high-risk group. Our findings were validated using Gene Expression Omnibus cohort data. We also established a nomogram, to expand the clinical applicability of our findings. The seven gene signature was associated with various molecular pathways, tumor mutation status, and immune microenvironment.

Conclusion

The pyroptosis-related risk signature consisting of seven genes developed here represents a potential robust biomarker for predicting prognosis and immunotherapy response in patients with CSCC.

Nine Pyroptosis-Related lncRNAs are Identified as Biomarkers for Predicting the Prognosis and Immunotherapy of Endometrial Carcinoma

Background

Endometrial carcinoma (EC) is one of the most common malignancies. Immunotherapy has shown promising effects in the treatment against specific subtypes of EC.

Methods

The RNA and clinical information of patients with EC were acquired from The Cancer Gene Atlas (TCGA) database. Firstly, the differentially expressed pyroptosis-related lncRNAs (PRLs) were screened between the tumor and normal control tissue. Secondly, the PRLs closely related to survival were identified by univariate and multivariate regression analysis, based on which, we evaluated the risk score for each EC patient to construct a risk signature. Moreover, we assessed the prognostic value, clinical relevance immunity, and immunotherapy based on this signature.

Results

We screened out 9 individual PRLs (AC087491.1, AL353622.1, AL035530.2, LINC02036, AL021578.1, AL390195.2, AC009097.2, AC004585.1, and AC244517.7) closely related to the prognosis of EC. Kaplan–Meier analyses showed a poorer prognosis for the patients in the high-risk FRLs signature (P < 0.001). The area under the curve (AUC) for 1 year, 2 years, 3 years was 0.693, 0.694, 0.750, respectively. Our risk model could be considered as an independent prognostic marker for EC (P < 0.001, HR:2.172, 95% CI:1.532–3.079). Moreover, immune functions and checkpoints were generally different in the 2 groups. Simulation analysis by termed immunophenoscores hinted that immunotherapy might bring optimal therapeutic effect in the low-risk group.

Conclusion

We successfully developed a novel signature with 9 lncRNAs related to pyroptosis, which may be used as biomarkers to evaluate the prognosis and immune treatment of EC.