Non-coding RNAs in necroptosis, pyroptosis and ferroptosis in cancer metastasis

The fate and function of non-coding RNAs during necroptosis

Necroptosis is a novel form of cell death which is activated when apoptotic cell death signals are disrupted. Accumulating body of observations suggests that noncoding RNAs, which are the lately discovered mystery of the human genome, are significantly associated with necroptotic signaling circuitry. The fate and function of miRNAs have been well documented in human disease, especially cancer. Recently, lncRNAs have gained much attention due to their diverse regulatory functions. Although available studies are currently based on bioinformatic analysis, predicted interactions desires further attention, as these hold significant promise and should not be overlooked. In the light of these, here we comprehensively review and discuss noncoding RNA molecules that play significant roles during execution of necroptotic cell death.

Exploring ncRNA-mediated pathways in sepsis-induced pyroptosis

Sepsis, a potentially fatal illness caused by an improper host response to infection, remains a serious problem in the world of healthcare. In recent years, the role of ncRNA has emerged as a pivotal aspect in the intricate landscape of cellular regulation. The exploration of ncRNA-mediated regulatory networks reveals their profound influence on key molecular pathways orchestrating pyroptotic responses during septic conditions. Through a comprehensive analysis of current literature, we navigate the diverse classes of ncRNAs, including miRNAs, lncRNAs, and circRNAs, elucidating their roles as both facilitators and inhibitors in the modulation of pyroptotic processes. Furthermore, we highlight the potential diagnostic and therapeutic implications of targeting these ncRNAs in the context of sepsis, aiming to cover the method for novel and effective strategies to mitigate the devastating consequences of septic pathogenesis. As we unravel the complexities of this regulatory axis, a deeper understanding of the intricate crosstalk between ncRNAs and pyroptosis emerges, offering promising avenues for advancing our approach to sepsis intervention. The intricate pathophysiology of sepsis is examined in this review, which explores the dynamic interaction between ncRNAs and pyroptosis, a highly regulated kind of programmed cell death.

Development of a necroptosis-related prognostic model for uterine corpus endometrial carcinoma

Necroptosis is a recently identified caspase-independent form of cell death which plays a significant role in the onset and progression of cancer. MicroRNAs (miRNAs) are vital for the development of uterine corpus endometrial carcinoma (UCEC) because they are an important regulatory component in necroptosis. This study developed a new necroptosis-related miRNAs profile to predict the prognosis of patients with UCEC. The TCGA-UCEC cohort's RNA sequencing data, consisting of 534 tumor samples and 33 normal samples, was downloaded. Ten differentially expressed miRNAs related to necroptosis were identified. A prediction model for necroptosis-related miRNAs was then created through COX regression and nomograms analysis. Clinical and pathological parameters were integrated to construct a nomogram and evaluate the model. Prognosis-related miRNAs were further used to predict target genes, and functional analysis was conducted to explore the potential mechanisms of these target genes. Subsequently, immune infiltration analysis was performed using transcriptome data to identify immune genes associated with prognosis, and the expression levels of target gene was validated using UCEC tissues. We identified 7 up-regulated miRNAs (hsa-miR-577, hsa-miR-7-5p, hsa-miR-210-3p, hsa-miR-210-5p, hsa-miR-200a-5p, hsa-miR-141-3p, hsa-miR-425-5p) and 3 down-regulated miRNAs (hsa-miR-7-2-3p, hsa-miR-383-5p, hsa-miR-29a-3p). The risk signature was based on univariate and multivariate COX analyses, constructed using 2 independent prognostic factors and miRNAs (hsa-miR-425-5p, hsa-miR-7-5p) associated with necroptosis. Nomograms demonstrated the prognostic value of risk level, age, FIGO stage, and histological type. Kaplan-Meier analysis revealed significant differences in overall survival (OS) outcomes associated with the expression of hsa-miR-425-5p (P < 0.001) and hsa-miR-7-5p (P = 0.015). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) investigations indicated that these miRNAs play crucial roles in tumor development, metastasis, and prognosis. Immune infiltration analysis showed decreased infiltration of CD8+ T cells, CD8+ T cells, NK cells, and M1 macrophages in normal tissues. Subsequently, a necroptosis-related immune gene significantly associated with prognosis (THRB) was identified, western blot and immunohistochemical staining confirmed the differential expression of THRB in normal endometrial tissues and tumor. Our findings demonstrate a close association between necroptosis and UCEC. The two necroptosis-related miRNAs used in this study may serve as valuable prognostic markers for UCEC patients, and are associated with immune cell infiltration. This suggests that necroptosis may be involved in the development of UCEC through its interaction with immune responses.

Development of a Novel Pyroptosis-Associated lncRNA Biomarker Signature in Lung Adenocarcinoma

Pyroptosis is a novel type of cell death observed in various diseases. Our study aimed to investigate the relationship between pyroptosis-associated-long non-coding RNAs (lncRNAs), immune infiltration, and expression of immune checkpoints in the setting of lung adenocarcinoma and the prognostic value of pyroptosis-related lncRNAs. RNA-seq transcriptome data and clinical information from The Cancer Genome Atlas (TCGA) were downloaded, and consensus clustering analysis was used to separate the samples into two groups. Least absolute shrinkage and selection operator (LASSO) analyses were conducted to construct a risk signature. The association between pyroptosis-associated lncRNAs, immune infiltration, and expression of immune checkpoints were analysed. The cBioPortal tool was used to discover genomic alterations. Gene set enrichment analysis (GSEA) was utilized to investigate downstream pathways of the two clusters. Drug sensitivity was also examined. A total of 43 DEGs and 3643 differentially expressed lncRNAs were identified between 497 lung adenocarcinoma tissues and 54 normal samples. A signature consisting of 11 pyroptosis-related lncRNAs was established as prognostic for overall survival. Patients in the low-risk group have a significant overall survival advantage over those in the high-risk group in the training group. Immune checkpoints were expressed differently between the two risk groups. Risk scores were validated to develop an independent prognostic model based on multivariate Cox regression analysis. The area under time-dependent receiver operating characteristic curve (AUC of the ROC) at 1-, 3-, and 5-years measured0.778, 0.757, and 0.735, respectively. The high-risk group was more sensitive to chemotherapeutic drugs than the low-risk group. This study demonstrates the association between pyroptosis-associated lncRNAs and prognosis in lung adenocarcinoma and enables a robust predictive signature of 11 lncRNAs to inform overall survival.

Pan-cancer analysis of cuproptosis-promoting gene signature from multiple perspectives

Cuproptosis is a newly discovered cell death form with a unique mechanism. Seven genes have been identified to facilitate the process. To explore the roles of cuproptosis in different cancers, we first used Gene Expression Profiling, Interactive Analysis, version 2, and cBioPortal to analyze expression, prognosis and mutation conditions in different cancers from The Cancer Genome Atlas (TCGA). Then, we conducted single sample gene set enrichment analysis to combine the signature of the cuproptosis-promoting genes for all TCGA cancers. Moreover, we performed a survival analysis to explore if cuproptosis-score could independently influence clinical outcomes. Next, we compared pathway enrichment, immune infiltration, gene set activity and gene mutation between different cuproptosis-score groups. Finally, based on the intersected genes from difference analysis and weighted gene co-expression network analysis, consensus clustering and Least Absolute Shrinkage and Selection Operator Cox regression were performed and nomograms were constructed. Cuproptosis-score was associated with a favorable prognosis in eight TCGA cancers. Cancer-associated fibroblasts, B cells, neutrophils and mast cells were generally less abundant, and ferroptosis activity was higher in high cuproptosis-score groups. The novel classifications could differentiate patients' overall survival, and the risk models could effectively predict patients' outcomes in kidney, renal clear cell carcinoma, liver hepatocellular carcinoma, mesothelioma and stomach adenocarcinoma. Cuproptosis activity was closely related to the prognosis of several cancers. Its effects on the immune microenvironment and its relationship with other cell death modes, especially ferroptosis, may become the focus of further research.

Molecular mechanism and potential therapeutic targets of necroptosis and ferroptosis in Alzheimer's disease

Alzheimer's disease (AD), a neurodegenerative condition, is defined by neurofibrillary tangles, amyloid plaques, and gradual cognitive decline. Regardless of the advances in understanding AD's pathogenesis and progression, its causes are still contested, and there are currently no efficient therapies for the illness. The post-mortem analyses revealed widespread neuronal loss in multiple brain regions in AD, evidenced by a decrease in neuronal density and correlated with the disease's progression and cognitive deterioration. AD's neurodegeneration is complicated, and different types of neuronal cell death, alone or in combination, play crucial roles in this process. Recently, the involvement of non-apoptotic programmed cell death in the neurodegenerative mechanisms of AD has received a lot of attention. Aberrant activation of necroptosis and ferroptosis, two newly discovered forms of regulated non-apoptotic cell death, is thought to contribute to neuronal cell death in AD. In this review, we first address the main features of necroptosis and ferroptosis, cellular signaling cascades, and the mechanisms involved in AD pathology. Then, we discuss the latest therapies targeting necroptosis and ferroptosis in AD animal/cell models and human research to provide vital information for AD treatment.

Establishment of a novel signature to predict prognosis and immune characteristics of pancreatic cancer based on necroptosis-related long non-coding RNA

BACKGROUND

Necroptosis plays an important role in tumorigenesis and tumour progression. Long noncoding RNAs (lncRNAs) have been proven to be regulatory factors of necroptosis in various tumours. However, the real role of necroptosis-related lncRNAs (NRLs) and their potential to predict the prognosis of pancreatic cancer (PC) remain largely unclear. The goal of this study was to identify NRLs and create a predictive risk signature in PC, explore its prognostic predictive performance, and further assess immunotherapy and chemotherapy responses.

METHODS

RNA sequencing data, tumour mutation burden (TMB) data, and clinical profiles of 178 PC patients were downloaded from The Cancer Genome Atlas (TCGA) database. NRLs were identified using Pearson correlation analysis. Then, patients were divided into the training set and the validation set at a 1:1 ratio. Subsequently, Cox and LASSO regression analyses were conducted to establish a prognostic NRL signature in the training set and validation set. The predictive efficacy of the 5-NRL signature was assessed by survival analysis, nomogram, Cox regression, clinicopathological feature correlation analysis, and receiver operating characteristic (ROC) curve analysis. Furthermore, correlations between the risk score (RS) and immune cell infiltration, immune checkpoint molecules, somatic gene mutations, and anticancer drug sensitivity were analysed. Finally, we used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to validate the 5-NRLs.

RESULTS

A 5-NRL signature was established to predict the prognosis of PC, including LINC00857, AL672291.1, PTPRN2-AS1, AC141930.2, and MEG9. The 5-NRL signature demonstrated a high degree of predictive power according to ROC and Kaplan‒Meier curves and was revealed to be an independent prognostic risk factor via stratified survival analysis. Nomogram and calibration curves indicated the clinical adaptability of the signature. Immune-related pathways were linked to the 5-NRL signature according to enrichment analysis. Additionally, immune cell infiltration, immune checkpoint molecules, somatic gene mutations and the half-maximal inhibitory concentration (IC50) of chemotherapeutic agents were significantly different between the two risk subgroups. These results suggested that our model can be used to evaluate the effectiveness of immunotherapy and chemotherapy, providing a potential new strategy for treating PC.

CONCLUSIONS

The novel 5-NRL signature is helpful for assessing the prognosis of PC patients and improving therapy options, so it can be further applied clinically.

Comprehensive analysis of the basement membrane in lung adenocarcinoma by bulk and single-cell sequencing analysis

Background: The basement membrane (BM), as a critical component of the extracellular matrix, plays a role in cancer progression. However, the role of the BM in lung adenocarcinoma (LUAD) remains unclear. Methods: A total of 1383 patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts were enrolled in the study, and BM-related differentially expressed genes (BM-DEGs) were screened using weighted gene coexpression network analysis (WGCNA) and differential expression analysis. We next built a prognostic model using Cox regression analysis and separated patients into two groups based on the median risk score. This signature was validated with in vitro experiments, and its mechanism was investigated by enrichment and tumour microenvironment analyses. We also evaluated whether this signature could predict sensitivity to chemotherapy and immunotherapy. Finally, single-cell RNA sequencing analysis was utilized to analyse the expression of signature genes in different cells. Results: Thirsty-seven BM-DEGs were discovered, and a prognostic signature based on 4 BM-DEGs (HMCN2, FBLN5, ADAMTS15 and LAD1) was obtained in the TCGA cohort and validated in GEO cohorts. Survival curves and ROC curve analysis demonstrated that the risk score was a significant predictor of survival in all cohorts even when considering the effect of other clinical indexes. Low-risk patients had longer survival times, higher immune cell infiltration levels and better immunotherapeutic responses. Single-cell analysis showed that FBLN5 and LAD1 were overexpressed in fibroblasts and cancer cells, respectively, compared to normal cells. Conclusion: This study evaluated the clinical role of the BM in LUAD and primarily explored its mechanism.

Development of a necroptosis-related gene signature and the immune landscape in ovarian cancer

BACKGROUND

Necroptosis is a novel type of programmed cell death distinct from apoptosis. However, the role of necroptosis in ovarian cancer (OC) remains unclear. The present study investigated the prognostic value of necroptosis-related genes (NRGs) and the immune landscape in OC.

METHODS

The gene expression profiling and clinical information were downloaded from the TCGA and GTEx databases. Differentially expressed NRGs (DE-NRGs) between OC and normal tissueswere identified. The regression analyses were conducted to screen the prognostic NRGs and construct the predictive risk model. Patients were then divided into high- and low-risk groups, and the GO and KEGG analyses were performed to explore bioinformatics functions between the two groups. Subsequently, the risk level and immune status correlations were assessed through the ESTIMATE and CIBERSORT algorithms. The tumor mutation burden (TMB) and the drug sensitivity were also analyzed based on the two-NRG signature in OC.

RESULTS

Totally 42 DE-NRGs were identified in OC. The regression analyses screened out two NRGs (MAPK10 and STAT4) with prognostic values for overall survival. The ROC curve showed a better predictive ability in five-year OS using the risk score. Immune-related functions were significantly enriched in the high- and low-risk group. Macrophages M1, T cells CD4 memory activated, T cells CD8, and T cells regulatory infiltration immune cells were associated with the low-risk score. The lower tumor microenvironment score was demonstrated in the high-risk group. Patients with lower TMB in the low-risk group showed a better prognosis, and a lower TIDE score suggested a better immune checkpoint inhibitor response in the high-risk group. Besides, cisplatin and paclitaxel were found to be more sensitive in the low-risk group.

CONCLUSIONS

MAPK10 and STAT4 can be important prognosis factors in OC, and the two-gene signature performs well in predicting survival outcomes. Our study provided novel ways of OC prognosis estimation and potential treatment strategy.

A novel prognostic signature for clear cell renal cell carcinoma constructed using necroptosis-related miRNAs

Background

This work aims to analyze the relationship between necroptosis-related microRNAs (miRNAs) and the prognosis of clear cell renal cell carcinoma (ccRCC).

Methods

The miRNAs expression profiles of ccRCC and normal renal tissues from The Cancer Genome Atlas (TCGA) database were used to construct a matrix of the 13 necroptosis-related miRNAs. Cox regression analysis was used to construct a signature to predict the overall survival of ccRCC patients. The genes targeted by the necroptosis-related miRNAs in the prognostic signature were predicted using miRNA databases. Gene Ontology (Go) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to investigate the genes targeted by the necroptosis-related miRNAs. The expression levels of selected miRNAs in 15 paired samples (of ccRCC tissues and adjacent normal renal tissues) were investigated using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR).

Results

Six necroptosis-related miRNAs were found to differentially expressed between ccRCC and normal renal tissues. A prognostic signature consisting of miR-223-3p, miR-200a-5p, and miR-500a-3p was constructed using Cox regression analysis and risk scores were calculated. Multivariate Cox regression analysis showed that the hazard ratio was 2.0315 (1.2627–3.2685, P = 0.0035), indicating that the risk score of the signature was an independent risk factor. The receiver operating characteristic (ROC) curve showed that the signature has a favorable predictive capacity and the Kaplan-Meier survival analysis indicated that ccRCC patients with higher risk scores had worse prognoses (P < 0.001). The results of the RT-qPCR verified that all three miRNAs used in the signature were differentially expressed between ccRCC and normal tissues (P < 0.05).

Conclusion

The three necroptosis-related-miRNAs used in this study could be a valuable signature for the prognosis of ccRCC patients. Necroptosis-related miRNAs should be further explored as prognostic indicators for ccRCC.

Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes

Lung adenocarcinoma (LUAD) is the most widely known histological subtype of lung cancer. Its classification is significant for the characteristic evaluation of patients. The aim of this research is to assess the categorization of LUAD and its risk model based on necroptosis and to investigate its potential regulatory mechanisms for diagnosing and treating LUAD. According to the expression profile data along with the clinical information related to LUAD from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we constructed a consistency matrix through consistency clustering, and used the ConsensusClusterPlus as the measurement distance to cluster and subtype the samples, and performed gene set enrichment analysis and immune infiltration analysis. Least absolute shrinkage and selection operator (Lasso) regression was utilized for obtaining prognostic significant necroptosis phenotype-related genes. Finally, we measured each patient's riskscore (RS) and build a risk model, and predicted the effect of immunotherapy for different groups of risk factors in the model. Three molecular subtypes of LUAD were obtained by cluster analysis of necroptosis-related genes in LUAD samples. Compared with C1, C3 had a better prognosis and higher immune cell infiltration. The prognosis of the C1 subtype was poor and had a high clinical grade. The proportion of Stage II, Stage III, and Stage IV was much more in comparison with that of the other two subtypes. TP53 gene had a high mutation frequency in the C1 subtype. Gene Set Enrichment Analysis (GSEA) indicated that the aberrant pathways in the C1 and C3 subtypes mainly included some cell cycle-related pathways. In addition, seven genes were identified as related genes of necroptosis phenotype affecting prognosis. High RS had a poor prognosis, while low RS had a good prognosis. The RS was verified to have a strong ability to predict survival. LUAD can be classified by the genes linked with cell necrosis and apoptosis. The difference among various types is helpful to deepen the understanding of LUAD. In addition, a risk model was constructed based. In conclusion, this study provides potential detection targets and treatment methods for LUAD from a new perspective.

Identification of a novel necroptosis-associated miRNA signature for predicting the prognosis in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is one of the most aggressive malignancies that have a poor prognosis. Necroptosis has been demonstrated in recent years to be a form of inflammatory cell death occurring in multicellular organism, which plays complex roles in cancer. However, the expression of necroptosis-related miRNAs and genes in HNSCC and their correlations with prognosis remain unclear. In this study, R software was used to screen differentially expressed miRNAs downloaded from The Cancer Genome Atlas. A prognostic model containing six necroptosis-related miRNAs (miR-141-3p, miR-148a-3p, miR-331-3p, miR-543, miR-425-5p, and miR-7-5p) was generated, whose risk score was validated as an independent prognostic factor for HNSCC. Target genes of the key miRNAs were obtained from TargetScan, miRDB, and miRTarBase, and 193 genes in the intersection of the three databases were defined as consensus genes. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses indicated that the composition of the tumor microenvironment as well as specific pathways may be closely related to necroptosis in HNSCC. Nine key genes were also obtained by the MCODE and cytoHubba plug-ins of Cytoscape: PIK3CD, NRAS, PTK2, IRS2, IRS1, PARP1, KLF4, SMAD2, and DNMT1. A prognostic model formed by the key gene was also established, which can efficiently predict the overall survival of HNSCC patients. In conclusion, necroptosis-related miRNAs and genes play important roles in tumor development and metastasis and can be used to predict the prognosis of HNSCC.

Transcription factor Nrf2 binds to circRNAPIBF1 to regulate SOD2 in lung adenocarcinoma progression

Emerging evidence indicates that circular RNAs (circRNAs) play important roles in disease development, especially in cancers. Analysis of circRNA expression microarrays from the Gene Expression Omnibus database revealed that circPIBF1 was highly upregulated in lung adenocarcinoma (LUAD). The main aim of this study was to probe the function of circPIBF1 in pyroptosis of LUAD cells and the signal transduction pathways involved. CircPIBF1 was significantly overexpressed in LUAD and was related to the dismal prognosis of patients with LUAD. CircPIBF1 could bind to nuclear factor erythroid 2-related factor 2 (Nrf2), which further promoted the expression of superoxide dismutase 2 (SOD2). In addition, Nrf2 was also observed to recruit histone acetyltransferase E1A binding protein p300 (EP300) to enhance H3K27ac modification of SOD2, thus modulating the Nrf2-Keap1 signaling pathway. Moreover, we found that knockdown of circPIBF1 significantly suppressed the expression of SOD2 in cells and LUAD cell growth, while enhanced the expression of pyroptosis-related factors, which were further reversed by overexpression of SOD2 or EP300. Collectively, our findings suggest a direct involvement of circPIBF1 in pyroptosis-related LUAD carcinogenesis and implicate a role of Nrf2/EP300/SOD2 signaling in this process.

Pan-cancer analysis of a novel indicator of necroptosis with its application in human cancer

As a type of programmed cell death, necroptosis is thought to play a dual role in tumorigenesis. However, a comprehensive assessment of necroptosis-related regulators across human cancers has not been reported. Therefore, in this study, we established a quantitative index to evaluate the necroptosis rate and determine its correlations with clinical prognosis, signaling pathways and molecular features, immune cell infiltration and regulation, immunotherapy, and chemotherapy sensitivity across cancers. Our results indicated that the necroptosis score can act as a favorable or risky prognostic factor in various cancer types. A gene set variation analysis suggested that necroptosis is significantly associated with immune- and inflammation-related signaling pathways, cell growth and apoptosis, and energy metabolism. Furthermore, necroptosis can affect the tumor microenvironment and immunity regulation, and the effect of necroptosis on immunity is different in different tumor types. There is crosstalk between components of necroptosis, pyroptosis, ferroptosis and autophagy pathways in multiple types of cancers. Finally, the necroptosis rate can be an indicator of immunotherapy effectiveness in multiple cancers and can affect the chemotherapy sensitivity of cancer cells. Our study presents a characterization of necroptosis across human cancers, highlights the potential necroptotic effects on immune regulation, and provides new insights into the development of individualized tumor treatments and clinical applications of immunotherapy.

A Novel-Defined Necroptosis-Related miRNA Signature for Forecasting the Prognosis of Low-Grade Glioma

Background

Increasing evidence has shown that necroptosis has enormous significance in the generation and deterioration of cancer, and miRNA molecular markers involved in necroptosis in low-grade gliomas (LGGs) have not been thoroughly reported.

Methods

Using the miRNA data of 512 samples from The Cancer Genome Atlas (TCGA), 689 miRNAs from LGG samples were split into high immunity score and low immunity score groups for analysis. The differential miRNAs related to necroptosis were analyzed by univariate Cox regression analysis. On the basis of the outcome of univariate Cox regression analysis, miRNAs with significant differences were selected to construct a multivariate Cox regression model and calculate the risk score. Then, we evaluated whether the risk score could be used as an unaided prognostic factor.

Results

Overall, six differential miRNAs were identified (hsa-miR-148a-3p, hsa-miR-141-3p, hsa-miR-223-3p, hsa-miR-7-5p, hsa-miR-500a-3p, and hsa-miR-200a-5p). Univariate and multivariate Cox regression analyses were performed, and the c index was 0.71. Then, by mixing the risk score with clinicopathological factors, univariate Cox regression (HR: 2.7146, 95% CI: 1.8402−4.0044, P < 0.0001) and multivariate Cox regression analyses (HR: 2.3280, 95% CI: 1.5692−3.4536, P < 0.001) were performed. The data suggested that the risk score is an unaided prognostic indicator, which is markedly related with the overall survival time of LGG sufferers. Thus, a lower risk score is correlated with better prediction of LGG.

Conclusion

In order to achieve the ultimate goal of improving the living conditions of patients, we established prognostic risk model using 6 miRNAs related to necroptosis, which has the ability to predict the prognosis of LGG. It is possible to further enrich the therapeutic targets for LGG and provide clinical guidance for the treatment of LGG in the future.

Identification of Necroptosis-Related miRNA Signature as a Potential Predictive Biomarker for Prognosis and Immune Status in Colon Adenocarcinoma

Objective

Increasing studies suggest that necroptosis is correlated with tumor progression. And aberrant microRNA (miRNA) expression plays a vital role in various tumors. Thus, we are committed to exploring a necroptosis-associated miRNA signature to serve as a prognostic biomarker in colon adenocarcinoma (COAD). Data Sources and Methods. In the current study, The Cancer Genome Atlas (TCGA) database was used to download the miRNA and mRNA expression profiles and clinical information of samples. All patients were stochastically assigned to TCGA-train and TCGA-test clusters. Subsequently, we established a prognostic signature comprised of necroptosis-related miRNAs (NR-mis) via LASSO-Cox regression and then developed a nomogram signature composed of the prognostic signature and clinical factors. Corresponding prognostic values were evaluated. Functional analysis, tumor microenvironment (TME), and chemosensitivity of risk subgroups were also identified.

Results

The prognostic signature based on miR-141-3p, miR-148a-3p, miR-16-5p, and miR-200a-5p was closely associated with overall survival (OS) of samples and tumor metastasis in COAD. The Area Under Curve (AUC) was 0.605, 0.721, and 0.752 in TCGA-train cluster , 0.661, 0.613, and 0.695 in the TCGA-test cluster at 1, 3, and 5 years, respectively. The C-index for nomogram signature was 0.754. Functional analysis showed the remarkable enrichment of the signature-dependent miRNAs in tumor progression and immune response. And two risk subgroups were correlated with the distinct immune infiltration and immune checkpoints. In addition, the high-risk subgroup is more sensitive to cisplatin, doxorubicin, etoposide, and gemcitabine.

Conclusions

Necroptosis-related miRNAs play a crucial role in the prognosis, metastasis, immune status, and drug sensitivity in COAD.

Classical epithelial-mesenchymal transition (EMT) and alternative cell death process-driven blebbishield metastatic-witch (BMW) pathways to cancer metastasis

Metastasis is a pivotal event that accelerates the prognosis of cancer patients towards mortality. Therapies that aim to induce cell death in metastatic cells require a more detailed understanding of the metastasis for better mitigation. Towards this goal, we discuss the details of two distinct but overlapping pathways of metastasis: a classical reversible epithelial-to-mesenchymal transition (hybrid-EMT)-driven transport pathway and an alternative cell death process-driven blebbishield metastatic-witch (BMW) transport pathway involving reversible cell death process. The knowledge about the EMT and BMW pathways is important for the therapy of metastatic cancers as these pathways confer drug resistance coupled to immune evasion/suppression. We initially discuss the EMT pathway and compare it with the BMW pathway in the contexts of coordinated oncogenic, metabolic, immunologic, and cell biological events that drive metastasis. In particular, we discuss how the cell death environment involving apoptosis, ferroptosis, necroptosis, and NETosis in BMW or EMT pathways recruits immune cells, fuses with it, migrates, permeabilizes vasculature, and settles at distant sites to establish metastasis. Finally, we discuss the therapeutic targets that are common to both EMT and BMW pathways.

Ferroptosis, necroptosis, and pyroptosis in the occurrence and development of ovarian cancer

Ovarian cancer (OC) is one of the most common malignancies that causes death in women and is a heterogeneous disease with complex molecular and genetic changes. Because of the relatively high recurrence rate of OC, it is crucial to understand the associated mechanisms of drug resistance and to discover potential target for rational targeted therapy. Cell death is a genetically determined process. Active and orderly cell death is prevalent during the development of living organisms and plays a critical role in regulating life homeostasis. Ferroptosis, a novel type of cell death discovered in recent years, is distinct from apoptosis and necrosis and is mainly caused by the imbalance between the production and degradation of intracellular lipid reactive oxygen species triggered by increased iron content. Necroptosis is a regulated non-cysteine protease–dependent programmed cell necrosis, morphologically exhibiting the same features as necrosis and occurring via a unique mechanism of programmed cell death different from the apoptotic signaling pathway. Pyroptosis is a form of programmed cell death that is characterized by the formation of membrane pores and subsequent cell lysis as well as release of pro-inflammatory cell contents mediated by the abscisin family. Studies have shown that ferroptosis, necroptosis, and pyroptosis are involved in the development and progression of a variety of diseases, including tumors. In this review, we summarized the recent advances in ferroptosis, necroptosis, and pyroptosis in the occurrence, development, and therapeutic potential of OC.

Ferroptosis in Glioma Immune Microenvironment: Opportunity and Challenge

Glioma is the most common intracranial malignant tumor in adults and the 5-year survival rate of glioma patients is extremely poor, even in patients who received Stupp treatment after diagnosis and this forces us to explore more efficient clinical strategies. At this time, immunotherapy shows great potential in a variety of tumor clinical treatments, however, its clinical effect in glioma is limited because of tumor immune privilege which was induced by the glioma immunosuppressive microenvironment, so remodeling the immunosuppressive microenvironment is a practical way to eliminate glioma immunotherapy resistance. Recently, increasing studies have confirmed that ferroptosis, a new form of cell death, plays an important role in tumor progression and immune microenvironment and the crosstalk between ferroptosis and tumor immune microenvironment attracts much attention. This work summarizes the progress studies of ferroptosis in the glioma immune microenvironment.

A Newly Established Cuproptosis-Associated Long Non-Coding RNA Signature for Predicting Prognosis and Indicating Immune Microenvironment Features in Soft Tissue Sarcoma

Cuproptosis, a new type of programmed cell death, is involved in the development and progression of malignancies. The study of cuproptosis-associated long non-coding RNAs (lncRNAs) in soft tissue sarcomas (STSs) is however limited. There is also uncertainty regarding the prognostic accuracy of cuproptosis-associated lncRNAs in STSs and their relationship to the tumor immune microenvironment. The aim of this study was to determine the prognostic significance of cuprotosis-associated lncRNAs in STSs and their relationship to the tumor immune microenvironment. Transcriptomic and clinical data from patients with STSs were obtained through The Cancer Genome Atlas (TCGA). Overall, 259 patients were randomly allocated to a training group or a testing group. In the training group, a cuproptosis-associated lncRNA signature was constructed, and the signature was verified in the testing group. On the basis of risk scores and clinical features, we later developed a hybrid nomogram. We also performed functional and tumor immune microenvironment analysis based on the cuproptosis-associated lncRNA signature. A signature of 5 cuproptosis-associated lncRNAs was created. Based on this signature, we categorized STS patients into high-risk and low-risk groups. The study showed that patients at high risk had a worse prognosis than those at low risk. A nomogram was then constructed combining clinical characteristics with the risk scores, and it was shown to have credible predictive power. Functional enrichment and tumor immune microenvironmental analyses showed that high-risk STSs tend to be immunologically sensitive tumors. In our study, we found a cuproptosis-associated lncRNAs signature, which serves as an independent prognostic indicator. Cuproptosis-associated lncRNAs may play a role in the tumor immune microenvironment, which might be a therapeutic target for patients with STSs.

Targeting Ferroptosis Pathway to Combat Therapy Resistance and Metastasis of Cancer

Ferroptosis is an iron-dependent regulated form of cell death caused by excessive lipid peroxidation. This form of cell death differed from known forms of cell death in morphological and biochemical features such as apoptosis, necrosis, and autophagy. Cancer cells require higher levels of iron to survive, which makes them highly susceptible to ferroptosis. Therefore, it was found to be closely related to the progression, treatment response, and metastasis of various cancer types. Numerous studies have found that the ferroptosis pathway is closely related to drug resistance and metastasis of cancer. Some cancer cells reduce their susceptibility to ferroptosis by downregulating the ferroptosis pathway, resulting in resistance to anticancer therapy. Induction of ferroptosis restores the sensitivity of drug-resistant cancer cells to standard treatments. Cancer cells that are resistant to conventional therapies or have a high propensity to metastasize might be particularly susceptible to ferroptosis. Some biological processes and cellular components, such as epithelial–mesenchymal transition (EMT) and noncoding RNAs, can influence cancer metastasis by regulating ferroptosis. Therefore, targeting ferroptosis may help suppress cancer metastasis. Those progresses revealed the importance of ferroptosis in cancer, In order to provide the detailed molecular mechanisms of ferroptosis in regulating therapy resistance and metastasis and strategies to overcome these barriers are not fully understood, we described the key molecular mechanisms of ferroptosis and its interaction with signaling pathways related to therapy resistance and metastasis. Furthermore, we summarized strategies for reversing resistance to targeted therapy, chemotherapy, radiotherapy, and immunotherapy and inhibiting cancer metastasis by modulating ferroptosis. Understanding the comprehensive regulatory mechanisms and signaling pathways of ferroptosis in cancer can provide new insights to enhance the efficacy of anticancer drugs, overcome drug resistance, and inhibit cancer metastasis.

Prediction of Necroptosis-Related Markers in Head and Neck Carcinoma by Bioinformatics

Necroptosis is a form of programmed cell death that has recently been shown to be important in the progression of head and neck cancer (HNC). Noncoding RNAs (ncRNAs) are known to function in cell death and tumor formation. In this study, we focused on microRNAs (miRNA) that play roles in necroptosis and the progression of HNC. We collected miRNA expression data, related clinical data of patients with HNC, and miRNA data related to necroptosis. A prognostic multimiRNA molecular marker was generated based on differential expression analysis and univariate and multivariate Cox regression analyses. Target genes of the prognosis-related miRNAs were identified, and their functions were evaluated by Gene Ontology Enrichment Analysis to reveal the processes the miRNAs may be involved in. Eight potentially prognostic miRNAs were identified through differential expression analysis: miR-331-3p, miR-181d-5p, miR-181b-5p, miR-500a-3p, miR-425-5p, miR-181a-5p, miR-141-3p, and miR-200a-5p. Multivariate Cox regression identified the risk score as an independent prognostic factor (univariate Cox regression results: hazard ratio (HR): 2.2028, 95% confidence interval (CI): 1.2640–3.8388, P = 0.0053; multivariate Cox regression results: HR: 2.4168, 95% CI: 1.3743–4.2501, P = 0.0022). Survival curve analysis revealed that patients with a high risk score had a bad prognosis (P = 0.0109). A receiver operating characteristic curve showed that the model has a certain prediction ability. We identified 187 miRNA-related genes, which were enriched in “cell cycle” and “cellular senescence.” In conclusion, this study identified eight novel miRNA markers for predicting the prognosis of patients with HNC and paved the way for future research on necroptosis-related genes.

Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer

Endometrial cancer (EC) is the gynecological tumor with the highest incidence. In recent years, it has been proved that necroptosis is a method of cell death related to EC. However, the expression of necroptosis-related miRNA in EC and its correlation with prognosis still ill-defined. Use the Cancer Genome Atlas (TCGA) cohort to obtain prognostic data and related clinical data for ECs and normal endometrium tissues. In this study, we identified three necroptotic regulatory miRNAs that are necroptosis-related and survival-related miRNAs (DENSMs) between normal endometrium tissues and EC from 13 necroptosis-related miRNAs. The three DENSMs signature was built to develop prognostic model and classified all EC patients into a high or low risk group. EC patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (p = 0.0242), and the risk score was found to be an independent prognosis factor for predicting the OS of EC patients (p = 0.0254) in multivariate Cox regression. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed dephosphorylation, microtubule, protein serine/threonine kinase activity, PI3K-Akt signaling pathway and MAPK signaling pathway are closely related to it. In conclusion, the risk prediction model based on necroptosis-related miRNAs can effectively predict the prognosis of EC patients.

LncRNA MNX1-AS1: A novel oncogenic propellant in cancers

To date, recent studies have shown that long non-coding RNAs (lncRNAs) are key players in gene regulation processes involved in cancer pathogenesis. In general, Motor neuron and pancreas homeobox 1-antisense RNA1 (MNX1-AS1) is highly expressed in all cancers as reported so far and exerts oncogenic effects through different mechanisms. In this review, we comprehensively summarize the detailed mechanisms of potential functions of MNX1-AS1 in different cancer types as well as the latest knowledge highlighting the potential of MNX1-AS1 as a therapeutic target for cancer. Aberrant expression of MNX1-AS1 closely correlates with clinicopathological parameters. such as lymphatic metastasis, tumor size, tumor stage, OS and DFS. Thus, MNX1-AS1 can be used as a diagnostic and prognostic biomarker or even a therapeutic prognostic target. This article reviews its function, molecular mechanism and clinical prognosis in various malignancies.

Deciphering a Novel Necroptosis-Related miRNA Signature for Predicting the Prognosis of Clear Cell Renal Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common histological and devastating subtype of renal cell carcinoma. Necroptosis is a form of programmed cell death that causes prominent inflammatory responses. miRNAs play a significant role in cancer progression through necroptosis. However, the prognostic value of necroptosis-related miRNAs remains ambiguous. In this study, 39 necroptosis-related miRNAs (NRMs) were extracted and 17 differentially expressed NRMs between normal and tumor samples were identified using data form The Cancer Genome Atlas (TCGA). After applying univariate Cox proportional hazard regression analysis and LASSO Cox regression model, six necroptosis-related miRNA signatures were identified in the training cohort and their expression levels were verified by qRT-PCR. Using the expression levels of these miRNAs, all patients were divided into the high- and low-risk groups. Patients in the high-risk group showed poor overall survival (P < 0.0001). Time-dependent ROC curves confirmed the good performance of our signature. The results were verified in the testing cohort and the entire TCGA cohort. Univariate and multivariate Cox regression models demonstrated that the risk score was an independent prognostic factor. Additionally, a predictive nomogram with good performance was constructed to enhance the implementation of the constructed signature in a clinical setting. We then employed miRBD, miRTarBase, and TargetScan to predict the target genes of six necroptosis-related miRNAs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that 392 potential target genes were enriched in cell proliferation-related biological processes. Six miRNAs and 59 differentially expressed target genes were used to construct an miRNA–mRNA interaction network, and 11 hub genes were selected for survival and tumor infiltration analysis. Drug sensitivity analysis revealed potential drugs that may contribute to cancer management. Hence, necroptosis-related genes play an important role in cancer biology. We developed, for the first time, a necroptosis-related miRNA signature to predict ccRCC prognosis.

Construction of a Necroptosis-Related miRNA Signature for Predicting the Prognosis of Patients With Hepatocellular Carcinoma

Background: Many miRNAs have been demonstrated to be associated with the prognosis of hepatocellular carcinoma (HCC). However, how to combine necroptosis-related miRNAs to achieve the best predictive effect in estimating HCC patient survival has not been explored.

Methods: The mRNA and miRNA expression profile were downloaded from a public database (TCGA-LIHC cohort). Necroptosis-related genes were obtained from previous references, and necroptosis-related miRNAs were identified using Pearson analysis. Subsequently, differential expression miRNAs (DEms) were identified in HCC and paracancer normal samples based on necroptosis-related miRNA expression. The whole set with HCC was randomized into a training set and testing set (1:1). LASSO-Cox regression analysis was used to construct an miRNA signature. Multiple statistical methods were used to validate the clinical benefit of signature in HCC patients, including receiver operator characteristic (ROC) curves, Kaplan–Meier survival analyses, and decision curve analysis (DCA). The downstream target genes of miRNAs were obtained from different online tools, and the potential pathways involved in miRNAs were explored. Finally, we conducted RT-qPCR in SK-HEP-1, THLE-3, and HUH-7 cell lines for miRNAs involved in the signature.

Results: The results showed that a total of eight specific necroptosis-related miRNAs were screened between HCC and adjacent tissues in the training set. Subsequently, based on the aforementioned miRNAs, 5-miRNA signature (miR-139-5p, hsa-miR-326, miR-10b-5p, miR-500a-3p, and miR-592) was generated by LASSO-Cox regression analysis. Multivariate Cox regression analysis showed that the risk scores were independent prognostic indicators in each set. The area under curves (AUCs) of 1 year, 3 years, 5 years, and 7 years were high in each set (AUC >0.7). DCA analysis also revealed that the risk score had a potential benefit than other clinical characteristics. Meanwhile, survival analysis showed that the high-risk group showed low survival probabilities. Moreover, the results of enrichment analysis showed that specific miRNAs were mainly enriched in the cAMP signaling pathway and TNF signaling pathway. Finally, the results of RT-qPCR were consistent with the prediction results in public databases.

Conclusion: Our study establishes a robust tool based on 5-necroptosis-related miRNAs for the prognostic management of HCC patients.

Regulation of apoptosis, autophagy and ferroptosis by non‑coding RNAs in metastatic non‑small cell lung cancer (Review)

Non-small cell lung cancer (NSCLC), a common type of cancer worldwide, is normally associated with a poor prognosis. It is difficult to treat successfully as it often metastasizes into brain or bone. Methods to facilitate the induction of effective programmed cell death (PCD) in NSCLC cells to reverse drug resistance, or to inhibit the invasion and migration of NSCLC cells, are currently under investigation. The present study summarized the regulatory functions of PCD, including apoptosis, autophagy and ferroptosis, in the context of NSCLC metastasis. It further summarized how regulatory agents, including long non-coding RNAs, circular RNAs and microRNAs, regulate PCD during the metastasis of NSCLC and characterized new potential diagnostic biomarkers of NSCLC metastasis.

A Novel Necroptosis-Related miRNA Signature for Predicting the Prognosis of Breast Cancer Metastasis

Objective

Necroptosis was recently identified as a form of programmed cell death that plays an essential role in breast cancer metastasis. MicroRNAs (miRNAs) have long been recognized to affect cell death and tumor growth. In this study, we aimed to screen for necroptosis-associated miRNAs that predict breast cancer metastasis.

Method

This study used The Cancer Genome Atlas (TCGA) public database to obtain miRNA expression data and associated clinical data from breast cancer patients and then retrieved miRNA data related to necrosis and apoptosis. Next, using Cox regression model analysis (univariate or multivariate) as well as a comparison analysis (differential analysis), a prognostic multi-miRNA molecular marker was established. Finally, prognosis-related miRNAs were utilized to identify target genes, and the functions of the target genes were analyzed for enrichment to investigate the probable mechanisms of the miRNAs.

Results

Ten miRNAs were screened through differential analysis to build models: hsa-miR-148a-3p, hsa-miR-223-3p, hsa-miR-331-3p, has-miR-181a-5p, hsa-miR-181b-5p, hsa-miR-181c-5p, hsa-miR-181d-5p, hsa-miR-200a-5p, hsa-miR-141-3p, and hsa-miR-425-5p. The multivariate Cox regression model was an independent prognostic factor (univariate Cox regression results: HR = 3.2642, 95%CI = 1.5773 − 6.7554, P = 0.0014; multivariate Cox regression results: HR = 3.1578, 95%CI = 1.5083 − 6, P = 0.0023). The survival curve of the risk score also revealed that patients with a high risk score had a poor prognosis (P = 2e − 04). The receiver operating characteristic (ROC) curve showed that the model has a certain prediction ability. Batch survival analysis of the miRNAs in the model was conducted and showed that hsa-miR-331-3p (P = 0.0182) was strongly associated with prognosis. Twenty-three predicted target genes were obtained, and Gene Ontology (GO) enrichment analysis showed that these target genes were strongly enriched in transcriptional initiation and cell membrane trafficking.

Conclusion

Our research identified a novel miRNA marker for predicting breast cancer patient prognosis and lays the groundwork for future research on necroptosis-related genes.

A Novel Prognostic Model Based on Seven Necroptosis-Related miRNAs for Predicting the Overall Survival of Patients with Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) remains one of the leading causes of cancer-related deaths worldwide. This study is aimed at constructing a risk scoring model based on necroptosis-related miRNAs to predict prognosis of LUAD. Expression profile of miRNA in LUAD was downloaded from The Cancer Genome Atlas (TCGA) database. We screened the differentially expressed necroptosis-related miRNAs between LUAD patients and normal samples, thus constructed a seven miRNA-based risk stratification on the basis of the TGCA cohort. This risk stratification was prove to be effective in predicting the overall survival (OS) of patients with LUAD. Furthermore, we constructed a nomogram model based on the combination of risk characteristics and clinicopathological features, which was also prove to be accurate and efficient in predicting OS of LUAD patients. Functional enrichment analyses on the targeted genes of these miRNAs with prognostic value were carried out. Results indicated that these targeted genes were closely related to the development and metastasis of tumors. In summary, our research has developed a prognostic model based on the expression of miRNAs related to necroptosis. This model might be used to predict the prognosis of LUAD accurately, which might be helpful in improving treatment efficacy of LUAD.

Pan-cancer analysis of necroptosis-related gene signature for the identification of prognosis and immune significance

BACKGROUND

Necroptosis is a novel programmed cell death mode independent on caspase. A number of studies have revealed that the induction of necroptosis could act as an alternative therapeutic strategy for drug-resistant tumors as well as affect tumor immune microenvironment.

METHODS

Gene expression profiles and clinical data were downloaded from XENA-UCSC (including The Cancer Genome Atlas and Genotype-Tissue Expression), Gene Expression Omnibus, International Cancer Genome Consortium and Chinese Glioma Genome Atlas. We used non-negative matrix factorization method to conduct tumor classification. The least absolute shrinkage and selection operator regression was applied to establish risk models, whose prognostic effectiveness was examined in both training and testing sets with Kaplan-Meier analysis, time-dependent receiver operating characteristic curves as well as uni- and multi-variate survival analysis. Principal Component Analysis, t-distributed Stochastic Neighbor Embedding and Uniform Manifold Approximation and Projection were conducted to check the risk group distribution. Gene Set Enrichment Analyses, immune infiltration analysis based on CIBERSORT, EPIC, MCPcounter, ssGSEA and ESTIMATE, gene mutation and drug sensitivity between the risk groups were also taken into consideration.

RESULTS

There were eight types of cancer with at least ten differentially expressed necroptosis-related genes which could influence patients' prognosis, namely, adrenocortical carcinoma (ACC), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), acute myeloid leukemia (LAML), brain lower grade glioma (LGG), pancreatic adenocarcinoma (PAAD), liver hepatocellular carcinoma (LIHC), skin cutaneous melanoma (SKCM) and thymoma (THYM). Patients could be divided into different clusters with distinct overall survival in all cancers above except for LIHC. The risk models could efficiently predict prognosis of ACC, LAML, LGG, LIHC, SKCM and THYM patients. LGG patients from high-risk group had a higher infiltration level of M2 macrophages and cancer-associated fibroblasts. There were more CD8+ T cells, Th1 cells and M1 macrophages in low-risk SKCM patients' tumor microenvironment. Gene mutation status and drug sensitivity are also different between low- and high-risk groups in the six cancers.

CONCLUSIONS

Necroptosis-related genes can predict clinical outcomes of ACC, LAML, LGG, LIHC, SKCM and THYM patients and help to distinguish immune infiltration status for LGG and SKCM.

m6A methylation is required for dihydroartemisinin to alleviate liver fibrosis by inducing ferroptosis in hepatic stellate cells

Activation of hepatic stellate cells (HSCs) is a central event in the development of liver fibrosis, and the elimination of activated HSCs is considered to be an effective anti-fibrotic strategy. Here, we report that dihydroartemisinin (DHA) prevented the activation of HSCs via ferroptosis pathway. Importantly, DHA treatment increased the level of autophagy in HSCs. The inhibition of autophagy by 3-MA dramatically abolished the DHA-induced ferroptosis in HSCs. Mechanistically, the up-regulated m⁶A modification is essential for the activation of autophagy by DHA through the reduction of fat mass and obesity-associated gene (FTO). Down-regulation of m⁶A modification by FTO overexpression could impair autophagy and the classical ferroptotic events. Interestingly, the m⁶A modification of BECN1 mRNA was evidently up-regulated compared with other autophagy-related genes. More importantly, YTHDF1 was identified as a key m⁶A reader protein for BECN1 mRNA stability, and knockdown of YTHDF1 could prevent DHA-induced HSC ferroptosis. Noteworthy, YTH domain was essential for YTHDF1 to prolong the half-life of BECN1 mRNA in DHA-induced HSC ferroptosis. In mice, DHA treatment alleviated liver fibrosis by triggering HSC ferroptosis. HSC-specific inhibition of m⁶A modification and autophagy could impair DHA-induced HSC ferroptosis in murine liver fibrosis. Overall, these results provided novel implications to reveal the molecular mechanism of DHA-induced ferroptosis, by which pointed to m⁶A modification-dependent ferroptosis as a potential target for the treatment of liver fibrosis.

Necroptosis-related lncRNA to establish novel prognostic signature and predict the immunotherapy response in breast cancer

Background

Necroptosis is a type of programmed cell death, and recent researches have showed that lncRNAs could regulate the process of necroptosis in multiple cancers. We tried to screen necroptosis‐related lncRNAs and investigate the immune landscape in breast cancer (BC).

Methods

The samples of breast normal and cancer tissue were acquired from TCGA and GTEx databases. A risk prognostic model was constructed based on the identified necroptosis‐related lncRNAs by Cox regression and least absolute shrinkage and selection operator (LASSO) method. Moreover, the forecast performance of this model was verified and accredited by synthetic approach. Subsequently, an accurate nomogram was constructed to predict the prognosis of BC patients. The biological differences were investigated through GO, GSEA, and immune analysis. The immunotherapy response was estimated through tumor mutation burden (TMB) and tumor immune dysfunction and exclusion (TIDE) score.

Results

A total of 251 necroptosis‐related lncRNAs were identified by differential coexpression analysis, and SH3BP5‐AS1, AC012073.1, AC120114.1, LINC00377, AL133467.1, AC036108.3, and AC020663.2 were involved in the risk model, which had an excellent concordance with the prediction. The pathway analyses showed that immune‐related pathways were relevant to the necroptosis‐related lncRNAs risk model. And the risk score was significantly correlated with immune cell infiltration, as well as the ESTIMATE score. Most notably, the patients of higher risk score were characterized with increased TMB and decreased TIDE score, indicating that these patients showed better immune checkpoint blockade response.

Conclusion

These findings were conducive to understand the function of necroptosis‐related lncRNAs in BC and provide a potential promising therapeutic strategy for BC.

Development and validation of Pyroptosis‑related lncRNAs prediction model for bladder cancer

Bladder cancer (BLCA) is one of the highly heterogeneous disorders accompanied by a poor prognosis. The present study aimed to construct a model based on pyroptosis-related long-stranded non-coding RNA (lncRNA) to evaluate the potential prognostic application in bladder cancer. The mRNA expression profiles of bladder cancer patients and corresponding clinical data were downloaded from the public database from The Cancer Genome Atlas (TCGA). Pyroptosis-related lncRNAs were identified by utilizing a co-expression network of pyroptosis-related genes and lncRNAs. The lncRNA was further screened by univariate Cox regression analysis. Finally, eight pyroptosis-related lncRNA markers were established using least absolute shrinkage and selection operator (Lasso) regression and multivariate Cox regression analyses. Patients were separated into high- and low-risk groups based on the performance value of the median risk score. Patients in the high-risk group had significantly poorer overall survival (OS) than those in the low-risk group (P<0.001). In multivariate Cox regression analysis, the risk score was an independent predictive factor of OS (HR > 1, P<0.01). The areas under the curve (AUCs) of the 3- and 5-year OS in the receiver operating characteristic (ROC) curve were 0.742 and 0.739, respectively. In conclusion, these eight pyroptosis-related lncRNA and their markers may be potential molecular markers and therapeutic targets for bladder cancer patients.

A Novel Defined Necroptosis-Related miRNAs Signature for Predicting the Prognosis of Colon Cancer

Objective

This study aims at exploring the relationship between necroptosis-related miRNAs and colon cancer prognosis.

Methods

We downloaded the miRNA sequencing data from the TCGA, and eight differentially expressed necroptosis-related miRNAs were screened. Then, we used Cox regression analysis to establish a prediction model of necroptosis-related miRNA. Finally, the prognosis related miRNAs were used to predict the target genes, and functional analysis was used to explore the potential mechanism of these target genes.

Results

The miRNA-seq data of 444 COAD cases were downloaded from TCGA. We identified 8 differentially expressed miRNAs (has-miR-16-5p, has-miR-141-3p, has-miR-148a-3p, has-miR-425-5p, has-miR-7-5p, has-miR-223-3p, has-miR-200a-5p, and has-miR-500a-3p), then Cox analysis was performed for determining eight-miRNA signature prognostic biomarkers with obviously different OS. The area under the curve (AUC) of receiver operating characteristic (ROC) curve for predicting 1-, 3-, and 5-year survival were 0.663, 0.653 and 0.639, respectively. The multivariate analysis also implied that the risk score was an independent prognostic factor considering other confounding factors (HR = 1.847, 95% CI = 1.197–2.848, P = 0.006). According to the Kaplan–Meier analysis, the expression of hsa-miR-500a-3p (P = 0.003), hsa-miR-16-5p (P = 0.004) and hsa-miR-148a-3p (P = 0.035) significantly affected OS outcomes. We predicted the target genes of these three miRNAs and then screened 10 hub genes (CCND1, SMAD3, SMAD2, CDK1, TGFB2, CDC25A, CHEK1, VEGFA, CCNE1, WEE1). In addition, CHEK1 was associated with the survival prognosis.

Conclusion

Our study demonstrated that necroptosis is closely associated with colon cancer, and the model of eight necroptosis-related miRNAs are potentially useful prognostic biomarkers and therapeutic targets for colon cancer.

Development of a novel necroptosis-associated miRNA risk signature to evaluate the prognosis of colon cancer patients

BACKGROUND

Necroptosis is a recently discovered caspase-independent form of cell death which plays an important role in the occurrence and development of cancer. As an important regulatory factor in necroptosis, microRNAs (miRNAs) are important for the development of colon cancer. This study established a novel necroptosis-related miRNA risk signature to evaluate the prognosis of patients with colon adenocarcinoma (COAD).

METHODS

The necroptosis-related miRNAs were selected by assessing the differential expression of miRNAs in 459 COAD patient samples and 8 control samples from The Cancer Genome Atlas (TCGA). Selection operator Cox analyses and survival analyses were used to establish the risk signature of 7 miRNAs related to necroptosis. Functional enrichment analysis and nomograms were used to explore the potential effects of necroptosis-related miRNAs on prognosis and metastasis. The target genes of the necroptosis-related miRNAs were predicted using online databases and the genes related to overall survival (OS) were screened.

RESULTS

The risk signature was based on 7 necroptosis-related miRNAs. Nomograms showed that the risk signature was effective at predicting the prognosis and TNM stage of COAD patients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that these miRNAs play an important role in cancer development, metastasis, and prognosis. A total of 38 target genes for these miRNAs were found to be associated with the OS in COAD patients.

CONCLUSIONS

This study provided novel evidence that necroptosis-related miRNAs are associated with the prognosis of COAD patients. A risk signature established based on these miRNAs could effectively predict the prognosis and metastasis of COAD in patients.