Receptor-interacting protein kinase 3 is a predictor of survival and plays a tumor suppressive role in colorectal cancer

Crosstalk among disulfidptosis-related lncRNAs in lung adenocarcinoma reveals a correlation with immune profile and clinical prognosis

Disulfidptosis refers to a specific programmed cell death process characterized by the accumulation of disulfides. It has recently been reported in several cancers. However, the impact of disulfidptosis-related long non-coding RNAs (lncRNAs) on malignant tumors has remained largely unknown. In the present work, we screened prognostic disulfidptosis-related lncRNAs and studied their effects on lung adenocarcinoma. Relevant clinical data of lung adenocarcinoma cases were retrieved from The Cancer Genome Atlas (TCGA) database. RNA sequencing was used to identify differentially expressed disulfidptosis-related lncRNAs within lung adenocarcinoma. In addition, prognostic disulfidptosis-related lncRNAs were obtained through univariate Cox regression analysis. LASSO-COX was used to construct new disulfidptosis-related lncRNA signatures. Different statistical approaches were used to validate the practicability and accuracy of the disulfidptosis-related lncRNAs signatures. Furthermore, several bioinformatic approaches were used to study relevant heterogeneities in biological processes and pathways of diverse risk groups. Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was conducted to analyze the expression of disulfidptosis-related lncRNAs. Finally, seven disulfidptosis-related lncRNA signatures were identified in lung adenocarcinoma cells. The prognosis prediction model constructed efficiently predicted patient survival. Subgroup analysis revealed significant differences in immune cell proportion, including T follicular helper cells and M0 macrophages. In addition, in vitro experimental results demonstrated significant differences in disulfidptosis-related lncRNAs. Altogether, the six disulfidptosis-related lncRNA signatures could serve as a potential prognostic biomarker for lung adenocarcinoma. Furthermore, these can be used as a prediction model in individualized immunotherapy for lung adenocarcinoma.

Inhibition of β2-adrenergic receptor regulates necroptosis in prostate cancer cell

As the malignant tumor with the highest incidence in male, prostate cancer poses a significant threat to the reproductive health of elderly men. Our previous studies have shown that promoting necroptosis of cancer cells can effectively inhibit cancer cell proliferation. This study includes lentivirus-mediated knockdown of β2AR which resulted in stable transfectants that exhibited an increased ability to form clones compared to that of the negative control group. In the protein and mRNA levels, necroptosis associated RIP and mixed lineage kinase domain-like (MLKL) were significantly higher in the treatment group than they were in the control group. Furthermore, cells treated with propranolol exhibited necrotic morphology as observed by transmission electron microscopy. The combination of β2AR suppression and necroptosis inhibitors resulted in a more potent suppression of cell proliferation compared to that observed in the control and negative control groups. Additionally, it elevated in the necrosis rate as determined by flow cytometry. Immunofluorescence staining revealed enhanced RIP and MLKL expression in the sh-β2AR group compared to levels in the negative control group. Co-immunoprecipitation experiments detected an interaction between β2AR and RIP. MLKL and RIPK3 levels were significantly higher in xenograft tumor sections from the sh-β2AR group compared to levels in the sh-NC group. To conclude, our research indicates the proliferation of PC-3 and DU-145 cprostate cancer cells can be suppressed by inhibiting β2AR, and this occurs through the RIP/MLKL-mediated pathway of necroptosis.

MLKL regulates radiation-induced death in breast cancer cells: an interplay between apoptotic and necroptotic signals

Resistance to caspase-dependent apoptosis is often responsible for treatments failure in cancer. Necroptosis is a type of programmed necrosis that occurs under caspase-deficient conditions that could overcome apoptosis resistance. Our purpose was to investigate the interrelationship between apoptotic and necroptotic death pathways and their influence on the response of breast cancer cells to radiotherapy in vitro. Human BC cell lines MCF-7 and MDA-MB-231 were treated with ionizing radiation, and then several markers of apoptosis, necroptosis, and survival were assessed in the presence and absence of necroptosis inhibition. MLKL knockdown was achieved by siRNA transfection. Our main findings emphasize the role of necroptosis in cellular response to radiation represented in the dose- and time-dependent elevated expression of necroptotic markers RIPK1, RIPK3, and MLKL. Knockdown of necroptotic marker MLKL by siRNA led to a significant elevation in MDA-MB-231 and MCF-7 survival with a dose modifying factor (DMF) of 1.23 and 1.61, respectively. Apoptotic markers Caspase 8 and TRADD showed transitory or delayed upregulation, indicating that apoptosis was not the main mechanism by which cells respond to radiation exposure. Apoptotic markers also showed a significant elevation following MLKL knockdown, suggesting its role either as a secondary or death alternative pathway. The result of our study emphasizes the critical role of the necroptotic pathway in regulating breast cancer cells responses to radiotherapy and suggests a promising utilization of its key modulator, MLKL, as a treatment strategy to improve the response to radiotherapy.

Recent advancements in nanomaterial-mediated ferroptosis-induced cancer therapy: Importance of molecular dynamics and novel strategies

Ferroptosis is a novel type of controlled cell death resulting from an imbalance between oxidative harm and protective mechanisms, demonstrating significant potential in combating cancer. It differs from other forms of cell death, such as apoptosis and necrosis. Molecular therapeutics have hard time playing the long-acting role of ferroptosis induction due to their limited water solubility, low cell targeting capacity, and quick metabolism in vivo. To this end, small molecule inducers based on biological factors have long been used as strategy to induce cell death. Research into ferroptosis and advancements in nanotechnology have led to the discovery that nanomaterials are superior to biological medications in triggering ferroptosis. Nanomaterials derived from iron can enhance ferroptosis induction by directly releasing large quantities of iron and increasing cell ROS levels. Moreover, utilizing nanomaterials to promote programmed cell death minimizes the probability of unfavorable effects induced by mutations in cancer-associated genes such as RAS and TP53. Taken together, this review summarizes the molecular mechanisms involved in ferroptosis along with the classification of ferroptosis induction. It also emphasized the importance of cell organelles in the control of ferroptosis in cancer therapy. The nanomaterials that trigger ferroptosis are categorized and explained. Iron-based and noniron-based nanomaterials with their characterization at the molecular and cellular levels have been explored, which will be useful for inducing ferroptosis that leads to reduced tumor growth. Within this framework, we offer a synopsis, which traverses the well-established mechanism of ferroptosis and offers practical suggestions for the design and therapeutic use of nanomaterials.

Necroptosis induced by ruthenium (II) complexes as mitochondrial disruptors

Inducing necroptosis in cancer cells has emerged as an effective strategy to overcome drug resistance. However, while organic small molecules have been extensively studied for this purpose, metal-based compounds have received relatively little attention as triggers of necroptosis. The development of ruthenium (II) hybrid compounds, particularly those containing triazene (Ru-TRZ), highlights a novel avenue for modulating necroptotic cell death. Here we show that incorporating a methyltriazene moiety, a known alkylating warhead, confers superior mitochondrial-targeting properties and enhances cell death compared to amide-containing counterparts. Ru-hybrid TRZ2 exhibits also antitumor efficacy against in vivo drug-resistant cancer cells. Mechanistically, we demonstrate that Ru-TRZ hybrids induce apoptosis. In addition, by activating downstream RIPK3-driven cell death, TRZ2 proficiently restrains normal mitochondrial function and activity, leading to cancer cell necroptosis. Finally, TRZ2 synergizes anti-proliferative activity and cell death effects induced by conventional drugs. In conclusion, Ru-TRZ2 stands as a promising ruthenium-based chemotherapeutic agent inducing necroptosis in drug resistant cancer cells.

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

Emerging role of immunogenic cell death in cancer immunotherapy

Cancer immunotherapy, such as immune checkpoint blockade (ICB), has emerged as a groundbreaking approach for effective cancer treatment. Despite its considerable potential, clinical studies have indicated that the current response rate to cancer immunotherapy is suboptimal, primarily attributed to low immunogenicity in certain types of malignant tumors. Immunogenic cell death (ICD) represents a form of regulated cell death (RCD) capable of enhancing tumor immunogenicity and activating tumor-specific innate and adaptive immune responses in immunocompetent hosts. Therefore, gaining a deeper understanding of ICD and its evolution is crucial for developing more effective cancer therapeutic strategies. This review focuses exclusively on both historical and recent discoveries related to ICD modes and their mechanistic insights, particularly within the context of cancer immunotherapy. Our recent findings are also highlighted, revealing a mode of ICD induction facilitated by atypical interferon (IFN)-stimulated genes (ISGs), including polo-like kinase 2 (PLK2), during hyperactive type I IFN signaling. The review concludes by discussing the therapeutic potential of ICD, with special attention to its relevance in both preclinical and clinical settings within the field of cancer immunotherapy.

Immunogenic cell death in cancer: targeting necroptosis to induce antitumour immunity

Most metastatic cancers remain incurable due to the emergence of apoptosis-resistant clones, fuelled by intratumour heterogeneity and tumour evolution. To improve treatment, therapies should not only kill cancer cells but also activate the immune system against the tumour to eliminate any residual cancer cells that survive treatment. While current cancer therapies rely heavily on apoptosis - a largely immunologically silent form of cell death - there is growing interest in harnessing immunogenic forms of cell death such as necroptosis. Unlike apoptosis, necroptosis generates second messengers that act on immune cells in the tumour microenvironment, alerting them of danger. This lytic form of cell death optimizes the provision of antigens and adjuvanticity for immune cells, potentially boosting anticancer treatment approaches by combining cellular suicide and immune response approaches. In this Review, we discuss the mechanisms of necroptosis and how it activates antigen-presenting cells, drives cross-priming of CD8+ T cells and induces antitumour immune responses. We also examine the opportunities and potential drawbacks of such strategies for exposing cancer cells to immunological attacks.

A guide to cell death pathways

Regulated cell death mediated by dedicated molecular machines, known as programmed cell death, plays important roles in health and disease. Apoptosis, necroptosis and pyroptosis are three such programmed cell death modalities. The caspase family of cysteine proteases serve as key regulators of programmed cell death. During apoptosis, a cascade of caspase activation mediates signal transduction and cellular destruction, whereas pyroptosis occurs when activated caspases cleave gasdermins, which can then form pores in the plasma membrane. Necroptosis, a form of caspase-independent programmed necrosis mediated by RIPK3 and MLKL, is inhibited by caspase-8-mediated cleavage of RIPK1. Disruption of cellular homeostatic mechanisms that are essential for cell survival, such as normal ionic and redox balance and lysosomal flux, can also induce cell death without invoking programmed cell death mechanisms. Excitotoxicity, ferroptosis and lysosomal cell death are examples of such cell death modes. In this Review, we provide an overview of the major cell death mechanisms, highlighting the latest insights into their complex regulation and execution, and their relevance to human diseases.

Unveiling NRlncRNAs as prognostic biomarkers and therapeutic targets for head-and-neck squamous cell carcinoma through machine learning

Head-and-neck squamous cell carcinoma (HNSCC) patients often exhibit insensitivity to immunotherapy, leading to treatment failure. Identifying potential biomarkers that can predict prognosis and improve the efficacy of treatment is crucial. In this study, we aimed to identify necroptosis-related long noncoding RNAs (NRlncRNAs) as potential therapeutic targets to improve the prognosis of HNSCC patients. By exploring the Genotype-Tissue Expression Project (GTEx) and the Cancer Genome Atlas (TCGA) databases, we identified NRlncRNAs and developed a risk model comprising 17 NRlncRNAs to predict the prognosis of HNSCC patients and to classify patients into two clusters based on their expression levels. We conducted various analyses, such as the Kaplan-Meier analysis, GSEA and IC50 prediction, to evaluate the differences in sensitivity to immunotherapy between the two clusters. Our findings suggest that NRlncRNAs have potential as therapeutic targets for improving the prognosis of HNSCC patients, and that individualized treatment approaches based on NRlncRNA expression levels can improve the sensitivity of immunotherapy and overall treatment outcomes. This study highlights new perspectives within clinical cancer informatics and provides insight into potential therapeutic strategies for HNSCC patients.

Construction of a necroptosis-related lncRNA signature for predicting prognosis and revealing the immune microenvironment in bladder cancer

BACKGROUND

Bladder cancer (BCa) is a common malignancy in the urinary system. Necroptosis, a recently discovered form of programmed cell death, is closely associated with the development and progression of various types of tumors. Targeting necroptosis through anti-cancer strategies has shown potential as a therapy for cancer. We aimed to develop a necroptosis-related lncRNAs (NRlncRNAs) risk model that can predict the survival and tumor immunity of BCa patients.

METHODS

We analyzed sequencing data obtained from the TCGA database, and applied least absolute shrinkage and selection operator (LASSO) and Cox regression analysis to identify crucial NRlncRNAs for building a risk model. Using the risk score, we categorized patients into high- and low-risk groups, and assessed the accuracy with the area under the receiver operating characteristic (AUROC) and Kaplan-Meier curves. We performed the RT-qPCR to detect the expression differences of the genes based on the risk model.

RESULTS

We identified a total of 296 NRlncRNAs, and 6 of them were included in the prognostic model. The AUC values for 1-, 3-, and 5-year predictions were 0.675, 0.726 and 0.734, respectively. Our risk model demonstrated excellent predictive performance and served as an independent predictor with high predictive power. Additionally, we performed PCA, TMB, GSEA analyses, and evaluated immune cell infiltration, to reveal significant differences between the high- and low-risk groups in functional signaling pathways, immunological status, and mutation profiles. Finally, we assessed the chemotherapeutic response of several drugs. According to the RT-qPCR results, we found that four NRlncRNAs of the risk model were more highly expressed in BCa cell lines than human immortalized uroepithelial cell line and regulated the occurrence and progression of bladder cancer.

CONCLUSION

We constructed a novel NRlncRNAs-associated risk model, which could predict the prognosis and immune response of BCa patients.

Regulated cell death in glioma: promising targets for natural small-molecule compounds

Gliomas are prevalent malignant tumors in adults, which can be categorized as either localized or diffuse gliomas. Glioblastoma is the most aggressive and deadliest form of glioma. Currently, there is no complete cure, and the median survival time is less than one year. The main mechanism of regulated cell death involves organisms coordinating the elimination of damaged cells at risk of tumor transformation or cells hijacked by microorganisms for pathogen replication. This process includes apoptosis, necroptosis, autophagy, ferroptosis, pyroptosis, necrosis, parthanayosis, entosis, lysosome-dependent death, NETosis, oxiptosis, alkaliptosis, and disulfidaptosis. The main goal of clinical oncology is to develop therapies that promote the effective elimination of cancer cells by regulating cell death are the main goal of clinical oncology. Recently, scientists have utilized pertinent regulatory factors and natural small-molecule compounds to induce regulated cell death for the treatment of gliomas. By analyzing the PubMed and Web of Science databases, this paper reviews the research progress on the regulation of cell death and the role of natural small-molecule compounds in glioma. The aim is to provide help for the treatment of glioblastoma.

Identification of a necroptosis-related gene signature for making clinical predictions of the survival of patients with lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a major pathological subtype of malignant lung cancer with a poor prognosis. Necroptosis is a caspase-independent programmed cell death mode that plays a pivotal role in cancer oncogenesis and metastasis. Here, we explore the prognostic values of different necroptosis-related genes (NRGs) in LUAD.

Methods

mRNA expression data and related clinical information for LUAD samples were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. NRGs were identified using the GeneCards database. Least absolute shrinkage and selection operator Cox regression and multivariate Cox analysis were used to construct a prognostic risk model. Time-dependent receiver-operating characteristic curves and a nomogram were constructed to validate the predictive values of the prognostic signatures. A necroptosis-related protein-protein interaction network was visualised using the STRING database and Cytoscape software. Functional analyses, including Gene Ontology, Kyoto Encyclopaedia of Genes and Genomes pathway enrichment, gene set enrichment, and gene set variation analyses, were conducted to explore the underlying molecular mechanisms. Finally, the mRNA expression of the prognostic signatures in LUAD cell lines was assessed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis.

Results

A prognostic model was established for eight NRGs (CALM1, DDX17, FPR1, OGT, PGLYRP1, PRDX1, TUFM, and CPSF3) based on TCGA-cohort data and validated with the GSE68465 cohort. Patients with low-risk scores had better survival outcomes than those with high-risk scores (p = 0.00013). The nomogram was used to predict the prognosis of patients with LUAD. The prediction curves for 1-, 3-, and 5-year OS showed good predictive performance and the accuracy of the nomograms increased over time. RT-qPCR results demonstrated that these eight genes, especially CALM1, PRDX1, and PGLYRP1, were differentially expressed in LUAD cells.

Conclusion

We constructed a reliable eight-NRG signature that provides new insights for guiding clinical practice in the prognosis and treatment of LUAD.

Conduction and validation of a novel prognostic signature in cervical cancer based on the necroptosis characteristic genes via integrating of multiomics data

The significance of necroptosis in recurrent or metastatic cervical cancer remains unclear. In this study, we utilized various bioinformatics methods to analyze the cancer genome atlas (TCGA) data, gene chip and the single-cell RNA-sequencing (scRNA seq) data. And a necroptosis-related genes signature for prognostic assessment of patients with cervical cancer was constructed successfully. Survival analysis, receiver operating characteristic (ROC) curve, the support vector machine recursive feature elimination (SVM-RFE) algorithm and random forest analysis were performed to validate this signature. Patients in TCGA-CESC cohort were grouped into "high-necroptosis score (H-NCPS)" vs "low-necroptosis score (L-NCPS)" subgroups based on the median of necroptosis score of each patient. Analyses of the tumor microenvironment manifested "H-NCPS" patients associated with lower degree of immune infiltration. Through the utilization of survival analysis, cell communication, and Gene Set Enrichment Analysis (GSEA), PGK1 was determined to be the pivotal gene within the 9-gene signature associated with necroptosis. The high expression of PGK1 in cervical cancer cells was confirmed through the utilization of quantitative real-time polymerase chain reaction (RT-qPCR) and the human protein atlas (HPA). In the interim, PGK1 prompted the transition of M1 macrophages to M2 macrophages and influenced the occurrence and development of necroptosis. In conclusion, the 9-gene signature developed from necroptosis-related genes has shown significant predictive capabilities for the prognosis of cervical cancer, offered valuable guidance for individualized and targeted treatment approaches for patients.

A Novel Necroptosis-Related Signature Can Predict Prognosis and Chemotherapy Sensitivity in Multiple Myeloma

BACKGROUND

Necroptosis is an inflammatory cell death mode, and its association with multiple myeloma (MM) remains unclear.

METHODS

This prospective study first analyzed the association between necroptosis-related signature as well as prognosis and chemotherapy sensitivity in MM using the necroptosis score. Consensus clustering was used to identify necroptosis-related molecular clusters. Least absolute shrinkage and selection operator analysis and multivariate Cox regression analysis were performed to establish the prognostic model of necroptosis-related genes (NRGs).

RESULTS

A high necroptosis score was associated with poor prognosis and abundant immune infiltration. Two molecular clusters (clusters A and B) significantly differed in terms of prognosis and tumor microenvironment. Cluster B had a worse prognosis and higher tumor marker pathway activity than cluster A. The risk score model based on four NRGs can accurately predict the prognosis of patients with MM, which was validated in two validation cohorts. Receiver operating characteristic curve analysis showed that the area under the curves of the risk score in predicting the 1-, 3-, and 5-year survival rates were 0.710, 0.758, and 0.834, respectively. Further, the activity of pathways related to proliferation and genetic regulation in the high-risk group significantly increased. The drug prediction results showed that the low-risk score group was more sensitive to bortezomib, cytarabine, and doxorubicin than the high-risk score group. Meanwhile, the high-risk score group was more sensitive to lenalidomide and vinblastine than the low-risk score group. Finally, the upregulation of model genes CHMP1A, FAS, JAK3, and HSP90AA1 in clinical samples collected from patients with MM was validated via real-time polymerase chain reaction.

CONCLUSION

A systematic analysis of NRGs can help identify potential necroptosis-related mechanisms and provide novel biomarkers for MM prognosis prediction, tumor microenvironment evaluation, and personalized treatment planning.

Pancancer analysis reveals the role of disulfidptosis in predicting prognosis, immune infiltration and immunotherapy response in tumors

Disulfidptosis has been reported as a novel cell death process, suggesting a therapeutic strategy for cancer treatment. Herein, we constructed a multiomics data analysis to reveal the effects of disulfidptosis in tumors. Data for 33 kinds of tumors were downloaded from UCSC Xene, and disulfidptosis-related genes (DRGs) were selected from a previous study. After finishing processing data by the R packages, the expression and coexpression of DRGs in different tumors were assessed as well as copy number variations. The interaction network was drawn by STRING, and the activity of disulfidptosis was compared to the single-sample gene set enrichment analysis algorithm. Subsequently, the differences in DRGs for prognosis and clinicopathological features were evaluated, and the tumor immune microenvironment was assessed by the TIMER and TISCH databases. Tumor mutation burden, stem cell features and microsatellite instability were applied to predict drug resistance, and the expression of checkpoints was identified for the prediction of immunotherapy. Moreover, the TCIA, CellMiner and Enrichr databases were also utilized for selecting potential agents. Ten DRGs were differentially expressed in tumors, and the plots of coexpression and interaction revealed their correlation. Survival analysis suggested SLC7A11 as the most prognosis-related DRG with the most significant results. Additionally, the comparison also reflected the differences in DRGs in the status of pathologic lymph node metastasis for 5 types of tumors. The tumor immune microenvironment showed commonality among tumors based on immune infiltration and single-cell sequencing, and the analysis of tumor mutation burden, stemness and microsatellite instability showed a mostly positive correlation with DRGs. Moreover, referring to the prediction about clinical treatment, most DRGs can enhance sensitivity to chemotherapeutic agents but decrease the response to immune inhibitors with increasing expression. In this study, a primarily synthetic landscape of disulfidptosis in tumors was established and provided guidance for further exploration and investigation.

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

Background

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

Methods

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

Results

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

Conclusion

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

Necroptosis in human cancers with special emphasis on oral squamous cell carcinoma

Necroptosis is a type of caspase independent 'programmed or regulated' necrotic cell death that has a morphological resemblance to necrosis and mechanistic analogy to apoptosis. This type of cell death requires RIPK1, RIPK3, MLKL, death receptors, toll like receptors, interferons, and various other proteins. Necroptosis is implicated in plethora of diseases like rheumatoid arthritis, Alzheimer's disease, Crohn's disease, and head and neck cancers including oral squamous cell carcinoma. Oral carcinomas show dysregulation or mutation of necroptotic proteins, mediate antitumoral immunity, activate immune response and control tumor progression. Necroptosis is known to play a dual role (pro tumorigenic and anti-tumorigenic) in cancer progression and targeting this pathway could be an effective approach in cancer therapy. Necroptosis based chemotherapy has been proposed in malignancies, highlighting the importance of necroptotic pathway to overcome apoptosis resistance and serve as a "fail-safe" pathway to modulate cancer initiation, progression, and metastasis. However, there is dearth of information regarding the use of necroptotic cell death mechanism in the treatment of oral squamous cell carcinoma. In this review, we summarise molecular mechanism of necroptosis, and its protumorigenic and antitumorigenic role in cancers to shed light on the possible therapeutic significance of necroptosis in oral squamous cell carcinoma.

Identification and validation of a novel necroptosis-related molecular signature to evaluate prognosis and immune features in breast cancer

Necroptosis has been shown to play an important role in the development of tumors. However, the characteristics of the necroptosis-related subtypes and the associated immune cell infiltration in the tumor microenvironment (TME) of breast cancer (BRCA) remain unclear. In this study, we identified three clusters related to necroptosis using the expression patterns of necroptosis-relevant genes (NRGs), and found that these three clusters had different clinicopathological features, prognosis and immune cell infiltration in the TME. Cluster 2 was characterized by less infiltration of immune cells in the TME and was associated with a worse prognosis. Then, a necroptosis risk score (NRS) composed of 14 NRGs was constructed using the least absolute shrinkage and selection operator regression (LASSO) Cox regression method. Based on NRS, all BRCA patients in the TCGA datasets were classified into a low-risk group and a high-risk group. Patients in the low-risk group were characterized by longer overall survival (OS), lower mutation burden, and higher infiltration level of immune cells in the TME. Moreover, the NRS was significantly associated with chemotherapeutic drug sensitivity. Finally, the knockdown of VDAC1 reduced the proliferation and migration of BRCA cells, and promoted cell death induced by necroptosis inducer. This study identified a novel necroptosis-related subtype of BRCA, and a comprehensive analysis of NRGs in BRCA revealed its potential roles in prognosis, clinicopathological features, TME, chemotherapy, tumor proliferation, and tumor necroptosis. These results may improve our understanding of NRGs in BRCA and provide a reference for developing individualized therapeutic strategies.

A novel necroptosis-related gene signature in acute myeloid leukemia

OBJECTIVE

Necroptosis has been reported to play an important role in different cancers, including leukemia. However, biomarkers of necroptosis-related genes (NRGs) that help predict the prognosis of AML are still lacking. Our research aims to build a novel signature of NRGs that could enhance our understanding of the molecular heterogeneity in leukemia.

METHOD

Gene expression profiles as well as clinical features were downloaded from TCGA and GEO databases. Data analysis were executed using R software version 4.2.1 and GraphPad Prism version 9.0.0.

RESULT

Univariate cox regression and lasso regression were applied to identify survival-specific genes. Four genes including FADD, PLA2G4A, PYCARD and ZBP1 were considered as independent risk factors that affect the prognosis of patients. Risk scores were calculated according to the coefficient of four genes. Then clinical characteristics and risk scores were enrolled to construct a nomogram. CellMiner was also used to screen potential drugs and analyze the correlations between genes and drug sensitivity.

CONCLUSION

In general, we established a signature of four genes related to necroptosis that could be helpful for future risk stratification in patients with AML.

The development of necroptosis: what we can learn

Necroptosis is a new type of programmed cell death discovered in recent years, playing an important role in various diseases. Since it was conceptualized in 2005, research on necroptosis has developed rapidly. However, few bibliometric analyses have provided a comprehensive overview of the field. This study aimed to employ a bibliometric analysis to assess necroptosis research's current status and hotspot, highlight landmark findings, and orientate future research. A total of 3993 publications from the WoSCC were collected for this study. Multiple tools were used for bibliometric analysis and data visualization, including an online website, VOSviewer, CiteSpace, and HistCite. Publications related to necroptosis have increased significantly annually, especially in the last 5 years. Globally, the USA and Harvard University are the most outstanding countries and institutions in this field, respectively. The academic groups managed by Peter Vandenabeele and Junying Yuan both have permanent and intensive research on necroptosis. Cell Death and Differentiation is the most vital journal in this field. The molecular mechanisms of necroptosis and its role in disease are the focus of current research, while the crosstalk between programmed cell death is an emerging direction in the field. The "reactive oxygen species", "innate immunity", and "programmed cell death" may be potential research hotspots. Our results present a comprehensive knowledge map and explore research trends. Researchers and funding agencies on necroptosis can obtain helpful references from our study.

Exploration and validation of a novel signature of seven necroptosis-related genes to improve the clinical outcome of hepatocellular carcinoma

Necroptosis has been reported to be involved in cancer progression and associated with cancer prognosis. However, the prognostic values of necroptosis-related genes (NRGs) in hepatocellular carcinoma (HCC) remain largely unknown. This study aimed to build a signature on the basis of NRGs to evaluate the prognosis of HCC patients. In this study, using bioinformatic analyses of transcriptome sequencing data of HCC (n = 370) from The Cancer Genome Atlas (TCGA) database, 63 differentially expressed NRGs between HCC and adjacent normal tissues were determined. 24 differentially expressed NRGs were found to be related with overall survival (OS). Seven optimum NRGs, determined using Lasso regression and multivariate Cox regression analysis, were used to construct a new prognostic risk signature for predicting the prognosis of HCC patients. Then survival status scatter plots and survival curves demonstrated that the prognosis of patients with high-Riskscore was worse. The prognostic value of this 7-NRG signature was validated by the International Cancer Genome Consortium (ICGC) cohort and a local cohort (Wenzhou, China). Notably, Riskscore was defined as an independent risk factor for HCC prognosis using multivariate cox regression analysis. Immune infiltration analysis suggested that higher macrophage infiltration was found in patients in the high-risk group. Finally, enhanced 7 NRGs were found in HCC tissues by immunohistochemistry. In conclusion, a novel 7-NRG prognostic risk signature is generated, which contributes to the prediction in the prognosis of HCC patients for the clinicians.

Molecular subtypes of lung adenocarcinoma patients for prognosis and therapeutic response prediction with machine learning on 13 programmed cell death patterns

BACKGROUND

Lung adenocarcinoma (LUAD) seriously threatens people's health worldwide. Programmed cell death (PCD) plays a critical role in regulating LUAD growth and metastasis as well as in therapeutic response. However, currently, there is a lack of integrative analysis of PCD-related signatures of LUAD for accurate prediction of prognosis and therapeutic response.

METHODS

The bulk transcriptome and clinical information of LUAD were obtained from TCGA and GEO databases. A total of 1382 genes involved in regulating 13 various PCD patterns (apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, netotic cell death, entotic cell death, lysosome-dependent cell death, parthanatos, autophagy-dependent cell death, oxeiptosis, alkaliptosis and disulfidptosis) were included in the study. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were performed to identify PCD-associated differential expression genes (DEGs). An unsupervised consensus clustering algorithm was used to explore the potential subtypes of LUAD based on the expression profiles of PCD-associated DEGs. Univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression, Random Forest (RF) analysis and stepwise multivariate Cox analysis were performed to construct a prognostic gene signature. The "oncoPredict" algorithm was utilized for drug-sensitive analysis. GSVA and GSEA were utilized to perform function enrichment analysis. MCPcounter, quanTIseq, Xcell and ssGSEA algorithms were used for tumor immune microenvironment analysis. A nomogram incorporating PCDI and clinicopathological characteristics was established to predict the prognosis of LUAD patients.

RESULTS

Forty PCD-associated DEGs related to LUAD were obtained by WGCNA analysis and differential expression analysis, followed by unsupervised clustering to identify two LUAD molecular subtypes. A programmed cell death index (PCDI) with a five-gene signature was established by machine learning algorithms. LUAD patients were then divided into a high PCDI group and a low PCDI group using the median PCDI as a cutoff. Survival and therapeutic analysis revealed that the high PCDI group had a poor prognosis and was more sensitive to targeted drugs but less sensitive to immunotherapy compared to the low PCDI group. Further enrichment analysis showed that B cell-related pathways were significantly downregulated in the high PCDI group. Accordingly, the decreased tumor immune cell infiltration and the lower tumor tertiary lymphoid structure (TLS) scores were also found in the high PCDI group. Finally, a nomogram with reliable predictive performance PCDI was constructed by incorporating PCDI and clinicopathological characteristics, and a user-friendly online website was established for clinical reference ( https://nomogramiv.shinyapps.io/NomogramPCDI/ ).

CONCLUSION

We performed the first comprehensive analysis of the clinical relevance of genes regulating 13 PCD patterns in LUAD and identified two LUAD molecular subtypes with distinct PCD-related gene signature which indicated differential prognosis and treatment sensitivity. Our study provided a new index to predict the efficacy of therapeutic interventions and the prognosis of LUAD patients for guiding personalized treatments.

Identification and assessment of differentially expressed necroptosis long non-coding RNAs associated with periodontitis in human

BACKGROUND

Periodontitis is the most common oral disease and is closely related to immune infiltration in the periodontal microenvironment and its poor prognosis is related to the complex immune response. The progression of periodontitis is closely related to necroptosis, but there is still no systematic study of long non-coding RNA (lncRNA) associated with necroptosis for diagnosis and treatment of periodontitis.

MATERIAL AND METHODS

Transcriptome data and clinical data of periodontitis and healthy populations were obtained from the Gene Expression Omnibus (GEO) database, and necroptosis-related genes were obtained from previously published literature. FactoMineR package in R was used to perform principal component analysis (PCA) for obtaining the necroptosis-related lncRNAs. The core necroptosis-related lncRNAs were screened by the Linear Models for Microarray Data (limma) package in R, PCA principal component analysis and lasso algorithm. These lncRNAs were then used to construct a classifier for periodontitis with logistic regression. The receiver operating characteristic (ROC) curve was used to evaluate the sensitivity and specificity of the model. The CIBERSORT method and ssGSEA algorithm were used to estimate the immune infiltration and immune pathway activation of periodontitis. Spearman's correlation analysis was used to further verify the correlation between core genes and periodontitis immune microenvironment. The expression level of core genes in human periodontal ligament cells (hPDLCs) was detected by RT-qPCR.

RESULTS

A total of 10 core necroptosis-related lncRNAs (10-lncRNAs) were identified, including EPB41L4A-AS1, FAM30A, LINC01004, MALAT1, MIAT, OSER1-DT, PCOLCE-AS1, RNF144A-AS1, CARMN, and LINC00582. The classifier for periodontitis was successfully constructed. The Area Under the Curve (AUC) was 0.952, which suggested that the model had good predictive performance. The correlation analysis of 10-lncRNAs and periodontitis immune microenvironment showed that 10-lncRNAs had an impact on the immune infiltration of periodontitis. Notably, the RT-qPCR results showed that the expression level of the 10-lncRNAs obtained was consistent with the chip analysis results.

CONCLUSIONS

The 10-lncRNAs identified from the GEO dataset had a significant impact on the immune infiltration of periodontitis and the classifier based on 10-lncRNAs had good detection efficiency for periodontitis, which provided a new target for diagnosis and treatment of periodontitis.

Genetic variants in key necroptosis regulators predict prognosis of non-small cell lung cancer after surgical resection

BACKGROUND

Necroptosis is a regulated inflammatory cell death which plays a significant role in cancer development and progression. In this study, we evaluated whether genetic variants in key regulators of necroptosis may affect survival outcome of non-small cell lung cancer (NSCLC) patients after surgical resection.

METHODS

A total of 674 patients who underwent curative surgery were included. Fifteen genetic variants in key regulators of necroptosis (RIPK1, RIPK3, and MLKL) were selected. The association of these variants with survival outcomes was evaluated.

RESULTS

Two variants, RIPK1 rs17548629C > T and MLKL rs877375G > C, were associated with better overall survival and disease-free survival in multivariate analyses. When the patients were divided according to histology, the associations were significant only in adenocarcinoma, but not in squamous cell carcinoma. RIPK1 rs17548629 C-to-T change was associated with significantly increased luciferase activity by modulating the binding of miR-642a. Promoter assays showed a significantly increased promoter activity in MLKL rs877375C allele compared to G allele. Consistently, the mRNA expression level of RIPK1 and MLKL showed significant positive correlation with RIPK1 rs17548629C-to-T and MLKL rs877375G-to-C changes.

CONCLUSION

Two genetic variants in key regulators in necroptosis, RIPK1 rs17548629C > T and MLKL rs877375G > C, may be used as biomarkers to predict survival outcomes in surgically resected NSCLC patients.

Scaffold hopping derived novel benzoxazepinone RIPK1 inhibitors as anti-necroptosis agents

Receptor-interacting protein kinase 1 (RIPK1)-mediated necroptosis is believed to have a significant role in contributing to inflammatory diseases. Inhibiting RIPK1 has shown promise in effectively alleviating the inflammation process. In our current study, we employed scaffold hopping to develop a series of novel benzoxazepinone derivatives. Among these derivatives, compound o1 displayed the most potent antinecroptosis activity (EC50=16.17±1.878nM) in cellular assays and exhibited the strongest binding affinity to the target site. Molecular docking analyses further elucidated the mechanism of action of o1, revealing its ability to fully occupy the protein pocket and form hydrogen bonds with the amino acid residue Asp156. Our findings highlight that o1 specifically inhibits necroptosis, rather than apoptosis, by impeding the RIPK1/Receptor-interacting protein kinase 3 (RIPK3)/mixed-lineage kinase domain-like (MLKL) pathway's phosphorylation, triggered by TNFα, Smac mimetic, and z-VAD (TSZ). Additionally, o1 demonstrated dose-dependent improvements in the survival rate of mice with Systemic Inflammatory Response Syndrome (SIRS), surpassing the protective effect observed with GSK'772.

The Active Fraction of Polyrhachis vicina Roger (AFPR) activates ERK to cause necroptosis in colorectal cancer

ETHNOPHARMACOLOGICAL RELEVANCE

Polyrhachis vicina Roger (P. vicina), a traditional Chinese medicinal animal, has been used to treat rheumatoid arthritis, hepatitis, cancer, and other conditions. Due to its anti-inflammatory properties, our previous pharmacological investigations have demonstrated that it is effective against cancer, depression, and hyperuricemia. Nevertheless, the key active components and targets of P. vicina in cancers are still unexplored.

AIM OF THE STUDY

The study aimed to evaluate the pharmacological treatment mechanism of the active fraction of P. vicina (AFPR) in treating colorectal cancer (CRC) and to further reveal its active ingredients and key targets.

METHODS

To examine the inhibitory impact of AFPR on CRC growth, tumorigenesis assays, cck-8 assays, colony formation assays, and MMP detection were utilized. The primary components of AFPR were identified by GC-MS analysis. The network pharmacology, molecular docking, qRT-PCR, western blotting, CCK-8 assays, colony formation assay, Hoechst staining, Annexin V-FITC/PI double staining, and MMP detection were performed to pick out the active ingredients and potential key targets of AFPR. The function of Elaidic acid on necroptosis was investigated through siRNA interference and the utilization of inhibitors. Elaidic acid's effectiveness to suppress CRC growth in vivo was assessed using a tumorigenesis experiment.

RESULTS

Studies confirmed that AFPR prevented CRC from growing and evoked cell death. Elaidic acid was the main bioactive ingredient in AFPR that targeted ERK. Elaidic acid greatly affected the ability of SW116 cells to form colonies, produce MMP, and undergo necroptosis. Additionally, Elaidic acid promoted necroptosis predominantly by activating ERK/RIPK1/RIPK3/MLKL.

CONCLUSION

According to our findings, Elaidic acid is the main active component of AFPR, which induced necroptosis in CRC through the activation of ERK. It represents a promising alternative therapeutic option for CRC. This work provided experimental support for the therapeutic application of P. vicina Roger in the treatment of CRC.

A necroptosis-related gene signature to predict prognosis and immune features in hepatocellular carcinoma

BACKGROUND AND AIM

Necroptosis plays an important role in hepatocellular carcinoma (HCC) development, recurrence, and immunotherapy tolerance. We aimed to build a new prognostic necroptosis-related gene signature that could be used for survival and immunotherapy prediction in HCC patients.

METHODS

We found that necroptosis was associated with HCC progression and survival outcomes and was involved in the immune infiltration of HCC. Multiple bioinformatics methods including WGCNA, LASSO-Cox regression, stepwise Cox regression, and Random Forest and Boruta model analysis, were used to establish a prognostic profile related to necroptosis. The necroptosis-related gene signature was validated in ICGC and GSE14520 datasets.

RESULTS

This five-gene signature showed excellent predictive performance and was an independent risk factor for patients' overall survival outcome in the three cohorts. Moreover, this signature was an exact predictor using fewer genes than previous gene signatures. Finally, qRT-PCR and immunohistochemical staining investigations were performed in previously collected fresh frozen tumor tissues from HCC patients and their paracancerous normal tissues, and the results were consistent with the bioinformatics results. We found that LGALS3 not only affected the proliferation and migration ability of HepG2 cells but also affected necroptosis and the expression of inflammatory cytokines.

CONCLUSION

In summary, we established and validated an individualized prognostic profile related to necroptosis to forecast the therapeutic response to immune therapy, which might offer a potential non-apoptotic therapeutic target for HCC patients.

Disulfidptosis classification of hepatocellular carcinoma reveals correlation with clinical prognosis and immune profile

A new mode of cell death, disulfidptosis, has been discovered. Clinical prognostic significance of disulfidptosis related pattern in hepatocellular carcinoma(HCC). In this study, a risk score model was established based on disulfidptosis model to analyze the role of risk score in clinical prognosis, immune cell infiltration, drug sensitivity and immunotherapy response. Disulfidptosis subtype were constructed based on the transcriptional profiles of 15 disulfidptosis-related genes(DRGs). All 601 samples were defined as high risk group(HRG) and low risk group(LRG) based on the disulfidptosis risk score. Drug sensitivity and response to immunotherapy were calculated by immunophenotypic score(IPS), tumor prediction, tumor immune dysfunction and rejection(TIDE). RT-qPCR was used to determine the mRNA level of disulfidptosis prognostic gene. Risk groups was identified as potential predictors of immune cell infiltration, drug sensitivity, and immunotherapy responsiveness. HRG may benefit from immunotherapy. Classification is very effective in predicting the prognosis and therapeutic effect of patients, and provides a reference for accurate individualized treatment. This study suggests that new biomarkers related to Disulfidptosis can be used in clinical diagnosis of liver cancer to predict prognosis and treatment targets.

Non-lethal outcomes of engaging regulated cell death pathways in cancer

Regulated cell death (RCD) is essential for successful systemic cancer therapy. Yet, the engagement of RCD pathways does not inevitably result in cell death. Instead, RCD pathways can take part in diverse biological processes if the cells survive. Consequently, these surviving cells, for which we propose the term 'flatliners', harbor important functions. These evolutionarily conserved responses can be exploited by cancer cells to promote their own survival and growth, with challenges and opportunities for cancer therapy.

Lnc-ing epigenetic mechanisms with autophagy and cancer drug resistance

Long noncoding RNAs (lncRNAs) comprise a diverse class of RNA molecules that regulate various physiological processes and have been reported to be involved in several human pathologies ranging from neurodegenerative disease to cancer. Therapeutic resistance is a major hurdle for cancer treatment. Over the past decade, several studies has emerged on the role of lncRNAs in cancer drug resistance and many trials have been conducted employing them. LncRNAs also regulate different cell death pathways thereby maintaining a fine balance of cell survival and death. Autophagy is a complex cell-killing mechanism that has both cytoprotective and cytotoxic roles. Similarly, autophagy can lead to the induction of both chemosensitization and chemoresistance in cancer cells upon therapeutic intervention. Recently the role of lncRNAs in the regulation of autophagy has also surfaced. Thus, lncRNAs can be used in cancer therapeutics to alleviate the challenges of chemoresistance by targeting the autophagosomal axis. In this chapter, we discuss about the role of lncRNAs in autophagy-mediated cancer drug resistance and its implication in targeted cancer therapy.

Caspase-6 is a key regulator of cross-talk signal way in PANoptosis in cancer

Cysteinyl aspartate specific proteinase (caspase)-6 belongs to the caspase family and plays a vital role in mediating cell death. Under certain conditions, three pathways of programmed cell death (PCD), including apoptosis, necroptosis and pyroptosis (PANoptosis), transform one way into another, with enormous therapeutic potential. Initially, scholars reported that caspase-6 is a caspase executor that mediates apoptosis. With the ceaseless exploration of the PCD types, studies have demonstrated that caspase-6 mediates pyroptosis by regulating gasdermin D and mediates necroptosis by regulating mixed lineage kinase domain-like. By regulating PANoptosis, caspase-6 plays a crucial role in tumorigenesis in humans and mediates anti-tumour immunity. Therefore, a comprehensive understanding of caspase-6 function in cancer via PANoptosis is important for the prevention and therapy of tumours. This article summarized the function of caspase-6 in PANoptosis and its impact on cancer development, providing targets and strategies for tumour treatment.

Necroptosis Related Genes Predict Prognosis and Therapeutic Potential in Gastric Cancer

The clinical significance of necroptosis in gastric cancer (GC) has yet to be fully elucidated. The purpose of our study was to identify a necroptosis-relevant gene and to establish a prediction model to estimate the prognosis and therapeutic potential in GC. Here, we explored the expression profile of 76 necroptosis-related genes in TCGA-STAD patients. A six-gene risk score prediction model was established via regression analysis of the least absolute shrinkage and selection operator (LASSO) and validated in a separate cohort. Patients were separated into low- or high-risk groups according to the median risk score. We then compared and analyzed the biological process characteristics of two risk groups. Additionally, cell-to-cell communications and metabolic activity were analyzed in a single-cell solution. The in vitro experiments were conducted to explore the biological functions and drug sensitivity of necroptosis-related genes in gastric cancer. Our results identified that compared with the low-risk group, the high-risk group was associated with a higher clinical stage or grade and a worse prognosis. In addition, the low-risk group had higher levels of immunity and immune cell infiltration. Necroptosis was triggered by the TNF pathway in myeloid cells and the glycolysis pathway was altered. Necroptosis-related genes modulated the cell function, including proliferation and migration in vitro. Furthermore, the potential drugs' sensitivity was higher in the low-risk subgroup. These findings could facilitate a better understanding and improve the treatment potential and prognosis of GC patients.

Establishing Patient-Derived Cancer Cell Cultures and Xenografts in Biliary Tract Cancer

PURPOSE

Biliary tract cancers (BTCs) are rare and show a dismal prognosis with limited treatment options. To improve our understanding of these heterogeneous tumors and develop effective therapeutic agents, suitable preclinical models reflecting diverse tumor characteristics are needed. We established and characterized new patient-derived cancer cell cultures and patient-derived xenograft (PDX) models using malignant ascites from five patients with BTC.

MATERIALS AND METHODS

Five patient-derived cancer cell cultures and three PDX models derived from malignant ascites of five patients with BTC, AMCBTC-01, -02, -03, -04, and -05, were established. To characterize the models histogenetically and confirm whether characteristics of the primary tumor were maintained, targeted sequencing and histopathological comparison between primary tissue and xenograft tumors were performed.

RESULTS

From malignant ascites of five BTC patients, five patient-derived cancer cell cultures (100% success rate), and three PDXs (60% success rate) were established. The morphological characteristics of three primary xenograft tumors were compared with those of matched primary tumors, and they displayed a similar morphology. The mutated genes in samples (models, primary tumor tissue, or both) from more than one patient were TP53 (n=2), KRAS (n=2), and STK11 (n=2). Overall, the pattern of commonly mutated genes in BTC cell cultures was different from that in commercially available BTC cell lines.

CONCLUSION

We successfully established the patient-derived cancer cell cultures and xenograft models derived from malignant ascites in BTC patients. These models accompanied by different genetic characteristics from commercially available models will help better understand BTC biology.

Identification and Validation of a Necroptosis-Related Prognostic Signature for Kidney Renal Clear Cell Carcinoma

Background

Necroptosis is progressively becoming an important focus of research because of its role in the pathogenesis of cancer and other inflammatory diseases. Our study is designed to anticipate the survival time of kidney renal clear cell carcinoma (KIRC) by constructing a prognostic signature of necroptosis-related genes.

Materials

Clinical information and RNA-seq data were acquired from Renal Cell Cancer-European Union (RECA-EU) and The Cancer Genome Atlas- (TCGA-) KIRC, respectively. ConsensusClusterPlus was used to identify molecular subtypes, and the distribution of immune cell infiltration, anticancer drug sensitivity, and somatic gene mutations was studied in these subtypes. Subsequently, LASSO-Cox regression and univariate Cox regression were also carried out to construct a necroptosis-related signature. Cox regression, survival analysis, clinicopathological characteristic correlation analysis, nomogram, cancer stem cell analysis, and receiver operating characteristic (ROC) curve were some tools employed to study the prognostic power of the signature.

Results

Based on the expression patterns of 66 survival-related necroptosis genes, we classified the KIRC into three subtypes (C1, C2, and C3) that are associated with necroptosis, which had significantly different tumor stem cell components. Among these, C2 patients had a longer survival time and enhanced immune status and were more sensitive to conventional chemotherapeutic drugs. Moreover, in order to predict the prognosis of KIRC patients, five genes (BMP8A, TLCD1, CLGN, GDF7, and RARB) were used to develop a necroptosis-related prognostic signature, which had an acceptable predictive potency. The results from Cox regression and stratified survival analysis revealed that the signature was an independent prognostic factor, whereas the nomogram and calibration curve demonstrated satisfactory survival time prediction based on the risk score.

Conclusions

Three molecular subtypes and five necroptosis-related genes were discovered in KIRC using data from TCGA-KIRC and RECA-EU. Thus, a new biomarker and a potentially effective therapeutic approach for KIRC patients were provided in the current study.

Identification and Validation a Necroptosis-Related Prognostic Signature in Cervical Cancer

Necroptosis is a promising novel target for cervical cancer therapy. Nevertheless, differentially expressed necroptosis-related genes (NRGs) in cervical cancer and their associations with prognosis are far from fully clarified. In this study, differentially expressed NRGs (DE-NRGs) were screened out and their bio-function was elucidated. Subsequently, a prognostic scoring model based on the regression coefficients of the screened out NRGs and their corresponding mRNA expressions were constructed and validated. Finally, the survival probability of cervical cancer patients based on the constructed prognostic scoring model in 3 and 5 years was predicted and assessed. We found 17 DE-NRGs in cervical cancer tissues which were closely related to cancer progression, and most of them were significantly highly expressed. Furthermore, 3 NRG were confirmed as the prognostic signature genes from 17 DE-NRGs by regression analysis. Overall survival predicted through our prognostic scoring model was lower in the high-risk group than in the low-risk group (p < 0.05) in both the TCGA cohort and the external GEO44001 validation cohort. What's more, the prediction performance of our prognostic scoring models well verified by the ROC curve, and the risk score calculated could act as an independent prognostic factor for cervical cancer patients. The calibration curve and C-index (0.776) of the nomogram analysis suggested that the predictive performance of the nomogram was satisfactory. Our study identified and validated a necroptosis-related prognostic signature in cervical cancer, which could well predict the prognosis for cervical cancer patients.

Integrated analysis of necroptosis-related genes for evaluating immune infiltration and colon cancer prognosis

Background

Colon cancer (CC) is the second most common gastrointestinal malignancy. About one in five patients have already developed distant metastases at the time of initial diagnosis, and up to half of patients develop distant metastases from initial local disease, which leads to a poor prognosis for CC patients. Necroptosis plays a key role in promoting tumor growth in different tumors. The purpose of this study was to construct a prognostic model composed of necroptosis-related genes (NRGs) in CC.

Methods

The Cancer Genome Atlas was used to obtain information on clinical features and gene expression. Gene expression differential analysis, weighted gene co-expression network analysis, univariate Cox regression analysis and the least absolute shrinkage and selection operator regression algorithm were utilized to identify prognostic NRGs. Thereafter, a risk scoring model was established based on the NRGs. Biological processes and pathways were identified by gene ontology and gene set enrichment analysis (GSEA). Further, protein-protein interaction and ceRNA networks were constructed based on mRNA-miRNA-lncRNA. Finally, the effect of necroptosis related risk score on different degrees of immune cell infiltration was evaluated.

Results

CALB1, CHST13, and SLC4A4 were identified as NRGs of prognostic significance and were used to establish a risk scoring model. The time-dependent receiver operating characteristic curve analysis revealed that the model could well predict the 1-, 3-, and 5-year overall survival (OS). Further, GSEA suggested that the NRGs may participate in biological processes, such as the WNT pathway and JAK-Stat pathway. Eight key hub genes were identified, and a ceRNA regulatory network, which comprised 1 lncRNA, 5 miRNAs and 3 mRNAs, was constructed. Immune infiltration analysis revealed that the low-risk group had significantly higher immune-related scores than the high-risk group. A nomogram of the model was constructed based on the risk score, necroptosis, and the clinicopathological features (age and TNM stage). The calibration curves implied that the model was effective at predicting the 1-, 3-, and 5-year OS of CC.

Conclusion

Our NRG-based prognostic model can assist in the evaluation of CC prognosis and the identification of therapeutic targets for CC.

Targeting cell death pathways for cancer therapy: recent developments in necroptosis, pyroptosis, ferroptosis, and cuproptosis research

Many types of human cells self-destruct to maintain biological homeostasis and defend the body against pathogenic substances. This process, called regulated cell death (RCD), is important for various biological activities, including the clearance of aberrant cells. Thus, RCD pathways represented by apoptosis have increased in importance as a target for the development of cancer medications in recent years. However, because tumor cells show avoidance to apoptosis, which causes treatment resistance and recurrence, numerous studies have been devoted to alternative cancer cell mortality processes, namely necroptosis, pyroptosis, ferroptosis, and cuproptosis; these RCD modalities have been extensively studied and shown to be crucial to cancer therapy effectiveness. Furthermore, evidence suggests that tumor cells undergoing regulated death may alter the immunogenicity of the tumor microenvironment (TME) to some extent, rendering it more suitable for inhibiting cancer progression and metastasis. In addition, other types of cells and components in the TME undergo the abovementioned forms of death and induce immune attacks on tumor cells, resulting in enhanced antitumor responses. Hence, this review discusses the molecular processes and features of necroptosis, pyroptosis, ferroptosis, and cuproptosis and the effects of these novel RCD modalities on tumor cell proliferation and cancer metastasis. Importantly, it introduces the complex effects of novel forms of tumor cell death on the TME and the regulated death of other cells in the TME that affect tumor biology. It also summarizes the potential agents and nanoparticles that induce or inhibit novel RCD pathways and their therapeutic effects on cancer based on evidence from in vivo and in vitro studies and reports clinical trials in which RCD inducers have been evaluated as treatments for cancer patients. Lastly, we also summarized the impact of modulating the RCD processes on cancer drug resistance and the advantages of adding RCD modulators to cancer treatment over conventional treatments.

Development and Validation of a Prognostic Model for Esophageal Adenocarcinoma Based on Necroptosis-Related Genes

Necroptosis is a newly developed cell death pathway that differs from necrosis and apoptosis; however, the potential mechanism of necroptosis-related genes in EAC and whether they are associated with the prognosis of EAC patients remain unclear. We obtained 159 NRGs from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and performed differential expression analysis of the NRGs in 9 normal samples and 78 EAC tumor samples derived from The Cancer Genome Atlas (TCGA). Finally, we screened 38 differentially expressed NRGs (DE-NRGs). The results of the GO and KEGG analyses indicated that the DE-NRGs were mainly enriched in the functions and pathways associated with necroptosis. Protein interaction network (PPI) analysis revealed that TNF, CASP1, and IL-1B were the core genes of the network. A risk score model based on four DE-NRGs was constructed by Least Absolute Shrinkage and Selection Operator (LASSO) regression, and the results showed that the higher the risk score, the worse the survival. The model achieved more efficient diagnosis compared with the clinicopathological variables, with an area under the receiver operating characteristic (ROC) curve of 0.885. The prognostic value of this model was further validated using Gene Expression Omnibus (GEO) datasets. Gene set enrichment analyses (GSEA) demonstrated that several metabolism-related pathways were activated in the high-risk population. Single-sample GSEA (ssGSEA) provided further confirmation that this prognostic model was remarkably associated with the immune status of EAC patients. Finally, the nomogram map exhibited a certain prognostic prediction efficiency, with a C-index of 0.792 and good consistency. Thus, the prognostic model based on four NRGs could better predict the prognosis of EAC and help to elucidate the mechanism of necroptosis-related genes in EAC, which can provide guidance for the target prediction and clinical treatment of EAC patients.

Identification of necroptosis-related genes for predicting prognosis and exploring immune infiltration landscape in colon adenocarcinoma

Background

Necroptosis is a recently discovered form of cell death that plays an important role in the occurrence and development of colon adenocarcinoma (COAD). Our study aimed to construct a risk score model to predict the prognosis of patients with COAD based on necroptosis-related genes.

Methods

The gene expression data of COAD and normal colon samples were obtained from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to calculate the risk score based on prognostic necroptosis-related differentially expressed genes (DEGs). Based on the risk score, patients were classified into high- and low-risk groups. Then, nomogram models were built based on the risk score and clinicopathological features. Otherwise, the model was verified in the Gene Expression Omnibus (GEO) database. Additionally, the tumor microenvironment (TME) and the level of immune infiltration were evaluated by "ESTIMATE" and single-sample gene set enrichment analysis (ssGSEA). Functional enrichment analysis was carried out to explore the potential mechanism of necroptosis in COAD. Finally, the effect of necroptosis on colon cancer cells was explored through CCK8 and transwell assays. The expression of necroptosis-related genes in colon tissues and cells treated with necroptotic inducers (TNFα) and inhibitors (NEC-1) was evaluated by quantitative real-time polymerase chain reaction (qRT-PCR).

Results

The risk score was an independent prognostic risk factor in COAD. The predictive value of the nomogram based on the risk score and clinicopathological features was superior to TNM staging. The effectiveness of the model was well validated in GSE152430. Immune and stromal scores were significantly elevated in the high-risk group. Moreover, necroptosis may influence the prognosis of COAD via influencing the cancer immune response. In in-vitro experiments, the inhibition of necroptosis can promote proliferation and invasion ability. Finally, the differential expression of necroptosis-related genes in 16 paired colon tissues and colon cancer cells was found.

Conclusion

A novel necroptosis-related gene signature for forecasting the prognosis of COAD has been constructed, which possesses favorable predictive ability and offers ideas for the necroptosis-associated development of COAD.

A novel necroptosis-related lncRNA signature for predicting prognosis and anti-cancer treatment response in endometrial cancer

BACKGROUND

Necroptosis, a form of programmed cell death, underlies tumorigenesis and the progression of cancers. Anti-cancer strategies targeting necroptosis have increasingly been shown to present a potential cancer therapy. However, the predictive utility and anticancer sensitivity value of necroptosis-related lncRNAs (NRLs) for endometrial cancer (EC) are currently unknown.

METHODS

EC patient gene expression profiles and the corresponding clinical information collected from The Cancer Genome Atlas were used to identify NRLs that constituted a predictive signature for EC. The functional pathways, immune status, clinicopathological correlation, and anticancer drug sensitivity of the patients relative to the NRLs signatures were analyzed.

RESULTS

A signature composed of 7 NRLs (AC019080.5, BOLA3-AS1, AC022144.1, AP000345.2, LEF1-AS1, AC010503.4, and RPARP-AS1) was identified. The high-risk patient group with this signature exhibited a poorer prognosis and lower survival rate than low-risk group lacking this signature. This necroptosis-related lncRNA signature had a higher predictive accuracy compared with other clinicopathological variables (area under the receiver operating characteristic curve of the risk score: 0.717). Additionally, when patients were stratified based on other clinicopathological variables, the overall survival was significantly shorter in the high-risk versus low-risk group across all cohorts. Gene set enrichment analysis (GSEA) revealed that immune- and tumor-related signaling pathways and biological processes were enriched in the high-risk group compared to the low-risk group. Single-sample gene set enrichment analysis (ssGSEA) additionally showed that the resulting risk score was strongly correlated with EC patient immune status. Finally, patients with high-risk scores were more sensitive to the anti-cancer drugs such as Docetaxel, Mitomycin.C, Vinblastine, AZD.2281 (olaparib), AZD6244, and PD.0332991 (Palbociclib).

CONCLUSION

These findings reveal a novel necroptosis-related lncRNA signature for predicting EC patient prognosis and shed new light on anticancer therapy strategies for EC.

Necroptosis pathways in tumorigenesis

Necroptosis is a caspase-independent form of programmed cell death executed by the receptor interacting protein kinase 1 (RIPK1)-RIPK3-mixed lineage kinase domain-like protein (MLKL) signaling cascade, deregulation of which can cause various human diseases including cancer. Escape from programmed cell death is a hallmark of cancer, leading to uncontrolled growth and drug resistance. Therefore, it is crucial to further understand whether necroptosis plays a key role in therapeutic resistance. In this review, we summarize the recent findings of the link between necroptosis and cancer, and discuss that targeting necroptosis is a new strategy to overcome apoptosis resistance in tumor therapy.

Role of Receptor Interacting Protein (RIP) kinases in cancer

The Receptor Interacting Protein (RIP) kinase family consists of seven Serine/Threonine kinases, which plays a key signaling role in cell survival and cell death. Each RIP family member contains a conserved kinase domain and other domains that determine the specific kinase function through protein-protein interactions. RIP1 and RIP3 are best known for their critical roles in necroptosis, programmed necrosis and a non-apoptotic inflammatory cell death process. Dysregulation of RIP kinases contributes to a variety of pathogenic conditions such as inflammatory diseases, neurological diseases, and cancer. In cancer cells, alterations of RIP kinases at genetic, epigenetic and expression levels are frequently found, and suggested to promote tumor progression and metastasis, escape of antitumor immune response, and therapeutic resistance. However, RIP kinases can be either pro-tumor or anti-tumor depending on specific tumor types and cellular contexts. Therapeutic agents for targeting RIP kinases have been tested in clinical trials mainly for inflammatory diseases. Deregulated expression of these kinases in different types of cancer suggests that they represent attractive therapeutic targets. The focus of this review is to outline the role of RIP kinases in cancer, highlighting potential opportunities to manipulate these proteins in cancer treatment.

A novel necroptosis-related gene index for predicting prognosis and a cold tumor immune microenvironment in stomach adenocarcinoma

Background

Gastric cancer (GC) represents a major global clinical problem with very limited therapeutic options and poor prognosis. Necroptosis, a recently discovered inflammatory form of cell death, has been implicated in carcinogenesis and inducing necroptosis has also been considered as a therapeutic strategy.

Objective

We aim to evaluate the role of this pathway in gastric cancer development, prognosis and immune aspects of its tumor microenvironment.

Methods and results

In this study, we evaluated the gene expression of 55 necroptosis-related genes (NRGs) that were identified via carrying out a comprehensive review of the medical literature. Necroptosis pathway was deregulated in gastric cancer samples (n=375) as compared to adjacent normal tissues (n=32) obtained from the “The Cancer Genome Atlas (TCGA)”. Based on the expression of these NRGs, two molecular subtypes were obtained through consensus clustering that also showed significant prognostic difference. Differentially expressed genes between these two clusters were retrieved and subjected to prognostic evaluation via univariate cox regression analysis and LASSO cox regression analysis. A 13-gene risk signature, termed as necroptosis-related genes prognostic index (NRGPI), was constructed that comprehensively differentiated the gastric cancer patients into high- and low-risk subgroups. The prognostic significance of NRGPI was validated in the GEO cohort (GSE84437: n=408). The NRGPI-high subgroup was characterized by upregulation of 10 genes (CYTL1, PLCL1, CGB5, CNTN1, GRP, APOD, CST6, GPX3, FCN1, SERPINE1) and downregulation of 3 genes (EFNA3, E2F2, SOX14). Further dissection of these two risk groups by differential gene expression analysis indicated involvement of signaling pathways associated with cancer cell progression and immune suppression such as WNT and TGF-β signaling pathway. Para-inflammation and type-II interferon pathways were activated in NRGPI-high patients with an increased infiltration of Tregs and M2 macrophage indicating an exhausted immune phenotype of the tumor microenvironment. These molecular characteristics were mainly driven by the eight NRGPI oncogenes (CYTL1, PLCL1, CNTN1, GRP, APOD, GPX3, FCN1, SERPINE1) as validated in the gastric cancer cell lines and clinical samples. NRGPI-high patients showed sensitivity to a number of targeted agents, in particular, the tyrosine kinase inhibitors.

Conclusions

Necroptosis appears to play a critical role in the development of gastric cancer, prognosis and shaping of its tumor immune microenvironment. NRGPI can be used as a promising prognostic biomarker to identify gastric cancer patients with a cold tumor immune microenvironment and poor prognosis who may response to selected molecular targeted therapy.

Development of necroptosis-related gene signature to predict the prognosis of colon adenocarcinoma

Colon adenocarcinoma (COAD) is a common malignancy and has a high mortality rate. However, the current tumor node metastasis (TNM) staging system is inadequate for prognostic assessment of COAD patients. Therefore, there is an urgent need to identify reliable biomarkers for the prognosis COAD patients. The aberrant expression of necroptosis-related genes (NRGs) is reported to be associated with tumorigenesis and metastasis. In the present work, we compared the expression profiles of NRGs between COAD patients and normal individuals. Based on seven differentially expressed NRGs, a risk score was defined to predict the prognosis of COAD patients. The validation results from both training and independent external cohorts demonstrated that the risk score is able to distinguish the high and low risk COAD patients with higher accuracies, and is independent of the other clinical factors. To facilitate its clinical use, by integrating the proposed risk score, a nomogram was built to predict the risk of individual COAD patients. The C-index of the nomogram is 0.75, indicating the reliability of the nomogram in predicting survival rates. Furthermore, two candidate drugs, namely dapsone and xanthohumol, were screed out and validated by molecular docking, which hold the potential for the treatment of COAD. These results will provide novel clues for the diagnosis and treatment of COAD.

Necroptosis: A Pathogenic Negotiator in Human Diseases

Over the past few decades, mechanisms of programmed cell death have attracted the scientific community because they are involved in diverse human diseases. Initially, apoptosis was considered as a crucial mechanistic pathway for programmed cell death; recently, an alternative regulated mode of cell death was identified, mimicking the features of both apoptosis and necrosis. Several lines of evidence have revealed that dysregulation of necroptosis leads to pathological diseases such as cancer, cardiovascular, lung, renal, hepatic, neurodegenerative, and inflammatory diseases. Regulated forms of necrosis are executed by death receptor ligands through the activation of receptor-interacting protein kinase (RIPK)-1/3 and mixed-lineage kinase domain-like (MLKL), resulting in the formation of a necrosome complex. Many papers based on genetic and pharmacological studies have shown that RIPKs and MLKL are the key regulatory effectors during the progression of multiple pathological diseases. This review focused on illuminating the mechanisms underlying necroptosis, the functions of necroptosis-associated proteins, and their influences on disease progression. We also discuss numerous natural and chemical compounds and novel targeted therapies that elicit beneficial roles of necroptotic cell death in malignant cells to bypass apoptosis and drug resistance and to provide suggestions for further research in this field.

A novel necroptosis-related gene signature associated with immune landscape for predicting the prognosis of papillary thyroid cancer

Background: Necroptosis, a type of programmed cell death, has been implicated in a variety of cancer-related biological processes. However, the roles of necroptosis-related genes in thyroid cancer yet remain unknown.

Methods: A necroptosis-related gene signature was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis and Cox regression analysis. The predictive value of the prognostic signature was validated in an internal cohort. Additionally, the single-sample gene set enrichment analysis (ssGSEA) was used to examine the relationships between necroptosis and immune cells, immunological functions, and immune checkpoints. Next, the modeled genes expressions were validated in 96 pairs of clinical tumor and normal tissue samples. Finally, the effects of modeled genes on PTC cells were studied by RNA interference approaches in vitro.

Results: In this study, the risk signature of seven necroptosis-related genes was created to predict the prognosis of papillary thyroid cancer (PTC) patients, and all patients were divided into high- and low-risk groups. Patients in the high-risk group fared worse in terms of overall survival than those in the low-risk group. The area under the curve (AUC) of the receiving operating characteristic (ROC) curves proved the predictive capability of created signature. The risk score was found to be an independent risk factor for prognosis in multivariate Cox analysis. The low-risk group showed increased immune cell infiltration and immunological activity, implying that they might respond better to immune checkpoint inhibitor medication. Next, GEO database and qRT-PCR in 96 pairs of matched tumorous and non-tumorous tissues were used to validate the expression of the seven modeled genes in PTCs, and the results were compatible with TCGA database. Finally, overexpression of IPMK, KLF9, SPATA2 could significantly inhibit the proliferation, invasion and migration of PTC cells.

Conclusion: The created necroptosis associated risk signature has the potential to have prognostic capability in PTC for patient outcome. The findings of this study could pave the way for further research into the link between necroptosis and tumor immunotherapy.

The Role of Programmed Necrosis in Colorectal Cancer

Simple Summary

Necrosis is a type of cell death characterized by plasma membrane rupture and the induction of inflammation. This review focuses on colorectal cancer and outlines the role of programmed necrosis in tumor development. Potential strategies for anti-tumor treatment via targeting programmed necrosis are also discussed.

Abstract

For quite a long time, necrosis was considered a chaotic and unorganized form of cell death. However, studies conducted during the past few decades unveiled multiple types of programmed necrosis, such as necroptosis, pyroptosis and ferroptosis. These types of programmed necrosis have been shown to play crucial roles in mediating pathological processes, including tumorigenesis. Almost all key mediators, such as RIPK3 and MLKL in necroptosis, GSDMD and caspase 1/11 in pyroptosis and GPX4 in ferroptosis, are highly expressed in intestinal epithelial cells (IECs). An aberrant increase or decrease in programmed necrosis in IECs has been connected to intestinal disorders. Here, we review the pathways of programmed necrosis and the specific consequences of regulated necrosis in colorectal cancer (CRC) development. Translational aspects of programmed necrosis induction as a novel therapeutic alternative against CRC are also discussed.

Regulated cell death (RCD) in cancer: key pathways and targeted therapies

Regulated cell death (RCD), also well-known as programmed cell death (PCD), refers to the form of cell death that can be regulated by a variety of biomacromolecules, which is distinctive from accidental cell death (ACD). Accumulating evidence has revealed that RCD subroutines are the key features of tumorigenesis, which may ultimately lead to the establishment of different potential therapeutic strategies. Hitherto, targeting the subroutines of RCD with pharmacological small-molecule compounds has been emerging as a promising therapeutic avenue, which has rapidly progressed in many types of human cancers. Thus, in this review, we focus on summarizing not only the key apoptotic and autophagy-dependent cell death signaling pathways, but the crucial pathways of other RCD subroutines, including necroptosis, pyroptosis, ferroptosis, parthanatos, entosis, NETosis and lysosome-dependent cell death (LCD) in cancer. Moreover, we further discuss the current situation of several small-molecule compounds targeting the different RCD subroutines to improve cancer treatment, such as single-target, dual or multiple-target small-molecule compounds, drug combinations, and some new emerging therapeutic strategies that would together shed new light on future directions to attack cancer cell vulnerabilities with small-molecule drugs targeting RCD for therapeutic purposes.