Necroptosis in Immuno-Oncology and Cancer Immunotherapy

A landscape of checkpoint blockade resistance in cancer: underlying mechanisms and current strategies to overcome resistance

The discovery of immune checkpoints and the development of immune checkpoint inhibitors (ICI) have achieved a durable response in advanced-stage cancer patients. However, there is still a high proportion of patients who do not benefit from ICI therapy due to a lack of response when first treated (primary resistance) or detection of disease progression months after objective response is observed (acquired resistance). Here, we review the current FDA-approved ICI for the treatment of certain solid malignancies, evaluate the contrasting responses to checkpoint blockade in different cancer types, explore the known mechanisms associated with checkpoint blockade resistance (CBR), and assess current strategies in the field that seek to overcome these mechanisms. In order to improve current therapies and develop new ones, the immunotherapy field still has an unmet need in identifying other molecules that act as immune checkpoints, and uncovering other mechanisms that promote CBR.

PBI-05204, a supercritical CO2 extract of Nerium oleander, suppresses glioblastoma stem cells by inhibiting GRP78 and inducing programmed necroptotic cell death

Successful treatment of glioblastoma multiforme (GBM), an aggressive form of primary brain neoplasm, mandates the need to develop new therapeutic strategies. In this study, we investigated the potential of PBI-05204 in targeting GBM stem cells (GSCs) and the underlying mechanisms. Treatment with PBI-05204 significantly reduced both the number and size of tumor spheres derived from patient-derived GSCs (GBM9, GSC28 and TS543), and suppressed the tumorigenesis of GBM9 xenografts. Moreover, PBI-05204 treatment led to a significant decrease in the expression of CD44 and NANOG, crucial markers of progenitor stem cells, in GBM9 and GSC28 GSCs. This treatment also down-regulated GRP78 expression in both GSC types. Knocking down GRP78 expression through GRP78 siRNA transfection in GBM9 and GSC28 GSCs also resulted in reduced spheroid size and CD44 expression. Combining PBI-05204 with GRP78 siRNA further decreased spheroid numbers compared to GRP78 siRNA treatment alone. PBI-05204 treatment led to increased expression of pRIP1K and pRIP3K, along with enhanced binding of RIPK1/RIPK3 in GBM9 and GSC28 cells, resembling the effects observed in GRP78-silenced GSCs, suggesting that PBI-05204 induced necroptosis in these cells. Furthermore, oleandrin, a principle active cardiac glycoside component of PBI-05204, showed the ability to inhibit the self-renewal capacity in GSCs. These findings highlight the potential of PBI-05204 as a promising candidate for the development of novel therapies that target GBM stem cells.

Integrated single-cell and bulk RNA-Seq analysis enhances prognostic accuracy of PD-1/PD-L1 immunotherapy response in lung adenocarcinoma through necroptotic anoikis gene signatures

In addition to presenting significant diagnostic and treatment challenges, lung adenocarcinoma (LUAD) is the most common form of lung cancer. Using scRNA-Seq and bulk RNA-Seq data, we identify three genes referred to as HMR, FAM83A, and KRT6A these genes are related to necroptotic anoikis-related gene expression. Initial validation, conducted on the GSE50081 dataset, demonstrated the model's ability to categorize LUAD patients into high-risk and low-risk groups with significant survival differences. This model was further applied to predict responses to PD-1/PD-L1 blockade therapies, utilizing the IMvigor210 and GSE78220 cohorts, and showed strong correlation with patient outcomes, highlighting its potential in personalized immunotherapy. Further, LUAD cell lines were analyzed using quantitative PCR (qPCR) and Western blot analysis to confirm their expression levels, further corroborating the model's relevance in LUAD pathophysiology. The mutation landscape of these genes was also explored, revealing their broad implication in various cancer types through a pan-cancer analysis. The study also delved into molecular subclustering, revealing distinct expression profiles and associations with different survival outcomes, emphasizing the model's utility in precision oncology. Moreover, the diversity of immune cell infiltration, analyzed in relation to the necroptotic anoikis signature, suggested significant implications for immune evasion mechanisms in LUAD. While the findings present a promising stride towards personalized LUAD treatment, especially in immunotherapy, limitations such as the retrospective nature of the datasets and the need for larger sample sizes are acknowledged. Prospective clinical trials and further experimental research are essential to validate these findings and enhance the clinical applicability of our prognostic model.

Revealing the role of necroptosis microenvironment: FCGBP + tumor-associated macrophages drive primary liver cancer differentiation towards cHCC-CCA or iCCA

Previous research has demonstrated that the conversion of hepatocellular carcinoma (HCC) to intrahepatic cholangiocarcinoma (iCCA) can be stimulated by manipulating the tumor microenvironment linked with necroptosis. However, the specific cells regulating the necroptosis microenvironment have not yet been identified. Additionally, further inquiry into the mechanism of how the tumor microenvironment regulates necroptosis and its impact on primary liver cancer(PLC) progression may be beneficial for precision therapy. We recruited a single-cell RNA sequencing dataset (scRNA-seq) with 34 samples from 4 HCC patients and 3 iCCA patients, and a Spatial Transcriptomic (ST) dataset including one each of HCC, iCCA, and combined hepatocellular-cholangiocarcinoma (cHCC-CCA). Quality control, dimensionality reduction and clustering were based on Seurat software (v4.2.2) process and batch effects were removed by harmony (v0.1.1) software. The pseudotime analysis (also known as cell trajectory) in the single cell dataset was performed by monocle2 software (v2.24.0). Calculation of necroptosis fraction was performed by AUCell (v1.16.0) software. Switch gene analysis was performed by geneSwitches(v0.1.0) software. Dimensionality reduction, clustering, and spatial image in ST dataset were performed by Seurat (v4.0.2). Tumor cell identification, tumor subtype characterization, and cell type deconvolution in spot were performed by SpaCET (v1.0.0) software. Immunofluorescence and immunohistochemistry experiments were used to prove our conclusions. Analysis of intercellular communication was performed using CellChat software (v1.4.0). ScRNA-seq analysis of HCC and iCCA revealed that necroptosis predominantly occurred in the myeloid cell subset, particularly in FCGBP + SPP1 + tumor-associated macrophages (TAMs), which had the highest likelihood of undergoing necroptosis. The existence of macrophages undergoing necroptosis cell death was further confirmed by immunofluorescence. Regions of HCC with poor differentiation, cHCC-CCA with more cholangiocarcinoma features, and the tumor region of iCCA shared spatial colocalization with FCGBP + macrophages, as confirmed by spatial transcriptomics, immunohistochemistry and immunofluorescence. Pseudotime analysis showed that premalignant cells could progress into two directions, one towards HCC and the other towards iCCA and cHCC-CCA. Immunofluorescence and immunohistochemistry experiments demonstrated that the number of macrophages undergoing necroptosis in cHCC-CCA was higher than in iCCA and HCC, the number of macrophages undergoing necroptosis in cHCC-CCA with cholangiocarcinoma features was more than in cHCC-CCA with hepatocellular carcinoma features. Further investigation showed that myeloid cells with the highest necroptosis score were derived from the HCC_4 case, which had a severe inflammatory background on pathological histology and was likely to progress towards iCCA and cHCC-CCA. Switchgene analysis indicated that S100A6 may play a significant role in the progression of premalignant cells towards iCCA and cHCC-CCA. Immunohistochemistry confirmed the expression of S100A6 in PLC, the more severe inflammatory background of the tumor area, the more cholangiocellular carcinoma features of the tumor area, S100A6 expression was higher. The emergence of necroptosis microenvironment was found to be significantly associated with FCGBP + SPP1 + TAMs in PLC. In the presence of necroptosis microenvironment, premalignant cells appeared to transform into iCCA or cHCC-CCA. In contrast, without a necroptosis microenvironment, premalignant cells tended to develop into HCC, exhibiting amplified stemness-related genes (SRGs) and heightened malignancy.

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.

LncRNAs in necroptosis: Deciphering their role in cancer pathogenesis and therapy

Necroptosis, a controlled type of cell death that is different from apoptosis, has become a key figure in the aetiology of cancer and offers a possible target for treatment. A growing number of biological activities, including necroptosis, have been linked to long noncoding RNAs (lncRNAs), a varied family of RNA molecules with limited capacity to code for proteins. The complex interactions between LncRNAs and important molecular effectors of necroptosis, including mixed lineage kinase domain-like pseudokinase (MLKL) and receptor-interacting protein kinase 3 (RIPK3), will be investigated. We will explore the many methods that LncRNAs use to affect necroptosis, including protein-protein interactions, transcriptional control, and post-transcriptional modification. Additionally, the deregulation of certain LncRNAs in different forms of cancer will be discussed, highlighting their dual function in influencing necroptotic processes as tumour suppressors and oncogenes. The goal of this study is to thoroughly examine the complex role that LncRNAs play in controlling necroptotic pathways and how that regulation affects the onset and spread of cancer. In the necroptosis for cancer treatment, this review will also provide insight into the possible therapeutic uses of targeting LncRNAs. Techniques utilising LncRNA-based medicines show promise in controlling necroptotic pathways to prevent cancer from spreading and improve the effectiveness of treatment.

Necroptosis-related KLRB1 was a potent tumor suppressor and immunotherapy determinant in breast cancer

Breast cancer is a multifaceted and diverse illness that impacts millions of people globally. Identifying the underlying causes of BRCA and creating efficient treatment plans are urgent. Necroptosis is widely involved in cancer development. However, the specific roles of necroptosis in cancer immunotherapy of breast cancer have not been explored. In this study, we aim to establish the connection between necroptosis and immunotherapy in BRCA. TCGA, METABRIC, GSE103091, GSE159956, and GSE96058 were included for bioinformatics analysis. NMF and CoxBoost algorithms were used to develop the necroptosis-related patterns and model, respectively. A necroptosis-related model was developed and determined KLRB1 as a critical tumor suppressor by in vitro validation. The mutation characteristics, immune characteristics, and molecular functions of KLRB1 were explored. We further examined how necroptosis-related KLRB1 functions in BRCA as a powerful tumor suppressor and regulates the activity of macrophages by in vitro validation, including CCK8, EdU, and Transwell assays. KLRB1 was also revealed to be an immunotherapy determinant.

The dance of macrophage death: the interplay between the inevitable and the microenvironment

Macrophages are highly plastic cells ubiquitous in various tissues, where they perform diverse functions. They participate in the response to pathogen invasion and inflammation resolution following the immune response, as well as the maintenance of homeostasis and proper tissue functions. Macrophages are generally considered long-lived cells with relatively strong resistance to numerous cytotoxic factors. On the other hand, their death seems to be one of the principal mechanisms by which macrophages perform their physiological functions or can contribute to the development of certain diseases. In this review, we scrutinize three distinct pro-inflammatory programmed cell death pathways - pyroptosis, necroptosis, and ferroptosis - occurring in macrophages under specific circumstances, and explain how these cells appear to undergo dynamic yet not always final changes before ultimately dying. We achieve that by examining the interconnectivity of these cell death types, which in macrophages seem to create a coordinated and flexible system responding to the microenvironment. Finally, we discuss the complexity and consequences of pyroptotic, necroptotic, and ferroptotic pathway induction in macrophages under two pathological conditions - atherosclerosis and cancer. We summarize damage-associated molecular patterns (DAMPs) along with other microenvironmental factors, macrophage polarization states, associated mechanisms as well as general outcomes, as such a comprehensive look at these correlations may point out the proper methodologies and potential therapeutic approaches.

Classification of molecular subtypes for colorectal cancer and development of a prognostic model based on necroptosis-related genes

Background

Necroptosis could regulate immunity in cancers, and stratification of colorectal cancer (CRC) subtypes based on key genes related to necroptosis might be a novel strategy for CRC treatment.

Method

The RNA-sequencing data of CRC and other 31 types of cancers were obtained from The Cancer Genome Atlas (TCGA) database. Consensus clustering was performed based on protein-coding genes (PCGs) related to necroptosis score calculated by single sample gene set enrichment analysis (ssGSEA). Module genes showing a significant positive correlation with the necroptosis score were identified by weighted correlation network analysis (WGCNA) and further used to develop a risk stratification model applying least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. The risks score for each sample in CRC cohorts, immunotherapy cohorts and pan-cancer study cohorts was calculated.

Result

Two subgroups (C1 cluster and C2 cluster) of CRC were identified based on the necroptosis score. Compared with C1 cluster, the survival possibility of C2 cluster was greatly reduced, the levels of necroptosis score, immune cell infiltration, immune score and expression of immune checkpoint molecules were significantly increased and immunotherapy response was less active. Low-risk patients defined by the risk model had a significant survival advantage than high-risk counterparts in both CRC and the other 31 cancer types. Furthermore, the risk model was also more efficient than the Tumor Immune Dysfunction and Exclusion (TIDE) tool in predicting OS and immunotherapy response for the samples in the immunotherapy cohort.

Conclusion

CRC patients were classified by necroptosis score-related PCGs, and a risk model was designed to evaluate the immunotherapy and prognosis of patients with CRC. The current molecular subtype and prognostic model could help stratify patients with different risks and predict their prognosis and immunotherapy sensitivity.

Optimal strategies of oncolytic virus-bortezomib therapy via the apoptotic, necroptotic, and oncolysis signaling network

Bortezomib and oncolytic virotherapy are two emerging targeted cancer therapies. Bortezomib, a proteasome inhibitor, disrupts protein degradation in cells, leading to the accumulation of unfolded proteins that induce apoptosis. On the other hand, virotherapy uses genetically modified oncolytic viruses (OVs) to infect cancer cells, trigger cell lysis, and activate anti-tumor response. Despite progress in cancer treatment, identifying administration protocols for therapeutic agents remains a significant concern, aiming to strike a balance between efficacy, minimizing toxicity, and administrative costs. In this work, optimal control theory was employed to design a cost-effective and efficient co-administration protocols for bortezomib and OVs that could significantly diminish the population of cancer cells via the cell death program with the NF$ \kappa $B-BAX-RIP1 signaling network. Both linear and quadratic control strategies were explored to obtain practical treatment approaches by adapting necroptosis protocols to efficient cell death programs. Our findings demonstrated that a combination therapy commencing with the administration of OVs followed by bortezomib infusions yields an effective tumor-killing outcome. These results could provide valuable guidance for the development of clinical administration protocols in cancer treatment.

Exploring beyond Common Cell Death Pathways in Oral Cancer: A Systematic Review

Oral squamous cell carcinoma (OSCC) is the most common and lethal type of head and neck cancer in the world. Variable response and acquisition of resistance to traditional therapies show that it is essential to develop novel strategies that can provide better outcomes for the patient. Understanding of cellular and molecular mechanisms of cell death control has increased rapidly in recent years. Activation of cell death pathways, such as the emerging forms of non-apoptotic programmed cell death, including ferroptosis, pyroptosis, necroptosis, NETosis, parthanatos, mitoptosis and paraptosis, may represent clinically relevant novel therapeutic opportunities. This systematic review summarizes the recently described forms of cell death in OSCC, highlighting their potential for informing diagnosis, prognosis and treatment. Original studies that explored any of the selected cell deaths in OSCC were included. Electronic search, study selection, data collection and risk of bias assessment tools were realized. The literature search was carried out in four databases, and the extracted data from 79 articles were categorized and grouped by type of cell death. Ferroptosis, pyroptosis, and necroptosis represented the main forms of cell death in the selected studies, with links to cancer immunity and inflammatory responses, progression and prognosis of OSCC. Harnessing the potential of these pathways may be useful in patient-specific prognosis and individualized therapy. We provide perspectives on how these different cell death types can be integrated to develop decision tools for diagnosis, prognosis, and treatment of OSCC.

Glioma: bridging the tumor microenvironment, patient immune profiles and novel personalized immunotherapy

Glioma is the most common primary brain tumor, characterized by a consistently high patient mortality rate and a dismal prognosis affecting both survival and quality of life. Substantial evidence underscores the vital role of the immune system in eradicating tumors effectively and preventing metastasis, underscoring the importance of cancer immunotherapy which could potentially address the challenges in glioma therapy. Although glioma immunotherapies have shown promise in preclinical and early-phase clinical trials, they face specific limitations and challenges that have hindered their success in further phase III trials. Resistance to therapy has been a major challenge across many experimental approaches, and as of now, no immunotherapies have been approved. In addition, there are several other limitations facing glioma immunotherapy in clinical trials, such as high intra- and inter-tumoral heterogeneity, an inherently immunosuppressive microenvironment, the unique tissue-specific interactions between the central nervous system and the peripheral immune system, the existence of the blood-brain barrier, which is a physical barrier to drug delivery, and the immunosuppressive effects of standard therapy. Therefore, in this review, we delve into several challenges that need to be addressed to achieve boosted immunotherapy against gliomas. First, we discuss the hurdles posed by the glioma microenvironment, particularly its primary cellular inhabitants, in particular tumor-associated microglia and macrophages (TAMs), and myeloid cells, which represent a significant barrier to effective immunotherapy. Here we emphasize the impact of inducing immunogenic cell death (ICD) on the migration of Th17 cells into the tumor microenvironment, converting it into an immunologically "hot" environment and enhancing the effectiveness of ongoing immunotherapy. Next, we address the challenge associated with the accurate identification and characterization of the primary immune profiles of gliomas, and their implications for patient prognosis, which can facilitate the selection of personalized treatment regimens and predict the patient's response to immunotherapy. Finally, we explore a prospective approach to developing highly personalized vaccination strategies against gliomas, based on the search for patient-specific neoantigens. All the pertinent challenges discussed in this review will serve as a compass for future developments in immunotherapeutic strategies against gliomas, paving the way for upcoming preclinical and clinical research endeavors.

Modulation of tumor microenvironment by targeting histone acetylation in bladder cancer

Alterations in the epigenetic machinery in both tumor and immune cells contribute to bladder cancer (BC) development, constituting a promising target as an alternative therapeutic option. Here, we have explored the effects of a novel histone deacetylase (HDAC) inhibitor CM-1758, alone or in combination with immune checkpoint inhibitors (ICI) in BC. We determined the antitumor effects of CM-1758 in various BC cell lines together with the induction of broad transcriptional changes, with focus on the epigenetic regulation of PD-L1. Using an immunocompetent syngeneic mouse model of metastatic BC, we studied the effects of CM-1758 alone or in combination with anti-PD-L1 not only on tumor cells, but also in the tumor microenvironment. In vitro, we found that CM-1758 has cytotoxic and cytostatic effects either by inducing apoptosis or cell cycle arrest in BC cells at low micromolar levels. PD-L1 is epigenetically regulated by histone acetylation marks and is induced after treatment with CM-1758. We also observed that treatment with CM-1758 led to an important delay in tumor growth and a higher CD8 + T cell tumor infiltration. Moreover, anti-PD-L1 alone or in combination with CM-1758 reprogramed macrophage differentiation towards a M1-like polarization state and increased of pro-inflammatory cytokines systemically, yielding potential further antitumor effects. Our results suggest the possibility of combining HDAC inhibitors with immunotherapies for the management of advanced metastatic BC.

The cell stress and immunity cycle in cancer: Toward next generation of cancer immunotherapy

The cellular stress and immunity cycle is a cornerstone of organismal homeostasis. Stress activates intracellular and intercellular communications within a tissue or organ to initiate adaptive responses aiming to resolve the origin of this stress. If such local measures are unable to ameliorate this stress, then intercellular communications expand toward immune activation with the aim of recruiting immune cells to effectively resolve the situation while executing tissue repair to ameliorate any damage and facilitate homeostasis. This cellular stress-immunity cycle is severely dysregulated in diseased contexts like cancer. On one hand, cancer cells dysregulate the normal cellular stress responses to reorient them toward upholding growth at all costs, even at the expense of organismal integrity and homeostasis. On the other hand, the tumors severely dysregulate or inhibit various components of organismal immunity, for example, by facilitating immunosuppressive tumor landscape, lowering antigenicity, and increasing T-cell dysfunction. In this review we aim to comprehensively discuss the basis behind tumoral dysregulation of cellular stress-immunity cycle. We also offer insights into current understanding of the regulators and deregulators of this cycle and how they can be targeted for conceptualizing successful cancer immunotherapy regimen.

Identification and validation of necroptosis-related gene signatures to predict clinical outcomes and therapeutic responses in acute myeloid leukemia

BACKGROUND

Necroptosis is a tightly regulated form of necrotic cell death that promotes inflammation and contributes to disease development. However, the potential roles of necroptosis-related genes (NRGs) in acute myeloid leukemia (AML) have not been elucidated fully.

METHODS

We conducted a study to identify a robust biomarker signature for predicting the prognosis and immunotherapy efficacy based on NRGs in AML. We analyzed the genetic and transcriptional alterations of NRGs in 151 patients with AML. Then, we identified three necroptosis clusters. Moreover, a necroptosis score was constructed and assessed based on the differentially expressed genes (DEGs) between the three necroptosis clusters.

RESULTS

Three necroptosis clusters were correlated with clinical characteristics, prognosis, the tumor microenvironment, and infiltration of immune cells. A high necroptosis score was positively associated with a poor prognosis, immune-cell infiltration, expression of programmed cell death 1/programmed cell death ligand 1 (PD-1/PD-L1), immune score, stromal score, interferon-gamma (IFNG), merck18, T-cell dysfunction-score signatures, and cluster of differentiation-86, but negatively correlated with tumor immune dysfunction and exclusion score, myeloid-derived suppressor cells, and M2-type tumor-associated macrophages. Our observations indicated that a high necroptosis score might contribute to immune evasion. More interestingly, AML patients with a high necroptosis score may benefit from treatment based on immune checkpoint blockade.

CONCLUSIONS

Consequently, our findings may contribute to deeper understanding of NRGs in AML, and facilitate assessment of the prognosis and treatment strategies.

The necroptosis signature and molecular mechanism of lung squamous cell carcinoma

BACKGROUND

Given the poor prognosis of lung squamous cell carcinoma (LUSC), the aim of this study was to screen for new prognostic biomarkers.

METHODS

The TGCA_LUSC dataset was used as the training set, and GSE73403 was used as the validation set. The genes involved in necroptosis-related pathways were acquired from the KEGG database, and the differential genes between the LUSC and normal samples were identified using the GSEA. A necroptosis signature was constructed by survival analysis, and its correlation with patient prognosis and clinical features was evaluated. The molecular characteristics and drug response associated with the necroptosis signature were also identified. The drug candidates were then validated at the cellular level.

RESULTS

The TCGA_LUSC dataset included 51 normal samples and 502 LUSC samples. The GSE73403 dataset included 69 samples. 159 genes involved in necroptosis pathways were acquired from the KEGG database, of which most showed significant differences between two groups in terms of genomic, transcriptional and methylation alterations. In particular, CHMP4C, IL1B, JAK1, PYGB and TNFRSF10B were significantly associated with the survival (p < 0.05) and were used to construct the necroptosis signature, which showed significant correlation with patient prognosis and clinical features in univariate and multivariate analyses (p < 0.05). Furthermore, CHMP4C, IL1B, JAK1 and PYGB were identified as potential targets of trametinib, selumetinib, SCH772984, PD 325901 and dasatinib. Finally, knockdown of these genes in LUSC cells increased chemosensitivity to those drugs.

CONCLUSION

We identified a necroptosis signature in LUSC that can predict prognosis and identify patients who can benefit from targeted therapies.

Identification of necroptosis-related lncRNAs for prognosis prediction and screening of potential drugs in patients with colorectal cancer

BACKGROUND

Tumor recurrence and metastasis lead to a poor prognosis in colorectal cancer (CRC). Necroptosis is closely related to the tumor microenvironment (TME) and affects tumor recurrence and metastasis. We aimed to stratify CRC patients according to necroptosis-related long noncoding RNAs (lncRNAs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also screen potential immunotherapy drugs.

AIM

To stratify CRC patients according to necroptosis-related lncRNAs (NRLs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also screen potential immunotherapy drugs.

METHODS

LncRNA expression profiles were collected from The Cancer Genome Atlas. NRLs were identified by coexpression analysis. Cox regression analysis identified a NRL signature. Then, the value of this signature was comprehensively and multidimensionally evaluated, and its reliability for CRC prognosis prediction was assessed with clinical CRC data and compared with that of six other lncRNA signatures. Gene set enrichment analysis, TME analysis and half-maximal inhibitory concentration (IC₅₀) prediction were also performed according to the risk score (RS) of the signature.

RESULTS

An 8-lncRNA signature significantly associated with overall survival (OS) was constructed, and its reliability was validated with clinical CRC data. Most of the areas under the receiver operating characteristic curves (AUCs) values for 1-, 3- and 5-year OS for this signature were higher than those for the other six lncRNA signatures. OS, disease-specific survival and the progression-free interval were all significantly poorer in the high-risk group. The RS of the signature showed good concordance with the predicted prognosis, with AUCs for 1-, 3- and 5-year OS of 0.79, 0.81 and 0.77, respectively. Additionally, the calibration plots for this signature combined with clinical factors showed that this combination could effectively improve the ability to predict OS. The RS was correlated with tumor stage, lymph node metastasis and distant metastasis. Most of the enriched Kyoto Encyclopedia of Genes and Genomes and Gene Ontology terms were tumor metastasis-related pathways in the high-risk group; these patients showed greater infiltration of immunosuppressive cells, such as cancer-associated fibroblasts, hematopoietic stem cells and M2 macrophages, but less infiltration of infiltrating antitumor effector immune cells, such as cluster of differentiation 8⁺ T cells and regulatory T cells (Tregs). We explored additional potential immune checkpoint genes and potential immunotherapeutic and chemotherapeutic drugs with relatively low IC₅₀ values.

CONCLUSION

We identified an NRL signature with strong fidelity that could stably predict prognosis and might be an indicator of the TME of CRC. Furthermore, additional potential immunotherapeutic and chemotherapeutic drugs were explored.

A systematic framework for identifying prognostic necroptosis-related lncRNAs and verification of lncRNA CRNDE/miR-23b-3p/IDH1 regulatory axis in glioma

Glioma remains the most frequent malignancy of the central nervous system. Recently, necroptosis has been identified as a cell death process that mediates the proliferation and development of tumor cells. LncRNAs play a key role in the diagnosis and treatment of various diseases. However, the impact that necrosis-related lncRNAs (NRLs) have on glioma remains unclear. In our studies, we selected 9 NRLs to construct a prognostic model. Meanwhile, we assessed the survival curves of these 9 NRLs. Our findings found ADGRA1-AS1 and WAC-AS1 were protective lncRNAs, while MIR210HG, LINC01503, CRNDE, HOXC-AS1, ZIM2-AS1, MIR22HG and PLBD1-AS1 were risk lncRNAs. Specifically, 12 immune cells, 25 immune-correlated pathways, and TME score were differentially expressed in the both risk groups. Additionally, the study predicted and validated the necroptosis-related lncRNA CRNDE/miR-23b-3p/IDH1 axis. CRNDE was strongly expressed in glioma specimens and several cell lines. Inhibiting CRNDE resulted in a substantial reduction in the proliferation and migration of U-118MG and U251 cells. Furthermore, the study predicted that CRNDE may exhibit oncogenic features by adsorbing miR-23b-3p and positively regulating IDH1 expression. Overall, the study constructed a prognostic model in glioma, and predicted a lncRNA CRNDE/miR-23b-3p/IDH1 axis, which could potentially be useful for gene therapy of glioma.

A comprehensive analysis of the potential role of necroptosis in hepatocellular carcinoma using single-cell RNA Seq and bulk RNA Seq

PURPOSE

Necroptosis plays an essential role in oncogenesis and tumor progression in hepatocellular carcinoma (HCC). This study aimed to investigate the role of necroptosis in the development and progression of HCC. Specifically, we constructed a prognostic prediction model using necroptosis-associated genes (NAGs) to predict patient outcomes.

METHODS

Using data from The Cancer Genome Atlas (TCGA) database, we analyzed gene expression and clinical data. We identified a 5-gene model associated with NAGs and explored genetic features and immune cell infiltration using the CIBERSORT algorithm. In addition, we conducted single-cell RNA sequencing to investigate the potential role of necroptosis in HCC.

RESULTS

We constructed a 5-gene prognostic model based on NAGs that demonstrated excellent predictive accuracy in both training and validation sets. Using multifactorial cox regression analysis, we confirmed the risk score derived from the model as an independent predictor of prognosis, surpassing other clinical characteristics. Patients with high risk scores had significantly worse prognosis than those with low risk scores. To enhance the clinical utility of the necroptosis score, we constructed an accurate nomogram. Additionally, we compared metabolic pathway and immune microenvironment differences between HCC tumors with high and low risk scores. Our single-cell RNA sequencing analyses revealed that necroptosis in HCC was primarily associated with a specific subset of macrophages.

CONCLUSIONS

Our study revealed the presence of two distinct necroptosis subtypes in HCC and developed a robust prognostic model with exceptional predictive accuracy. We observed significantly higher infiltration of M0 macrophages in the high-risk group. We propose that rescuing cytochrome c metabolism in HCC could serve as a potential therapeutic strategy. Furthermore, at a single-cell resolution, our analysis identified myeloid cells as the primary cells exhibiting necroptosis. Specifically, macrophages expressing CD5L, CETP, and MARCO, which may belong to a subset of tissue-resident macrophages, were found to be highly susceptible to necroptosis. These findings suggest the involvement of this specific macrophage subset in potential antitumor therapies. Our study provides novel insights into predicting patient prognosis and developing personalized therapeutic approaches for HCC.

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.

Identification and validation of a necroptosis-related gene prognostic signature for colon adenocarcinoma

Background

Necroptosis is a novel programmed cell death pathway proposed in 2005, which is mainly activated by the tumor necrosis factor (TNF) family and mediates cellular disassembly via receptor interacting serine/threonine kinase 1 (RIPK1), receptor interacting serine/threonine kinase 3 (RIPK3) and mixed lineage kinase domain like pseudokinase (MLKL). We tried to analyze the relationship of necroptosis-related genes (NRGs) expression with colon adenocarcinoma (COAD) and propose potential therapeutic targets through immunological analysis.

Methods

First, we evaluated the expression of NRGs in COAD patients and constructed a prognostic signature. The prognostic signature was validated using The Cancer Genome Atlas (TCGA)-COAD and GSE39582 datasets, respectively. And the Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and principal component analysis were used to evaluate the signature. Then we analyzed the enrichment of NRGs in the signature using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Finally, we analyzed the immunological characteristics of the COAD patients by single sample gene set enrichment analysis (ssGSEA) and predicted the possible immune checkpoints.

Results

We constructed a prognostic signature with 8 NRGs (RIPK3, MLKL, TRAF2, CXCL1, RBCK1, CDKN2A, JMJD7-PLA2G4B and CAMK2B). The Kaplan-Meier analysis, ROC curves, and principal component analysis demonstrated good predictivity of the signature. In addition, we constructed a nomogram with good individualized predictive ability (C-index =0.772). The immunological analysis revealed that the prognosis of COAD was associated with autoimmune function, and we proposed 10 potential therapeutic targets.

Conclusions

Overall, we constructed an NRGs prognostic signature and suggested potential therapeutic targets for the COAD treatment.

Plasma Membrane Channel TRPM4 Mediates Immunogenic Therapy-Induced Necrosis

Several emerging therapies kill cancer cells primarily by inducing necrosis. As necrosis activates immune cells, potentially, uncovering the molecular drivers of anticancer therapy-induced necrosis could reveal approaches for enhancing immunotherapy efficacy. To identify necrosis-associated genes, we performed a genome-wide CRISPR-Cas9 screen with negative selection against necrosis-inducing preclinical agents BHPI and conducted follow-on experiments with ErSO. The screen identified transient receptor potential melastatin member 4 (TRPM4), a calcium-activated, ATP-inhibited, sodium-selective plasma membrane channel. Cancer cells selected for resistance to BHPI and ErSO exhibited robust TRPM4 downregulation, and TRPM4 reexpression restored sensitivity to ErSO. Notably, TRPM4 knockout (TKO) abolished ErSO-induced regression of breast tumors in mice. Supporting a broad role for TRPM4 in necrosis, knockout of TRPM4 reversed cell death induced by four additional diverse necrosis-inducing cancer therapies. ErSO induced anticipatory unfolded protein response (a-UPR) hyperactivation, long-term necrotic cell death, and release of damage-associated molecular patterns that activated macrophages and increased monocyte migration, all of which was abolished by TKO. Furthermore, loss of TRPM4 suppressed the ErSO-induced increase in cell volume and depletion of ATP. These data suggest that ErSO triggers initial activation of the a-UPR but that it is TRPM4-mediated sodium influx and cell swelling, resulting in osmotic stress, which sustains and propagates lethal a-UPR hyperactivation. Thus, TRPM4 plays a pivotal role in sustaining lethal a-UPR hyperactivation that mediates the anticancer activity of diverse necrosis-inducing therapies.

SIGNIFICANCE

A genome-wide CRISPR screen reveals a pivotal role for TRPM4 in cell death and immune activation following treatment with diverse necrosis-inducing anticancer therapies, which could facilitate development of necrosis-based cancer immunotherapies.

A novel necroptosis related gene signature and regulatory network for overall survival prediction in lung adenocarcinoma

We downloaded the mRNA expression profiles of patients with LUAD and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and used the Least Absolute Shrinkage and Selection Operator Cox regression model to construct a multigene signature in the TCGA cohort, which was validated with patient data from the GEO cohort. Results showed differences in the expression levels of 120 necroptosis-related genes between normal and tumor tissues. An eight-gene signature (CYLD, FADD, H2AX, RBCK1, PPIA, PPID, VDAC1, and VDAC2) was constructed through univariate Cox regression, and patients were divided into two risk groups. The overall survival of patients in the high-risk group was significantly lower than of the patients in the low-risk group in the TCGA and GEO cohorts, indicating that the signature has a good predictive effect. The time-ROC curves revealed that the signature had a reliable predictive role in both the TCGA and GEO cohorts. Enrichment analysis showed that differential genes in the risk subgroups were associated with tumor immunity and antitumor drug sensitivity. We then constructed an mRNA-miRNA-lncRNA regulatory network, which identified lncRNA AL590666. 2/let-7c-5p/PPIA as a regulatory axis for LUAD. Real-time quantitative PCR (RT-qPCR) was used to validate the expression of the 8-gene signature. In conclusion, necroptosis-related genes are important factors for predicting the prognosis of LUAD and potential therapeutic targets.

Whole tumour cell-based vaccines: tuning the instruments to orchestrate an optimal antitumour immune response

Immunotherapy, particularly those based on immune checkpoint inhibitors (ICIs), has become a useful approach for many neoplastic diseases. Despite the improvements of ICIs in supporting tumour regression and prolonging survival, many patients do not respond or develop resistance to treatment. Thus, therapies that enhance antitumour immunity, such as anticancer vaccines, constitute a feasible and promising therapeutic strategy. Whole tumour cell (WTC) vaccines have been extensively tested in clinical studies as intact or genetically modified cells or tumour lysates, injected directly or loaded on DCs with distinct adjuvants. The essential requirements of WTC vaccines include the optimal delivery of a broad battery of tumour-associated antigens, the presence of tumour cell-derived molecular danger signals, and adequate adjuvants. These factors trigger an early and robust local innate inflammatory response that orchestrates an antigen-specific and proinflammatory adaptive antitumour response capable of controlling tumour growth by several mechanisms. In this review, the strengths and weaknesses of our own and others' experiences in studying WTC vaccines are revised to discuss the essential elements required to increase anticancer vaccine effectiveness.

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.

Development and validation of a novel necroptosis-related gene signature for predicting prognosis and therapeutic response in Ewing sarcoma

Ewing sarcoma (ES) is the second most common malignant bone tumor in children and has a poor prognosis due to early metastasis and easy recurrence. Necroptosis is a newly discovered cell death method, and its critical role in tumor immunity and therapy has attracted widespread attention. Thus, the emergence of necroptosis may provide bright prospects for the treatment of ES and deserves our further study. Here, based on the random forest algorithm, we identified 6 key necroptosis-related genes (NRGs) and used them to construct an NRG signature with excellent predictive performance. Subsequent analysis showed that NRGs were closely associated with ES tumor immunity, and the signature was also good at predicting immunotherapy and chemotherapy response. Next, a comprehensive analysis of key genes showed that RIPK1, JAK1, and CHMP7 were potential therapeutic targets. The Cancer Dependency Map (DepMap) results showed that CHMP7 is associated with ES cell growth, and the Gene Set Cancer Analysis (GSCALite) results revealed that the JAK1 mutation frequency was the highest. The expression of 3 genes was all negatively correlated with methylation and positively with copy number variation (CNV). Finally, an accurate nomogram was constructed with this signature and clinical traits. In short, this study constructed an accurate prognostic signature and identified 3 novel therapeutic targets against ES.

The Dual Role of Necroptosis in Pancreatic Ductal Adenocarcinoma

Pancreatic cancer (PC) is the seventh leading cause of cancer-related death. PC incidence has continued to increase by about 1% each year in both men and women. Although the 5-year relative survival rate of PC has increased from 3% to 12%, it is still the lowest among cancers. Hence, novel therapeutic strategies are urgently needed. Challenges in PC-targeted therapeutic strategies stem from the high PC heterogeneity and from the poorly understood interplay between cancer cells and the surrounding microenvironment. Signaling pathways that drive PC cell growth have been the subject of intense scrutiny and interest has been attracted by necroptosis, a distinct type of programmed cell death. In this review, we provide a historical background on necroptosis and a detailed analysis of the ongoing debate on the role of necroptosis in PC malignant progression.

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.

Necroptosis-related signatures identify two distinct hepatocellular carcinoma subtypes: Implications for predicting drug sensitivity and prognosis

Background

Necroptosis is associated with oncogenesis, tumor immunity and progression. This research aims to investigate the association of necroptosis-related genes with drug sensitivity and prognosis in hepatocellular carcinoma (HCC).

Methods

Based on necroptosis-related signatures, HCC patients retrieved from the TCGA database were categorized. Survival outcomes, mutation profile, immune microenvironment, and drug sensitivity between HCC subtypes were further compared. Then, LASSO analysis was performed to construct a necroptosis-related prognostic signature, which was further evaluated using another independent cohort.

Results

A total of 371 patients with HCC could be categorized into two necroptosis-related subtypes. About 36% of patients were allocated to subtype A, with worse survival, more mutant TP53, and a lower likelihood of immunotherapy response. In contrast, patients in subtype B had a favorable prognosis, with lower expression of immunosuppressive signatures but a lower abundance of B and CD8⁺ T-cell infiltration. The prognostic risk score calculated using the expression levels of nine genes involved in the necroptosis pathway (MLKL, FADD, XIAP, USP22, UHRF1, CASP8, RIPK3, ZBP1, and FAS) showed a significant association with tumor stage, histologic grade, and Child‒Pugh score. Additionally, the risk score model was proven to be accurate in both the training and independent external validation cohorts and performed better than the TNM staging system and three well-recognized risk score models.

Conclusions

Based on necroptosis-related signatures, we identified two HCC subtypes with distinctive immune microenvironments, mutation profiles, drug sensitivities, and survival outcomes. A novel well-performing prognostic model was further constructed.

Systematic analysis of the necroptosis index in pan-cancer and classification in discriminating the prognosis and immunotherapy responses of 1716 glioma patients

Necroptosis is a programmed form of necrotic cell death that serves as a host gatekeeper for defense against invasion by certain pathogens. Previous studies have uncovered the essential role of necroptosis in tumor progression and implied the potential for novel therapies targeting necroptosis. However, no comprehensive analysis of multi-omics data has been conducted to better understand the relationship between necroptosis and tumor. We developed the necroptosis index (NI) to uncover the effect of necroptosis in most cancers. NI not only correlated with clinical characteristics of multiple tumors, but also could influence drug sensitivity in glioma. Based on necroptosis-related differentially expressed genes, the consensus clustering was used to classify glioma patients into two NI subgroups. Then, we revealed NI subgroup I were more sensitive to immunotherapy, particularly anti-PD1 therapy. This new NI-based classification may have prospective predictive factors for prognosis and guide physicians in prioritizing immunotherapy for potential responders.

Trial watch: chemotherapy-induced immunogenic cell death in oncology

Immunogenic cell death (ICD) refers to an immunologically distinct process of regulated cell death that activates, rather than suppresses, innate and adaptive immune responses. Such responses culminate into T cell-driven immunity against antigens derived from dying cancer cells. The potency of ICD is dependent on the immunogenicity of dying cells as defined by the antigenicity of these cells and their ability to expose immunostimulatory molecules like damage-associated molecular patterns (DAMPs) and cytokines like type I interferons (IFNs). Moreover, it is crucial that the host's immune system can adequately detect the antigenicity and adjuvanticity of these dying cells. Over the years, several well-known chemotherapies have been validated as potent ICD inducers, including (but not limited to) anthracyclines, paclitaxels, and oxaliplatin. Such ICD-inducing chemotherapeutic drugs can serve as important combinatorial partners for anti-cancer immunotherapies against highly immuno-resistant tumors. In this Trial Watch, we describe current trends in the preclinical and clinical integration of ICD-inducing chemotherapy in the existing immuno-oncological paradigms.

Comprehensive prediction of immune microenvironment and hot and cold tumor differentiation in cutaneous melanoma based on necroptosis-related lncRNA

As per research, causing cancer cells to necroptosis might be used as a therapy to combat cancer drug susceptibility. Long non-coding RNA (lncRNA) modulates the necroptosis process in Skin Cutaneous Melanoma (SKCM), even though the precise mechanism by which it does so has yet been unknown. RNA sequencing and clinical evidence of SKCM patients were accessed from The Cancer Genome Atlas database, and normal skin tissue sequencing data was available from the Genotype-Tissue Expression database. Person correlation analysis, differential screening, and univariate Cox regression were successively utilized to identify necroptosis-related hub lncRNAs. Following this, we adopt the least absolute shrinkage and selection operator regression analysis to construct a risk model. The model was evaluated on various clinical characteristics using many integrated approaches to ensure it generated accurate predictions. Through risk score comparisons and consistent cluster analysis, SKCM patients were sorted either high-risk or low-risk subgroups as well as distinct clusters. Finally, the effect of immune microenvironment, m7G methylation, and viable anti-cancer drugs in risk groups and potential clusters was evaluated in further detail. Included USP30-AS1, LINC01711, LINC00520, NRIR, BASP1-AS1, and LINC02178, the 6 necroptosis-related hub lncRNAs were utilized to construct a novel prediction model with excellent accuracy and sensitivity, which was not influenced by confounding clinical factors. Immune-related, necroptosis, and apoptosis pathways were enhanced in the model structure, as shown by Gene Set Enrichment Analysis findings. TME score, immune factors, immune checkpoint-related genes, m7G methylation-related genes, and anti-cancer drug sensitivity differed significantly between the high-risk and low-risk groups. Cluster 2 was identified as a hot tumor with a better immune response and therapeutic effect. Our study may provide potential biomarkers for predicting prognosis in SKCM and provide personalized clinical therapy for patients based on hot and cold tumor classification.

Cell death, therapeutics, and the immune response in cancer

Induction of cell death is inexorably linked with cancer therapy, but this can also initiate wound-healing processes that have been linked to cancer progression and therapeutic resistance. Here we describe the contribution of apoptosis and the lytic cell death pathways in the response to therapy (including chemotherapy and immunotherapy). We also discuss how necroptosis, pyroptosis, and ferroptosis function to promote tumor immunogenicity, along with emerging findings that these same forms of death can paradoxically contribute to immune suppression and tumor progression. Understanding the duality of cell death in cancer may allow for the development of therapeutics that shift the balance towards regression.

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.

Hepatocellular carcinoma (HCC) immunotherapy by anti-PD-1 monoclonal antibodies: A rapidly evolving strategy

Hepatocellular carcinoma (HCC) is one of the deadliest cancers in the world, with a high relapse rate. Delayed symptom onset observed in 70-80% of patients leads to diagnosis in advanced stages commonly associated with chronic liver disease. Programmed cell death protein 1 (PD-1) blockade therapy has recently emerged as a promising therapeutic option in the clinical management of several advanced malignancies, including HCC, due to the activation of exhausted tumor-infiltrating lymphocytes and improved outcomes of T-cell function. However, many people with HCC do not respond to PD-1 blockade therapy, and the diversity of immune-related adverse events (irAEs) restricts their clinical utility. Therefore, numerous effective combinatory strategies, including combinations with anti-PD-1 antibodies and other therapeutic methods ranging from chemotherapy to targeted therapies, are evolving to improve therapeutic outcomes and evoke synergistic anti-tumor impressions in patients with advanced HCC. Unfortunately, combined therapy may have more side effects than single-agent treatment. Nonetheless, identifying appropriate predictive biomarkers can aid in managing potential immune-related adverse events by distinguishing patients who respond best to PD-1 inhibitors as single agents or in combination strategies. In the present review, we summarize the therapeutic potential of PD-1 blockade therapy for advanced HCC patients. Besides, a glimpse of the pivotal predictive biomarkers influencing a patient's response to anti-PD-1 antibodies will be provided.

An Ionic Liquid Ablation Agent for Local Ablation and Immune Activation in Pancreatic Cancer

Pancreatic ductal adenocarcinoma rapidly acquires resistance to chemotherapy, remaining a fatal disease. Immunotherapy is one of the breakthroughs in cancer treatment, which includes immune checkpoint inhibitors, chimeric antigen receptor T-cell immunotherapy, and neoantigen vaccines. However, immunotherapy has not achieved satisfactory results in the treatment of pancreatic cancer. Immunogenic death comprises proinflammatory cell death, which provides a way to enhance tumor immunogenicity and promote an immune response in solid tumors. Herein, an ionic liquid ablation agent (LAA), synthesized from choline and geranic acid, which triggers necrosis-induced immunotherapy by remodeling an immunosuppressive "cold" tumor to an immune activated "hot" tumor is described. The results indicate that LAA-treated tumor cells can enhance immunogenicity, inducing dendritic cell maturation, macrophage M1 polarization, and cytotoxic T lymphocyte infiltration. The results of the present study provide a novel strategy for solid tumor immunotherapy.

Immunogenic cell death-inducing metal complexes: From the benchtop to the clinic

The immune system presents a complex array of processes designed to maintain homeostasis in malignant cellular growth. Malignancy is the result of a breakdown in immune surveillance by cancer cells evading immune recognition. Significant efforts have been made in modulating immune checkpoint signaling cascades to bypass the resulting immune evasion and establish an anticancer effect. More recently, it was discovered that a form of regulated cell death can involve the stimulation of immune response as its downstream effect and subsequently re-establish immune surveillance. This mechanism, known as immunogenic cell death (ICD), is being exploited as a target to prevent tumor relapse and prevent cancer metastasis. It is now appreciated that metal-based compounds play a key role in ICD activation due to their unique biochemical properties and interactions within cancer cells. With fewer than 1% of known anticancer agents documented as ICD inducers, recent efforts have been made to identify novel entities capable of stimulating a more potent anticancer immune response. While the recent reviews by us or others focus primarily on either discussing the chemical library of ICD inducers or intricate detailing of biological pathways associated with ICD, this review aims to bridge these two topics as a concise summary. Furthermore, early clinical evidence and future directions of ICD are briefly summarized.

Predicting the Clinical Outcome of Triple-Negative Breast Cancer Based on the Gene Expression Characteristics of Necroptosis and Different Molecular Subtypes

Necroptosis, a kind of programmed necrotic cell apoptosis, is the gatekeeper for the host to defend against the invasion of pathogens. It helps to regulate different biological processes regarding human cancer. Nevertheless, studies that determine the impact of death on triple-negative breast cancer (TNBC) are scarce. Therefore, this paper has comprehensively examined the expression as well as clinical significance of necroptosis in TNBC. ConsensusClusterPlus was used to establish a stable molecular classification that used the expression regarding the necroptosis-linked genes. The clinical and immune characteristics of different subclasses were evaluated. Then, the weighted gene coexpression network analysis (WGCNA) assisted in determining key modules, and we selected the genes exhibiting obvious association with necroptosis prognosis through the relationship with prognosis. The univariate Cox regression analysis together with least absolute shrinkage and selection operator (LASSO) techniques served for the construction of the necroptosis-related prognostic risk score (NPRS) model, and the pathway characteristics of NPRS model grouping were further studied. Finally, the NPRS, taking into account the clinicopathological features, used the decision tree model for enhancing the prognostic model as well as the survival prediction. First, two stable molecular subtypes with different prognosis and immune characteristics were identified using necroptosis marker genes. Then, the key modules were identified, and 10 genes significantly related to the prognosis of necroptosis were selected. Then, the clinical prognostic model of NPRS was developed considering the prognosis-linked necroptosis genes. Finally, the NPRS model, taking into account the clinicopathological features, adopted the decision tree model for enhancing the prognostic model as well as the survival prediction. Herein, two new molecular subgroups considering necroptosis-linked genes are proposed, and an NPRS model composed of 10 genes is developed, which maybe assist in the personalized treatment and clinical treatment guidance of TNBC patients.

From (Tool)Bench to Bedside: The Potential of Necroptosis Inhibitors

Necroptosis is a regulated caspase-independent form of necrotic cell death that results in an inflammatory phenotype. This process contributes profoundly to the pathophysiology of numerous neurodegenerative, cardiovascular, infectious, malignant, and inflammatory diseases. Receptor-interacting protein kinase 1 (RIPK1), RIPK3, and the mixed lineage kinase domain-like protein (MLKL) pseudokinase have been identified as the key components of necroptosis signaling and are the most promising targets for therapeutic intervention. Here, we review recent developments in the field of small-molecule inhibitors of necroptosis signaling, provide guidelines for their use as chemical probes to study necroptosis, and assess the therapeutic challenges and opportunities of such inhibitors in the treatment of a range of clinical indications.

Necroptosis-Related LncRNA Signatures for Prognostic Prediction in Uterine Corpora Endometrial Cancer

Necroptosis is one of the common modes of apoptosis, and it has an intrinsic association with cancer prognosis. However, the role of the necroptosis-related long non-coding RNA LncRNA (NRLncRNAs) in uterine corpora endometrial cancer (UCEC) has not yet been fully elucidated at present. Therefore, the present study is designed to investigate the potential prognostic value of necroptosis-related LncRNAs in UCEC. In the present study, the expression profiles and clinical data of UCEC patients were downloaded from TCGA database to identify the differentially expressed NRLncRNAs associated with overall survival. A LncRNA risk model was constructed via Cox regression analysis, and its prognostic value was evaluated. We have also further evaluated the relationships between the LncRNA features and the related cellular function, related pathways, immune status, and immune checkpoints m6A-related genes. Seven signatures, including PCAT19, CDKN2B-AS1, LINC01936, LINC02178, BMPR1B-DT, LINC00237, and TRPM2-AS, were established to assess the overall survival (OS) of the UCEC in the present study. Survival analysis and ROC curves indicated that the correlated signature has good predictable performance. The normogram could accurately predict the overall survival of the patients with an excellent clinical practical value. Enrichment analysis of gene sets indicated that risk signals were enriched in several immune-related pathways. In addition, the risk characteristics were significantly correlated with immune cells, immune function, immune cell infiltration, immune checkpoints, and some m6A-related genes. This study has identified seven necroptosis-related LncRNA signatures for the first time, providing a valuable basis for a more accurate prognostic prediction of UCEC.

Immune infiltration and a necroptosis-related gene signature for predicting the prognosis of patients with cervical cancer

Background: Cervical cancer (CC), the fourth most common cancer among women worldwide, has high morbidity and mortality. Necroptosis is a newly discovered form of cell death that plays an important role in cancer development, progression, and metastasis. However, the expression of necroptosis-related genes (NRGs) in CC and their relationship with CC prognosis remain unclear. Therefore, we screened the signature NRGs in CC and constructed a risk prognostic model. Methods: We downloaded gene data and clinical information of patients with cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) from The Cancer Genome Atlas (TCGA) database. We performed functional enrichment analysis on the differentially expressed NRGs (DENRGs). We constructed prognostic models and evaluated them by Cox and LASSO regressions for DENRGs, and validated them using the International Cancer Genome Consortium (ICGC) dataset. We used the obtained risk score to classify patients into high- and low-risk groups. We employed the ESTIMATE and single sample gene set enrichment analysis (ssGSEA) algorithms to explore the relationship between the risk score and the clinical phenotype and the tumor immune microenvironment. Results: With LASSO regression, we established a prognostic model of CC including 16 signature DENRGs (TMP3, CHMP4C, EEF1A1, FASN, TNF, S100A10, IL1A, H1.2, SLC25A5, GLTP, IFNG, H2AC13, TUBB4B, AKNA, TYK2, and H1.5). The risk score was associated with poor prognosis in CC. Survival was lower in the high-risk group than the low-risk group. The nomogram based on the risk score, T stage, and N stage showed good prognostic predictive power. We found significant differences in immune scores, immune infiltration analysis, and immune checkpoints between the high- and low-risk groups (p < 0.05). Conclusion: We screened for DENRGs based on the TCGA database by using bioinformatics methods, and constructed prognostic models based on the signature DENRGs, which we confirmed as possibly having important biological functions in CC. Our study provides a new perspective on CC prognosis and immunity, and offers a series of new targets for future 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.

A new approach: Evaluation of necroptosis and immune status enables prediction of the tumor microenvironment and treatment targets in pancreatic cancer

Growing evidence indicates a potential correlation between necroptosis and pancreatic cancer, and the relationship between necroptosis, immune infiltration and the microenvironment in pancreatic cancer has drawn increasing attention. However, two-dimensional phenotype and prognostic assessment systems based on a combination of necroptosis and immunity have not been explored. In our present study, we explored the pancancer genomics signature of necroptosis-related molecules, identifying necroptosis-related molecule mutation profiles, expression profiles, and correlations between expression levels and methylation/CNV levels. We identified distinct necroptotic as well as immune statuses in pancreatic cancer, and a high necroptosis phenotype and high immunity phenotype both indicated better prognosis than a low necroptosis phenotype and low immunity phenotype. The two-dimensional phenotype we constructed has ideal discriminative effects on pancreatic cancer prognosis, inflammation, and the immune microenvironment. The "high-necroptosis and high-immunity (HNHI)" group exhibited the best prognosis and the highest proportion of infiltrating immune cells. The NI score can be used to predict patient prognosis and is correlated with the immune microenvironment score, chemotherapeutic drug IC50, and tumor mutational burden. In addition, it may be useful for predicting the effect of individualized chemotherapy and immunotherapy. Our study also revealed that SLC2A1 is associated with both necroptosis and immunity and acts as a potential oncogene in pancreatic cancer. In conclusion, the two-dimensional phenotype and NI score we developed are promising tools for clinical multiomics applications and prediction of chemotherapy and immunotherapy response and present benefits in terms of precision medicine and individualized treatment decision-making for pancreatic cancer patients.

Prognostic Value of the Lung Immune Prognostic Index for Metastatic Non-Small Cell Lung Cancer Patients: A Chinese Cohort Study

Background

Most cancer-related deaths around the globe are caused by lung cancer. The present treatments for metastatic non-small cell lung cancer (mNSCLC) are cytotoxic chemotherapy (CCT), targeted therapy (TT) and immunotherapy, but the benefit of the same regime varies greatly. Hence, it is important to identify biomarkers to predict the efficacy of modalities. Previous literature suggested certain parameters might be predictive factors. Nevertheless, the utility of these parameters is limited due to the types of solid tumors.

Purpose

The study aimed to examine whether the lung immune prognostic index (LIPI) was related to outcomes of CCT, immune checkpoint inhibitors (ICIs) and TT for mNSCLC patients.

Materials and Methods

A retrospective cohort study between September 2012 and May 2020 was conducted on 350 Chinese mNSCLC patients, including 147 patients receiving ICIs, 103 TT, and 100 CCT. The data were examined to analyze the prognostic value of LIPI among various treatments.

Main Outcomes and Measures

The associations between PFS and good, intermediate, or poor prognostic LIPI scores in ICIs, TT, and CCT were determined, respectively.

Results

In univariable analyses, there was a relevance between a good LIPI score and better PFS among patients receiving ICIs (HR, 0.81; 95% CI, 0.44-1.51), TT (HR, 0.35; 95% CI, 0.16-1.74), and CCT (HR, 0.39; 95% CI, 0.19-0.80). In multivariable analyses, the intermediate LIPI score was linked to better PFS only in patients receiving TT (HR, 0.31; 95% CI, 0.17-0.92) rather than ICIs (HR, 1.12; 95% CI, 0.66-2.45) or CCT (HR, 1.24; 95% CI, 0.49-4.55).

Conclusion

Baseline LIPI value is an important prognostic biomarker for mNSCLC patients treated with TT. Shorter PFS with TT was associated with poor baseline LIPI. Poor LIPI score may be considered as a promising indicator showing which patients are unlikely to respond well to TT. The prognostic value of LIPI can be more clearly determined through prospective clinical study.

From targeted therapy to a novel way: Immunogenic cell death in lung cancer

Lung cancer (LC) is one of the most incident malignancies and a leading cause of cancer mortality worldwide. Common tumorigenic drivers of LC mainly include genetic alterations of EGFR, ALK, KRAS, BRAF, ROS1, and MET. Small inhibitory molecules and antibodies selectively targeting these alterations or/and their downstream signaling pathways have been approved for treatment of LC. Unfortunately, following initial positive responses to these targeted therapies, a large number of patients show dismal prognosis due to the occurrence of resistance mechanisms, such as novel mutations of these genes and activation of alternative signaling pathways. Over the past decade, it has become clear that there is no possible cure for LC unless potent antitumor immune responses are induced by therapeutic intervention. Immunogenic cell death (ICD) is a newly emerged concept, a form of regulated cell death that is sufficient to activate adaptive immune responses against tumor cells. It transforms dying cancer cells into a therapeutic vaccine and stimulates long-lasting protective antitumor immunity. In this review, we discuss the key targetable genetic aberrations and the underlying mechanism of ICD in LC. Various agents inducing ICD are summarized and the possibility of harnessing ICD in LC immunotherapy is further explored.

A necroptosis-related lncRNA signature was identified to predict the prognosis and immune microenvironment of IDH-wild-type GBM

Introduction

Necroptosis-related genes are essential for the advancement of IDH-wild-type GBM. However, the putative effects of necroptosis-related lncRNAs (nrlncRNAs) in IDH-wild-type GBM remain unknown.

Methods

By using the TCGA and GTEx databases, a nrlncRNA prognostic signature was created using LASSO Cox regression. The median risk score was used to categorize the patients into low and high-risk groups. To confirm the validity, univariate, multivariate Cox regression and ROC curves were used. Furthermore, by enrichment analysis, immune correlation analysis, and drug sensitivity analysis, the targeted lncRNAs were selected for further verification. As the highest upregulated expression in tumor than peritumor specimens, RP11-131L12.4 was selected for phenotype and functional experiments in primary GBM cells.

Results

Six lncRNAs were proved to be closely related to necroptosis in IDH-1-wild-type GBM, which were used to create a new signature. For 1-, 2-, and 3-year OS, the AUCs were 0.709, 0.645 and 0.694, respectively. Patients in the low-risk group had a better prognosis, stronger immune function activity, and more immune cell infiltration. In contrast, enrichment analysis revealed that the malignant phenotype was more prevalent in the high-risk group. In vitro experiments indicated that RP11-131L12.4 increased the tumor proliferation, migration and invasion, but decreased the necroptosis. Moreover, this nrlncRNA was also proved to be negatively associated with patient prognosis.

Conclusion

The signature of nrlncRNAs may aid in the formulation of tailored and precise treatment for individuals with IDH-wild-type GBM. RP11-131L12.4 may play indispensable role in necroptosis suppression.

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.

Prognostic implications of necroptosis-related long noncoding RNA signatures in muscle-invasive bladder cancer

Background: Bladder cancer (BLCA) is the sixth most common cancer in men, with an increasing incidence of morbidity and mortality. Necroptosis is a type of programmed cell death and plays a critical role in the biological processes of bladder cancer (BLCA). However, current studies focusing on long noncoding RNA (lncRNA) and necroptosis in cancer are limited, and there is no research about necroptosis-related lncRNAs (NRLs) in BLCA. Methods: We obtained the RNA-seq data and corresponding clinical information of BLCA from The Cancer Genome Atlas (TCGA) database. The seven determined prognostic NLRs were analyzed by several methods and verified by RT-qPCR. Then, a risk signature was established based on the aforementioned prognostic NLRs. To identify it, we evaluated its prognostic value by Kaplan-Meier (K-M) survival curve and receiver operating characteristics (ROC) curve analysis. Moreover, the relationships between risk signature and clinical features, functional enrichment, immune landscape, and drug resistance were explored as well. Results: We constructed a signature based on seven defined NLRs (HMGA2-AS1, LINC02489, ETV7-AS1, EMSLR, AC005954.1, STAG3L5P-PVRIG2P-PILRB, and LINC02178). Patients in the low-risk cohort had longer survival times than those in the high-risk cohort, and the area under the ROC curve (AUC) value of risk signature was higher than other clinical variables. Functional analyses, the infiltrating level of immune cells and functions, ESTIMATE score, and immune checkpoint analysis all indicated that the high-risk group was in a relatively immune-activated state. In terms of treatments, patients in the high-risk group were more sensitive to immunotherapy, especially anti-PD1/PD-L1 immunotherapy and conventional chemotherapy. Conclusion: The novel NLR signature acts as an invaluable tool for predicting prognosis, immune microenvironment, and drug resistance in muscle-invasive bladder cancer (MIBC) patients.

The Interface of Tumour-Associated Macrophages with Dying Cancer Cells in Immuno-Oncology

Tumour-associated macrophages (TAMs) are essential players in the tumour microenvironment (TME) and modulate various pro-tumorigenic functions such as immunosuppression, angiogenesis, cancer cell proliferation, invasion and metastasis, along with resistance to anti-cancer therapies. TAMs also mediate important anti-tumour functions and can clear dying cancer cells via efferocytosis. Thus, not surprisingly, TAMs exhibit heterogeneous activities and functional plasticity depending on the type and context of cancer cell death that they are faced with. This ultimately governs both the pro-tumorigenic and anti-tumorigenic activity of TAMs, making the interface between TAMs and dying cancer cells very important for modulating cancer growth and the efficacy of chemo-radiotherapy or immunotherapy. In this review, we discuss the interface of TAMs with cancer cell death from the perspectives of cell death pathways, TME-driven variations, TAM heterogeneity and cell-death-inducing anti-cancer therapies. We believe that a better understanding of how dying cancer cells influence TAMs can lead to improved combinatorial anti-cancer therapies, especially in combination with TAM-targeting immunotherapies.