Necroptosis in Immuno-Oncology and Cancer Immunotherapy

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.

PGAM5: A necroptosis gene associated with poor tumor prognosis that promotes cutaneous melanoma progression

Cutaneous melanoma is the deadliest type of skin cancer, and its highly aggressive and metastatic nature leads to an extremely poor prognosis. Necrotizing apoptosis, a specific form of programmed cell death, has been extensively studied in recent years. In this study, we analyzed the relationship between necroptosis-related functional genes and cutaneous melanoma in order to identify the biomarkers associated with the prognosis and progression of cutaneous melanoma. Cutaneous melanoma samples were classified into three subgroups on the basis of a necroptosis gene set. These subgroups were subjected to a prognostic survival analysis, and the greatest differences were observed between subgroups C1 and C3. Between these subgroups, 28 necrotizing apoptosis-related genes were significantly differently expressed. Among these, 16 necrotizing apoptosis-related genes were associated with cutaneous melanoma prognosis. Downscaling analysis and prognostic modeling using the least absolute shrinkage and selection operator analysis yielded nine pivotal genes and revealed phosphoglycerate translocase 5 (PGAM5) as the key gene. Then, qRT-PCR was used to verify the expression level of PGAM5. The results showed that PGAM5 was highly expressed in cutaneous melanoma tissues. In this study, a bioinformatics approach was used to identify PGAM5, a biomarker whose high expression is associated with the poor prognosis of cutaneous melanoma.

Prognostic necroptosis-related gene signature aids immunotherapy in lung adenocarcinoma

Background: Necroptosis is a phenomenon of cellular necrosis resulting from cell membrane rupture by the corresponding activation of Receptor Interacting Protein Kinase 3 (RIPK3) and Mixed Lineage Kinase domain-Like protein (MLKL) under programmed regulation. It is reported that necroptosis is closely related to the development of tumors, but the prognostic role and biological function of necroptosis in lung adenocarcinoma (LUAD), the most important cause of cancer-related deaths, is still obscure. Methods: In this study, we constructed a prognostic Necroptosis-related gene signature based on the RNA transcription data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases as well as the corresponding clinical information. Kaplan-Meier analysis, receiver operating characteristic (ROC), and Cox regression were made to validate and evaluate the model. We analyzed the immune landscape in LUAD and the relationship between the signature and immunotherapy regimens. Results: Five genes (RIPK3, MLKL, TLR2, TNFRSF1A, and ALDH2) were used to construct the prognostic signature, and patients were divided into high and low-risk groups in line with the risk score. Cox regression showed that risk score was an independent prognostic factor. Nomogram was created for predicting the survival rate of LUAD patients. Patients in high and low-risk groups have different tumor purity, tumor immunogenicity, and different sensitivity to common antitumor drugs. Conclusion: Our results highlight the association of necroptosis with LUAD and its potential use in guiding immunotherapy.

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

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

A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma

Background

Glioma is a highly aggressive brain cancer with a poor prognosis. Necroptosis is a form of programmed cell death occurring during tumor development and in immune microenvironments. The prognostic value of necroptosis in glioma is unclear. This study aimed to develop a prognostic glioma model based on necroptosis.

Methods

A necroptosis-related risk model was constructed by Cox regression analysis based on The Cancer Genome Atlas (TCGA) training set, validated in two Chinese Glioma Genome Atlas (CGGA) validation sets. We explored the differences in immune infiltration and immune checkpoint genes between low and high risk groups and constructed a nomogram. Moreover, we compiled a third validation cohort including 43 glioma patients. The expression of necroptosis-related genes was verified in matched tissues using immunochemical staining in the third cohort, and we analyzed their relationship to clinicopathological features.

Results

Three necroptosis-related differentially expressed genes (EZH2, LEF1, and CASP1) were selected to construct the prognostic model. Glioma patients with a high risk score in the TCGA and CGGA cohorts had significantly shorter overall survival. The necroptosis-related risk model and nomogram exhibited good predictive performance in the TCGA training set and the CGGA validation sets. Furthermore, patients in the high risk group had higher immune infiltration status and higher expression of immune checkpoint genes, which was positively correlated with poorer outcomes. In the third validation cohort, the expression levels of the three proteins encoded by EZH2, LEF1, and CASP1 in glioma tissues were significantly higher than those from paracancerous tissues. They were also closely associated with disease severity and prognosis.

Conclusions

Our necroptosis-related risk model can be used to predict the prognosis of glioma patients and improve prognostic accuracy, which may provide potential therapeutic targets and a theoretical basis for treatment.

A necroptosis related prognostic model of pancreatic cancer based on single cell sequencing analysis and transcriptome analysis

Background

As a tumor type with high mortality and poor therapeutic effect, the pathogenesis of pancreatic cancer is still unclear. It is necessary to explore the significance of necroptosis in pancreatic cancer.

Methods

Pancreatic cancer transcriptome data were obtained from the TCGA database, ICGC database, and GSE85916 in the GEO database. The TCGA cohort was set as a training cohort, while the ICGC and GSE85916 cohort were set as the validation cohorts. Single-cell sequencing data of pancreatic cancer were obtained from GSE154778 in the GEO database. The genes most associated with necroptosis were identified by weighted co-expression network analysis and single-cell sequencing analysis. COX regression and Lasso regression were performed for these genes, and the prognostic model was established. By calculating risk scores, pancreatic cancer patients could be divided into NCPTS_high and NCPTS_low groups, and survival analysis, immune infiltration analysis, and mutation analysis between groups were performed. Cell experiments including gene knockdown, CCK-8 assay, clone formation assay, transwell assay and wound healing assay were conducted to explore the role of the key gene EPS8 in pancreatic cancer. PCR assays on clinical samples were further used to verify EPS8 expression.

Results

We constructed the necroptosis-related signature in pancreatic cancer using single-cell sequencing analysis and transcriptome analysis. The calculation formula of risk score was as follows: NCPTS = POLR3GL * (-0.404) + COL17A1 * (0.092) + DDIT4 * (0.007) + PDE4C * (0.057) + CLDN1 * 0.075 + HMGA2 * 0.056 + CENPF * 0.198 +EPS8 * 0.219. Through this signature, pancreatic cancer patients with different cohorts can be divided into NCPTS_high and NCPTS_low group, and the NCPTS_high group has a significantly poorer prognosis. Moreover, there were significant differences in immune infiltration level and mutation level between the two groups. Cell assays showed that in CAPAN-1 and PANC-1 cell lines, EPS8 knockdown significantly reduced the viability, clonogenesis, migration and invasion of pancreatic cancer cells. Clinical PCR assay of EPS8 expression showed that EPS8 expression was significantly up-regulated in pancreatic cancer (*P<0.05).

Conclusion

Our study can provide a reference for the diagnosis, treatment and prognosis assessment of pancreatic cancer.

Construction and validation model of necroptosis-related gene signature associates with immunity for osteosarcoma patients

Osteosarcoma is the most common malignant tumor in children and adolescents and its diagnosis and treatment still need to be improved. Necroptosis has been associated with many malignancies, but its significance in diagnosing and treating osteosarcoma remains unclear. The objective is to establish a predictive model of necroptosis-related genes (NRGs) in osteosarcoma for evaluating the tumor microenvironment and new targets for immunotherapy. In this study, we download the osteosarcoma data from the TARGET and GEO websites and the average muscle tissue data from GTEx. NRGs were screened by Cox regression analysis. We constructed a prediction model through nonnegative matrix factorization (NMF) clustering and the least absolute shrinkage and selection operator (LASSO) algorithm and verified it with a validation cohort. Kaplan–Meier survival time, ROC curve, tumor invasion microenvironment and CIBERSORT were assessed. In addition, we establish nomograms for clinical indicators and verify them by calibration evaluation. The underlying mechanism was explored through the functional enrichment analysis. Eight NRGs were screened for predictive model modeling. NRGs prediction model through NMF clustering and LASSO algorithm was established. The survival, ROC and tumor microenvironment scores showed significant statistical differences among subgroups (P < 0.05). The validation model further verifies it. By nomogram and calibration, we found that metastasis and risk score were independent risk factors for the poor prognosis of osteosarcoma. GO and KEGG analyses demonstrate that the genes of osteosarcoma cluster in inflammatory, apoptotic and necroptosis signaling pathways. The significant role of the correlation between necroptosis and immunity in promoting osteosarcoma may provide a novel insight into detecting molecular mechanisms and targeted therapy.

A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma

Necroptosis is a regulated form of cell necroptotic process, playing a pivotal role in tumors. In renal cell cancer (RCC), inhibiting necroptosis could promote the proliferation of tumor cells. However, the molecular mechanisms and prognosis prediction of necroptotic-process-related genes in RCC are still unclear. In this study, we first identified the necroptotic process prognosis-related genes (NPRGss) by analyzing the kidney renal clear cell carcinoma (KIRC) data in The Cancer Genome Atlas (TCGA, n=607). We systematically analyzed the expression alteration, clinical relevance, and molecular mechanisms of NPRGss in renal clear cell carcinoma. We constructed an NPRGs risk signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression analysis on the basis of the expression of seven NPRGss. We discovered that the overall survival (OS) of KIRC patients differed significantly in high- or low-NPRGs-risk groups. The univariate/multivariate Cox regression revealed that the NPRGs risk signature was an independent prognosis factor in RCC. The gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to explore the molecular mechanisms of NPRGss. Immune-/metabolism-related pathways showed differential enrichment in high-/low-NPRGs-risk groups. The E-MTAB-1980, TCGA-KIRP, GSE78220, the cohort of Alexandra et al., and IMvigor210 cohort datasets were respectively used as independent validation cohorts of NPRGs risk signature. The patients in high- or low-NPRGs-risk groups showed different drug sensitivity, immune checkpoint expression, and immune therapy response. Finally, we established a nomogram based on the NPRGs risk signature, stage, grade, and age for eventual clinical translation; the nomogram possesses an accurate and stable prediction effect. The signature could predict patients’ prognosis and therapy response, which provides the foundation for further clinical therapeutic strategies for RCC patients.

Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes

Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.

Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.

Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.

Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research.

Machine learning identification of cuproptosis and necroptosis-associated molecular subtypes to aid in prognosis assessment and immunotherapy response prediction in low-grade glioma

Both cuproptosis and necroptosis are typical cell death processes that serve essential regulatory roles in the onset and progression of malignancies, including low-grade glioma (LGG). Nonetheless, there remains a paucity of research on cuproptosis and necroptosis-related gene (CNRG) prognostic signature in patients with LGG. We acquired patient data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and captured CNRGs from the well-recognized literature. Firstly, we comprehensively summarized the pan-cancer landscape of CNRGs from the perspective of expression traits, prognostic values, mutation profiles, and pathway regulation. Then, we devised a technique for predicting the clinical efficacy of immunotherapy for LGG patients. Non-negative matrix factorization (NMF) defined by CNRGs with prognostic values was performed to generate molecular subtypes (i.e., C1 and C2). C1 subtype is characterized by poor prognosis in terms of disease-specific survival (DSS), progression-free survival (PFS), and overall survival (OS), more patients with G3 and tumour recurrence, high abundance of immunocyte infiltration, high expression of immune checkpoints, and poor response to immunotherapy. LASSO-SVM-random Forest analysis was performed to aid in developing a novel and robust CNRG-based prognostic signature. LGG patients in the TCGA and GEO databases were categorized into the training and test cohorts, respectively. A five-gene signature, including SQSTM1, ZBP1, PLK1, CFLAR, and FADD, for predicting OS of LGG patients was constructed and its predictive reliability was confirmed in both training and test cohorts. In both the training and the test datasets (cohorts), higher risk scores were linked to a lower OS rate. The time-dependent ROC curve proved that the risk score had outstanding prediction efficiency for LGG patients in the training and test cohorts. Univariate and multivariate Cox regression analyses showed the CNRG-based prognostic signature independently functioned as a risk factor for OS in LGG patients. Furthermore, we developed a highly reliable nomogram to facilitate the clinical practice of the CNRG-based prognostic signature (AUC > 0.9). Collectively, our results gave a promising understanding of cuproptosis and necroptosis in LGG, as well as a tailored prediction tool for prognosis and immunotherapeutic responses in patients.

Identification of Prognostic Signature of Necroptosis-Related lncRNAs and Molecular Subtypes in Glioma

Background

In tumor progression and epigenetic regulation, long non-coding RNA (lncRNA) and necroptosis are crucial regulators. However, in glioma microenvironment, the role of necroptosis-related lncRNAs (NRLs) remains unknown.

Method

In this study, the RNA-seq and clinical annotation of glioma patients were analyzed using the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. To investigate prognosis and tumor microenvironment of NRLs in gliomas, we conducted a prediction model based on the training cohort. The accuracy of the model was verified in the verification cohort.

Results

A signature composed of 13 NRLs was identified, and all glioma patients were divided into two groups. We found that each group has unique survival outcomes, biological behaviors, and immune infiltrating status. The necroptosis-related lncRNA signature (NRLS) model was found to be an independent risk factor in multivariate Cox analysis. Immunosuppressive microenvironment was positively correlated with the high-risk group. Due to significantly different IC50 between risk groups, NRLS could be used as a guide for chemotherapeutic treatment. Further, the entire cohort was divided into two clusters depending on NRLs. Consensus clustering method and the risk scoring system were basically similar. Survival probability was higher in Cluster 2, while Cluster 1 has stronger immunologic infiltration.

Conclusion

The predictive signature could be a prognostic factor independently and serve to detect the role of NRLs in glioma immunotherapy response.

Development and validation of a necroptosis-related gene prognostic score to predict prognosis and efficiency of immunotherapy in gastric cancer

Necroptosis is a novel type of regulated cell death that is intimately associated with a variety of tumors. However, how necroptosis affects the identification of gastric cancer (GC) remains unclear. Here we seek to find new potential necroptosis-related biomarkers to predict GC prognosis and immunotherapy effect. We used Cox analysis to obtain shared prognostic markers related to necroptosis from five datasets (TCGA and four GEO datasets). Then, a necroptosis-related gene prognostic score (NRGPS) system was constructed using LASSO Cox regression, NRGPS consisting of three necroptosis-related mRNAs (AXL, RAI14, and NOX4) was identified, 31 pairs of GC and adjacent normal tissues from the Second Hospital of Harbin Medical University were collected and Real-Time Quantitative PCR (RT-qPCR) was used to detect the relative expression levels of the three necroptosis-related mRNAs, and external validation was performed on four GEO datasets (GSE84437, GSE26901, GSE62254 and GSE15459). In this study, Overall survival (OS) in the high-NRGPS group was significantly lower than in the low-NRGPS group. Cox regression analyses showed that NRGPS was an independent prognostic variable. Tumor-mutation-burden (TMB), tumor microenvironment (TME), microsatellite instability (MSI), and Tumor Immune Dysfunction and Exclusion (TIDE) scoring were used as predictors of the immunotherapy response. A cancer-friendly immune microenvironment, a high TIDE score, a low TMB, and a low MSI were all characteristics of the high-NRGPS group, and they all consistently showed that the issues seen there are related to immune escape in GC. The combination of three candidate genes may be an effective method for diagnostic assessment of GC prognosis and immunotherapy efficacy.

A novel prognostic and therapeutic target biomarker based on necroptosis-related gene signature and immune microenvironment infiltration in gastric cancer

Background: Gastric cancer is a major global public health burden worldwide. Although treatment strategies are continuously improving, the overall prognosis remains poor. Necroptosis is a newly discovered form of cell death associated with anti-tumor immunity.

Methods: Gastric cancer (GC) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were downloaded. Bioinformatics analysis was performed to construct a necroptosis-related risk model and to establish cancer subtypes. Potential associations of the tumor immune microenvironment and immunotherapy response with necroptosis-related prognostic risk score (NRG risk score) were comprehensively explored. 16 GC and paired normal tissues were collected and RT-PCR was performed to examine expression of NRG related genes.

Results: GC samples were stratified into three subtypes according to prognostic necroptosis gene expression. A necroptosis risk model based on 12 genes (NPC1L1, GAL, RNASE1, PCDH7, NOX4, GJA4, SLC39A4, BASP1, BLVRA, NCF1, PNOC, and CCR5) was constructed and validated. The model was significantly associated with the OS and PFS of GC patients and the tumor immune microenvironment including immune cell infiltration, microsatellite instability (MSI) status, tumor mutational burden (TMB) score, immune checkpoint, and human leukocyte antigen (HLA) gene expression. A prognostic nomogram based on the NRG_score was additionally constructed. A low NRG risk score was correlated with high tumor immunogenicity and might benefit from immunotherapy.

Conclusion: We have identified a useful prognostic model based on necroptosis-related genes in GC and comprehensively the relationship between necroptosis and tumor immunity. Predicting value to immunotherapy response is promising, and further research to validate the model in clinical practice is needed.

Necroptosis throws novel insights on patient classification and treatment strategies for hepatocellular carcinoma

Introduction

Necroptosis is a novel pattern of immunogenic cell death and has triggered an emerging wave in antitumor therapy. More evidence has suggested the potential associations between necroptosis and intra-tumoral heterogeneity. Currently, the underlying role of necroptosis remains elusive in hepatocellular carcinoma (HCC) at antitumor immunity and inter-tumoral heterogeneity.

Methods

This study enrolled a total of 728 HCC patients and 139 immunotherapy patients from eight public datasets. The consensus clustering approach was employed to depict tumor heterogeneity of cancer necroptosis. Subsequently, our study further decoded the heterogeneous clinical outcomes, genomic landscape, biological behaviors, and immune characteristics in necroptosis subtypes. For each patient, providing curative clinical recommendations and developing potential therapeutic drugs were used to promote precise medicine.

Results

With the use of the weighted gene coexpression network analysis (WGCNA) algorithm, necroptosis-associated long non-coding RNAs (lncRNAs) (NALRs) were identified in HCC. Based on the NALR expression, two heterogeneous subtypes were decoded with distinct clinical outcomes. Compared to patients in C1, patients in C2 harbored superior pathological stage and presented more unfavorable overall survival and recurrence-free survival. Then, the robustness and reproducibility of necroptosis subtypes were further validated via the nearest template prediction (NTP) approach and classical immune phenotypes. Through comprehensive explorations, C1 was characterized by enriched immune-inflammatory and abundant immune infiltration, while C2 possessed elevated proliferative and metabolic activities and highly genomic instability. Moreover, our results indicated that C1 was more prone to obtain desirable benefits from immunotherapy. For patients in C2, numerous underlying therapeutic agents were developed, which might produce significant efficacy.

Conclusion

This study identified two necroptosis subtypes with distinct characteristics, decoding the tumor heterogeneity. For an individualized patient, our work tailored corresponding treatment strategies to improve clinical management.

Identification of necroptosis‐related gene signature and characterization of tumour microenvironment infiltration in non‐small‐cell lung cancer

Necroptosis is a programmed necrosis in a caspase‐independent fashion. The role of necroptosis‐related genes (NRGs) in lung cancer remains unknow. Herein, we classified TCGA‐LUAD cohort into two necroptosis‐related subtypes (C1 and C2) by consensus clustering analysis. The result showed that subtype C1 had a favourable prognosis and higher infiltration levels of immune cells. Moreover, subtype C1 was more activated in immune‐associated pathways. Then, we established an NRG prognosis model (NRG score) composed of six NRGs (RIPK3, MLKL, TLR2, TLR4, TNFRSF1A, NDRG2) and divided the cohort into low‐ and high‐risk group. We found that the NRG score was associated with prognosis, tumour immune microenvironment and tumour mutation burden. We also constructed an accurate nomogram model to improve the clinical applicability of NRG score. The result indicated that NRG score may be an independent prognostic marker for lung cancer patients. Taken together, we established a prognosis model that may deepen the understanding of NRGs in lung cancer and provide a basis for developing more effective immunotherapy strategies.

Expression Patterns of Necroptosis-Related Genes: Predicting Prognosis and Immunotherapeutic Effects in Cutaneous Melanoma

Background

Increasing evidence has shown a strong correlation between necroptosis and antitumor immunity. However, precise expression patterns of necroptosis-related genes in cutaneous melanoma (CM) have not been clearly elucidated nor have their effects on the immune cell infiltration in the tumor microenvironment.

Method

We investigated the expression patterns of necroptosis-related genes of individuals with cutaneous melanoma based on 67 necroptotic genes and methodically associated the expression patterns with the comprehensive characterization of tumor immune microenvironment. Using principal component analysis methods, the NRG score was developed to quantify the expression patterns of necroptotic genes in CM patients.

Result

Three different necroptotic subtypes were determined with marked survival differences, showing distinct characteristics of immune cell infiltration. The high NRG score group with comprehensive immunosuppression was characterized by the worse immunotherapeutic efficacy and the poor prognosis, while the low NRG score group indicated a robust activation of immune function and a better response to immunotherapy, which may be responsible for a better prognosis. Furthermore, the predictive ability of the NRG score on prognosis and immunotherapeutic benefits was further revalidated using the other independent datasets of cutaneous melanoma. The results indicated that patients with low NRG scores exhibited prolonged survival. Surprisingly, all patients with CM with clinical response, including complete response/partial response, belonged to the low NRG score group.

Conclusion

Our present work revealed the close association between expression patterns of necroptosis-associated genes and tumor immune microenvironment. NRG score can serve as a potential predictor to independently assess patients' prognosis with CM and effectively estimate the response to immunological therapy, thus facilitating the identification of appropriate candidates with CM for immunotherapy and the formulation of individualized therapeutic approaches.

Association of Cell Death Markers With Tumor Immune Cell Infiltrates After Chemo-Radiation in Cervical Cancer

Irradiation induces distinct cellular responses such as apoptosis, necroptosis, iron-dependent cell death (a feature of ferroptosis), senescence, and mitotic catastrophe. Several of these outcomes are immunostimulatory and may represent a potential for immunogenic type of cell death (ICD) induced by radiotherapy triggering abscopal effects. The purpose of this study is to determine whether intra-tumoral ICD markers can serve as biomarkers for the prediction of patient's outcomes defined as the metastasis status and survival over a 5-year period. Thirty-eight patients with locally advanced cervical cancer, treated with neoadjuvant chemoradiotherapy using cisplatin were included in this study. Pre-treatment tumor biopsy and post-treatment hysterectomy samples were stained for cell death markers and danger associated molecular patterns (DAMPs): cleaved caspase-3 (apoptosis), phosphorylated mixed lineage kinase domain like pseudokinase (pMLKL; necroptosis), glutathione peroxidase 4 (GPX4; ferroptosis) and 4-hydroxy-2-noneal (4-HNE; ferroptosis), high mobility group box 1 (HMGB1) and calreticulin. Although these markers could not predict the patient's outcome in terms of relapse or survival, many significantly correlated with immune cell infiltration. For instance, inducing ferroptosis post-treatment seems to negatively impact immune cell recruitment. Measuring ICD markers could reflect the impact of treatment on the tumor microenvironment with regard to immune cell recruitment and infiltration.

One Sentence Summary

Cell death readouts during neoadjuvant chemoradiation in cervical cancer.

Potential of Black Phosphorus in Immune-Based Therapeutic Strategies

Black phosphorus (BP) consists of phosphorus atoms, an essential element of bone and nucleic acid, which covalently bonds to three adjacent phosphorus atoms to form a puckered bilayer structure. With its anisotropy, band gap, biodegradability, and biocompatibility properties, BP is considered promising for cancer therapy. For example, BP under irradiation can convert near-infrared (NIR) light into heat and reactive oxygen species (ROS) to damage cancer cells, called photothermal therapy (PTT) and photodynamic therapy (PDT). Compared with PTT and PDT, the novel techniques of sonodynamic therapy (SDT) and photoacoustic therapy (PAT) exhibit amplified ROS generation and precise photoacoustic-shockwaves to enhance anticancer effect when BP receives ultrasound or NIR irradiation. Based on the prospective phototherapy, BP with irradiation can cause a “double-kill” to tumor cells, involving tumor-structure damage induced by heat, ROS, and shockwaves and a subsequent anticancer immune response induced by in situ vaccines construction in tumor site, which is referred to as photoimmunotherapy (PIT). In conclusion, BP shows promise in natural antitumor biological activity, biological imaging, drug delivery, PTT/PDT/SDT/PAT/PIT, nanovaccines, nanoadjuvants, and combination immunotherapy regimens.

Targeting necroptosis as an alternative strategy in tumor treatment: From drugs to nanoparticles

Over last decades, most antitumor therapeutic strategies have focused on apoptosis, however, apoptosis resistance and immunological silence usually led to treatment failure. In this sense, triggering other programmed cell death such as necroptosis may achieve a better therapeutic efficacy and has gained widespread attentions in tumor therapy. Studies in this field have identified several types of necroptosis modulators and highlighted the therapeutic potential of necroptotic cell death in cancer. Nanoparticles further provide possibilities to improve therapeutic outcomes as an efficient drug delivery system, facilitating tumor targeting and controlled cargo release. Furthermore, some nanoparticles themselves can trigger/promote programmed necrosis through hyperthermia, ultrasound and autophagy blockage. These investigations have entered necroptosis for consideration as a promising strategy for tumor therapy, though numerous challenges remain and clinical applications are still distant. In this review, we would briefly introduce molecular mechanism and characteristics of necroptosis, and then summarize recent progress of programmed necrosis and their inducers in tumor therapy. Furthermore, the antitumor strategies that take advantages of nanoparticles to induce necroptosis are also discussed.

Trial watch: Dendritic cell (DC)-based immunotherapy for cancer

Dendritic cell (DC)-based vaccination for cancer treatment has seen considerable development over recent decades. However, this field is currently in a state of flux toward niche-applications, owing to recent paradigm-shifts in immuno-oncology mobilized by T cell-targeting immunotherapies. DC vaccines are typically generated using autologous (patient-derived) DCs exposed to tumor-associated or -specific antigens (TAAs or TSAs), in the presence of immunostimulatory molecules to induce DC maturation, followed by reinfusion into patients. Accordingly, DC vaccines can induce TAA/TSA-specific CD8⁺/CD4⁺ T cell responses. Yet, DC vaccination still shows suboptimal anti-tumor efficacy in the clinic. Extensive efforts are ongoing to improve the immunogenicity and efficacy of DC vaccines, often by employing combinatorial chemo-immunotherapy regimens. In this Trial Watch, we summarize the recent preclinical and clinical developments in this field and discuss the ongoing trends and future perspectives of DC-based immunotherapy for oncological indications.

Immunogenic Cell Death and Role of Nanomaterials Serving as Therapeutic Vaccine for Personalized Cancer Immunotherapy

Immunogenic cell death (ICD) is a rapidly growing research area representing one of the emerging therapeutic strategies of cancer immunotherapy. ICD is an umbrella term covering several cell death modalities including apoptosis, necroptosis, ferroptosis and pyroptosis, and is the product of a balanced combination of adjuvanticity (damage-associated molecular patterns and chemokines/cytokines) and antigenicity (tumor associated antigens). Only a limited number of anti-cancer therapies are available to induce ICD in experimental cancer therapies and even much less is available for clinical use. To overcome this limitation, nanomaterials can be used to increase the immunogenicity of cancer cells killed by anti-cancer therapy, which in themselves are not necessarily immunogenic. In this review, we outline the current state of knowledge of ICD modalities and discuss achievements in using nanomaterials to increase the immunogenicity of dying cancer cells. The emerging trends in modulating the immunogenicity of dying cancer cells in experimental and translational cancer therapies and the challenges facing them are described. In conclusion, nanomaterials are expected to drive further progress in their use to increase efficacy of anti-cancer therapy based on ICD induction and in the future, it is necessary to validate these strategies in clinical settings, which will be a challenging research area.

Necroptosis-Related Genes Associated With Immune Activity and Prognosis of Colorectal Cancer

This study aims at screening out the key necroptosis-related genes in colorectal cancer and elucidating the role of necroptosis-related genes in the immune activity and prognosis of colorectal cancer (CRC). The CRC patients’ data were downloaded from The Cancer Genome Atlas (TCGA). The non-negative matrix factorization method was applied to identify new molecular subgroups. Survival analysis and single sample Gene Set Enrichment Analysis were performed to determinate the differences in the overall survival time and immune status of the subgroups. Prognostic model was constructed on the basis of univariate Cox regression and LASSO analysis. Functional analyses were used to explore the potential mechanisms. Based on prognostic related necroptosis genes, we identify two molecular subgroups with significantly different survival. The better prognosis was associated with more active immune infiltration and upregulated expression of immune checkpoints. We screened nine necroptosis related genes as key prognostic genes and established a risk model, which showed a good potential for survival prediction in colorectal cancer. Nomogram assessment showed that the model had high reliability for predicting the prognosis of colorectal cancer patients. The high-risk and low-risk group also has different sensitivity to immunotherapy and commonly used drugs for colorectal cancer. Overall, necroptosis related genes were involved in the immune microenvironment of colorectal cancer patient, could be utilized to predict the prognosis of colorectal cancer and develop more individualized treatment.

Which cell death modality wins the contest for photodynamic therapy of cancer?

Photodynamic therapy (PDT) was discovered more than 100 years ago. Since then, many protocols and agents for PDT have been proposed for the treatment of several types of cancer. Traditionally, cell death induced by PDT was categorized into three types: apoptosis, cell death associated with autophagy, and necrosis. However, with the discovery of several other regulated cell death modalities in recent years, it has become clear that this is a rather simple understanding of the mechanisms of action of PDT. New observations revealed that cancer cells exposed to PDT can pass through various non-conventional cell death pathways, such as paraptosis, parthanatos, mitotic catastrophe, pyroptosis, necroptosis, and ferroptosis. Nowadays, immunogenic cell death (ICD) has become one of the most promising ways to eradicate tumor cells by activation of the T-cell adaptive immune response and induction of long-term immunological memory. ICD can be triggered by many anti-cancer treatment methods, including PDT. In this review, we critically discuss recent findings on the non-conventional cell death mechanisms triggered by PDT. Next, we emphasize the role and contribution of ICD in these PDT-induced non-conventional cell death modalities. Finally, we discuss the obstacles and propose several areas of research that will help to overcome these challenges and lead to the development of highly effective anti-cancer therapy based on PDT.

Biological causes of immunogenic cancer cell death (ICD) and anti-tumor therapy; Combination of Oncolytic virus-based immunotherapy and CAR T-cell therapy for ICD induction

Chimeric antigen receptor (CAR) T-cell therapy is a promising and rapidly expanding therapeutic option for a wide range of human malignancies. Despite the ongoing progress of CAR T-cell therapy in hematologic malignancies, the application of this therapeutic strategy in solid tumors has encountered several challenges due to antigen heterogeneity, suboptimal CAR T-cell trafficking, and the immunosuppressive features of the tumor microenvironment (TME). Oncolytic virotherapy is a novel cancer therapy that employs competent or genetically modified oncolytic viruses (OVs) to preferentially proliferate in tumor cells. OVs in combination with CAR T-cells are promising candidates for overcoming the current drawbacks of CAR T-cell application in tumors through triggering immunogenic cell death (ICD) in cancer cells. ICD is a type of cellular death in which danger-associated molecular patterns (DAMPs) and tumor-specific antigens are released, leading to the stimulation of potent anti-cancer immunity. In the present review, we discuss the biological causes of ICD, different types of ICD, and the synergistic combination of OVs and CAR T-cells to reach potent tumor-specific immunity.

A Risk Model Developed Based on Necroptosis Predicts Overall Survival for Hepatocellular Carcinoma and Identification of Possible Therapeutic Drugs

Background

Necroptosis is a form of regulatory cell death (RCD) that attracts and activates immune cells, resulting in pro-tumor or anti-tumor effects. The purpose of this study was to investigate genes associated with necroptosis, to construct a risk score for predicting overall survival in patients with hepatocellular carcinoma, and to find potentially effective drugs.

Methods

The three algorithms ssGSEA, EPIC, and ESTIMATE were used to quantify the immune cell infiltration of the samples, differentially expressed genes (DEGs) analysis, and weighted gene co-expression network analysis were used to screen necroptosis related genes. Variables were screened according to random survival forest analysis, and combinations with significant p-values and a low number of genes were defined as prognostic signatures by using log-rank test after gene combination. Based on the sensitivity data of PRISM and CTRP2.0 datasets, we predicted the potential therapeutic agents for high-NRS patients.

Results

Seven genes such as TOP2A were used to define necroptosis-related risk score (NRS). The prognostic value of risk score was further validated, where high NRS was identified as a poor prognostic factor and tended to have higher grades of histologic grade, pathologic stage, T stage, BCLC, CLIP, and higher AFP. Higher NRS was also negatively correlated with the abundance of DCs, Neutrophils, Th17 cells, Macrophages, Endothelial, and positively correlated with Th2 cells. Necroptosis is often accompanied by the release of multiple cytokines, and we found that some cytokines were significantly correlated with both NRS and immune cells, suggesting that necroptosis may affect the infiltration of immune cells through cytokines. In addition, we found that TP53 mutations were more common in samples with high NRS, and these mutations may be associated with changes in NRS. Patients with high NRS may be more sensitive to gemcitabine, and gemcitabine may be an effective drug to improve the prognosis of patients with high NRS, which may play a role by inhibiting the expression of TOP2A.

Conclusions

We constructed a necroptosis-related scoring model to predict OS in HCC patients, and NRS was associated with immune response, TP53 mutation, and poor clinical classification in HCC patients. In addition, gemcitabine may be an effective drug for high-NRS patients.

Construction and Validation of a Necroptosis-Related Signature Associated With the Immune Microenvironment in Liver Hepatocellular Carcinoma

Background: Liver hepatocellular carcinoma (LIHC) is a widespread and often deadly neoplasm. There is increasing evidence that necroptosis mediates numerous tumor-associated behaviors, as well as the regulation of the tumor microenvironment, suggesting its use as a biomarker for tumor prognosis.

Methods: Data on mRNA expression and necroptosis regulators were acquired from the TCGA and KEGG databases, respectively. Clinical liver hepatocellular carcinoma (LIHC) patient data and information on the expression of necroptosis regulators were processed by unsupervised cluster analysis was performed on LIHC patients together with necroptotic regulator expression and, differentially expressed necroptosis-related genes (DENRGs) were identified by comparing the two clusters. A signature based on eight DENRGs was constructed and verified through independent data sets, and its relationship with the tumor microenvironment was investigated.

Results: Unsupervised cluster analysis demonstrated inherent immune differences among LIHC patients. In all, 1,516 DENRGs were obtained by comparison between the two clusters. In the training set, the final eight genes obtained by univariate, LASSO, and multivariate Cox regression were utilized for constructing the signature. The survival and receiver operating characteristic (ROC) curve achieved satisfactory results in both sets. The high-risk group was characterized by greater immune infiltration and poor prognosis. The results of survival analysis based on the expression of eight DENRGs further confirmed the signature.

Conclusion: We established and validated a risk signature based on eight DERNGs related to the tumor microenvironment. This provides a possible explanation for the different clinical effects of immunotherapy and provides a novel perspective for predicting tumor prognosis in LIHC.

Necroptosis as a Novel Facet of Mitotic Catastrophe

Mitotic catastrophe is a defensive mechanism that promotes elimination of cells with aberrant mitosis by triggering the cell-death pathways and/or cellular senescence. Nowadays, it is known that apoptosis, autophagic cell death, and necrosis could be consequences of mitotic catastrophe. Here, we demonstrate the ability of a DNA-damaging agent, doxorubicin, at 600 nM concentration to stimulate mitotic catastrophe. We observe that the inhibition of caspase activity leads to accumulation of cells with mitotic catastrophe hallmarks in which RIP1-dependent necroptotic cell death is triggered. The suppression of autophagy by a chemical inhibitor or ATG13 knockout upregulates RIP1 phosphorylation and promotes necroptotic cell death. Thus, in certain conditions mitotic catastrophe, in addition to apoptosis and autophagy, can precede necroptosis.

Ag/Au Bimetallic Nanoparticles Trigger Different Cell Death Pathways and Affect Damage Associated Molecular Pattern Release in Human Cell Lines

Simple Summary

Apoptosis is the goal of several therapeutic strategies for cancer. However, the apoptotic pathway is not always functional in many cancers and thus, alternative ways to destroy cancer cells are required. In this context, we investigated whether nanoparticles composed of a gold and silver alloy (AgAu NPs) can induce other programmed cell death pathways. These include necroptosis and pyroptosis, while their effects on the release of molecules that serve as danger signals, the damage associated molecular patterns (DAMPs) were also investigated. Our findings suggest that MDA-MB-231 cells, one of the cancer cell lines tested, experience mixed cell death (several cell death pathways are activated), while a second cell line, HCT116 cells, releases DAMPS. This is important, since necroptosis and pyroptosis have promising anticancer effects, while DAMPs trigger inflammation and current knowledge suggests a rather beneficial role in cancer.

Abstract

Apoptosis induction is a common therapeutic approach. However, many cancer cells are resistant to apoptotic death and alternative cell death pathways including pyroptosis and necroptosis need to be triggered. At the same time, danger signals that include HMGB1 and HSP70 can be secreted/released by damaged cancer cells that boost antitumor immunity. We studied the cytotoxic effects of AgAu NPs, Ag NPs and Au NPs with regard to the programmed cell death (apoptosis, necroptosis, pyroptosis) and the secretion/release of HSP70 and HMGB1. Cancer cell lines were incubated with 30, 40 and 50 μg/mL of AgAu NPs, Ag NPs and Au NPs. Cytotoxicity was estimated using the MTS assay, and mRNA fold change of CASP1, CASP3, BCL-2, ZPB1, HMGB1, HSP70, CXCL8, CSF1, CCL20, NLRP3, IL-1β and IL-18 was used to investigate the associated programmed cell death. Extracellular levels of HMGB1 and IL-1β were investigated using the ELISA technique. The nanoparticles showed a dose dependent toxicity. Pyroptosis was triggered for LNCaP and MDA-MB-231 cells, and necroptosis for MDA-MB-231 cells. HCT116 cells experience apoptotic death and show increased levels of extracellular HMGB1. Our results suggest that in a manner dependent of the cellular microenvironment, AgAu NPs trigger mixed programmed cell death in P53 deficient MDA-MB-231 cells, while they also trigger IL-1β release in MDA-MB-231 and LNCaP cells and release of HMGB1 in HCT116 cells.

A Novel Necroptosis-Related lncRNA Signature Predicts the Prognosis of Lung Adenocarcinoma

Background: Necroptosis is closely related to the tumorigenesis and development of cancer. An increasing number of studies have demonstrated that targeting necroptosis could be a novel treatment strategy for cancer. However, the predictive potential of necroptosis-related long noncoding RNAs (lncRNAs) in lung adenocarcinoma (LUAD) still needs to be clarified. This study aimed to construct a prognostic signature based on necroptosis-related lncRNAs to predict the prognosis of LUAD.

Methods: We downloaded RNA sequencing data from The Cancer Genome Atlas database. Co-expression network analysis, univariate Cox regression, and least absolute shrinkage and selection operator were adopted to identify necroptosis-related prognostic lncRNAs. We constructed the predictive signature by multivariate Cox regression. Kaplan–Meier analysis, time-dependent receiver operating characteristics, nomogram, and calibration curves were used to validate and evaluate the signature. Subsequently, we used gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) to explore the relationship between the predictive signature and tumor immune microenvironment of risk groups. Finally, the correlation between the predictive signature and immune checkpoint expression of LUAD patients was also analyzed.

Results: We constructed a signature composed of 7 necroptosis-related lncRNAs (AC026355.2, AC099850.3, AF131215.5, UST-AS2, ARHGAP26-AS1, FAM83A-AS1, and AC010999.2). The signature could serve as an independent predictor for LUAD patients. Compared with clinicopathological variables, the necroptosis-related lncRNA signature has a higher diagnostic efficiency, with the area under the receiver operating characteristic curve being 0.723. Meanwhile, when patients were stratified according to different clinicopathological variables, the overall survival of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the low-risk group. ssGSEA further confirmed that the predictive signature was significantly related to the immune status of LUAD patients. The immune checkpoint analysis displayed that low-risk patients had a higher immune checkpoint expression, such as CTLA-4, HAVCR2, PD-1, and TIGIT. This suggested that immunological function is more active in the low-risk group LUAD patients who might benefit from checkpoint blockade immunotherapies.

Conclusion: The predictive signature can independently predict the prognosis of LUAD, helps elucidate the mechanism of necroptosis-related lncRNAs in LUAD, and provides immunotherapy guidance for patients with LUAD.

A Necroptosis-Related Prognostic Model of Uveal Melanoma Was Constructed by Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases

Background

Uveal melanoma(UVM) is the most common intraocular malignancy and has a poor prognosis. The clinical significance of necroptosis(NCPS) in UVM is unclear.

Methods

We first identified necroptosis genes in UVM by single-cell analysis of the GSE139829 dataset from the GEO database and weighted co-expression network analysis of TCGA data. COX regression and Lasso regression were used to construct the prognostic model. Then survival analysis, immune microenvironment analysis, and mutation analysis were carried out. Finally, cell experiments were performed to verify the role of ITPA in UVM.

Result

By necroptosis-related prognostic model, UVM patients in both TCGA and GEO cohorts could be classified as high-NCPS and low-NCPS groups, with significant differences in survival time between the two groups (P<0.001). Besides, the high-NCPS group had higher levels of immune checkpoint-related gene expression, suggesting that they might be more likely to benefit from immunotherapy. The cell experiments confirmed the role of ITPA, the most significant gene in the model, in UVM. After ITPA was knocked down, the activity, proliferation, and invasion ability of the MuM-2B cell line were significantly reduced.

Conclusion

Our study can provide a reference for the diagnosis and treatment of patients with UVM.

Identification and Quantification of Necroptosis Landscape on Therapy and Prognosis in Kidney Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) has high morbidity and gradually increased in recent years, and the rate of progression once relapsed is high. At present, owing to lack of effective prognosis predicted markers and post-recurrence drug selection guidelines, the prognosis of KIRC patients is greatly affected. Necroptosis is a regulated form of cell necrosis in a way that is independent of caspase. Induced necroptosis is considered an effective strategy in chemotherapy and targeted drugs, and it can also be used to improve the efficacy of immunotherapy. Herein, we quantified the necroptosis landscape of KIRC patients from The Cancer Genome Atlas (TCGA) database and divided them into two distinct necroptosis-related patterns (C1 and C2) through the non-negative matrix factorization (NMF) algorithm. Multi-analysis revealed the differences in clinicopathological characteristics and tumor immune microenvironment (TIME). Then, we constructed the NRG prognosis signature (NRGscore), which contained 10 NRGs (PLK1, APP, TNFRSF21, CXCL8, MYCN, TNFRSF1A, TRAF2, HSP90AA1, STUB1, and FLT3). We confirmed that NRGscore could be used as an independent prognostic marker for KIRC patients and performed excellent stability and accuracy. A nomogram model was also established to provide a more beneficial prognostic indicator for the clinic. We found that NRGscore was significantly correlated with clinicopathological characteristics, TIME, and tumor mutation burden (TMB) of KIRC patients. Moreover, NRGscore had effective guiding significance for immunotherapy, chemotherapy, and targeted drugs.

Improved Multimodal Tumor Necrosis Imaging with IRDye800CW-DOTA Conjugated to an Albumin-Binding Domain

Simple Summary

Anti-tumor treatment efficacy is determined by tumor shrinkage, which takes valuable time to become apparent and poses a risk of unnecessary treatment with severe side effects. Therefore, there is an unmet need for more reliable and specific methods to monitor treatment efficacy. We explore radiolabeled cyanines for imaging tumor necrosis as a unique marker for therapy efficacy. Moreover, spontaneous tumor necrosis is a hallmark for aggressively growing tumor types with poor prognosis. We improved the binding properties of a previously reported necrosis-avid contrast agent (NACA) and successfully detected spontaneous and therapy-induced tumor necrosis in mice using radioactivity and fluorescence imaging modalities. This NACA may pave the way to in vivo detection of tumor necrosis for early-stage determination of tumor aggressiveness and therapy efficacy.

Abstract

Purpose: To assess our improved NACA for the detection of tumor necrosis. Methods: We increased the blood circulation time of our NACA by adding an albumin-binding domain to the molecular structure. We tested the necrosis avidity on dead or alive cultured cells and performed SPECT and fluorescence imaging of both spontaneous and treatment-induced necrosis in murine breast cancer models. We simultaneously recorded [¹⁸F]FDG-PET and bioluminescence images for complementary detection of tumor viability. Results: We generated two albumin-binding IRDye800CW derivatives which were labeled with indium-111 with high radiochemical purity. Surprisingly, both albumin-binding NACAs had >10x higher in vitro binding towards dead cells. We selected [¹¹¹In]3 for in vivo experiments which showed higher dead cell binding in vitro and in vivo stability. The doxorubicin-treated tumors showed increased [¹¹¹In]3-uptake (1.74 ± 0.08%ID/g after saline treatment, 2.25 ± 0.16%ID/g after doxorubicin treatment, p = 0.044) and decreased [¹⁸F]FDG-uptake (3.02 ± 0.51%ID/g after saline treatment, 1.79 ± 0.11%ID/g after doxorubicin treatment, p = 0.040), indicating therapy efficacy. Moreover, we detected increased [¹¹¹In]3-uptake and tumor necrosis in more rapidly growing EMT6 tumors. Conclusions: Our albumin-binding NACA based on IRDye800CW facilitates tumor-necrosis imaging for assessment of therapy efficacy and aggressiveness in solid tumors using both fluorescence and SPECT imaging.

Organoantimony (III) Derivative induces necroptosis in human breast cancer MDA-MB-231 cells

PURPOSE

This study aimed to investigate the anticancer effect and the underlying mechanisms of organoantimony (III) fluoride on MDA-MB-231 human breast cancer cells.

METHODS

Five cancer and one normal cell line were treated with an organoantimony (III) compound 6-cyclohexyl-12-fluoro-5,6,7,12-tetrahydrodibenzo[c,f][1,5]azastibocine (denoted as C4). The cell viability was detected by MTT assay. Induction of cell death was determined by Hoechst 33342/PI staining and Annexin-V/PI staining. The effect of C4 on the necroptotic relative protein was determined by Western blot analysis.

RESULTS

Among the five cancer cell lines, C4 decreased the viability of MDA-MB-231, MCF-7 and A2780/cisR, and showed less toxicity to normal human embryonic kidney cells. In breast cancer cell line MDA-MB-231, the C4 treatment induced the percentage of necrotic cell death as well as LDH releasing in a time- and dose-dependent manner. Moreover, C4 could increase the expression of phosphorylated RIPK3 and MLKL proteins. Overall, the C4 treatment resulted in reduction of mitochondrial transmembrane potential and accumulation ROS in MDA-MB-231 cells.

CONCLUSION

C4-induced necroptosis could be ascribed to glutathione depletion and ROS elevation in MDA-MB-231 cells. Our findings illustrate that C4 is a potential necroptosis inducer for breast cancer treatment.

Directing hypoxic tumor microenvironment and HIF to illuminate cancer immunotherapy's existing prospects and challenges in drug targets

Cancer is now also reflected as a disease of the tumor microenvironment, primarily supposed to be a decontrolled genetic and cellular expression disease. Over the past two decades, significant and rapid progress has been made in recognizing the dynamics of the tumor's microenvironment and its contribution to influencing the response to various anti-cancer therapies and drugs. Modulations in the tumor microenvironment and immune checkpoint blockade are interesting in cancer immunotherapy and drug targets. Simultaneously, the immunotherapeutic strategy can be done by modulating the immune regulatory pathway; however, the tumor microenvironment plays an essential role in suppressing the antitumor's immunity by its substantial heterogeneity. Hypoxia inducible factor (HIF) is a significant contributor to solid tumor heterogeneity and a key stressor in the tumor microenvironment to drive adaptations to prevent immune surveillance. Checkpoint inhibitors here halt the ability of cancer cells to stop the immune system from activating, and in turn, amplify your body's immune system to help destroy cancer cells. Common checkpoints that these inhibitors affect are the PD-1/PD-L1 and CTLA-4 pathways and important drugs involved are Ipilimumab and Nivolumab, mainly along with other drugs in this group. Targeting the hypoxic tumor microenvironment may provide a novel immunotherapy strategy, break down traditional cancer therapy resistance, and build the framework for personalized precision medicine and cancer drug targets. We hope that this knowledge can provide insight into the therapeutic potential of targeting Hypoxia and help to develop novel combination approaches of cancer drugs to increase the effectiveness of existing cancer therapies, including immunotherapy.

A canthin-6-one derivative induces cell death by apoptosis/necroptosis-like with DNA damage in acute myeloid cells

Natural products have long been considered a relevant source of new antitumor agents. Despite advances in the treatment of younger patients with acute myeloid leukemia (AML), the prognosis of elderly patients remains poor, with a high frequency of relapse. The cytotoxicity of canthin-6-one alkaloids has been extensively studied in different cell types, including leukemic strains. Among the canthin-6-one analogs tested, 10-methoxycanthin-6-one (Mtx-C) showed the highest cytotoxicity in the malignant AML cells Kasumi-1 and KG-1. Thus, we evaluated the cytotoxicity and cell death mechanisms related to Mtx-C using the EC50 (80 µM for Kasumi-1 and 36 µM for KG-1) treatment for 24 h. Our results identify reactive oxygen species production, mitochondrial depolarization, annexin V-FITC/7-AAD double staining, caspase cleave and upregulation of mitochondria-dependent apoptosis proteins (Bax, Bim, Bik, Puma and phosphorylation of p53) for both cell lineages. However, downregulation of Bcl-2 and the simultaneous execution of the apoptotic and necroptotic programs associated with the phosphorylation of the proteins receptor-interacting serine/threonine-protein kinase 3 and mixed lineage kinase domain-like pseudokinase occurred only in Kasumi-1 cells. About the lasted events, Kasumi-1 cell death was inhibited by pharmacological agents such as Zvad-FMK and necrostatin-1. The underlying molecular mechanisms of Mtx-C still include participation in the DNA damage and stress-signaling pathways involving p38 and c-Jun N-terminal mitogen-activated protein kinases and interaction with DNA. Thus, Mtx-C represents a promising tool for the development of new antileukemic molecules.

Immunogenic cell death and its therapeutic or prognostic potential in high-grade glioma

Immunogenic cell death (ICD) has emerged as a key component of therapy-induced anti-tumor immunity. Over the past few years, ICD was found to play a pivotal role in a wide variety of novel and existing treatment modalities. The clinical application of these techniques in cancer treatment is still in its infancy. Glioblastoma (GBM) is the most lethal primary brain tumor with a dismal prognosis despite maximal therapy. The development of new therapies in this aggressive type of tumors remains highly challenging partially due to the cold tumor immune environment. GBM could therefore benefit from ICD-based therapies stimulating the anti-tumor immune response. In what follows, we will describe the mechanisms behind ICD and the ICD-based (pre)clinical advances in anticancer therapies focusing on GBM.

A Novel Prognostic Predictor of Immune Microenvironment and Therapeutic Response in Kidney Renal Clear Cell Carcinoma based on Necroptosis-related Gene Signature

Background: Necroptosis, a cell death of caspase-independence, plays a pivotal role in cancer biological regulation. Although necroptosis is closely associated with oncogenesis, cancer metastasis, and immunity, there remains a lack of studies determining the role of necroptosis-related genes (NRGs) in the highly immunogenic cancer type, kidney renal clear cell carcinoma (KIRC). Methods: The information of clinicopathology and transcriptome was extracted from TCGA database. Following the division into the train and test cohorts, a three-NRGs (TLR3, FASLG, ZBP1) risk model was identified in train cohort by LASSO regression. The overall survival (OS) comparison was conducted between different risk groups through Kaplan-Meier analysis, which was further validated in test cohort. The Cox proportional hazards regression model was introduced to assess its impact of clinicopathological factors and risk score on survival. ESTIMATE and CIBERSORT algorithms were introduced to evaluate immune microenvironment, while enrichment analysis was conducted to explore the biological significance. Correlation analysis was applied for the correlation assessment between checkpoint gene expression and risk score, between gene expression and therapeutic response. Gene expressions from TCGA were verified by GEO datasets and immunohistochemistry (IHC) analysis. Results: This NRGs-related signature predicted poorer OS in high-risk group, which was also verified in test cohort. Risk score could also independently predict survival outcome of KIRC. Significant changes were also found in immune microenvironment and checkpoint gene expressions between different risk groups, with immune functional enrichment in high-risk group. Interestingly, therapeutic response was correlated with the expressions of NRGs. The expressions of NRGs from TCGA were consistent with those from GEO datasets and IHC analysis. Conclusion: The NRGs-related signature functions as a novel prognostic predictor of immune microenvironment and therapeutic response in KIRC.

Synthesis and biological evaluation of celastrol derivatives as potential anti-glioma agents by activating RIP1/RIP3/MLKL pathway to induce necroptosis

Celastrol, a quinone methide triterpenoid, possesses potential anti-glioma activity. However, its relatively low activity limit its application as an effective agent for glioma treatment. In search for effective anti-glioma agents, this work designed and synthesized two series of celastrol C-3 OH and C-20 COOH derivatives 4a-4o and 6a-6o containing 1, 2, 3-triazole moiety. Their anti-glioma activities against four human glioma cell lines (A172, LN229, U87, and U251) were then evaluated using MTT assay in vitro. Results showed that compound 6i (IC₅₀ = 0.94 μM) exhibited substantial antiproliferative activity against U251 cell line, that was 4.7-fold more potent than that of celastrol (IC₅₀ = 4.43 μM). In addition, compound 6i remarkably inhibited the colony formation and migration of U251 cells. Further transmission electron microscopy and mitochondrial depolarization assays in U251 cells indicated that the potent anti-glioma activity of 6i was attributed to necroptosis. Mechanism investigation revealed that compound 6i induced necroptosis mainly by activating the RIP1/RIP3/MLKL pathway. Additionally, compound 6i exerted acceptable BBB permeability in mice and inhibited U251 cell proliferation in an in vivo zebrafish xenograft model, obviously. In summary, compound 6i might be a promising lead compound for potent celastrol derivatives as anti-glioma agents.

Peripherally-driven myeloid NFkB and IFN/ISG responses predict malignancy risk, survival, and immunotherapy regime in ovarian cancer

Background

Tumors can influence peripheral immune macroenvironment, thereby creating opportunities for non-invasive serum/plasma immunobiomarkers for immunostratification and immunotherapy designing. However, current approaches for immunobiomarkers’ detection are largely quantitative, which is unreliable for assessing functional peripheral immunodynamics of patients with cancer. Hence, we aimed to design a functional biomarker modality for capturing peripheral immune signaling in patients with cancer for reliable immunostratification.

Methods

We used a data-driven in silico framework, integrating existing tumor/blood bulk-RNAseq or single-cell (sc)RNAseq datasets of patients with cancer, to inform the design of an innovative serum-screening modality, that is, serum-functional immunodynamic status (sFIS) assay. Next, we pursued proof-of-concept analyses via multiparametric serum profiling of patients with ovarian cancer (OV) with sFIS assay combined with Luminex (cytokines/soluble immune checkpoints), CA125-antigen detection, and whole-blood immune cell counts. Here, sFIS assay’s ability to determine survival benefit or malignancy risk was validated in a discovery (n=32) and/or validation (n=699) patient cohorts. Lastly, we used an orthotopic murine metastatic OV model, with anti-OV therapy selection via in silico drug–target screening and murine serum screening via sFIS assay, to assess suitable in vivo immunotherapy options.

Results

In silico data-driven framework predicted that peripheral immunodynamics of patients with cancer might be best captured via analyzing myeloid nuclear factor kappa-light-chain enhancer of activated B cells (NFκB) signaling and interferon-stimulated genes' (ISG) responses. This helped in conceptualization of an ‘in sitro’ (in vitro+in situ) sFIS assay, where human myeloid cells were exposed to patients’ serum in vitro, to assess serum-induced (si)-NFκB or interferon (IFN)/ISG responses (as active signaling reporter activity) within them, thereby ‘mimicking’ patients’ in situ immunodynamic status. Multiparametric serum profiling of patients with OV established that sFIS assay can: decode peripheral immunology (by indicating higher enrichment of si-NFκB over si-IFN/ISG responses), estimate survival trends (si-NFκB or si-IFN/ISG responses associating with negative or positive prognosis, respectively), and coestimate malignancy risk (relative to benign/borderline ovarian lesions). Biologically, we documented dominance of pro-tumorigenic, myeloid si-NFκB response^HIGHsi-IFN/ISG response^LOW inflammation in periphery of patients with OV. Finally, in an orthotopic murine metastatic OV model, sFIS assay predicted the higher capacity of chemo-immunotherapy (paclitaxel–carboplatin plus anti-TNF antibody combination) in achieving a pro-immunogenic peripheral milieu (si-IFN/ISG response^HIGHsi-NFκB response^LOW), which aligned with high antitumor efficacy.

Conclusions

We established sFIS assay as a novel biomarker resource for serum screening in patients with OV to evaluate peripheral immunodynamics, patient survival trends and malignancy risk, and to design preclinical chemo-immunotherapy strategies.

Efferocytosis and the Story of "Find Me," "Eat Me," and "Don't Eat Me" Signaling in the Tumor Microenvironment

The process of efferocytosis involves removal of dying or dead cells by phagocytosis. Another term "efferosome" is used which means a fluid-filled membrane vesicle which engulfs dead cells. The process of efferocytosis works in coordination with apoptosis because before the contents of apoptotic cells are bleached out, they are engulfed by efferosomes. Thus, the microenvironment is not polluted with toxic enzymes and oxidants. A defect in the apoptotic cell clearance may participate in autoimmunity and chronic inflammation for homeostasis and proper tissue development, for which removal of dead cells is essential. This also protects from chronic inflammation and autoimmunity. In different tumor types and other diseases, efferocytosis has been studied extensively and potential pathways identified. A few of the intermediates in different pathways, which create aggressive and tolerogenic tumor microenvironment, might be considered for therapeutic or interventional purposes. Since the key players in efferocytosis are macrophages and dendritic cells, development of antigen-dependent antitumor immunity is affected by efferocytosis. The literature analysis suggests that efferocytosis is an underappreciated immune checkpoint, perhaps one that might be therapeutically targeted in the setting of cancer. The current status of efferocytosis and its role in tumor microenvironment is discussed in this article.

Gallic acid for cancer therapy: Molecular mechanisms and boosting efficacy by nanoscopical delivery

Cancer is the second leading cause of death worldwide. Majority of recent research efforts in the field aim to address why cancer resistance to therapy develops and how to overcome or prevent it. In line with this, novel anti-cancer compounds are desperately needed for chemoresistant cancer cells. Phytochemicals, in view of their pharmacological activities and capacity to target various molecular pathways, are of great interest in the development of therapeutics against cancer. Plant-derived-natural products have poor bioavailability which restricts their anti-tumor activity. Gallic acid (GA) is a phenolic acid exclusively found in natural sources such as gallnut, sumac, tea leaves, and oak bark. In this review, we report on the most recent research related to anti-tumor activities of GA in various cancers with a focus on its underlying molecular mechanisms and cellular pathwaysthat that lead to apoptosis and migration of cancer cells. GA down-regulates the expression of molecular pathways involved in cancer progression such as PI3K/Akt. The co-administration of GA with chemotherapeutic agents shows improvements in suppressing cancer malignancy. Various nano-vehicles such as organic- and inorganic nano-materials have been developed for targeted delivery of GA at the tumor site. Here, we suggest that nano-vehicles improve GA bioavailability and its ability for tumor suppression.

Failure of Immunotherapy-The Molecular and Immunological Origin of Immunotherapy Resistance in Lung Cancer

Immune checkpoint inhibitors (ICIs) have a huge impact on clinical treatment results in non-small cell lung cancer (NSCLC). Blocking antibodies targeting programmed cell death protein 1 (PD-1), programmed cell death protein ligand 1 (PD-L1) or CTLA-4 (cytotoxic T cell antigen 4) have been developed and approved for the treatment of NSCLC patients. However, a large number of patients develop resistance to this type of treatment. Primary and secondary immunotherapy resistance are distinguished. No solid biomarkers are available that are appropriate to predict the unique sensitivity to immunotherapy. Knowledge of predictive markers involved in treatment resistance is fundamental for planning of new treatment combinations. Scientists focused research on the use of immunotherapy as an essential treatment in combination with other therapy strategies, which could increase cancer immunogenicity by generating tumor cells death and new antigen release as well as by targeting other immune checkpoints and tumor microenvironment. In the present review, we summarize the current knowledge of molecular bases underlying immunotherapy resistance and discuss the capabilities and the reason of different therapeutic combinations.

Early memory differentiation and cell death resistance in T cells predicts melanoma response to sequential anti-CTLA4 and anti-PD1 immunotherapy

Immune checkpoint blockers (ICBs)-based immunotherapy has revolutionised oncology. However, the benefits of ICBs are limited to only a subset of patients. Herein, the biomarkers-driven application of ICBs promises to increase their efficacy. Such biomarkers include lymphocytic IFNγ-signalling and/or cytolytic activity (granzymes and perforin-1) footprints, whose levels in pre-treatment tumours can predict favourable patient survival following ICB-treatment. However, it is not clear whether such biomarkers have the same value in predicting survival of patients receiving first-line anti-CTLA4 ICB-therapy, and subsequently anti-PD1 ICB-therapy (i.e., sequential ICB-immunotherapy regimen). To address this, we applied highly integrated systems/computational immunology approaches to existing melanoma bulk-tumour transcriptomic and single-cell (sc)RNAseq data originating from immuno-oncology clinical studies applying ICB-treatment. Interestingly, we observed that CD8⁺/CD4⁺T cell-associated IFNγ-signalling or cytolytic activity signatures fail to predict tumour response in patients treated with anti-CTLA4 ICB-therapy as a first-line and anti-PD1 ICB-therapy in the second-line setting. On the contrary, signatures associated with early memory CD8⁺/CD4⁺T cells (integrating TCF1-driven stem-like transcriptional programme), capable of resisting cell death/apoptosis, better predicted objective response rates to ICB-immunotherapy, and favourable survival in the setting of sequential ICB-immunotherapy. These observations suggest that sequencing of ICB-therapy might have a specific impact on the T cell-repertoire and may influence the predictive value of tumoural immune biomarkers.

The Great Escape: The Power of Cancer Stem Cells to Evade Programmed Cell Death

Cancer is one of the primary causes of death worldwide. Tumour malignancy is related to tumor heterogeneity, which has been suggested to be due to a small subpopulation of tumor cells named cancer stem cells (CSCs). CSCs exert a key role in metastasis development, tumor recurrence, and also epithelial-mesenchymal transition, apoptotic resistance, self-renewal, tumorigenesis, differentiation, and drug resistance. Several current therapies fail to eradicate tumors due to the ability of CSCs to escape different programmed cell deaths. Thus, developing CSC-selective and programmed death-inducing therapeutic approaches appears to be of primary importance. In this review, we discuss the main programmed cell death occurring in cancer and the promising CSC-targeting agents developed in recent years. Even if the reported studies are encouraging, further investigations are necessary to establish a combination of agents able to eradicate CSCs or inhibit their growth and proliferation.

Synergistic Effects of Acoustics-based Therapy and Immunotherapy in Cancer Treatment

Cancer is an intractable disease and has ability to escape immunological recognition. Cancer immunotherapy to enhance the autogenous immune response to cancer tissue is reported to be the most promising method for cancer treatment. After the release of damage-associated molecular patterns, dendritic cells come mature and then recruit activated T cells to induce immune response. To trigger the release of cancer associated antigens, cancer acoustics-based therapy has various prominent advantages and has been reported in various research. In this review, we classified the acoustics-based therapy into sonopyrolysis-, sonoporation-, and sonoluminescence-based therapy. Then, detailed mechanisms of these therapies are discussed to show the status of cancer immunotherapy induced by acoustics-based therapy in quo. Finally, we express some future prospects in this research field and make some predictions of its development direction