Programmed Cell Death Tunes Tumor Immunity

Programmed Cell Death-Related Gene Signature Associated with Prognosis and Immune Infiltration and the Roles of HMOX1 in the Proliferation and Apoptosis were Investigated in Uveal Melanoma

BACKGROUND

Uveal melanoma (UVM) is the most common primary ocular malignancy, with a wide range of symptoms and outcomes. The programmed cell death (PCD) plays an important role in tumor development, diagnosis, and prognosis. There is still no research on the relationship between PCD-related genes and UVM. A novel PCD-associated prognostic model is urgently needed to improve treatment strategies.

OBJECTIVE

We aim to screen PCD-related prognostic signature and investigate its proliferation ability and apoptosis in UVM cells.

METHODS

The clinical information and RNA-seq data of the UVM patients were collected from the TCGA cohort. All the patients were classified using consensus clustering by the selected PCD-related genes. After univariate Cox regression and PPI network analysis, the prognostic PCD-related genes were then submitted to the LASSO regression analysis to build a prognostic model. The level of immune infiltration of 8-PCD signature in high- and low-risk patients was analyzed using xCell. The prediction on chemotherapy and immunotherapy response in UVM patients was assessed by GDSC and TIDE algorithm. CCK-8, western blot and Annexin V-FITC/PI staining were used to explore the roles of HMOX1 in UVM cells.

RESULTS

A total of 8-PCD signature was constructed and the risk score of the PCD signature was negatively correlated with the overall survival, indicating strong predictive ability and independent prognostic value. The risk score was positively correlated with CD8 Tcm, CD8 Tem and Th2 cells. Immune cells in high-risk group had poorer overall survival. The drug sensitivity demonstrated that cisplatin might impact the progression of UVM and better immunotherapy responsiveness in the high-risk group. Finally, Overespression HMOX1 (OE-HMOX1) decreased the cell viability and induced apoptosis in UVM cells. Recuse experiment results showed that ferrostatin-1 (fer-1) protected MP65 cells from apoptosis and necrosis caused by OE-HMOX1.

CONCLUSION

The PCD signature may have a significant role in the tumor microenvironment, clinicopathological characteristics, prognosis and drug sensitivity. More importantly, HMOX1 depletion greatly induced tumor cell growth and inhibited cell apoptosis and fer-1 protected UVM cells from apoptosis and necrosis induced by OE-HMOX1. This work provides a foundation for effective therapeutic strategy in tumour treatment.

Integrative machine learning and neural networks for identifying PANoptosis-related lncRNA molecular subtypes and constructing a predictive model for head and neck squamous cell carcinoma

PURPOSE

PANoptosis is considered a novel type of cell death that plays important roles in tumor progression. In this study, we applied machine learning algorithms to explore the relationships between PANoptosis-related lncRNAs (PRLs) and head and neck squamous cell carcinoma (HNSCC) and established a neural network model for prognostic prediction.

METHODS

Information about the HNSCC cohort was downloaded from the TCGA database, and the differentially expressed prognostic PRLs between tumor and normal samples were assessed in patients with different tumor subtypes via nonnegative matrix factorization (NMF) analysis. Subsequently, five kinds of machine-learning algorithms were used to select the core PRLs across the subtypes, and the interactive features were pooled into a neural network model to establish a PRL-related risk score (PLRS) system. Survival differences were compared via Kaplan‒Meier analysis, and the predictive effects were assessed with the areas under the ROCs. Moreover, functional enrichment analysis, immune infiltration, tumor mutation burden (TMB) and clinical therapeutic response were also conducted to further evaluate the novel predictive model.

RESULTS

A total of 347 PRLs were identified, 225 of which were differentially expressed between tumor and normal samples. Patients were divided into two clusters via NMF analysis, in which cluster 1 had a better prognosis and more immune cells and functional infiltrates. With the application of five machine learning algorithms, we selected 13 interactive PRLs to construct the predictive model. The AUCs for the ROCs in the entire set were 0.735, 0.740 and 0.723, respectively. Patients in the low-PLRS group exhibited a better prognosis, greater immune cell enrichment, greater immune function activation, lower TMB and greater sensitivity to immunotherapy.

CONCLUSION

In this study, we established a novel neural network prognostic model to predict survival and identify tumor subtypes in HNSCC patients. This novel assessment system is useful for prediction, providing ideas for clinical treatment.

Programmed cell death disrupts inflammatory tumor microenvironment (TME) and promotes glioblastoma evolution

Glioblastoma (GBM) is the most common malignant brain tumor and has a dismal prognosis even under the current first-line treatment, with a 5-year survival rate less than 7%. Therefore, it is important to understand the mechanism of treatment resistance and develop new anti-tumor strategies. Induction of programmed cell death (PCD) has become a promising anti-tumor strategy, but its effectiveness in treating GBM remains controversial. On the one hand, PCD triggers tumor cell death and then release mediators to draw in immune cells, creating a pro-inflammatory tumor microenvironment (TME). One the other hand, mounting evidence suggests that PCD and inflammatory TME will force tumor cells to evolve under survival stress, leading to tumor recurrence. The purpose of this review is to summarize the role of PCD and inflammatory TME in the tumor evolution of GBM and promising methods to overcome tumor evolution.

Cell death shapes cancer immunity: spotlighting PANoptosis

PANoptosis represents a novel type of programmed cell death (PCD) with distinctive features that incorporate elements of pyroptosis, apoptosis, and necroptosis. PANoptosis is governed by a newly discovered cytoplasmic multimeric protein complex known as the PANoptosome. Unlike each of these PCD types individually, PANoptosis is still in the early stages of research and warrants further exploration of its specific regulatory mechanisms and primary targets. In this review, we provide a brief overview of the conceptual framework and molecular components of PANoptosis. In addition, we highlight recent advances in the understanding of the molecular mechanisms and therapeutic applications of PANoptosis. By elucidating the complex crosstalk between pyroptosis, apoptosis and necroptosis and summarizing the functional consequences of PANoptosis with a special focus on the tumor immune microenvironment, this review aims to provide a theoretical basis for the potential application of PANoptosis in cancer therapy.

Deacetylated MDH1 and IDH1 aggravates PANoptosis in acute liver failure through endoplasmic reticulum stress signaling

Acute liver failure (ALF) is a disease with a high mortality rate and poor prognosis, whose pathogenesis is not fully understood. PANoptosis is a recently proposed mode of cell death characterized by pyroptosis, apoptosis, and necroptosis, but it cannot be explained by any of them alone. This study aims to explore the role of PANoptosis in ALF and the impact and mechanism of deacetylated malate dehydrogenase 1 (MDH1) and isocitrate dehydrogenase 1 (IDH1) on PANoptosis. Our results found that, compared with the control group, the cell viability in the lipopolysaccharide (LPS)/D-galactosamine (D-Gal) group decreased, lactate dehydrogenase (LDH) release increased, cell death increased, and the levels of PANoptosis-related molecules RIPK1, GSDMD, caspase-3, MLKL, IL-18, IL-1β increased, indicating that PANoptosis increased during ALF. Deacetylated MDH1 at K118 and IDH1 at K93 increased the expression of PANoptosis-related molecules RIPK1, GSDMD, caspase-3, MLKL, IL-18, and IL-1β in vivo and in vitro. The deacetylation weakened the inhibitory effect of histone deacetylase (HDAC) inhibitor ACY1215 on PANoptosis-related molecules, suggesting that deacetylated MDH1 at K118 and IDH1 at K93 aggravated PANoptosis during ALF. Deacetylated MDH1 at K118 and IDH1 at K93 also promoted the expression of endoplasmic reticulum stress-related molecules BIP, ATF6, XBP1, and CHOP in vivo and in vitro. The use of endoplasmic reticulum stress inhibitor 4-PBA weakened the promotion effect of deacetylated MDH1 K118 and IDH1 K93 on PANoptosis. The results suggested that deacetylated MDH1 at K118 and IDH1 at K93 may aggravate PANoptosis in ALF through endoplasmic reticulum stress signaling. In conclusion, deacetylated MDH1 and IDH1 may aggravate PANoptosis in ALF, and the mechanism may act through endoplasmic reticulum stress signaling.

PANoptosis subtypes predict prognosis and immune efficacy in gastric cancer

PANoptosis is a form of inflammatory programmed cell death that is regulated by the PANoptosome. This PANoptosis possesses key characteristics of pyroptosis, apoptosis, and necroptosis, yet cannot be fully explained by any of these cell death modes. The unique nature of this cell death mechanism has garnered significant interest. However, the specific role of PANoptosis-associated features in gastric cancer (GC) is still uncertain. Patients were categorized into different PAN subtypes based on the expression of genes related to the PANoptosome. We conducted a systematic analysis to investigate the variations in prognosis and tumor microenvironment (TME) among these subtypes. Furthermore, we developed a risk score, called PANoptosis-related risk score (PANS), which is constructed from genes associated with the PANoptosis. We comprehensively analyzed the correlation between PANS and GC prognosis, TME, immunotherapy efficacy and chemotherapeutic drug sensitivity. Additionally, we performed in vitro experiments to validate the impact of Keratin 7 (KRT7) on GC. We identified two PAN subtypes (PANcluster A and B). PANoptosome genes were highly expressed in PANcluster A. PANcluster A has the characteristics of favorable prognosis, abundant infiltration of anti-tumor lymphocytes, and sensitivity to immunotherapy, thus it was categorized as an immune-inflammatory type. Meanwhile, our constructed PANS can effectively predict the prognosis and immune efficacy of GC. Patients with low PANS have a good prognosis, and have the characteristics of high tumor mutation load (TMB), high microsatellite instability (MSI), low tumor purity and sensitivity to immunotherapy. In addition, PANS can also identify suitable populations for different chemotherapy drugs. Finally, we confirmed that KRT7 is highly expressed in GC. Knocking down the expression of KRT7 significantly weakens the proliferation and migration abilities of GC cells. The models based on PANoptosis signature help to identify the TME features of GC and can effectively predict the prognosis and immune efficacy of GC. Furthermore, the experimental verification results of KRT7 provide theoretical support for anti-tumor treatment.

Mitochondrial quality control in human health and disease

Mitochondria, the most crucial energy-generating organelles in eukaryotic cells, play a pivotal role in regulating energy metabolism. However, their significance extends beyond this, as they are also indispensable in vital life processes such as cell proliferation, differentiation, immune responses, and redox balance. In response to various physiological signals or external stimuli, a sophisticated mitochondrial quality control (MQC) mechanism has evolved, encompassing key processes like mitochondrial biogenesis, mitochondrial dynamics, and mitophagy, which have garnered increasing attention from researchers to unveil their specific molecular mechanisms. In this review, we present a comprehensive summary of the primary mechanisms and functions of key regulators involved in major components of MQC. Furthermore, the critical physiological functions regulated by MQC and its diverse roles in the progression of various systemic diseases have been described in detail. We also discuss agonists or antagonists targeting MQC, aiming to explore potential therapeutic and research prospects by enhancing MQC to stabilize mitochondrial function.

Molecular subtypes of clear cell renal carcinoma based on PCD-related long non-coding RNAs expression: insights into the underlying mechanisms and therapeutic strategies

BACKGROUND

PCD-related long non-coding RNAs (PRLs) are rarely investigated in relation to clear cell renal carcinoma (ccRCC). As part of this study, we evaluated the immunological potential of PRL signatures as a biomarker for ccRCC prognosis and immunological function.

MATERIALS AND METHODS

Data were downloaded from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases. A Pearson correlation analysis was conducted on the 27 PCD-associated genes to determine whether lncRNAs were significantly associated with PCD. Kaplan-Meier analysis, biological function identification, immune infiltration analysis, estimation of efficacy of immunotherapy and targeted drug screening, and exploration of the landscape of mutation status were conducted by analyzing the risk scores.

RESULTS

Seven PRLs, LINC02747, AP001636.3, AC022126.1, LINC02657, LINC02609, LINC02154, and ZNNT1, were used to divide patients with ccRCC into groups with high and low risk. High-risk patients had a worse prognosis than low-risk patients, according to the results, and the PRL signature showed promising predictive ability. More immune cells were clustered in the high-risk group, whereas the immune cell function of the low-risk group was significantly suppressed. The high-risk group was less sensitive to immunotherapy, whereas the low-risk group had positive responses to most drugs.

CONCLUSIONS

Collectively, we established and verified a PRL signature that could competently guide the prognostic survival and immunotherapy of ccRCC. In addition, molecular subtypes were determined for ccRCC based on PRL expression, which may help elucidate the underlying molecular mechanism of ccRCC and develop targeted treatments.

Deciphering the Molecular Nexus: An In-Depth Review of Mitochondrial Pathways and Their Role in Cell Death Crosstalk

Cellular demise is a pivotal event in both developmental processes and disease states, with mitochondrial regulation playing an essential role. Traditionally, cell death was categorized into distinct types, considered to be linear and mutually exclusive pathways. However, the current understanding has evolved to recognize the complex and interconnected mechanisms of cell death, especially within apoptosis, pyroptosis, and necroptosis. Apoptosis, pyroptosis, and necroptosis are governed by intricate molecular pathways, with mitochondria acting as central decision-makers in steering cells towards either apoptosis or pyroptosis through various mediators. The choice between apoptosis and necroptosis is often determined by mitochondrial signaling and is orchestrated by specific proteins. The molecular dialogue and the regulatory influence of mitochondria within these cell death pathways are critical research areas. Comprehending the shared elements and the interplay between these death modalities is crucial for unraveling the complexities of cellular demise.

A novel signature based on twelve programmed cell death patterns to predict the prognosis of lung adenocarcinoma

Programmed cell death (PCD) plays a pivotal role in tumor initiation and progression. However, the prognostic value and clinical characteristics of PCD-related genes (PRGs) remain unclear. We collected and analyzed genes associated with twelve PCD patterns, including apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis to construct a gene signature. Our analysis identified 215 differentially expressed PRGs out of 1254 in lung adenocarcinoma (LUAD) and normal lung tissues. Subsequently, we performed univariate Cox regression analysis and identified 58 prognostic PRGs. Based on LASSO Cox regression analysis, we constructed a risk score using the expression levels of seven genes: DAPK2, DDIT4, E2F2, GAPDH, MET, PIM2, and FOXF1. Patients with lower risk scores showed earlier stages of cancer, longer survival times, and better immune infiltrations and functions. Notably, we found that knockdown of DDIT4 significantly increased apoptosis and impaired the proliferation of human LUAD cell lines. Our study proposes a PRG-based prognostic signature that sheds light on the potential role of PCD-related genes in LUAD and provides valuable insights into future therapeutic strategies.

Assessing the role of programmed cell death signatures and related gene TOP2A in progression and prognostic prediction of clear cell renal cell carcinoma

Kidney Clear Cell Carcinoma (KIRC), the predominant form of kidney cancer, exhibits a diverse therapeutic response to Immune Checkpoint Inhibitors (ICIs), highlighting the need for predictive models of ICI efficacy. Our study has constructed a prognostic model based on 13 types of Programmed Cell Death (PCD), which are intertwined with tumor progression and the immune microenvironment. Validated by analyses of comprehensive datasets, this model identifies seven key PCD genes that delineate two subtypes with distinct immune profiles and sensitivities to anti-PD-1 therapy. The high-PCD group demonstrates a more immune-suppressive environment, while the low-PCD group shows better responses to PD-1 treatment. In particular, TOP2A emerged as crucial, with its inhibition markedly reducing KIRC cell growth and mobility. These findings underscore the relevance of PCDs in predicting KIRC outcomes and immunotherapy response, with implications for enhancing clinical decision-making.

Noncoding RNAs: the crucial role of programmed cell death in osteoporosis

Osteoporosis is the most common skeletal disease characterized by an imbalance between bone resorption and bone remodeling. Osteoporosis can lead to bone loss and bone microstructural deterioration. This increases the risk of bone fragility and fracture, severely reducing patients' mobility and quality of life. However, the specific molecular mechanisms involved in the development of osteoporosis remain unclear. Increasing evidence suggests that multiple noncoding RNAs show differential expression in the osteoporosis state. Meanwhile, noncoding RNAs have been associated with an increased risk of osteoporosis and fracture. Noncoding RNAs are an important class of factors at the level of gene regulation and are mainly involved in cell proliferation, cell differentiation, and cell death. Programmed cell death is a genetically-regulated form of cell death involved in regulating the homeostasis of the internal environment. Noncoding RNA plays an important role in the programmed cell death process. The exploration of the noncoding RNA-programmed cell death axis has become an interesting area of research and has been shown to play a role in many diseases such as osteoporosis. In this review, we summarize the latest findings on the mechanism of noncoding RNA-mediated programmed cell death on bone homeostasis imbalance leading to osteoporosis. And we provide a deeper understanding of the role played by the noncoding RNA-programmed cell death axis at the gene regulatory level of osteoporosis. We hope to provide a unique opportunity to develop novel diagnostic and therapeutic approaches for osteoporosis.

Identification of PANoptosis-related biomarkers and analysis of prognostic values in head and neck squamous cell carcinoma

PANoptosis plays a crucial role in cancer initiation and progression. However, the roles of PANoptosis-related genes (PARGs) in the prognosis and immune landscape of head and neck squamous cell carcinoma (HNSCC) remain unclear. Integrated bioinformatics analyses based on the data of HNSCC patients in the TCGA database were conducted. We extracted 48 PARGs expression profile and then conducted differentially expressed analysis, following building a Cox model to predict the survival of HNSCC patients. Subsequently, the relationships between the risk score, immune landscape, chemo-, and immune-therapy responses were analyzed, respectively. Moreover, we investigated the prognostic value, and further predicted the pathways influenced by PARGs. Finally, we identified the biological function of crucial PARGs. A total of 18 differentially expressed PARGs were identified in HNSCC, and a Cox model including CASP8, FADD, NLRP1, TNF, and ZBP1 was constructed, which showed that the risk score was associated with the prognosis as well as immune infiltration of HNSCC patients, and the risk score could be regarded as an independent biomarker. Additionally, patients with high-risk score might be an indicator of lymph node metastasis and advanced clinical stage. High-risk scores also contributed to the chemotherapy resistance and immune escape of HNSCC patients. In addition, FADD and ZBP1 played a crucial role in various cancer-related pathways, such as the MAPK, WNT, and MTOR signaling pathways. On the other hand, we suggested that FADD facilitated the progression and 5-fluorouracil (5-FU) resistance of HNSCC cells. A signature based on PANoptosis showed great predictive power for lymph node metastasis and advanced stage, suggesting that the risk score might be an independent prognostic biomarker for HNSCC. Meanwhile, FADD, identified as a prognostic biomarker, may represent an effective therapeutic target for HNSCC.

Nanomedicine-induced cell pyroptosis to enhance antitumor immunotherapy

Immunotherapy is a therapeutic modality designed to elicit or augment an immune response against malignancies. Despite the immune system's ability to detect and eradicate neoplastic cells, certain neoplastic cells can elude immune surveillance and elimination through diverse mechanisms. Therefore, antitumor immunotherapy has emerged as a propitious strategy. Pyroptosis, a type of programmed cell death (PCD) regulated by Gasdermin (GSDM), is associated with cytomembrane rupture due to continuous cell expansion, which results in the release of cellular contents that can trigger robust inflammatory and immune responses. The field of nanomedicine has made promising progress, enabling the application of nanotechnology to enhance the effectiveness and specificity of cancer therapy by potentiating, enabling, or augmenting pyroptosis. In this review, we comprehensively examine the paradigms underlying antitumor immunity, particularly paradigms related to nanotherapeutics combined with pyroptosis; these treatments include chemotherapy (CT), hyperthermia therapy, photodynamic therapy (PDT), chemodynamic therapy (CDT), ion-interference therapy (IIT), biomimetic therapy, and combination therapy. Furthermore, we thoroughly discuss the coordinated mechanisms that regulate these paradigms. This review is expected to enhance the understanding of the interplay between pyroptosis and antitumor immunotherapy, broaden the utilization of diverse nanomaterials in pyroptosis-based antitumor immunotherapy, and facilitate advancements in clinical tumor therapy.

A novel TCGA-validated programmed cell-death-related signature of ovarian cancer

BACKGROUND

Ovarian cancer (OC) is a gynecological malignancy tumor with high recurrence and mortality rates. Programmed cell death (PCD) is an essential regulator in cancer metabolism, whose functions are still unknown in OC. Therefore, it is vital to determine the prognostic value and therapy response of PCD-related genes in OC.

METHODS

By mining The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) and Genecards databases, we constructed a prognostic PCD-related genes model and performed Kaplan-Meier (K-M) analysis and Receiver Operating Characteristic (ROC) curve for its predictive ability. A nomogram was created via Cox regression. We validated our model in train and test sets. Quantitative real-time PCR (qRT-PCR) was applied to identify the expression of our model genes. Finally, we analyzed functional analysis, immune infiltration, genomic mutation, tumor mutational burden (TMB) and drug sensitivity of patients in low- and high-risk group based on median scores.

RESULTS

A ten-PCD-related gene signature including protein phosphatase 1 regulatory subunit 15 A (PPP1R15A), 8-oxoguanine-DNA glycosylase (OGG1), HECT and RLD domain containing E3 ubiquitin protein ligase family member 1 (HERC1), Caspase-2.(CASP2), Caspase activity and apoptosis inhibitor 1(CAAP1), RB transcriptional corepressor 1(RB1), Z-DNA binding protein 1 (ZBP1), CD3-epsilon (CD3E), Clathrin heavy chain like 1(CLTCL1), and CCAAT/enhancer-binding protein beta (CEBPB) was constructed. Risk score performed well with good area under curve (AUC) (AUC3 - year =0.728, AUC5 - year = 0.730). The nomogram based on risk score has good performance in predicting the prognosis of OC patients (AUC1 - year =0.781, AUC3 - year =0.759, AUC5 - year = 0.670). Kyoto encyclopedia of genes and genomes (KEGG) analysis showed that the erythroblastic leukemia viral oncogene homolog (ERBB) signaling pathway and focal adhesion were enriched in the high-risk group. Meanwhile, patients with high-risk scores had worse OS. In addition, patients with low-risk scores had higher immune-infiltrating cells and enhanced expression of checkpoints, programmed cell death 1 ligand 1 (PD-L1), indoleamine 2,3-dioxygenase 1 (IDO-1) and lymphocyte activation gene-3 (LAG3), and were more sensitive to A.443,654, GDC.0449, paclitaxel, gefitinib and cisplatin. Finally, qRT-PCR confirmed RB1, CAAP1, ZBP1, CEBPB and CLTCL1 over-expressed, while PPP1R15A, OGG1, CASP2, CD3E and HERC1 under-expressed in OC cell lines.

CONCLUSION

Our model could precisely predict the prognosis, immune status and drug sensitivity of OC patients.

Crosstalk between cancer-associated fibroblasts and regulated cell death in tumors: insights into apoptosis, autophagy, ferroptosis, and pyroptosis

Cancer-associated fibroblasts (CAFs), the main stromal component of the tumor microenvironment (TME), play multifaceted roles in cancer progression through paracrine signaling, exosome transfer, and cell interactions. Attractively, recent evidence indicates that CAFs can modulate various forms of regulated cell death (RCD) in adjacent tumor cells, thus involving cancer proliferation, therapy resistance, and immune exclusion. Here, we present a brief introduction to CAFs and basic knowledge of RCD, including apoptosis, autophagy, ferroptosis, and pyroptosis. In addition, we further summarize the different types of RCD in tumors that are mediated by CAFs, as well as the effects of these modes of RCD on CAFs. This review will deepen our understanding of the interactions between CAFs and RCD and might offer novel therapeutic avenues for future cancer treatments.

Exploring a specialized programmed-cell death patterns to predict the prognosis and sensitivity of immunotherapy in cutaneous melanoma via machine learning

The mortality and therapeutic failure in cutaneous melanoma (CM) are mainly caused by wide metastasis and chemotherapy resistance. Meanwhile, immunotherapy is considered a crucial therapy strategy for CM patients. However, the efficiency of currently available methods and biomarkers in predicting the response of immunotherapy and prognosis of CM is limited. Programmed cell death (PCD) plays a significant role in the occurrence, development, and therapy of various malignant tumors. In this research, we integrated fourteen types of PCD, multi-omics data from TCGA-SKCM and other cohorts in GEO, and clinical CM patients to develop our analysis. Based on significant PCD patterns, two PCD-related CM clusters with different prognosis, tumor microenvironment (TME), and response to immunotherapy were identified. Subsequently, seven PCD-related features, especially CD28, CYP1B1, JAK3, LAMP3, SFN, STAT4, and TRAF1, were utilized to establish the prognostic signature, namely cell death index (CDI). CDI accurately predicted the response to immunotherapy in both CM and other cancers. A nomogram with potential superior predictive ability was constructed, and potential drugs targeting CM patients with specific CDI have also been identified. Given all the above, a novel CDI gene signature was indicated to predict the prognosis and exploit precision therapeutic strategies of CM patients, providing unique opportunities for clinical intelligence and new management methods for the therapy of CM.

Targeting novel regulated cell death: Ferroptosis, pyroptosis and necroptosis in anti-PD-1/PD-L1 cancer immunotherapy

Chemotherapy, radiotherapy, and immunotherapy represent key tumour treatment strategies. Notably, immune checkpoint inhibitors (ICIs), particularly anti-programmed cell death 1 (PD1) and anti-programmed cell death ligand 1 (PD-L1), have shown clinical efficacy in clinical tumour immunotherapy. However, the limited effectiveness of ICIs is evident due to many cancers exhibiting poor responses to this treatment. An emerging avenue involves triggering non-apoptotic regulated cell death (RCD), a significant mechanism driving cancer cell death in diverse cancer treatments. Recent research demonstrates that combining RCD inducers with ICIs significantly enhances their antitumor efficacy across various cancer types. The use of anti-PD-1/PD-L1 immunotherapy activates CD8+ T cells, prompting the initiation of novel RCD forms, such as ferroptosis, pyroptosis, and necroptosis. However, the functions and mechanisms of non-apoptotic RCD in anti-PD1/PD-L1 therapy remain insufficiently explored. This review summarises the emerging roles of ferroptosis, pyroptosis, and necroptosis in anti-PD1/PD-L1 immunotherapy. It emphasises the synergy between nanomaterials and PD-1/PD-L1 inhibitors to induce non-apoptotic RCD in different cancer types. Furthermore, targeting cell death signalling pathways in combination with anti-PD1/PD-L1 therapies holds promise as a prospective immunotherapy strategy for tumour treatment.

Angiogenesis and Apoptosis: Data Comparison of Similar Microenvironments in the Corpus Luteum and Tumors

The corpus luteum is a temporary endocrine gland formed in the ovary after ovulation, and it plays a critical role in animal reproductive processes. Tumors rely on the development of an adequate blood supply to ensure the delivery of nutrients and oxygen and the removal of waste products. While angiogenesis occurs in various physiological and pathological contexts, the corpus luteum and tumors share similarities in terms of the signaling pathways that promote angiogenesis. In the corpus luteum and tumors, apoptosis plays a crucial role in controlling cell numbers and ensuring proper tissue development and function. Interestingly, there are similarities between the apoptotic-regulated signaling pathways involved in apoptosis in the corpus luteum and tumors. However, the regulation of apoptosis in both can differ due to their distinct physiological and pathological characteristics. Thus, we reviewed the biological events of the corpus luteum and tumors in similar microenvironments of angiogenesis and apoptosis.

Bioinformatics analyses and experimental validation of the role of phagocytosis in low-grade glioma

BACKGROUND

Phagocytosis is of vital importance in tumor immune response. The alteration of phagocytosis in low-grade glioma (LGG) has not been investigated.

METHODS

The mRNA, copy number variation, single nucleotide variation, and methylation levels of phagocytosis-related genes were summarized in pan-cancer. Non-negative matrix factorization clustering was utilized to identify two LGG subtypes. LASSO regression analysis was performed to construct a phagocytosis-related prognostic signature (PRPS). Immune characteristics, immunotherapy response, and targeted-drug sensitivity were further explored. The phagocytosis activity in glioma was evaluated using scRNA-seq data. Multiplex immunohistochemical (m-IHC) technology was performed to identify the tumor-infiltrating immune cells in LGG.

RESULTS

The phagocytosis-related genes altered obviously in pan-cancer compared with corresponding normal tissues. Two LGG subtypes were obtained and the subtype with poor prognosis was combined with lower tumor purity, more active immune-related pathways, increasing infiltration of CD4+ T cells, CD8+ T cells, and natural killer (NK) cells, decreasing infiltration of macrophages, mast cells, and neutrophils, distinct pathway activity and cell death status, greater response to immunotherapy, and higher sensitivity to cyclophosphamide, erlotinib, gefitinib, lapatinib, and sorafenib. In addition, a PRPS involving 10 genes (i.e., SLC11A1, CAMK1D, PLA2G5, STAP1, ALOX15, PLCG2, SFTPD, AZU1, RAB27A, and LAMTOR2) was constructed to estimate the risk level of each LGG sample and high risk LGG patients had poor prognosis, upregulated infiltration of neutrophil, macrophage, Treg, and myeloid dendritic cell, down regulated infiltration of monocyte and NK cell, and increasing expression of large number of immune checkpoint genes. The phagocytosis activity is notably active in monocyte/macrophage. The m-IHC results confirmed increased infiltration of macrophages and neutrophils in LGG samples with high SLC11A1 expression.

CONCLUSION

The molecular characteristics of phagocytosis were revealed and the PRPS laid the foundation for personalized therapy in LGG.

Recent advances in the potential effects of natural products from traditional Chinese medicine against respiratory diseases targeting ferroptosis

Respiratory diseases, marked by structural changes in the airways and lung tissues, can lead to reduced respiratory function and, in severe cases, respiratory failure. The side effects of current treatments, such as hormone therapy, drugs, and radiotherapy, highlight the need for new therapeutic strategies. Traditional Chinese Medicine (TCM) offers a promising alternative, leveraging its ability to target multiple pathways and mechanisms. Active compounds from Chinese herbs and other natural sources exhibit anti-inflammatory, antioxidant, antitumor, and immunomodulatory effects, making them valuable in preventing and treating respiratory conditions. Ferroptosis, a unique form of programmed cell death (PCD) distinct from apoptosis, necrosis, and others, has emerged as a key area of interest. However, comprehensive reviews on how natural products influence ferroptosis in respiratory diseases are lacking. This review will explore the therapeutic potential and mechanisms of natural products from TCM in modulating ferroptosis for respiratory diseases like acute lung injury (ALI), asthma, pulmonary fibrosis (PF), chronic obstructive pulmonary disease (COPD), lung ischemia-reperfusion injury (LIRI), pulmonary hypertension (PH), and lung cancer, aiming to provide new insights for research and clinical application in TCM for respiratory health.

A programmed cell death-related gene signature to predict prognosis and therapeutic responses in liver hepatocellular carcinoma

BACKGROUND

Programmed cell death (PCD) functions critically in cancers and PCD-related genes are associated with tumor microenvironment (TME), prognosis and therapeutic responses of cancer patients. This study stratified hepatocellular carcinoma (HCC) patients and develop a prognostic model for predicting prognosis and therapeutic responses.

METHODS

Consensus clustering analysis was performed to subtype HCC patients in The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) among the subtypes were filtered and subjected to the least absolute shrinkage and selection operator (LASSO) regression analysis and univariate Cox regression analysis to filter prognostic genes. A PCD-related prognostic gene signature in TCGA was constructed and validated in ICGC-LIRI-JP and GSE14520 datasets. TME was analyzed using CIBERSORT, MCP-counter, TIMER and EPIC algorithms. Drug sensitivity was predicted by oncoPredict package. Spearman analysis was used to detect correlation.

RESULTS

Four molecular subtypes were categorized based on PCD-related genes. Subtype C1 showed the poorest prognosis, the most infiltration of Fibroblasts, dentritic cell (DC) and cancer-associated fibroblasts (CAFs), and the highest TIDE score. C4 had a better prognosis survival outcome, and lowest immune cell infiltration. The survival outcomes of C2 and C3 were intermediate. Next, a total of 69 co-DEGs were screened among the four subtypes and subsequently we identified five prognostic genes (MCM2, SPP1, S100A9, MSC and EPO) for developing the prognostic model. High-risk patients not only had unfavorable prognosis, higher clinical stage and grade, and more inflammatory pathway enrichment, but also possessed higher possibility of immune escape and were more sensitive to Cisplatin and 5. Fluorouracil. The robustness of the prognostic model was validated in external datasets.

CONCLUSION

This study provides new insights into clinical subtyping and the PCD-related prognostic signature may serve as a useful tool to predict prognosis and guide treatments for patients with HCC.

Machine learning-based cell death signature for predicting the prognosis and immunotherapy benefit in stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is a one of most common malignancies with high mortality-to-incidence ratio. Programmed cell death (PCD) exerts vital functions in the progression of cancer. The role of PCD-related genes (PRGs) in STAD are not fully clarified. Using TCGA, GSE15459, GSE26253, GSE62254 and GSE84437 datasets, PCD-related signature (PRS) was constructed with an integrative procedure including 10 machine learning methods. The role of PRS in predicting the immunotherapy benefits was evaluated by several predicting score and 3 immunotherapy datasets (GSE91061, GSE78220, and IMvigor210). The model developed by Lasso + CoxBoost algorithm having a highest average C-index of 0.66 was considered as the optimal PRS. As an independent risk factor for STAD patients, PRS had a good performance in predicting the overall survival rate of patients, with an AUC of 1-, 3-, and 5-year ROC curve being 0.771, 0.751 and 0.827 in TCGA cohort. High PRS score demonstrated a lower gene set score of some immune-activated cells and immune-activated activities. Patient with high PRS score had a higher TIDE score, higher immune escape score, lower PD1&CTLA4 immunophenoscore, lower TMB score, lower response rate and poor prognosis, indicating a less immunotherapy response. The IC50 value of some drugs correlated with chemotherapy and targeted therapy was higher in high PRS score group. Our investigation developed an optimal PRS in STAD and it acted as an indicator for predicting the prognosis, stratifying risk and guiding treatment for STAD patients.

Comprehensive Analyses of PANoptosome with Potential Implications in Cancer Prognosis and Immunotherapy

Cell death resistance significantly contributes to poor therapeutic outcomes in various cancers. PANoptosis, a unique inflammatory programmed cell death (PCD) pathway activated by specific triggers and regulated by the PANoptosome, possesses key features of apoptosis, pyroptosis, and necroptosis, but these cannot be accounted for by any of the three PCD pathways alone. While existing studies on PANoptosis have predominantly centered on infectious and inflammatory diseases, its role in cancer malignancy has been understudied. In this comprehensive investigation, we conducted pan-cancer analyses of PANoptosome component genes across 33 cancer types. We characterized the genetic, epigenetic, and transcriptomic landscapes, and introduced a PANoptosome-related potential index (PANo-RPI) for evaluating the intrinsic PANoptosome assembly potential in cancers. Our findings unveil PANo-RPI as a prognostic factor in numerous cancers, including KIRC, LGG, and PAAD. Crucially, we established a significant correlation between PANo-RPI and tumor immune responses, as well as the infiltration of diverse lymphoid and myeloid cell subsets across nearly all cancer types. Moreover, a high PANo-RPI was consistently associated with improved immunotherapy response and efficacy, as evidenced by re-analysis of multiple immunotherapy cohorts. In conclusion, our study suggests that targeting PANoptosome components and modulating PANoptosis may hold tremendous therapeutic potential in the context of cancer.

Exploration of the prognostic prediction value of the PANoptosis-based risk score and its correlation with tumor immunity in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common cancer with high mortality worldwide. PANoptosis is a novel inflammatory programmed cell death modality with the characteristics of pyroptosis, apoptosis and necroptosis. It is necessary to explore PANoptosis-related genes in LUAD patients and offer evidence for prognosis prediction and therapeutic strategies. Single-cell RNA sequencing data and RNA expression profiles of LUAD patients from The Cancer Genome Atlas and Gene Expression Omnibus databases are used to screen PANoptosis-related differential genes for the construction of a risk model. Fifteen PANoptosis-related markers with prognostic value were identified by Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression analysis. Kaplan-Meier analysis and receiver operating characteristic curve analysis further demonstrated the significant predictive capability. Immune infiltration, Single Nucleotide Variants (SNV) mutations, and clinical drug susceptibility were analyzed. In conclusion, a risk model of 15 PANoptosis-related genes has significant value in prognostic prediction for LUAD and has potential to direct clinical therapeutic strategies during the treatment.

Exploring diverse programmed cell-death patterns to develop a novel gene signature for predicting the prognosis of lung adenocarcinoma patients

Background

Programmed cell death (PCD) plays a critical role in tumor progression and malignancy, and exploring its relationship with lung adenocarcinoma (LUAD)'s survival outcomes is important for personalized diagnosis and treatment. This study aimed to identify survival-related genes and construct an effective prognostic indicator for LUAD based on 12 forms of PCD.

Methods

A total of 1,933 candidate genes related to PCD were collected from published studies and public data center. A prognostic gene signature, called the cell death index (CDI), was established based on RNA-Seq and immunohistochemistry (IHC). IHC staining on tissue microarray was applied for the validation of protein level. Moreover, GSE42127, GSE72094 were used as validation datasets.

Results

The CDI based on expression level of nine genes (CCNB2, HMGA1, CACNA2D2, BUB1B, BTG2, KIF14, PTGDS, SERPINB5, BRCA1) was highly predictive for overall survival (OS) of LUAD in our cohort [36-month area under the curve (AUC): 0.750, 60-month AUC: 0.809]. The CDI was further validated in independent cohorts (GSE72094, 36-month AUC: 0.717, 60-month AUC: 0.737; GSE42127, 12-month AUC: 0.829, 60-month AUC: 0.663). And the CDI was found to be an independent prognostic factor after adjusting for other clinical characteristics. Furthermore, the high-CDI group was associated with upregulated tumor immune infiltration compared to the low-CDI group.

Conclusions

This study identified a 9-gene signature (CDI) based on PCD-related genes that accurately predicted the prognosis of LUAD patients. The CDI could serve as a valuable prognostic indicator and guide personalized therapeutic strategies for LUAD.

Ferroptosis and EMT resistance in cancer: a comprehensive review of the interplay

Ferroptosis differs from traditional cell death mechanisms like apoptosis, necrosis, and autophagy, primarily due to its reliance on iron metabolism and the loss of glutathione peroxidase activity, leading to lipid peroxidation and cell death. The dysregulation of iron metabolism is a hallmark of various cancers, contributing to tumor progression, metastasis, and notably, drug resistance. The acquisition of mesenchymal characteristics by epithelial cells is known as Epithelial-Mesenchymal Transition (EMT), a biological process intricately linked to cancer development, promoting traits such as invasiveness, metastasis, and resistance to therapeutic interventions. EMT plays a pivotal role in cancer progression and contributes significantly to the complex dynamics of carcinogenesis. Research findings indicate that mesenchymal cancer cells exhibit greater susceptibility to ferroptosis compared to their epithelial counterparts. The induction of ferroptosis becomes more effective in eliminating drug-resistant cancer cells during the process of EMT. The interplay between ferroptosis and EMT, a process where epithelial cells transform into mobile mesenchymal cells, is crucial in understanding cancer progression. EMT is associated with increased cancer metastasis and drug resistance. The review delves into how ferroptosis and EMT influence each other, highlighting the role of key proteins like GPX4, which protects against lipid peroxidation, and its inhibition can induce ferroptosis. Conversely, increased GPX4 expression is linked to heightened resistance to ferroptosis in cancer cells. Moreover, the review discusses the implications of EMT-induced transcription factors such as Snail, Zeb1, and Twist in modulating the sensitivity of tumor cells to ferroptosis, thereby affecting drug resistance and cancer treatment outcomes. Targeting the ferroptosis pathway offers a promising therapeutic strategy, particularly for tumors resistant to conventional treatments. The induction of ferroptosis in these cells could potentially overcome drug resistance. However, translating these findings into clinical practice presents challenges, including understanding the precise mechanisms of ferroptosis induction, identifying predictive biomarkers, and optimizing combination therapies. The review underscores the need for further research to unravel the complex interactions between ferroptosis, EMT, and drug resistance in cancer. This could lead to the development of more effective, targeted cancer treatments, particularly for drug-resistant tumors, offering new hope in cancer therapeutics.

Melanoma biology and treatment: a review of novel regulated cell death-based approaches

The incidence of melanoma, the most lethal form of skin cancer, has increased due to ultraviolet exposure. The treatment of advanced melanoma, particularly metastatic cases, remains challenging with poor outcomes. Targeted therapies involving BRAF/MEK inhibitors and immunotherapy based on anti-PD1/anti-CTLA4 antibodies have achieved long-term survival rates of approximately 50% for patients with advanced melanoma. However, therapy resistance and inadequate treatment response continue to hinder further breakthroughs in treatments that increase survival rates. This review provides an introduction to the molecular-level pathogenesis of melanoma and offers an overview of current treatment options and their limitations. Cells can die by either accidental or regulated cell death (RCD). RCD is an orderly cell death controlled by a variety of macromolecules to maintain the stability of the internal environment. Since the uncontrolled proliferation of tumor cells requires evasion of RCD programs, inducing the RCD of melanoma cells may be a treatment strategy. This review summarizes studies on various types of nonapoptotic RCDs, such as autophagy-dependent cell death, necroptosis, ferroptosis, pyroptosis, and the recently discovered cuproptosis, in the context of melanoma. The relationships between these RCDs and melanoma are examined, and the interplay between these RCDs and immunotherapy or targeted therapy in patients with melanoma is discussed. Given the findings demonstrating melanoma cell death in response to different stimuli associated with these RCDs, the induction of RCD shows promise as an integral component of treatment strategies for melanoma.

A novel PANoptosis-related long non-coding RNA index to predict prognosis, immune microenvironment and personalised treatment in hepatocellular carcinoma

BACKGROUND

PANoptosis is involved in the interaction of apoptosis, necroptosis and pyroptosis, playing a role in programmed cell death. Moreover, long non-coding RNAs (lncRNAs) regulate the PCD. This work aims to explore the role of PANoptosis-associated lncRNAs in hepatocellular carcinoma (HCC).

METHODS

Co-expression analysis identified PANoptosis-associated lncRNAs in HCC. Cox and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms were utilised to filter lncRNAs and establish a PANoptosis-related lncRNA index (PANRI). Additionally, Cox, Kaplan-Meier and receiver operating characteristic (ROC) curves were utilised to systematically evaluate the PANRI. Furthermore, Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE), single sample gene set enrichment analysis (ssGSEA) and immune checkpoints were performed to analyse the potential of the PANRI in differentiating different tumour immune microenvironment (TIME) populations. The consensus clustering algorithm was used to distinguish individuals with HCC having different TIME subtypes. Finally, HCC cell lines HepG2 were utilised for further validation in in vitro experiments.

RESULTS

The PANRI differentiates patients according to risk. Notably, ESTIMATE and ssGSEA algorithms revealed a high immune infiltration status in high-risk patients. Additionally, consensus clustering divided the patients into three clusters to identify different subtypes of TIME. Moreover, in vitro results showed that siRNA-mediated silencing of AL049840.4 inhibited the viability and migration of HepG2 cells and promoted apoptosis.

CONCLUSIONS

This is the first PANoptosis-related, lncRNA-based risk index in HCC to assess patient prognosis, TIME and response to immunotherapy. This study offers novel perspectives on the role of PANoptosis-associated lncRNAs in HCC.

Programmed cell death in tumor immunity: mechanistic insights and clinical implications

Programmed cell death (PCD) is an evolutionarily conserved mechanism of cell suicide that is controlled by various signaling pathways. PCD plays an important role in a multitude of biological processes, such as cell turnover, development, tissue homeostasis and immunity. Some forms of PCD, including apoptosis, autophagy-dependent cell death, pyroptosis, ferroptosis and necroptosis, contribute to carcinogenesis and cancer development, and thus have attracted increasing attention in the field of oncology. Recently, increasing research-based evidence has demonstrated that PCD acts as a critical modulator of tumor immunity. PCD can affect the function of innate and adaptive immune cells, which leads to distinct immunological consequences, such as the priming of tumor-specific T cells, immunosuppression and immune evasion. Targeting PCD alone or in combination with conventional immunotherapy may provide new options to enhance the clinical efficacy of anticancer therapeutics. In this review, we introduce the characteristics and mechanisms of ubiquitous PCD pathways (e.g., apoptosis, autophagy-dependent cell death, pyroptosis and ferroptosis) and explore the complex interaction between these cell death mechanisms and tumor immunity based on currently available evidence. We also discuss the therapeutic potential of PCD-based approaches by outlining clinical trials targeting PCD in cancer treatment. Elucidating the immune-related effects of PCD on cancer pathogenesis will likely contribute to an improved understanding of oncoimmunology and allow PCD to be exploited for cancer treatment.

Advances on adaptive immune responses affected by infectious bursal disease virus in chicken

Infectious bursal disease (IBD) is an acute, highly infectious, and immunosuppressive disease caused by the infectious bursal disease virus (IBDV), which interferes with the immune system, causes hypoimmunity and seriously threatens the healthy development of the poultry industry. Adaptive immune response, an important defense line of host resistance to pathogen infection, is the host-specific immune response mainly mediated by T and B lymphocytes. As an important immunosuppressive pathogen in poultry, IBDV infection is closely related to the injury of the adaptive immune system. In this review, we focus on recent advances in adaptive immune response influenced by IBDV infection, especially the damage on immune organs, as well as the effect on humoral immune response and cellular immune response, hoping to provide a theoretical basis for further exploration of the molecular mechanism of immunosuppression induced by IBDV infection and the establishment of novel prevention and control measures for IBD.

Novel cuproptosis-related prognostic gene profiles in preeclampsia

BACKGROUND

Preeclampsia (PE) is a pregnancy-specific disorder with complex pathogenesis. Cuproptosis is a novel identified form of programmed cell death, however, the link between cuproptosis and clinical outcomes in PE is still not fully understood. In this study, we searched for cuproptosis-related genes (CRGs) in the placental tissues of normal and PE patients to clarify the importance of cuproptosis in the development of PE and provide potential predictive indicators for the occurrence of PE.

METHODS

Using RNA sequencing data in the GEO database, we conducted functional enrichment analysis of Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA), supported by linear regression model and operating characteristic curve (ROC) curve analysis, and summarized the role of CRGs in preeclampsia.

RESULTS

A total of 2831 differentially expressed genes related to PE were screened through multiple database analyses. After further intersection with 19 reported CRGs, 5 CRGs have been closely associated with the pathogenesis of PE, including NFE2L2, PDHA1, PDHB, DLD and GLS. NFE2L2 was identified as a key central gene. Pearson correlation analysis showed that CRGs could be related to several maternal and fetal outcome factors, including the highest pregnancy blood pressure, placenta weight, umbilical blood flow pulsatility index (PI), and neonatal weight. Linear regression equation revealed that the expression of NFE2L2 is negatively correlated with the highest pregnancy blood pressure and umbilical blood flow PI but positively correlated with placental weight and neonatal weight. QRT-PCR showed that the expression of these CRGs was significantly lower in placental tissues.

CONCLUSIONS

This cuproptosis pattern may be a potential prognostic factor in patients with PE and could provide new insights into disease progression.

Immunomodulation of cuproptosis and ferroptosis in liver cancer

According to statistics, the incidence of liver cancer is increasing yearly, and effective treatment of liver cancer is imminent. For early liver cancer, resection surgery is currently the most effective treatment. However, resection does not treat the disease in advanced patients, so finding a method with a better prognosis is necessary. In recent years, ferroptosis and cuproptosis have been gradually defined, and related studies have proved that they show excellent results in the therapy of liver cancer. Cuproptosis is a new form of cell death, and the use of cuproptosis combined with ferroptosis to inhibit the production of hepatocellular carcinoma cells has good development prospects and is worthy of in-depth discussion by researchers. In this review, we summarize the research progress on cuproptosis combined with ferroptosis in treating liver cancer, analyze the value of cuproptosis and ferroptosis in the immune of liver cancer, and propose potential pathways in oncotherapy with the combination of cuproptosis and ferroptosis, which can provide background knowledge for subsequent related research.

Integrated analysis of single-cell RNA-seq and chipset data unravels PANoptosis-related genes in sepsis

Background

The poor prognosis of sepsis warrants the investigation of biomarkers for predicting the outcome. Several studies have indicated that PANoptosis exerts a critical role in tumor initiation and development. Nevertheless, the role of PANoptosis in sepsis has not been fully elucidated.

Methods

We obtained Sepsis samples and scRNA-seq data from the GEO database. PANoptosis-related genes were subjected to consensus clustering and functional enrichment analysis, followed by identification of differentially expressed genes and calculation of the PANoptosis score. A PANoptosis-based prognostic model was developed. In vitro experiments were performed to verify distinct PANoptosis-related genes. An external scRNA-seq dataset was used to verify cellular localization.

Results

Unsupervised clustering analysis using 16 PANoptosis-related genes identified three subtypes of sepsis. Kaplan-Meier analysis showed significant differences in patient survival among the subtypes, with different immune infiltration levels. Differential analysis of the subtypes identified 48 DEGs. Boruta algorithm PCA analysis identified 16 DEGs as PANoptosis-related signature genes. We developed PANscore based on these signature genes, which can distinguish different PANoptosis and clinical characteristics and may serve as a potential biomarker. Single-cell sequencing analysis identified six cell types, with high PANscore clustering relatively in B cells, and low PANscore in CD16+ and CD14+ monocytes and Megakaryocyte progenitors. ZBP1, XAF1, IFI44L, SOCS1, and PARP14 were relatively higher in cells with high PANscore.

Conclusion

We developed a machine learning based Boruta algorithm for profiling PANoptosis related subgroups with in predicting survival and clinical features in the sepsis.

Bioinformatics-based analysis of programmed cell death pathway and key prognostic genes in gastric cancer: Implications for the development of therapeutics

BACKGROUND

Gastric cancer (GC) represents a major global health burden as a result of its high incidence and poor prognosis. The present study examined the role of the programmed cell death (PCD) pathway and identified key genes influencing the prognosis of patients with GC.

METHODS

Bioinformatics analysis, machine learning techniques and survival analysis were systematically integrated to identify core prognostic genes from the The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) dataset. A prognostic model was then developed to stratify patients into high-risk and low-risk groups, and further validated in the GSE84437 dataset. The model also demonstrated clinical relevance with tumor staging and histopathology. Immune infiltration analysis and the potential benefits of immunotherapy for each risk group were assessed. Finally, subgroup analysis was performed based on the expression of three key prognostic genes.

RESULTS

Three core prognostic genes (CAV1, MMP9 and MAGEA3) were identified. The prognostic model could effectively differentiate patients into high-risk and low-risk groups, leading to significantly distinct survival outcomes. Increased immune cell infiltration was observed in the high-risk group, and better potential for immunotherapy outcomes was observed in the low-risk group. Pathways related to cancer progression, such as epithelial-mesenchymal transition and tumor necrosis factor-α signaling via nuclear factor-kappa B, were enriched in the high-risk group. By contrast, the low-risk group showed a number of pathways associated with maintenance of cell functionality and immune responses. The two groups differed in gene mutation patterns and drug sensitivities. Subgroup analysis based on the expression of the three key genes revealed two distinct clusters with distinct survival outcomes, tumor immune microenvironment characteristics and pathway enrichment.

CONCLUSIONS

The present study offers novel insights into the significance of PCD pathways and identifies key genes associated with the prognosis of patients with GC. This robust prognostic model, along with the delineation of distinct risk groups and molecular subtypes, provides valuable tools for risk stratification, treatment selection and personalized therapeutic interventions for GC.

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

Background

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

Methods

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

Results

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

Conclusion

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

PANoptosis in cancer, the triangle of cell death

BACKGROUND

PANoptosis is a novel form of programmed cell death (PCD) found in 2019 that is regulated by the PANoptosome. PANoptosis combines essential features of pyroptosis, apoptosis, and necroptosis, forming a "death triangle" of cells. While apoptosis, pyroptosis, and necroptosis have been extensively studied for their roles in human inflammatory diseases and many other clinical conditions, historically they were considered as independent processes. However, emerging evidence indicates that these PCDs exhibit cross talk and interactions, resulting in the development of the concept of PANoptosis.

METHODS

In this review, we offer a concise summary of the fundamental mechanisms of apoptosis, pyroptosis, and necroptosis. We subsequently introduce the notion of PANoptosis and detail the assembly mechanism of the PANoptosome complex which is responsible for inducing cell death. We also describe some regulatory networks of PANoptosis.

RESULTS

PANoptosis now has been associated with various human diseases including cancer. Although the exact function of PANoptosis in each tumor is not fully understood, it represents a prospective avenue for cancer therapy, offering promise for advancements in cancer therapy.

CONCLUSIONS

In the future, in-depth study of PANoptosis will continue to help us in understanding the fundamental processes underlying cell death and provide scientific support for cancer research.

Higher expression of programmed cell death 4 (PDCD4) in acute myeloid leukemia is associated with better prognosis after chemotherapy

Acute myeloid leukemia (AML) is a common heterogeneous malignancy. Novel molecular markers aid diagnosis, patient sub-categorization, and optimal clinical decisions. Here, we explored the prognostic implications associated with the expression of the programmed cell death (PDCD) family of molecules in AML patients. Based on the findings from the TCGA and OHSU cohorts, we observed that the mRNA abundance of PDCD4 is significantly higher compared to other molecules within the PDCD family. Furthermore, high expression of PDCD4 was associated with predicted long-term patient survival in diagnosed AML patients. In the chemotherapy group, patients with high PDCD4 expression showed a tendency toward longer overall survival (OS) (P = 0.0266) and event-free survival (EFS) (P = 0.0008). High PDCD4 levels served as a favorable independent predictor for both OS and EFS in AML patients. However, subgroup analyses in the hematopoietic stem cell transplantation (HSCT) group revealed no significant difference in OS or EFS between individuals with high and low PDCD4 expression. Furthermore, in the low PDCD4 expression group, AML patients who underwent HSCT experienced improved survival outcomes (P = 0.0015), helping to mitigate the unfavorable prognosis associated with PDCD4 downregulation. Conversely, in the high PDCD4 expression group, HSCT offered a notable short-term survival advantage, while patients with high PDCD4 expression responded favorably to long-term survival through chemotherapy. Biological function enrichment showed that the expression of PDCD4 was correlated with complement and coagulation cascades, cell receptor signaling pathways, and cholesterol metabolism. The findings from this study will aid in better categorizing heterogeneous AML patients and guiding more appropriate clinical decision-making.

The Prognosis of Cancer Depends on the Interplay of Autophagy, Apoptosis, and Anoikis within the Tumor Microenvironment

Within the tumor microenvironment, the fight between the immune system and cancer influences tumor transformation. Metastasis formation is an important stage in the progression of cancer. This process is aided by cellular detachment and resistance to anoikis, which are achieved by altering intercellular signaling. Autophagy, specifically pro-survival autophagy, aids cancer cells in developing treatment resistance. Numerous studies have shown that autophagy promotes tumor growth and resistance to anoikis. To regulate protective autophagy, cancer-related genes phosphorylate both pro- and anti-apoptotic proteins. Apoptosis, a type of controlled cell death, eliminates damaged or unwanted cells. Anoikis is a type of programmed cell death in which cells lose contact with the extracellular matrix. The dysregulation of these cellular pathways promotes tumor growth and spread. Apoptosis, anoikis, and autophagy interact meticulously and differently depending on the cellular circumstances. For instance, autophagy can protect cancer cells from apoptosis by removing cellular components that are damaged and might otherwise trigger apoptotic pathways. Similarly, anoikis dysregulation can trigger autophagy by causing cellular harm and metabolic stress. In order to prevent or treat metastatic disease, specifically, targeting these cellular mechanisms may present a promising prospect for cancer therapy. This review discourses the state of our understanding of the molecular and cellular mechanisms underlying tumor transformation and the establishment of metastatic tumors. To enhance the prognosis for cancer, we highlight and discuss potential therapeutic approaches that target these processes and genes involved in them.

LncPCD: a manually curated database of experimentally supported associations between lncRNA-mediated programmed cell death and diseases

Programmed cell death (PCD) refers to controlled cell death that is conducted to keep the internal environment stable. Long noncoding RNAs (lncRNAs) participate in the progression of PCD in a variety of diseases. However, no specialized online repository is available to collect and store the associations between lncRNA-mediated PCD and diseases. Here, we developed LncPCD, a comprehensive database that provides information on experimentally supported associations of lncRNA-mediated PCD with diseases. The current version of LncPCD documents 6666 associations between five common types of PCD (apoptosis, autophagy, ferroptosis, necroptosis and pyroptosis) and 1222 lncRNAs in 331 diseases. We also manually curated a wealth of information: (1) 7 important lncRNA regulatory mechanisms, (2) 310 PCD-associated cell types in three species, (3) detailed information on lncRNA subcellular locations and (4) clinical applications for lncRNA-mediated PCD in diseases. Additionally, 10 single-cell sequencing datasets were integrated into LncPCD to characterize the dynamics of lncRNAs in diseases. Overall, LncPCD is an extremely useful resource for understanding the functions and mechanisms of lncRNA-mediated PCD in diseases. Database URL:  http://spare4.hospital.studio:9000/lncPCD/Home.jsp.

Metabolic reprogramming involves in transition of activated/resting CD4+ memory T cells and prognosis of gastric cancer

Background

Little is known on how metabolic reprogramming potentially prompts transition of activated and resting CD4+ memory T cells infiltration in tumor microenvironment of gastric cancer (GC). The study aimed to evaluate their interactions and develop a risk model for predicting prognosis in GC.

Methods

Expression profiles were obtained from TCGA and GEO databases. An immunotherapeutic IMvigor210 cohort was also enrolled. CIBERSORT algorithm was used to evaluate the infiltration of immune cells. The ssGSEA method was performed to assess levels of 114 metabolism pathways. Prognosis and correlation analysis were conducted to identify metabolism pathways and genes correlated with activated CD4+ memory T cells ratio (AR) and prognosis. An AR-related metabolism gene (ARMG) risk model was constructed and validated in different cohorts. Flow cytometry was applied to validate the effect of all-trans retinoic acid (ATRA) on CD4+ memory T cells.

Results

Since significantly inverse prognostic value and negative correlation of resting and activated CD4+ memory T cells, high AR level was associated with favorable overall survival (OS) in GC. Meanwhile, 15 metabolism pathways including retinoic acid metabolism pathway were significantly correlated with AR and prognosis. The ARMG risk model could classify GC patients with different outcomes, treatment responses, genomic and immune landscape. The prognostic value of the model was also confirmed in the additional validation, immunotherapy and pan-cancer cohorts. Functional analyses revealed that the ARMG model was positively correlated with pro-tumorigenic pathways. In vitro experiments showed that ATRA could inhibit levels of activated CD4+ memory T cells and AR.

Conclusion

Our study showed that metabolic reprogramming including retinoic acid metabolism could contribute to transition of activated and resting CD4+ memory T cells, and affect prognosis of GC patients. The ARMG risk model could serve as a new tool for GC patients by accurately predicting prognosis and response to treatment.

Diagnostic role and immune correlates of programmed cell death-related genes in hepatocellular carcinoma

Programmed cell death (PCD) is thought to have multiple roles in tumors. Here, the roles of PCD-related genes were comprehensively analyzed to evaluate their values in hepatocellular carcinoma (HCC) diagnosis and prognosis. Gene expression and single-cell data of HCC patients, and PCD-related genes were collected from public databases. The diagnostic and prognostic roles of differentially expressed PCD-related genes in HCC were explored by univariate and multivariate Cox regression analyses. Single-cell data were further analyzed for the immune cells and expression of feature genes. Finally, we evaluated the expression of genes by quantitative real-time polymerase chain reaction and Western blot, and the proportion of immune cells was detected by flow cytometry in HCC samples. We obtained 52 differentially expressed PCD-related genes in HCC, based on which the consensus clustering analysis cluster 2 was found to have a worse prognosis than cluster 1. Then 10 feature genes were identified using LASSO analysis, and programmed cell death index (PCDI) was calculated to divided HCC patients into high-PCDI and low-PCDI groups. Worse prognosis was observed in high-PCDI group. Cox regression analysis showed that PCDI is an independent prognostic risk factor for HCC patients. Additionally, SERPINE1 and G6PD of feature genes significantly affect patient survival. Macrophages and Tregs were significantly positively correlated with PCDI. G6PD mainly expressed in macrophages, SERPINE1 mainly expressed in fibroblast. The experimental results confirmed the high expression of SERPINE1 and G6PD in HCC compared with the control, and the infiltration level of macrophages and Treg in HCC was also obviously elevated. PCDI may be a new predictor for the diagnosis of patients with HCC. The association of SERPINE1 and G6PD with the immune environment will provide new clues for HCC therapy.

A prognostic risk model for programmed cell death and revealing TRIB3 as a promising apoptosis suppressor in renal cell carcinoma

Programmed cell death (PCD), a common modality of cell death, affects tumor development and acts as a target for tumor therapeutics. Many modalities of PCD regulate genesis, progression and metastasis of cancers, thus affecting the patients' prognosis, but the comprehensive molecular mechanisms of PCD in tumors are lacking, especially in renal cancer. Here, seventeen PRPCDGs were identified from 1257 genes associated with thirteen PCD modalities, which were highly differentially expressed and significantly affected patients' prognosis. Then, LASSO regression analysis of these PRPCDGs screened the 9-gene PRPCDGs risk signature in TCGA-KIRC database. The PRPCDGs risk signature was closely associated with the patients' prognosis and presented stable prediction efficacy for 5- and 7-year overall survival (OS) in three different cohorts of renal cancer. Immune cell infiltration, immune checkpoint expression and pathway enrichment (including GO, KEGG pathway, tumor-associated pathways and metabolism-associated pathways) were significantly different in the high- or low-PRPCDGs-risk group. Finally, we illustrated that TRIB3 might be a protumor factor responsible for the elevated proliferation and invasion capacities of renal cell carcinoma (RCC) cells. In summary, the PRPCDGs risk signature was developed and showed stable prediction efficacy for the prognosis of patients and that (such as TRIB3) could be a potential target for RCC management.

Head and neck squamous cell carcinoma-specific prognostic signature and drug sensitive subtypes based on programmed cell death-related genes

Background

As a complex group of malignancies, head and neck squamous cell carcinoma (HNSC) is one of the leading causes of cancer mortality. This study aims to establish a reliable clinical classification and gene signature for HNSC prognostic prediction and precision treatments.

Methods

A consensus clustering analysis was performed to group HNSC patients in The Cancer Genome Atlas (TCGA) database based on genes linked to programmed cell death (PCD). Differentially expressed genes (DEGs) between subtypes were identified using the "limma" R package. The TCGA prognostic signature and PCD-related prognostic genes were found using a least absolute shrinkage and selection operator (LASSO) regression analysis and univariate Cox regression analysis. The robustness of the LASSO analysis was validated using datasets GSE65858 and GSE41613. A cell counting kit-8 (CCK-8) test, Western blot, and real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) were used to evaluate the expression and viability of prognostic genes.

Results

Four molecular subtypes were identified in PCD-related genes. Subtype C4 had the best prognosis and the highest immune score, while subtype C1 exhibited the most unfavorable outcomes. Three hundred shared DEGs were identified among the four subtypes, and four prognostic genes (CTLA4, CAMK2N1, PLAU and CALML5) were used to construct a TCGA-HNSC prognostic model. High-risk patients manifested poorer prognosis, more inflammatory pathway enrichment, and lower immune cell infiltration. High-risk patients were more prone to immune escape and were more likely to be resistant to Cisplatin and 5-Fluorouracil. Prognosis prediction was validated in external datasets. The expression of CTLA4, CAMK2N1, PLAU and CALML5 was enhanced in CAL-27 and SCC-25 cell lines, and CALML5 inhibited CAL-27 and SCC-25 cell viability.

Conclusion

This study shares novel insights into HNSC classification and provides a reliable PCD-related prognostic signature for prognosis prediction and treatment for patients with HNSC.

Leveraging diverse cell-death patterns to predict the prognosis, immunotherapy and drug sensitivity of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) poses clinical challenges due to its varied prognosis, tumor microenvironment attributes, and responses to immunotherapy. We established a novel Programmed Cell Death-related Signature (PRS) for ccRCC assessment, derived through the Least Absolute Shrinkage and Selection Operator (LASSO) regression method. We validated PRS using the E-MTAB-1980 dataset and created PCD-related clusters via non-negative matrix factorization (NMF). Our investigation included an in-depth analysis of immune infiltration scores using various algorithms. Additionally, we integrated data from the Cancer Immunome Atlas (TCIA) for ccRCC immunotherapy insights and leveraged the Genomics of Drug Sensitivity in Cancer (GDSC) database to assess drug sensitivity models. We complemented our findings with single-cell sequencing data and employed the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and qRT-PCR to compare gene expression profiles between cancerous and paracancerous tissues. PRS serves as a valuable tool for prognostication, immune characterization, tumor mutation burden estimation, immunotherapy response prediction, and drug sensitivity assessment in ccRCC. We identify five genes with significant roles in cancer promotion and three genes with cancer-suppressive properties, further validated by qRT-PCR and CPTAC analyses, showcasing gene expression differences in ccRCC tissues. Our study introduces an innovative PCD model that amalgamates diverse cell death patterns to provide accurate predictions for clinical outcomes, mutational profiles, and immune characteristics in ccRCC. Our findings hold promise for advancing personalized treatment strategies in ccRCC patients.

Identification of necroptosis-related features in diabetic nephropathy and analysis of their immune microenvironent and inflammatory response

Background: Diabetic nephropathy (DN) was considered a severe microvascular complication of diabetes, which was recognized as the second leading cause of end-stage renal diseases. Therefore, identifying several effective biomarkers and models to diagnosis and subtype DN is imminent. Necroptosis, a distinct form of programmed cell death, has been established to play a critical role in various inflammatory diseases. Herein, we described the novel landscape of necroptosis in DN and exploit a powerful necroptosis-mediated model for the diagnosis of DN. Methods: We obtained three datasets (GSE96804, GSE30122, and GSE30528) from the Gene Expression Omnibus (GEO) database and necroptosis-related genes (NRGs) from the GeneCards website. Via differential expression analysis and machine learning, significant NRGs were identified. And different necroptosis-related DN subtypes were divided using consensus cluster analysis. The principal component analysis (PCA) algorithm was utilized to calculate the necroptosis score. Finally, the logistic multivariate analysis were performed to construct the necroptosis-mediated diagnostic model for DN. Results: According to several public transcriptomic datasets in GEO, we obtained eight significant necroptosis-related regulators in the occurrence and progress of DN, including CFLAR, FMR1, GSDMD, IKBKB, MAP3K7, NFKBIA, PTGES3, and SFTPA1 via diversified machine learning methods. Subsequently, employing consensus cluster analysis and PCA algorithm, the DN samples in our training set were stratified into two diverse necroptosis-related subtypes based on our eight regulators' expression levels. These subtypes exhibited varying necroptosis scores. Then, we used various functional enrichment analysis and immune infiltration analysis to explore the biological background, immune landscape and inflammatory status of the above subtypes. Finally, a necroptosis-mediated diagnostic model was exploited based on the two subtypes and validated in several external verification datasets. Moreover, the expression level of our eight regulators were verified in the singe-cell level and glomerulus samples. And we further explored the relationship between the expression of eight regulators and the kidney function of DN. Conclusion: In summary, our necroptosis scoring model and necroptosis-mediated diagnostic model fill in the blank of the relationship between necroptosis and DN in the field of bioinformatics, which may provide novel diagnostic insights and therapy strategies for DN.

A novel model based on disulfidptosis-related genes to predict prognosis and therapy of bladder urothelial carcinoma

PURPOSE

Disulfidptosis is a novel type of cell death induced by disulphide stress that depends on the accumulation of cystine disulphide, causing cytotoxicity and triggering cell death. However, the direct prognostic effect and regulatory mechanism of disulfidptosis-related genes in bladder urothelial carcinoma (BLCA) remain unclear.

METHODS

To explore the role of 10 disulfidptosis-related genes, the multiomic data of 10 genes were comprehensively analysed. Next, based on seven disulfidptosis-related differentially expressed genes, a novel disulfidptosis-related gene score was developed to help predict the prognosis of BLCA. Immunohistochemistry, EDU, Real-time PCR and western blot were used to verify the model.

RESULTS

Significant functional differences were found between the high- and low-risk score groups, and samples with a higher risk score were more malignant. Furthermore, the tumour exclusion and Tumour Immune Dysfunction and Exclusion scores of the high-risk score group were higher than those of the low-risk score group. The risk score was positively correlated with the expression of immune checkpoints. Drug sensitivity analyses revealed that the low-risk score group had a higher sensitivity to cisplatin, doxorubicin, docetaxel and gemcitabine than the high-risk score group. Moreover, the expression of the TM4SF1 was positively correlated with the malignancy degree of BLCA, and the proliferation ability of BLCA cells was reduced after knockdown TM4SF1.

CONCLUSION

The present study results suggest that disulfidptosis-related genes influence the prognosis of BLCA through their involvement in immune cell infiltration. Thus, these findings indicate the role of disulfidptosis in BLCA and its potential regulatory mechanisms.

Predicting Prognosis and Immunotherapy Response in Multiple Cancers Based on the Association of PANoptosis-Related Genes with Tumor Heterogeneity

PANoptosis is a newly recognized inflammatory pathway for programmed cell death (PCD). It participates in regulating the internal environment, homeostasis, and disease process in various complex ways and plays a crucial role in tumor development, but its mechanism of action is still unclear. In this study, we comprehensively analyzed the expression of 14 PANoptosis-related genes (PANRGs) in 28 types of tumors. Most PANRGs are upregulated in tumors, including Z-DNA binding protein 1 (ZBP1), nucleotide-binding oligomerization domain (NOD)-like receptor pyrin domain-containing 3 (NLRP3), caspase (CASP) 1, CASP6, CASP8, PYCARD, FADD, MAP3K7, RNF31, and RBCK1. PANRGs are highly expressed in GBM, LGG, and PAAD, while their levels in ACC are much lower than those in normal tissues. We found that both the CNV and SNV gene sets in BLCA are closely related to survival performance. Subsequently, we conducted clustering and LASSO analysis on each tumor and found that the inhibitory and the stimulating immune checkpoints positively correlate with ZBP1, NLRP3, CASP1, CASP8, and TNFAIP3. The immune infiltration results indicated that KIRC is associated with most infiltrating immune cells. According to the six tumor dryness indicators, PANRGs in LGG show the strongest tumor dryness but have a negative correlation with RNAss. In KIRC, LIHC, and TGCT, most PANRGs play an important role in tumor heterogeneity. Additionally, we analyzed the linear relationship between PANRGs and miRNA and found that MAP3K7 correlates to many miRNAs in most cancers. Finally, we predicted the possible drugs for targeted therapy of the cancers. These data greatly enhance our understanding of the components of cancer and may lead to the discovery of new biomarkers for predicting immunotherapy response and improving the prognosis of cancer patients.

Identification of pyroptosis-related lncRNA subtype and signature predicts the prognosis in bladder cancer

Pyroptosis is a new type of programmed cell death involved in all stages of tumorigenesis. Herein, a comprehensive study was conducted to evaluate the prognostic significance of pyroptosis-related lncRNAs in bladder cancer. Consensus clustering analysis was performed to identify the subclusters of bladder cancer. The prognostic pyroptosis-related lncRNA signature was constructed using LASSO Cox regression analysis. Consensus clustering identified 2 clusters of bladder cancer. Interestingly, significant differences in the ESTIMAE score, immune cell infiltration and immune checkpoint expression were obtained between the 2 clusters. A signature consisting of 11 pyroptosis-related lncRNAs was established and it had a good performance in predicting the overall survival rate of bladder cancer, with an AUC of 0.713. Moreover, pyroptosis-related lncRNA signature acted as a risk factor in bladder cancer. Bladder cancer patients with high-risk score had a higher tumor grade and higher clinical stage. A significant correlation was obtained between the risk score and immune cell infiltration. The expression of most checkpoints was higher in bladder cancer patients with high-risk score. A novel pyroptosis-related lncRNA signature was identified with prognostic value for bladder cancer patients. Pyroptosis-related lncRNAs have a potential role in cancer immunology and may serve as prognostic or therapeutic targets in bladder cancer.

Targeting Ferroptosis in Bone-Related Diseases: Facts and Perspectives

Ferroptosis is a new cell fate decision discovered in recent years. Unlike apoptosis, autophagy or pyroptosis, ferroptosis is characterized by iron-dependent lipid peroxidation and mitochondrial morphological changes. Ferroptosis is involved in a variety of physiological and pathological processes. Since its discovery, ferroptosis has been increasingly studied concerning bone-related diseases. In this review, we focus on the latest research progress and prospects, summarize the regulatory mechanisms of ferroptosis, and discuss the role of ferroptosis in the pathogenesis of bone-related diseases, such as osteoporosis (OP), osteoarthritis (OA), rheumatoid arthritis (RA), and osteosarcoma (OS), as well as its therapeutic potential.