Hepatocellular carcinoma (HCC) is the second most lethal malignant tumor worldwide, with an increasing incidence and mortality. Due to general resistance to antitumor drugs, only limited therapies are currently available for advanced HCC patients, leading to a poor prognosis with a 5-year survival rate less than 20%. Pyroptosis is a type of inflammation-related programmed cell death and may become a new potential target for cancer therapy. However, the function and prognostic value of pyroptosis-related genes (PRGs) in HCC remain unknown. Here, we identified a total of 58 PRGs reported before and conducted a six-PRG signature via the LASSO regression method in the GEO training cohort, and model efficacy was further validated in an external dataset. The HCC patients can be classified into two subgroups based on the median risk score. High-risk patients have significantly shorter overall survival (OS) than low-risk patients in both training and validation cohorts. Multivariable analysis indicated that the risk score was an independent prognostic factor for OS of HCC patients. Functional enrichment analysis and immune infiltration evaluation suggested that immune status was more activated in the low-risk group. In summary, PRGs can be a prediction factor for prognosis of HCC patients and targeting pyroptosis is a potential therapeutic alternative in HCC.

Acute myeloid leukaemia (AML) is a heterogeneous disease with a difficult to predict prognosis. Ferroptosis, an iron‐induced programmed cell death, is a promising target for cancer therapy. Nevertheless, not much is known about the relationship between ferroptosis‐related genes and AML prognosis. Herein, we retrieved RNA profile and corresponding clinical data of AML patients from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Univariate Cox analysis was employed to identify ferroptosis‐related genes significantly associated with AML prognosis. Next, the least absolute shrinkage and selection operator (LASSO) regression was employed to establish a prognostic ferroptosis‐related gene profile. 12 ferroptosis‐related genes were screened to generate a prognostic model, which stratified patients into a low‐ (LR) or high‐risk (HR) group. Using Kaplan‐Meier analysis, we demonstrated that the LR patients exhibited better prognosis than HR patients. Moreover, receiver operating characteristic (ROC) curve analysis confirmed that the prognostic model showed good predictability. Functional enrichment analysis indicated that the infiltration of regulatory T cells (Treg) differed vastly between the LR and HR groups. Our prognostic model can offer guidance into the accurate prediction of AML prognosis and selection of personalized therapy in clinical practice.

Diffuse large B-cell lymphoma (DLBCL) is a highly prominent class of non-Hodgkin lymphoma (NHL), accounting for 30%-40% of all NHL cases. It has been reported to be highly heterogeneous in epidemiological studies. 1,2 Though anti-CD20 (rituximab) immunotherapy has been the standard treatment regimen with satisfactory survival rates for decades, 3 it was only effective on a small portion of patients. Approximately 40% of patients with DLBCL still had poor prognoses and often suffered from an early relapse after the treatment, 4 emphasizing the need for risk stratification to provide accurate and effective therapy. The International Prognostic Index (IPI), 5 involving conventional clinical and pathological parameters, is widely used for prognosis of patients with DLBCL. However, IPI

PurposePyroptosis is an inflammation-based programmed cell death that holds great potential as a novel cancer therapeutic target in patients with multiple myeloma (MM). However, thus far, the function of pyroptosis-related genes (PRGs) in MM and their prognostic relevance remains undetermined.MethodsThe model was established by the LASSO analysis, based on the Gene Expression Omnibus (GEO) dabatase, and its efficacy was verified using two external datasets. The model’s predictive ability was assessed by the Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) curves. Finally, a nomogram was established for clinical application. We also confirmed the validity of our model using specimens and in vitro experiments.ResultsWe established an 11-PRG signature profile, and verified its efficacy using two validation cohorts (VCs). In both cohorts, patients were separated into two subpopulations, according to their median risk scores (RS). Our analysis revealed that high-risk (HR) patients experienced considerably lower overall survival (OS), compared to the low-risk (LR) patients. Using functional enrichment and immune infiltration analyses, we demonstrated that the immunologic status was strongly related to RS. Furthermore, using a pyroptosis inhibitor Q-VD-OPh, we revealed that MM cell proliferation and progression was drastically suppressed and the doxorubicin (DOX)-induced apoptosis was reversed.ConclusionBased on our analysis, pyroptosis not only serves as a measure of MM treatment efficiency and patient prognosis, but is also a possible target for anti-MM therapy.

Background Ferroptosis is an iron-dependent mode of cell death that could be induced by erastin and exert antitumor effects. However, the clinical and biological roles of ferroptosis-related gene (FRG) signature and the therapeutic value of erastin in multiple myeloma (MM) remained unknown. Methods Clinical and gene expression data of MM subjects were extracted from the Gene Expression Omnibus (GEO) public database. Univariable cox analysis was applied to determine FRGs related to survival and the least absolute shrinkage and selection operator (LASSO) regression analysis was used to develop a prognostic model. Prediction accuracy of the model was estimated by receiver operating characteristic (ROC) curves. Functional pathway enrichments and infiltrating immune status were also analyzed. We conducted in vitro experiments to investigate the combination therapy of erastin and doxorubicin. Results 17 FRGs were strongly associated with patient survival and 11 genes were identified to construct the prognostic model. ROC curves indicated great predictive sensitivity and specificity of the model in all cohorts. Patients were divided into low- and high-risk groups by median risk score in each cohort and the survival of the low-risk group was significantly superior than that of the high-risk group. We also observed a close relevance between functional pathways and immune infiltration with risk scores. Moreover, we combined erastin and doxorubicin in our in vitro experiments and found synergetic antitumor effects of the two agents, and the underlying mechanism is the overgeneration of intracellular Reactive Oxygen Species (ROS). Conclusions We demonstrated the important value of ferroptosis in patient prognosis and as a potential antitumor target for MM.