Doramapimod

Mantle cell lymphoma (MCL) is a B-cell non-Hodgkin’s lymphoma. Ferroptosis, an iron-dependent programmed cell death, is closely related to cancer prognosis. In this study, we established a model of ferroptosis related genes for prognostic evaluation of patients with MCL.

Using the single-cell RNA sequencing datasets GSE184031 and mRNA sequencing data GSE32018 from the Gene Expression Omnibus, we identified 139 ferroptosis-related genes in MCL. Next a prognostic model was constructed by Cox regression and Least absolute selection and shrinkage Operator regression analysis. Finally, we used CIBERSORT to analyze the immune microenvironment and the “oncoPredict” package to predict potential drugs.

In our model, the prognosis of MCL patients was assessed by risk scoring using 7 genes ANXA1, IL1B, YBX1, CCND1, MS4A1, MFHAS1, and RILPL2. The patients were divided into high-risk and low-risk groups based on our model, and the high-risk patients had inferior overall survival. Finally, according to our model and computational drug sensitivity analysis, four small molecule compounds, BMS-754807, SB216763, Doramapimod, and Trametinib, were identified as potential therapeutic agents for patients with MCL.

In summary, we provide a prognostic model with ferroptosis-related gene signature for MCL. This study provides a prognostic model with ferroptosis-related gene signature for MCL. The results show that the model helps predict prognosis in MCL.

Acute myeloid leukemia (AML), an uncommonly low 5-year survival and high mortality rate, is a potentially catastrophic diagnosed subtype of leukemia. The development of new prognostic markers is urgently needed to guide its treatment. Necroptosis is a newly defined biological process for regulating cell death, and previous studies have confirmed that the abnormality of the physical function can lead to multiple malignancies. Here, we performed necroptosis-related genes (NRGs) to build a predictive model in the Cancer Genome Atlas (TCGA)-AML patients, thus exploring the correlation between the NRG prognosis signature (NRG score) of this model and immune infiltration, pathway activity, clinical features, and immunotherapy. Besides, we computed the statistical measure Spearman rank correlation between the NRG score and the Log IC50 values of therapeutic agents. Subsequently, we divided the TCGA-AML cohort into 2 groups, one with high scores and the other with low scores depending on the model score. AML patients with high NRG scores exhibited a lower estimated overall survival (OS) rate than those with low NRG scores, which was confirmed in the validation set. The prognostic value of the constructed NRG signature to the AML, independent of other variables, was demonstrated by uni- and multivariate stepwise regression analysis. When comparing the infiltrating states of specialized cells associated with immune system from the 2 groups, B cells naive, Plasma cells, and monocytes represented significant differences among various subgroups of samples. Moreover, the 30 hallmark-related pathways related to necroptosis characteristics were remarkably different between the high/low NRG score groups. And patients showed remarkable NRG score distribution in clinical features of bone marrow lymphocyte, category, and FAB classifications. Besides, we found that the BIRB0796, VX680, Vorinostat, and Axitinib positively related with NRG score, whereas CI. 1040, PD. 0325901, Z.L LNle. CHO, and AZD6244 negatively correlated with the NRG score. These drugs may provide a reference for subsequent treatment.