Proteomic Profiling Identifies Specific Leukemic Stem Cell-Associated Protein Expression Patterns in Pediatric AML Patients

Risk score constructed with neutrophil extracellular traps-related genes predicts prognosis and immune microenvironment in multiple myeloma

Background

Multiple myeloma (MM) exhibits considerable heterogeneity in treatment responses and survival rates, even when standardized care is administered. Ongoing efforts are focused on developing prognostic models to predict these outcomes more accurately. Recently, neutrophil extracellular traps (NETs) have emerged as a potential factor in MM progression, sparking investigation into their role in prognostication.

Methods

In this study, a multi-gene risk scoring model was constructed using the intersection of NTEs and differentially expressed genes (DEGs), applying the least absolute shrinkage and selection operator (LASSO) Cox regression model. A nomogram was established, and the prognostic model's effectiveness was determined via Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). The ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) were employed to evaluate the level of immune infiltration. The sensitivity of chemotherapy drugs was assessed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Ultimately, the presence of the detected genes was confirmed through quantitative real-time polymerase chain reaction (qRT-PCR) analysis in MM cell specimens.

Results

64 NETs-DEGs were yielded, and through univariate Cox regression and LASSO regression analysis, we constructed a risk score composed of six genes: CTSG, HSPE1, LDHA, MPO, PINK1, and VCAM1. MM patients in three independent datasets were classified into high- and low-risk groups according to the risk score. The overall survival (OS) of patients in the high-risk group was significantly reduced compared to the low-risk group. Furthermore, the risk score was an independent predictive factor for OS. In addition, interactions between the risk score, immune score, and immune cell infiltration were investigated. Further analysis indicated that patients in the high-risk group were more sensitive to a variety of chemotherapy and targeted drugs, including bortezomib. Moreover, the six genes provided insights into the progression of plasma cell disorders.

Conclusion

This study offers novel insights into the roles of NETs in prognostic prediction, immune status, and drug sensitivity in MM, serving as a valuable supplement and enhancement to existing grading systems.

A Comprehensive Metabolism-Related Gene Signature Predicts the Survival of Patients with Acute Myeloid Leukemia

(1) Background: Acute myeloid leukemia (AML) is a clonal malignancy with heterogeneity in genomics and clinical outcome. Metabolism reprogramming has been increasingly recognized to play an important role in the leukemogenesis and prognosis in AML. A comprehensive prognostic model based on metabolism signatures has not yet been developed. (2) Methods: We applied Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) normalization to establish a metabolism-related prognostic gene signature based on glycolysis, fatty acid metabolism, and the tricarboxylic acid cycle gene signatures. The Cancer Genome Atlas-Acute Myeloid Leukemia-like (TCGA-LAML) cohort was set as the training dataset for model construction. Three independent AML cohorts (GSE37642, GSE10358, and GSE12417) combined from Gene Expression Omnibus (GEO) datasets and the Beat-AML dataset were retrieved as two validation sets to test the robustness of the model. The transcriptome data and clinic information of the cohorts were enrolled for the analysis. (3) Results: Divided by the median value of the metabolism risk score, the five-year overall survival (OS) of the high-risk and low-risk groups in the training set were 8.2% and 41.3% (p < 0.001), respectively. The five-year OS of the high-risk and low-risk groups in the combined GEO cohort were 25.5% and 37.3% (p = 0.002), respectively. In the Beat-AML cohort, the three-year OS of the high-risk and low-risk groups were 16.2% and 40.2% (p = 0.0035), respectively. The metabolism risk score showed a significantly negative association with the long-term survival of AML. Furthermore, this metabolism risk score was an independent unfavorable factor for OS by univariate analysis and multivariate analysis. (4) Conclusions: Our study constructed a comprehensive metabolism-related signature with twelve metabolism-related genes for the risk stratification and outcome prediction of AML. This novel signature might contribute to a better use of metabolism reprogramming factors as prognostic markers and provide novel insights into potential metabolism targets for AML treatment.

LILRB3 Modulates Acute Myeloid Leukemia Progression and Acts as an Effective Target for CAR T-cell Therapy

Identifying novel cell surface receptors that regulate leukemia cell differentiation and can be targeted to inhibit cellular proliferation is crucial to improve current treatment modalities in acute myeloid leukemia (AML), especially for relapsed or chemotherapy-refractory leukemia. Leukocyte immunoglobulin-like receptor type B (LILRB) is an immunomodulatory receptor originally found to be expressed in myeloid cells. In this study, we found that LILRB receptors can be induced under inflammatory stimuli and chemotherapy treatment conditions. Blockade of LILRB3 inhibited leukemia cell proliferation and leukemia progression. In addition, treatment with LILRB3 blocking antibodies upregulated myeloid lineage differentiation transcription factors, including PU.1, C/EBP family, and IRF, whereas phosphorylation of proliferation regulators, for example, AKT, cyclin D1, and retinoblastoma protein, was decreased. Conversely, transcriptomic analysis showed LILRB3 activation by agonist antibodies may enhance leukemia survival through upregulation of cholesterol metabolism, which has been shown to promote leukemia cell survival. Moreover, LILRB3-targeted CAR T cells exhibited potent antitumor effects both in vitro and in vivo. Taken together, our results suggest that LILRB3 is a potentially potent target for multiple treatment modalities in AML.

SIGNIFICANCE

LILRB3 regulates differentiation and proliferation in acute myeloid leukemia and can be targeted with monoclonal antibodies and CAR T cells to suppress leukemia growth.