Molecular subtyping of acute myeloid leukemia through ferroptosis signatures predicts prognosis and deciphers the immune microenvironment

Drug-tolerant persister cells in acute myeloid leukemia: pressing challenge and promising new strategies for treatment

Acute myeloid leukemia (AML) exhibits a pronounced ability to develop drug resistance and undergo disease relapse. Recent research has noticed that resistance to treatments could substantially be attributed to drug-tolerant persister (DTP) cells, which are capable of surviving under therapeutic pressures. These are transient, reversibly dormant cells with the capability to act as a reservoir for disease relapse. DTP cells utilize diverse adaptive strategies to optimize the ecological niche, undergo metabolic reprogramming, and interact with microenvironment. The persister state of AML is established through transient cellular reprogramming, thus allowing cells to survive the initial phase of drug therapy and develop drug resistance. Our review explores the identification and phenotypic characteristics of AML DTP cells, as well as their clinical relevance. We summarize the mechanisms underlying the persistence of AML DTP cells and the molecular attributes that define the DTP state. We further address the current challenges and future prospects of DTP-targeting approaches. Understanding these features may provide critical insights into novel therapeutic strategies aimed at targeting AML DTP cells, especially in the new era of immunotherapy against AML.

Network-based multi-class classifier to identify optimized gene networks for acute leukemia cell line classification

Unraveling the genetic regulatory networks that underlie diseases is essential for comprehending the intricate mechanisms of these conditions. While various computational strategies were developed, the approaches in the existing studies concerning network-based prediction and classification are based on the pre-estimated gene networks. However, the gene network that is pre-estimated fails to yield biologically meaningful explanations for classifying cell lines into particular clinical states. The reason for this limitation is the lack of inclusion of any information about the clinical status of cell lines during the process of network estimation. To achieve effective cell line classification and ensure the biological validity of the cell lines classification, we develop a computational strategy referred to as GRN-multiClassifier for network-based multi-class classification. The GRN-multiClassifier estimates gene network in a manner that simultaneously minimizes both the network estimation error and the negative log-likelihood function of multinomial logistic regression. That is, our strategy estimates optimized gene network to enable the multi-class classification of cell lines into specific clinical conditions. Monte Carlo simulations demonstrate the efficacy of the GRN-multiClassifier. We applied our strategy to network-based classification of acute leukemia cell lines into three distinct categories of acute leukemia. Our strategy shows outstanding performance in the classification of acute leukemia cell lines. The results for the acute leukemia marker identification are strongly supported by existing literature. The implications of our findings suggest that potential pathways involving the inhibition of ACTB and the molecular interactions between "HBA1&HBB," "HBB&HBA1," "IGKV1-5&IGHV4-31," "IGHV4-31&IGKV1-5," "HLA-DRA&CD74" and "ACTB&ACTB" could offer significant insights into the underlying mechanism of acute leukemia.

Cysteine-rich intestinal protein family: structural overview, functional diversity, and roles in human disease

The cysteine-rich intestinal protein (CRIP) family, including CRIP1, CRIP2, and CRIP3, is a subfamily of the highly conserved Lin-1, Isl1, Mec3/double zinc finger protein family that exhibits diverse biological functions. The CRIP family is known to play an important role in cellular epithelial-mesenchymal transition, cell death, and tumor progression and participate in multiple signaling pathways. This article summarizes the roles and potential molecular mechanisms of the CRIP family in diseases, which will help to explore new research directions for this family and provide useful information for clinical applications such as disease diagnosis and treatment.

Proteomic Comparison of Acute Myeloid Leukemia Cells and Normal CD34+ Bone Marrow Cells: Studies of Leukemia Cell Differentiation and Regulation of Iron Metabolism/Ferroptosis

Acute myeloid leukemia (AML) is an aggressive bone marrow malignancy that can be cured only by intensive chemotherapy possibly combined with allogeneic stem cell transplantation. We compared the pretreatment proteomic profiles of AML cells derived from 50 patients at the time of first diagnosis with normal CD34+ bone marrow cells. A comparison based on all AML and CD34+ normal cell populations identified 121 differentially abundant proteins that showed at least 2-fold differences, and these proteins included several markers of neutrophil differentiation (e.g., TLR2, the integrins ITGM and ITGX, and downstream mediators including RHO GTPase, S100A8, S100A9, S100A22). However, the expression of these 121 proteins varied between patients, and a subset of 28 patients was characterized by increased long-term AML-free survival, signs of myeloid AML cell differentiation, and favorable genetic abnormalities. These two main patient subsets (28 with differentiation versus 22 with fewer signs of differentiation) also differed with regard to the phosphorylation of 16 differentially abundant proteins. Furthermore, we also classified our patients based on their expression of 16 proteins involved in the regulation of iron metabolism/ferroptosis and showing differential expression when comparing AML cells and normal CD34+ cells. Among the 22 patients with less favorable prognosis, we could then identify a genetically heterogeneous subset characterized by adverse prognosis (i.e., death from primary resistance/relapse) and an iron metabolism/ferroptosis protein profile showing similarities with normal CD34+ cells. We conclude that proteomic profiles differ between AML and normal CD34+ cells; especially, proteomic differences reflecting differentiation and regulation of iron metabolism/ferroptosis are associated with risk of relapse after intensive conventional therapy.

[Research progress of iron metabolism and ferroptosis in myeloid neoplasms]

It is reported that iron metabolism and ferroptosis can influence the occurrence and development of myeloid tumors, which can serve as therapeutic targets. Dysregulation of iron metabolism is present in a variety of myeloid neoplasms. The prognosis of acute myeloid leukemia is related to differential expression of molecules related to iron metabolism. The prognosis of myelodysplastic syndrome patients with iron overload is poor. Myeloproliferative neoplasms are often characterized by the coexistence of iron deficiency and erythrocytosis, which can be treated by targeting hepcidin. Myeloid tumor cells are susceptible to oxidative damage caused by the accumulation of reactive oxygen species and are sensitive to ferroptosis. Ferroptosis has anti-tumor effect in acute myeloid leukemia and myelodysplastic syndrome. Targeting ferroptosis can reverse imatinib resistance in chronic myeloid leukemia. This article reviews the characteristics of iron metabolism in the development and progression of myeloid neoplasms, as well as the mechanism of ferroptosis, to provide a basis for the development of new therapeutic strategies.

Advances in integrating single-cell sequencing data to unravel the mechanism of ferroptosis in cancer

Ferroptosis, a commonly observed type of programmed cell death caused by abnormal metabolic and biochemical mechanisms, is frequently triggered by cellular stress. The occurrence of ferroptosis is predominantly linked to pathophysiological conditions due to the substantial impact of various metabolic pathways, including fatty acid metabolism and iron regulation, on cellular reactions to lipid peroxidation and ferroptosis. This mode of cell death serves as a fundamental factor in the development of numerous diseases, thereby presenting a range of therapeutic targets. Single-cell sequencing technology provides insights into the cellular and molecular characteristics of individual cells, as opposed to bulk sequencing, which provides data in a more generalized manner. Single-cell sequencing has found extensive application in the field of cancer research. This paper reviews the progress made in ferroptosis-associated cancer research using single-cell sequencing, including ferroptosis-associated pathways, immune checkpoints, biomarkers, and the identification of cell clusters associated with ferroptosis in tumors. In general, the utilization of single-cell sequencing technology has the potential to contribute significantly to the investigation of the mechanistic regulatory pathways linked to ferroptosis. Moreover, it can shed light on the intricate connection between ferroptosis and cancer. This technology holds great promise in advancing tumor-wide diagnosis, targeted therapy, and prognosis prediction.

MT1E in AML: a gateway to understanding regulatory cell death and immunotherapeutic responses

Regulated cell death (RCD) plays a crucial role in the initiation and progression of tumors, particularly in acute myeloid leukemia (AML). This study investigates the prognostic importance of RCD-related genes in AML and their correlation with immune infiltration. We combined TCGA and GTEx data, analyzing 1,488 RCD-related genes, to develop a predictive model using LASSO regression and survival analysis. The model's accuracy was validated against multiple databases, examining immune cell infiltration, therapy responses, and drug sensitivity among risk groups. RT-qPCR confirmed MT1E expression in AML patients and healthy bone marrow. CCK8 and Transwell assays measured cell proliferation, adhesion, migration, and invasion, while flow cytometry and Western blotting assessed apoptosis and protein expression. We developed a prognostic model using 10 RCD methods, which demonstrated strong predictive ability, showing an inverse correlation between age and risk scores with survival in AML patients. Functional enrichment analysis of the model is linked to immune modulation pathways. RT-qPCR revealed significantly lower MT1E expression in AML vs healthy bone marrow (P < 0.05). Consequently, experiments were designed to assess the function of MT1E overexpression. Findings indicated that MT1E overexpression showed it significantly reduced THP-1 cell proliferation and adhesion (P < 0.001), decreased migration (P < 0.001), and invasiveness (P < 0.05), and increased apoptosis (P < 0.05), with a notable rise in Caspase3 expression. A novel AML RCD risk model was developed, showing promise as a prognostic marker for evaluating outcomes and immune therapy effectiveness. Insights into MT1E's impact on AML cell proliferation and apoptosis open possibilities for improving patient outcomes and devising personalized treatment strategies.

Establishment and validation of a gene mutation-based risk model for predicting prognosis and therapy response in acute myeloid leukemia

Background

Acute myeloid leukemia (AML) is a malignant clonal proliferative disease of hematopoietic system. Despite tremendous progress in uncovering the AML genome, only a small number of mutations have been incorporated into risk stratification and used as therapeutic targets. In this research, we performed to construct a predictive prognosis risk model for AML patients according to gene mutations.

Methods

Next-generation sequencing (NGS) technology was utilized to detect gene mutation from 118 patients. mRNA expression profiles and related clinical information were mined from TCGA and GEO databases. Consensus cluster analysis was applied to obtain molecular subtypes, and differences in clinicopathological features, prognosis, and immune microenvironment of different clusters were systematically compared. According to the differentially expressed genes (DEGs) between clusters, univariate and LASSO regression analysis were applied to identify gene signatures to build a prognostic risk model. Patients were classified into high-risk (HR) and low-risk (LR) groups according to the median risk score (RS). Differences in prognosis, immune profile, and therapeutic sensitivity between two groups were analyzed. The independent predictive value of RS was assessed and a nomogram was developed.

Results

NGS detected 24 mutated genes, with higher mutation frequencies in CBL (63 %) and SETBP1 (49 %). Two clusters exhibited different immune microenvironments and survival probability (p = 0.0056) were identified. A total of 444 DEGs were screened in two clusters, and a mutation-associated risk model was constructed, including MPO, HGF, SH2B3, SETBP1, HLA-DRB1, LGALS1, and KDM5B. Patients in LR had a superior survival time compared to HR. Predictive performance of this model was confirmed and the developed nomogram further improved the applicability of the risk model with the AUCs for predicting 1-, 3-, 5-year survival rate were 0.829, 0.81 and 0.811, respectively. HR cases were more sensitive to erlotinib, CI-1040, and AZD6244.

Conclusion

These findings supplemented the understanding of gene mutations in AML, and constructed models had good application prospect to provide effective information for predicting prognosis and treatment response of AML.

Targeting ferroptosis for leukemia therapy: exploring novel strategies from its mechanisms and role in leukemia based on nanotechnology

The latest findings in iron metabolism and the newly uncovered process of ferroptosis have paved the way for new potential strategies in anti-leukemia treatments. In the current project, we reviewed and summarized the current role of nanomedicine in the treatment and diagnosis of leukemia through a comparison made between traditional approaches applied in the treatment and diagnosis of leukemia via the existing investigations about the ferroptosis molecular mechanisms involved in various anti-tumor treatments. The application of nanotechnology and other novel technologies may provide a new direction in ferroptosis-driven leukemia therapies. The article explores the potential of targeting ferroptosis, a new form of regulated cell death, as a new therapeutic strategy for leukemia. It discusses the mechanisms of ferroptosis and its role in leukemia and how nanotechnology can enhance the delivery and efficacy of ferroptosis-inducing agents. The article not only highlights the promise of ferroptosis-targeted therapies and nanotechnology in revolutionizing leukemia treatment, but also calls for further research to overcome challenges and fully realize the clinical potential of this innovative approach. Finally, it discusses the challenges and opportunities in clinical applications of ferroptosis.

Prognostic insights and immune microenvironment delineation in acute myeloid leukemia by ferroptosis-derived signature

Acute myeloid leukemia (AML) represents as a prevalent and formidable hematological malignancy, characterized by notably low 5-year survival rates. Ferroptosis has been found to be correlated with cancer initiation, therapeutic response, and clinical outcome. Nevertheless, the involvement of Ferroptosis-related genes (FRGs) in AML remains ambiguous. Five independent AML cohorts totaling 1,470 (GSE37642, GSE12417, GSE10358, Beat-AML, and TCGA-AML) patients with clinical information were used to systematically investigated the influence of these FRGs expression on outcome and tumor microenvironment. The integration of these datasets led to the subdivision into training and validation sets. Nineteen FRGs were identified as correlated with the overall survival (OS) of AML patients, primarily enriched in ferroptosis, fatty acid metabolism, and leukemia-related signaling pathways. The prognostic signature, consisting of 11 FRGs, was formulated using LASSO-Cox stepwise regression analysis. Patients with high-risk scores exhibited reduced survival compared to those in the low-risk group. The receiver operating characteristic (ROC) analysis underscored the signature's robust predictive accuracy. The high predictive efficacy was confirmed by both internal and external validation datasets. Leukemia and signaling related to immune regulation were mainly enriched pathways of the differentially expressed genes by comparing high- and low-risk groups. The immune composition deconvolution might indicate an immunosuppressive niche in the high-risk patients. The pRRophetic algorithm exploration unveiled chemical drugs with potentially sensitivity among patients in both groups. Collectively, our study developed a ferroptosis-derived prognostic signature that provides the OS prediction and identifies the immune microenvironment for AML patients on large-scale AML cohorts.

Broadening the horizon: potential applications of CAR-T cells beyond current indications

Engineering immune cells to treat hematological malignancies has been a major focus of research since the first resounding successes of CAR-T-cell therapies in B-ALL. Several diseases can now be treated in highly therapy-refractory or relapsed conditions. Currently, a number of CD19- or BCMA-specific CAR-T-cell therapies are approved for acute lymphoblastic leukemia (ALL), diffuse large B-cell lymphoma (DLBCL), mantle cell lymphoma (MCL), multiple myeloma (MM), and follicular lymphoma (FL). The implementation of these therapies has significantly improved patient outcome and survival even in cases with previously very poor prognosis. In this comprehensive review, we present the current state of research, recent innovations, and the applications of CAR-T-cell therapy in a selected group of hematologic malignancies. We focus on B- and T-cell malignancies, including the entities of cutaneous and peripheral T-cell lymphoma (T-ALL, PTCL, CTCL), acute myeloid leukemia (AML), chronic myeloid leukemia (CML), chronic lymphocytic leukemia (CLL), classical Hodgkin-Lymphoma (HL), Burkitt-Lymphoma (BL), hairy cell leukemia (HCL), and Waldenström's macroglobulinemia (WM). While these diseases are highly heterogenous, we highlight several similarly used approaches (combination with established therapeutics, target depletion on healthy cells), targets used in multiple diseases (CD30, CD38, TRBC1/2), and unique features that require individualized approaches. Furthermore, we focus on current limitations of CAR-T-cell therapy in individual diseases and entities such as immunocompromising tumor microenvironment (TME), risk of on-target-off-tumor effects, and differences in the occurrence of adverse events. Finally, we present an outlook into novel innovations in CAR-T-cell engineering like the use of artificial intelligence and the future role of CAR-T cells in therapy regimens in everyday clinical practice.