Copy Number Alterations Associated with Acute Lymphoblastic Leukemia in Mexican Children. A report from The Mexican Inter-Institutional Group for the identification of the causes of childhood leukemia

The Role of miRNAs in Childhood Acute Lymphoblastic Leukemia Relapse and the Associated Molecular Mechanisms

Acute lymphoblastic leukemia (ALL) is the most common cancer in children worldwide. Although ALL patients' overall survival rates in wealthy countries currently surpass 80%, 15-20% of patients still experience relapse. The underlying mechanisms of relapse are still not fully understood, and little progress has been made in treating refractory or relapsed disease. Disease relapse and treatment failure are common causes of leukemia-related death. In ALL relapse, several gene signatures have been identified, but it is also important to study miRNAs involved in ALL relapse in an effort to avoid relapse and to achieve better survival rates since miRNAs regulate target genes that participate in signaling pathways involved in relapse, such as those related to drug resistance, survival signals, and antiapoptotic mechanisms. Several miRNAs, such as miR-24, miR-27a, miR-99/100, miR-124, miR-1225b, miR-128b, miR-142-3p, miR-155 and miR-335-3p, are valuable biomarkers for prognosis and treatment response in ALL patients. Thus, this review aimed to analyze the primary miRNAs involved in pediatric ALL relapse and explore the underlying molecular mechanisms in an effort to identify miRNAs that may be potential candidates for anti-ALL therapy soon.

Hit Identification Driven by Combining Artificial Intelligence and Computational Chemistry Methods: A PI5P4K-β Case Study

Computer-aided drug design (CADD), especially artificial intelligence-driven drug design (AIDD), is increasingly used in drug discovery. In this paper, a novel and efficient workflow for hit identification was developed within the ID4Inno drug discovery platform, featuring innovative artificial intelligence, high-accuracy computational chemistry, and high-performance cloud computing. The workflow was validated by discovering a few potent hit compounds (best IC50 is ∼0.80 μM) against PI5P4K-β, a novel anti-cancer target. Furthermore, by applying the tools implemented in ID4Inno, we managed to optimize these hit compounds and finally obtained five hit series with different scaffolds, all of which showed high activity against PI5P4K-β. These results demonstrate the effectiveness of ID4inno in driving hit identification based on artificial intelligence, computational chemistry, and cloud computing.

Pitavastatin Is Anti-Leukemic in a Bone Marrow Microenvironment Model of B-Lineage Acute Lymphoblastic Leukemia

Simple Summary

Chemoresistance after chemotherapy is a negative prognostic indicator for B-cell acute lymphoblastic leukemia (ALL), necessitating the search for novel therapies. By growing ALL cells together with bone marrow stromal cells, we developed a chemoresistant ALL model. Using this model, we found that the lipid lowering drug pitavastatin had antileukemic activity in this chemoresistant co-culture model. Our data suggests that pitavastatin may be a novel treatment option for repurposing in chemoresistant, relapse ALL.

Abstract

The lack of complete therapeutic success in the treatment of B-cell acute lymphoblastic leukemia (ALL) has been attributed, in part, to a subset of cells within the bone marrow microenvironment that are drug resistant. Recently, the cholesterol synthesis inhibitor, pitavastatin (PIT), was shown to be active in acute myeloid leukemia, prompting us to evaluate it in our in vitro co-culture model, which supports a chemo-resistant ALL population. We used phospho-protein profiling to evaluate the use of lipid metabolic active compounds in these chemo-resistant cells, due to the up-regulation of multiple active survival signals. In a co-culture with stromal cells, a shift towards anabolic processes occurred, which was further confirmed by assays showing increased lipid content. The treatment of REH leukemia cells with pitavastatin in the co-culture model resulted in significantly higher leukemic cell death than exposure to the standard-of-care chemotherapeutic agent, cytarabine (Ara-C). Our data demonstrates the use of pitavastatin as a possible alternative treatment strategy to improve patient outcomes in chemo-resistant, relapsed ALL.

Genetic Biomarkers and Their Clinical Implications in B-Cell Acute Lymphoblastic Leukemia in Children

Acute lymphoblastic leukemia (ALL) is a heterogeneous group of hematologic malignancies characterized by abnormal proliferation of immature lymphoid cells. It is the most commonly diagnosed childhood cancer with an almost 80% cure rate. Despite favorable survival rates in the pediatric population, a significant number of patients develop resistance to therapy, resulting in poor prognosis. ALL is a heterogeneous disease at the genetic level, but the intensive development of sequencing in the last decade has made it possible to broaden the study of genomic changes. New technologies allow us to detect molecular changes such as point mutations or to characterize epigenetic or proteomic profiles. This process made it possible to identify new subtypes of this disease characterized by constellations of genetic alterations, including chromosome changes, sequence mutations, and DNA copy number alterations. These genetic abnormalities are used as diagnostic, prognostic and predictive biomarkers that play an important role in earlier disease detection, more accurate risk stratification, and treatment. Identification of new ALL biomarkers, and thus a greater understanding of their molecular basis, will lead to better monitoring of the course of the disease. In this article, we provide an overview of the latest information on genomic alterations found in childhood ALL and discuss their impact on patients' clinical outcomes.

Copy Number Alterations are Associated with the Risk of Very Early Relapse in Pediatric B-lineage Acute Lymphoblastic Leukemia: A Nested Case-control MIGICCL Study

BACKGROUND

Refining risk stratification to avoid very early relapses (VER) in Mexican patients with B-lineage acute lymphoblastic leukemia (B-ALL) could lead to better survival rates in our population.

AIM OF THE STUDY

The purpose of this study was to investigate the association between the United Kingdom ALL (UKALL)-CNA classifier and VER risk in Mexican patients with childhood B-ALL.

METHODS

A nested case-control study of 25 cases with VER and 38 frequency-matched controls without relapse was conducted within the MIGICCL study cohort. They were grouped into the categories of the UKALL-CNA risk classifier (good [reference], intermediate and poor), according to the results obtained by multiplex ligation dependent probe amplification. Overall and disease-free survival (DFS) were estimated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards analyses were conducted.

RESULTS

The CDKN2A/B genes were most frequently deleted in the group with relapse. According to UKALL-CNA classifier, 33 (52.4%) patients were classified as good, 21 (33.3%) intermediate and 9 (14.3%) poor-risk B-ALL. The intermediate and poor risk groups were associated with an increased risk of VER (HR = 4.94, 95% CI = 1.87-13.07 and HR = 7.42, 95% CI = 2.37-23.26, respectively) in comparison to the good-risk patients. After adjusting by NCI risk classification and chemotherapy scheme in a multivariate model, the risks remained significant.

CONCLUSIONS

Our data support the clinical utility of profiling CNAs to potentially refine current risk stratification strategies of patients with B-ALL.

Prognostic Impact of Somatic Copy Number Alterations in Childhood B-Lineage Acute Lymphoblastic Leukemia

PURPOSE OF REVIEW

The high prevalence of relapse in pediatric B-lineage acute lymphoblastic leukemia (B-ALL) despite the improvements achieved using current risk stratification schemes, demands more accurate methods for outcome prediction. Here, we provide a concise overview about the key advances that have expanded our knowledge regarding the somatic defects across B-ALL genomes, particularly focusing on copy number alterations (CNAs) and their prognostic impact.

RECENT FINDINGS

The identification of commonly altered genes in B-ALL has inspired the development of risk classifiers based on copy number states such as the IKZF1^plus and the United Kingdom (UK) ALL-CNA classifiers to improve outcome prediction in B-ALL. CNA-risk classifiers have emerged as effective tools to predict disease relapse; though, their clinical applications are yet to be transferred to routine practice.

Targeting the PI5P4K Lipid Kinase Family in Cancer Using Covalent Inhibitors

The PI5P4Ks have been demonstrated to be important for cancer cell proliferation and other diseases. However, the therapeutic potential of targeting these kinases is understudied due to a lack of potent, specific small molecules available. Here, we present the discovery and characterization of a pan-PI5P4K inhibitor, THZ-P1-2, that covalently targets cysteines on a disordered loop in PI5P4Kα/β/γ. THZ-P1-2 demonstrates cellular on-target engagement with limited off-targets across the kinome. AML/ALL cell lines were sensitive to THZ-P1-2, consistent with PI5P4K's reported role in leukemogenesis. THZ-P1-2 causes autophagosome clearance defects and upregulation in TFEB nuclear localization and target genes, disrupting autophagy in a covalent-dependent manner and phenocopying the effects of PI5P4K genetic deletion. Our studies demonstrate that PI5P4Ks are tractable targets, with THZ-P1-2 as a useful tool to further interrogate the therapeutic potential of PI5P4K inhibition and inform drug discovery campaigns for these lipid kinases in cancer metabolism and other autophagy-dependent disorders.