The hematopoietic transcription factor Ikaros (IKZF1) regulates normal B cell development and functions as a tumor suppressor in precursor B cell acute lymphoblastic leukemia (B-ALL). MicroRNAs (miRNAs) are small regulatory RNAs that through post-transcriptional gene regulation play critical roles in intracellular processes including cell growth in cancer. However, the role of Ikaros in the regulation of miRNA expression in developing B cells is unknown. In this study, we examined the Ikaros-regulated miRNA targets using patient-derived IKZF1-mutated B-ALL xenograft-derived cell lines. Inducible expression of wild-type Ikaros (the Ik1 isoform) caused B-ALL growth arrest and exit from the cell cycle. Global miRNA expression analysis revealed a total of 31 miRNAs regulated by IK1, and ChIP-seq analysis showed that Ikaros bound to several Ik1-responsive miRNA genes. Examination of the prognostic significance of miRNA expression in B-ALL indicate that the IK1-regulated miRNAs hsa-miR-26b, hsa-miR-130b and hsa-miR-4649 are significantly associated with outcome in B-ALL. Our findings establish a potential regulatory circuit between the tumor-suppressor Ikaros and the oncogenic miRNA networks in IKZF1-mutated B-ALL. These results indicate that Ikaros regulates the expression of a subset of miRNAs, of which several may contribute to B-ALL growth.

Acute lymphoblastic leukemia is the most common malignancy in children and is characterized by numerous genetic and epigenetic abnormalities. Epigenetic mechanisms, which involve DNA methylations and histone modifications, result in the heritable silencing of genes without a change in their coding sequence. Emerging studies are increasing our understanding of the epigenetic role of leukemogenesis and have demonstrated the potential of DNA methylations and histone modifications as a biomarker for lineage and subtypes classification, predicting relapse, and disease progression in ALL. Epigenetic abnormalities are relatively reversible when treated with some small molecule-based agents compared to genetic alterations. In this review, we conclude the genetic and epigenetic characteristics in ALL and discuss the future role of DNA methylation and histone modifications in predicting relapse, finally focus on the individual and precision therapy targeting epigenetic alterations.

Methotrexate (MTX), a structurally related substance to folic acid, is an important chemotherapeutic agent used for decades in the treatment of pediatric acute lymphoblastic leukemia (ALL) and other types of cancer as non Hodgkin lymphomas and osteosarcomas. Despite the successful outcomes observed, the primary drawback is the variability in the pharmacokinetics and pharmacodynamics between patients. The main adverse events related to its use are mainly nephrotoxicity, mucositis and myelosuppression especially when used in high doses. The potential adverse reactions and toxicities associated with MTX are a cause for concern and may lead to dose reduction or treatment interruption. Genetic variants in MTX transport genes have been linked to toxicity. Pharmacogenetic studies conducted in the past focused on single nucleotide polymorphisms (SNPs) in the coding and 5′-regulatory regions of genes. Recent studies have demonstrated a significant role of miRNAs in the transport and metabolism of drugs, and in the regulation of target genes. The last few years, the number of annotated miRNAs is continually rising, as well as the studies of miRNA polymorphisms and MTX toxicity. Therefore, the objective of the present study is to investigate the role of miRNA variants related to MTX adverse effects.

Acute leukemias constitute some of the most common malignant disorders. Despite significant progress made in the treatment of these disorders, their etiology remains unknown. A large and diverse group of genetic and environmental variables have been proposed. The role of a variety of factors, including pre-existing and acquired genetic mutations, exposure to radiation and various chemicals during pre-conception, pregnancy and throughout life have been explored. The effects of inherited genetic variations and disorders, pre-existing diseases, infectious agents, hobbies, occupations, prior treatments and a host of other factors have been proposed, but none is universally applicable to all cases. Variation in the incidence and prognosis based on the age, sex, race, type of the disease, geographic area of residence and other factors are intriguing, but remains unexplained. Advances in genomic profiling, including genome‐wide gene expression, DNA copy number, and single nucleotide polymorphism [SNP] genotype may shed some light on the role of genetics in these disparities. Separate two-hit hypothesis for the development of acute myeloblastic and lymphoblastic leukemia have been proposed. The latter combines genetics and infection factors resulting in leukemogenesis. A number of pre- and post-natal environmental conditions and exposure to infections, including a mycovirus infected Aspergillus flavus, have been suggested. The exact nature, timing, sequence of the events and mechanisms resulting in occurrence of leukemia requires further investigations. This review summarizes some of the above factors and the direction for future research on the etiology of acute leukemias.

Leukemia is a cancer of the bone marrow, a spongy tissue that secretes into the bones and serves as the site for the production of blood cells. One of the most prevalent kinds of leukemia in adults is acute myeloid leukemia (AML). Leukemia has non-specific signs and symptoms that are also similar to those of other interpersonal illnesses. The only way to accurately diagnose leukemia is by manually examining a stained blood smear or bone marrow aspirate under the microscope. However, this approach takes more time and is less precise. This paper describes a method for the automatic recognition and classification of AML in blood smears. Classification techniques include decision trees, logistic regression, support vector machines, and naive bayes.

Alterations in the composition and diversity, metabolism, and products of the microbiome, and of the gut microbiome (GM), have been shown to be closely associated with the onset and progression of many human diseases, including cancer (i.e. hematological neoplasms). Acute lymphoblastic leukemia (ALL) is the most common form of childhood malignancy. Affected cases present typical alterations of GM, followed by inflammation, which contribute to its progression, response to therapy, as well as possible relapses. Recent evidence also reports that GM influences the development and functions of the newborn's hematopoietic system through the process of developmental programming during fetal life, as well as its susceptibility to the onset of onco-hematological pathologies, namely ALL. Furthermore, in children with ALL, GM has been found to vary in composition, variety, and functions during the clinical stages of ALL, and such variation may influence and predict the complications and prognosis of ALL after chemotherapy treatment or stem cell hematopoietic transplant. Here, we suggest some therapeutic strategies, which can be applied at two levels of intervention to recover the microbiome, and consequently prevent/delay ALL or arrest its progression.

Long non-coding RNA (lncRNA) aberrant expression have been found in several types of cancer, including acute lymphoblastic leukemia (ALL), but lncRNA mapped in transcribed ultraconserved regions (T-UCRs) are little explored. The T-UCRs uc.112, uc.122, uc.160 and uc.262 were evaluated in pediatric ALL and uc.112 expression was higher in T-ALL compared to patients with B-ALL and in patients with hyperdiploid karyotype. These findings suggest a potential role of this uc.112 in pediatric ALL and emphasize the need for further investigation of T-UCR in pediatric ALL.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Although prognosis continually improved along years, a significant proportion of patients still relapse from the disease due to leukemia resistance to therapy. Methotrexate (MTX), a folic acid antagonist, is a chemotherapy agent commonly used against ALL and a immune-system suppressant for rheumatoid arthritis, that presents multiple and complex mechanisms of action and resistance. Previous studies have shown that MTX modulates the nuclear factor kappa B (NF-κB) pathway, an important family of transcription factors involved in inflammation, immunity, cell survival, and proliferation, frequently hyperactivated in ALL. Using gene set enrichment analysis (GSEA) on publicly available gene expression data from 161 newly diagnosed pediatric ALL patients, we found “TNF-α signaling pathway” to be the most enriched Cancer Hallmark in MTX poor responder patients. Transcriptomic analysis in a panel of ALL cell lines (6 BCP-ALL and 7 T-ALL) also identified the same pathway as differentially enriched among MTX resistant cell lines, as well as in slowly dividing cells. To better understand the crosstalk between NF-κB activity and MTX resistance, we genetically modified the cell lines to express luciferase under a NF-κB biding site promoter. We observed that the fold change in NF-κB activity triggered by TNF-α (but not MTX) treatment correlated with MTX resistance and proliferation across the lines. At the individual gene level, NFKB1 expression was directly associated with a poorer clinical response to MTX, and with both an increased TNF-α-triggered NF-κB activation and MTX resistance in the cell lines. Despite these results, pharmacological inhibition (with BAY 11-7082 and parthenolide) or stimulation (with exogenous TNF-α supplementation) of the NF-κB pathway did not alter MTX resistance of the cell lines significantly, evidencing a complex interplay between MTX and NF-κB in ALL.

Relapsed acute lymphoblastic leukemia (ALL) represents a continuous challenge for the clinician. Despite recent advances in treatment, the risk of relapse remains significant. The clinical, biological, cytogenetic, and molecular characteristics may be different at the time of relapse. Current comprehensive genome sequencing studies suggest that most relapsed patients, especially those with late relapses, acquire new genetic abnormalities, usually within a minor clone that emerges after ALL diagnosis. We report the case of a 23-year-old young woman diagnosed with Philadelphia chromosome negative B-cell acute lymphoblastic leukemia. The patient underwent allogeneic stem cell transplantation (allo-HSCT) after complete remission. Although having favorable prognostic factors at diagnosis, the disease relapsed early after allo-HSCT. The cytogenetic and molecular exam at relapse was positive for the Philadelphia chromosome, respectively for the bcr-abl transcript. What exactly led to the relapse of this disease in a more aggressive cytogenetic and molecular form, although there were no predictive elements in the diagnosis of this relapse?

Although automated Acute Lymphoblastic Leukemia (ALL) detection is essential, it is challenging due to the morphological correlation between malignant and normal cells. The traditional ALL classification strategy is arduous, time-consuming, often suffers inter-observer variations, and necessitates experienced pathologists. This article has automated the ALL detection task, employing deep Convolutional Neural Networks (CNNs). We explore the weighted ensemble of deep CNNs to recommend a better ALL cell classifier. The weights are estimated from ensemble candidates' corresponding metrics, such as accuracy, F1-score, AUC, and kappa values. Various data augmentations and pre-processing are incorporated for achieving a better generalization of the network. We train and evaluate the proposed model utilizing the publicly available C-NMC-2019 ALL dataset. Our proposed weighted ensemble model has outputted a weighted F1-score of 88.6%, a balanced accuracy of 86.2%, and an AUC of 0.941 in the preliminary test set. The qualitative results displaying the gradient class activation maps confirm that the introduced model has a concentrated learned region. In contrast, the ensemble candidate models, such as Xception, VGG-16, DenseNet-121, MobileNet, and InceptionResNet-V2, separately produce coarse and scatter learned areas for most example cases. Since the proposed ensemble yields a better result for the aimed task, it can experiment in other domains of medical diagnostic applications.

Chimeric Antigen Receptor (CAR) T-cell therapy has demonstrated high rates of response in recurrent B-cell Acute Lymphoblastic Leukemia in children and young adults. Despite this success, a fraction of patients experience relapse after treatment. Relapse is often preceded by recovery of healthy B cells, which suggests loss or dysfunction of CAR T cells in bone marrow. This site is harder to access, and thus is not monitored as frequently as peripheral blood. Understanding the interplay between B cells, leukemic cells and CAR T cells in bone marrow is paramount in ascertaining the causes of lack of response. In this paper, we put forward a mathematical model representing the interaction between constantly renewing B cells, CAR T cells and leukemic cells in the bone marrow. Our model accounts for the maturation dynamics of B cells and incorporates effector and memory CAR T cells. The model provides a plausible description of the dynamics of the various cellular compartments in bone marrow after CAR T infusion. After exploration of the parameter space, we found that the dynamics of CAR T product and disease were independent of the dose injected, initial B-cell load and tumor burden. We also show theoretically the importance of CAR T product attributes in determining therapy outcome, and have studied a variety of possible response scenarios, including second dosage schemes. We conclude by setting out ideas for the refinement of the model.

Natural killer (NK) cells play a crucial role in innate immunity, particularly in combating infections and tumors. However, in hematological cancers, NK cells often exhibit impaired functions. Therefore, it is very important to activate its endosomal toll-like receptors (TLRs) as a potential strategy to restore its antitumor activity. We stimulate NK cells from the peripheral blood mononuclear cells from children with acute lymphoblastic leukemia and NK cells isolated, the NK cells were stimulated with specific TLR ligands (Poly I:C, Imiquimod, R848, and ODN2006) and evaluated changes in IFN-γ, CD107a, NKG2D, NKp44 expression, Granzyme B secretion, cytokine/chemokine release, and cytotoxic activity. Results revealed that Poly I:C and Imiquimod enhanced activation of both immunoregulatory and cytotoxic NK cells, increasing IFN-γ, CD107a, NKG2D, and NKp44 expression. R848 activated immunoregulatory NK cells, while ODN2006 boosted CD107a, NKp44, NKG2D, and IFN-γ secretion in cytotoxic NK cells. R848 also increased secretion of various cytokines/chemokines. Importantly, R848 and ODN 2006 significantly improved cytotoxicity against leukemic cells. Overall, TLR stimulation enhances NK cell activation, suggesting TLR8 (R848) and TLR9 (ODN 2006) ligands as promising candidates for antitumor immunotherapy.

Artificial intelligence methods may help in unveliling information hidden in high-dimensional oncological data. Flow cytometry studies of haematological malignancies provide quantitative data with the potential to be used for the construction of response biomarkers. Many computational methods from the bioinformatics toolbox can be applied to these data but have not been exploited in their full potential in leukaemias, specifically for the case of childhood B-cell acute lymphoblastic leukemia. In this paper we analysed flow cytometry data obtained on diagnosis from 54 paediatric B-cell acute lymphoblastic leukemia patients from two local institutions. We constructed classifiers based on the Fisher’s Ratio to quantify differences in expression levels of immunophenotypical markers between patients with relapsing and non-relapsing disease. The distribution of the marker CD38 was found and validated to have a strong discriminating power between both patient cohorts, thus providing a classifier.

In this report we describe the case of a healthy, young, athletic woman who developed acute lymphoblastic leukaemia (ALL)/lymphoblastic lymphoma (LBL) after receiving the second dose of the Pfizer/BioNTech modified mRNA (modRNA) COVID-19 genetic vaccine (marketed as Comirnaty^®). The first dose of the genetic vaccine did not appear to illicit any noticeable side effects, but within 24 hours of the second dose the patient suffered widespread and intensifying bone pain, fever, vomiting, and general malaise. Due to the persistence of the symptoms, the patient underwent a series of tests and examinations including a full laboratory workup, a consult with a clinical immunologist and rheumatologist, a Positron Emission Tomography (PET) imaging, as well as an osteomedullary biopsy. These together led to a definitive diagnosis of ALL. A time interval of 16 weeks from the second vaccination to the diagnosis of cancer was noted. Several similar cases with identical pathology which developed after the modRNA COVID-19 vaccination, are described in case reports in the scientific literature. The massive and indiscriminate use of genetic vaccines to fight COVID-19 is raising serious concerns about their safety and about the technology platform as a whole for this purpose. Growing evidence is accumulating regarding the biodistribution and persistence of the modRNA which can reach, thanks to the lipid nanoparticles, a multitude of tissues and organs of the body, including the bone marrow and other blood-forming organs and tissues. Moreover, there is evidence that the modRNA vaccines display a particular tropism for the bone marrow, influencing the immune system at multiple levels and being able to trigger not only autoimmune-based pathologies, but also neoplastic mechanisms. The aim of this article is to assess, on the basis of the available scientific literature, the risk of developing haematopoietic cancers after modRNA vaccination, and to investigate the potential genetic mechanisms involved in the pathogenesis of disease.

Acute lymphoblastic leukemia (ALL) is the most common cancer among children worldwide, characterized by an overproduction of undifferentiated lymphoblasts in the bone marrow. The treatment of choice for this disease is the enzyme L-asparaginase (ASNase) from bacterial sources. ASNase hydrolyzes circulating L-asparagine in plasma, leading to starvation of leukemic cells. The ASNase formulations of E. coli and E. chrysanthemi present notorious adverse effects, especially the immunogenicity they generate, which undermines both their effectiveness as drugs and patient safety. In this study, we developed a humanized chimeric enzyme from E. coli L-asparaginase, which would reduce the immunological problems associated with current L-asparaginase therapy. For these, the immunogenic epitopes of E. coli L-asparaginase (PDB: 3ECA) were determined and replaced with those of the less immunogenic Homo sapiens asparaginase (PDB:4O0H). The structures were modeled using the Pymol software and the chimeric enzyme was modeled using the SWISS MODEL service. A humanized chimeric enzyme with four subunits similar to the template structure was obtained, and the presence of asparaginase enzymatic activity was predicted by protein-ligand docking.

To the best of the author’s knowledge, studies of mature plasmacytoid dendritic cell proliferation associated with T lymphoblastic lymphoma were extremely rare in the literature. Here, we report a patient who underwent both mature plasmacytoid dendritic cell proliferation and T lymphoblastic lymphoma. With the findings of lymph node biopsy taken from the right cervical and inguinal regions, we identified eye-catching mature plasmacytoid dendritic cells that were considered to be responsible for this lesion at the beginning, until the immunostaining of Ki67 and TDT showed a small group of positive cells hiding in these plasmacytoid dendritic cells. Bone marrow biopsy was also performed in this patient. Microscopically, the hematopoietic tissue was almost completely replaced by lymphoblastoid cells with condensed chromatin, inconspicuous nucleoli and scanty cytoplasm, which were basically the same as those seen in the lymph nodes in morphology. However, there was no sign of plasmacytoid dendritic cells or Langerhans cells in the bone marrow biopsy. With the help of bone marrow biopsy, our final diagnosis of the lymph node was T lymphoblastic lymphoma coexisting with mature plasmacytoid dendritic cell proliferation . Although accumulations of plasmacytoid dendritic cells may occur in some infections or reactive lymphadenopathy, the presence of extensive nodules or infiltration of plasmacytoid dendritic cells strongly reminds the pathologist to carefully evaluate the bone marrow or peripheral blood status of the patient to exclude a hidden myeloid or other neoplasm.

In Philadelphia chromosome positive B-cell (Ph+) acute lymphoblastic leukemia (LLA), growing evidence has ac-cumulated about the efficacy of low-intensity and chemo-free regimens. Our objective was to analyze all recent trials evaluating these treatments and to compare them in terms of efficacy. We applied the Shiny method, an artificial intelligence technique, to analyze Kaplan-Meier curves and reconstruct patient-level data. Reconstructed patient data were then evaluated through standard survival statistics and subjected to indirect head-to-head treatment comparisons. The endpoint was progression-free survival (PFS). Based on 848 reconstructed patients, 9 trials were analyzed. The survival data from these trials were pooled into three types of treatments: i) treatments based on ty-rosine kinase inhibitors (TKIs) combined with reduced-intensity chemotherapy (denoted as TKICHE); ii) TKIs as-sociated to steroids with no chemotherapy (TKISTE); iii) chemotherapy-free combinations of blinatumomab plus TKIs (TKIBLI). According to the Shiny method, the three PFS curves were reported in a single Kaplan-Meier graph and subjected to survival statistics. In terms of PFS, TKIBLI ranked first, TKICHE second, and TKISTE third; the differences between these three regimens were statistically significant. This multi-treatment Kaplan-Meier graph, generated through the Shiny method, summarized the current evidence on these treatments in both qualitative and quantitative terms.

: In Philadelphia chromosome positive B-cell (Ph+) acute lymphoblastic leukemia (LLA), growing evidence has accumulated about the efficacy of low-intensity and chemo-free regimens. Our objective was to analyse all recent trials evaluating these treatments and to compare them in terms of efficacy. We applied the Shiny method, an artificial intelligence technique, to analyse Kaplan-Meier curves and reconstruct patient-level data. Reconstructed patient data were then evaluated through standard survival statistics and subjected to indirect head-to-head treatment comparisons. The endpoint was progression-free survival (PFS). Based on 562 reconstructed patients, 8 trials were analyzed. The survival data from these trials were pooled into three types of treatment: i) treatments based on tyrosine kinase inhibitors (TKIs) combined with reduced-intensity chemotherapy (denoted as TKICHE); ii) TKIs associated to steroids with no chemotherapy (TKISTE); iii) chemotherapy-free combinations of blinatumomab plus TKIs (TKIBLI). According to the Shiny method, the three PFS curves were reported in a single Kaplan-Meier graph and subjected to survival statistics. In terms of PFS, TKIBLI ranked first, TKICHE second, and TKISTE third; the differences between these three regimens were statistically significant. In conclusion, the multi-treatment Kaplan-Meier graph generated in this study has effectively summarized the current evidence on these treatments in comparative terms.

Transplant of human cancer cells into zebrafish larvae has emerged as a useful methodology in cancer research. Zebrafish have very low husbandry costs, are amenable to large-scale drug screening, and are unmatched for optical clarity in live animal imaging. However, there is currently no consensus on the ideal methods for xenograft of human cancer cells into zebrafish. Here, we have examined the effects of transplant site and housing temperature on both zebrafish larvae and human cancer cells using survival analyses, metabolomic approaches, and in vivo imaging. Our data show that while zebrafish larvae can adapt to the ideal conditions for mammalian cells, human cancer cells are highly sensitive to both temperature change and transplant site. Human cells housed in slightly cooler than physiologic temperatures had a significantly altered metabolism that resulted in changes in growth, survival, and response to chemotherapy. Cancer cells xenografted into the yolk of the larvae also had reduced proliferation and drug response compared to those xenografted into the soma, in part due to the differences in metabolites available at these sites. In total, temperature and transplant site can have profound effects on xenografted cells. Standardization of zebrafish xenograft methods will enhance data reproducibility between individual laboratories.

The molecular basis of Down syndrome (DS) predisposition to leukemia is not fully understood but involves various factors such as chromosomal abnormalities, oncogenic mutations, epigenetic alterations, and changes in selection dynamics. Myeloid leukemia associated with DS (ML-DS) is preceded by a preleukemic phase called transient abnormal myelopoiesis driven by GATA1 gene mutations and progresses to ML-DS through additional mutations in cohesin genes, CTCF, RAS, or JAK/STAT pathway genes. DS-related ALL (ALL-DS) differs from non-DS ALL in terms of cytogenetic subgroups and genetic driver events and aberrant expression of CRLF2, JAK2 mutations, and RAS pathway activating mutations are frequent in ALL-DS. Recent advancements in single-cell multi-omics technologies have provided unprecedented insights into the cellular and molecular heterogeneity of DS-associated hematologic neoplasms. Single-cell RNA sequencing and digital spatial profiling enable the identification of rare cell subpopulations, characterization of clonal evolution dynamics, and exploration of the tumor microenvironment's role. These approaches may help identify new druggable targets and tailor therapeutic interventions based on distinct molecular profiles, ultimately improving patient outcomes with the potential to guide personalized medicine approaches and the development of targeted therapies.