Biology subjects

Deshpande, A.

Publications and source records attributed to Deshpande, A..

At least 73 records · Page 4Linked to original sources

bioRxiv2022

The Ferrous Iron Transporter FeoB1 is Essential for Clostridioides difficile Toxin Production and Pathogenesis in Mice

Ferrous iron is the dominant form of iron in the oxygen-limited large intestine, the site for Clostridioides difficile infection (CDI). We investigated the extent to which C. difficile requires the ferrous iron transporter 1 (FeoB1), a main permease for iron acquisition, using in vitro and in vivo approaches. Construction of feoB1 deletion mutant in C. difficile R20291 (i.e., R20291{Delta}feoB1) decreased intracellular iron content by [~]25%. This was accompanied by downregulation of tcdA and tcdB genes and reduced synthesis of TcdA and TcdB toxins, which was reflected by a [~]1000-fold reduction in cytopathy against Vero cells. Complementation with WT feoB1 restored toxin production. Transcriptional and biochemical analyses revealed {Delta}feoB1 altered metabolic pathways that negatively impact toxin production, including downregulation of the oxidative branch of the Kreb cycle and an associated cellular accumulation of pyruvate. Hence FeoB1 influences multiple bioenergetic and redox pathways, which in turn inhibits toxin biosynthesis. R20291{Delta}feoB1 was avirulent in mice with underlying colitis. In this model, mice are prone to develop severe CDI, but mice infected with the mutant lacked diarrheal symptoms, had lesser inflammatory responses, bacterial bioburdens and cecal toxin titers. These results strongly imply that ferrous iron acquisition and homeostasis is central to toxin metabolism and virulence. Hence targeting FeoB1 could be a potential therapeutic strategy to impede the colonization and pathogenesis of C. difficile, even in the setting of colitis where intestinal bleeding may occur and CDI is more severe.

microbiology↗

bioRxiv2022

Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGE uses deep learning and a ctDNA-specific feature space to increase SNV signal to noise enrichment in WGS by 300X compared to our previous noise suppression platform MRDetect. MRD-EDGE also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1Gb to 200Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal to noise enrichment in MRD-EDGE enables de novo mutation calling in melanoma without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition.

genomics↗

bioRxiv2021

scatterHatch: an R/Bioconductor package for colorblind accessible visualization of single-cell data

Reduced-dimension or spatial in situ scatter plots are widely employed in bioinformatics papers analyzing single-cell data to present phenomena or cell-conditions of interest in cell groups. When displaying these cell groups, color is frequently the only graphical cue used to differentiate them. However, as the complexity of the information presented in these visualizations increases, the usefulness of color as the only visual cue declines, especially for the sizable readership with color-vision deficiencies (CVDs). In this paper, we present scatterHatch, an R package that creates easily interpretable scatter plots by redundant coding of cell groups using colors as well as patterns. We give examples to demonstrate how the scatterHatch plots are more accessible than simple scatter plots when simulated for various types of CVDs.

bioinformatics↗

bioRxiv2021

Transcriptomic response of Cinachyrella cf. cavernosa sponges to spatial competition

Spatial competition in the intertidal zones drives the community structure in marine benthic habitats. Organisms inhabiting these areas not only need to withstand fluctuations of temperature, water level, pH, and salinity, but also need to compete for the best available space. Sponges are key members of the intertidal zones, and their life history processes (e.g. growth, reproduction, and regeneration) are affected by competition. Here we used transcriptomics to investigate the effects of interspecific competition between the tetillid sponge Cinachyrella cf. cavernosa, the zoantharid Zoanthus sansibaricus, and the macroalgae Dictyota ciliolata. The analysis of differentially expressed genes showed that Z. sansibaricus was the most stressful competitor to C. cf. cavernosa, which showed an increased rate of cellular respiration under stress of competition. Similarly, an up-regulation of energy metabolism, lipid metabolism, and the heat-shock protein (HSP) 70 was also observed along with an indication of a viral infection and decreased ability to synthesise protein. A down-regulation of purine and pyrimidine metabolism indicated reduction in physiological activities of the competing sponges. Moreover, a putative case of possible kleptocnidism, not previously reported in Cinachyrella cf. cavernosa was also observed. This study opens the door for more detailed investigations of marine organisms competing for spatial resources using transcriptome data.

ecology↗

bioRxiv2021

Loose ends in cancer genome structure

Recent pan-cancer studies have delineated patterns of structural genomic variation across thousands of tumor whole genome sequences. It is not known to what extent the shortcomings of short read ([≤] 150 bp) whole genome sequencing (WGS) used for structural variant analysis has limited our understanding of cancer genome structure. To formally address this, we introduce the concept of "loose ends" - copy number alterations that cannot be mapped to a rearrangement by WGS but can be indirectly detected through the analysis of junction-balanced genome graphs. Analyzing 2,319 pan-cancer WGS cases across 31 tumor types, we found loose ends were enriched in reference repeats and fusions of the mappable genome to repetitive or foreign sequences. Among these we found genomic footprints of neotelomeres, which were surprisingly enriched in cancers with low telomerase expression and alternate lengthening of telomeres phenotype. Our results also provide a rigorous upper bound on the role of non-allelic homologous recombination (NAHR) in large-scale cancer structural variation, while nominating INO80, FANCA, and ARID1A as positive modulators of somatic NAHR. Taken together, we estimate that short read WGS maps >97% of all large-scale (>10 kbp) cancer structural variation; the rest represent loose ends that require long molecule profiling to unambiguously resolve. Our results have broad relevance for future research and clinical applications of short read WGS and delineate precise directions where long molecule studies might provide transformative insight into cancer genome structure.

genomics↗

bioRxiv2021

Epitope classification and RBD binding properties of neutralizing antibodies against SARS-CoV-2 variants of concern

Severe acute respiratory syndrome coronavirus-2 (SAR-CoV-2) causes coronavirus disease 2019 (COVID19) that is responsible for short and long-term disease, as well as death, in susceptible hosts. The receptor binding domain (RBD) of the SARS-CoV-2 Spike (S) protein binds to cell surface angiotensin converting enzyme type-II (ACE2) to initiate viral attachment and ultimately viral pathogenesis. The SARS-CoV-2 S RBD is a major target of neutralizing antibodies (NAbs) that block RBD - ACE2 interactions. In this report, NAb-RBD binding epitopes in the protein databank were classified as C1, C1D, C2, C3, or C4, using a RBD binding profile (BP), based on NAb-specific RBD buried surface area and used to predict the binding epitopes of a series of uncharacterized NAbs. Naturally occurring SARS-CoV-2 RBD sequence variation was also quantified to predict NAb binding sensitivities to the RBD-variants. NAb and ACE2 binding studies confirmed the NAb classifications and determined whether the RBD variants enhanced ACE2 binding to promote viral infectivity, and/or disrupted NAb binding to evade the host immune response. Of 9 single RBD mutants evaluated, K417T, E484K, and N501Y disrupted binding of 65% of the NAbs evaluated, consistent with the assignment of the SARS-CoV-2 P.1 Japan/Brazil strain as a variant of concern (VoC). RBD variants E484K and N501Y exhibited ACE2 binding equivalent to a Wuhan-1 reference SARS-CoV-2 RBD. While slightly less disruptive to NAb binding, L452R enhanced ACE2 binding affinity. Thus, the L452R mutant, associated with the SARS-CoV-2 California VoC (B.1.427/B.1.429-California), has evolved to enhance ACE2 binding, while simultaneously disrupting C1 and C2 NAb classes. The analysis also identified a non-overlapping antibody pair (1213H7 and 1215D1) that bound to all SARS-CoV-2 RBD variants evaluated, representing an excellent therapeutic option for treatment of SARS-CoV-2 WT and VoC strains.

immunology↗

bioRxiv2021

HIV-1 uncoating occurs via a series of rapid biomechanical changes in the core related to individual stages of reverse transcription

The HIV core consists of the viral genome and associated proteins encased by a cone-shaped protein shell termed the capsid. Successful infection requires reverse transcription of the viral genome and disassembly of the capsid shell within a cell in a process known as uncoating. The integrity of the viral capsid is critical for reverse transcription, yet the viral capsid must be breached to release the nascent viral DNA prior to integration. We employed atomic force microscopy to study the stiffness changes in HIV-1 cores during reverse transcription in vitro in reactions containing the capsid-stabilizing host metabolite IP6. Cores exhibited a series of stiffness spikes, with up to three spikes typically occurring between 10-30, 40-80, and 120-160 minutes after initiation of reverse transcription. Addition of the reverse transcriptase (RT) inhibitor efavirenz eliminated the appearance of these spikes and the subsequent disassembly of the capsid, thus establishing that both result from reverse transcription. Using timed addition of efavirenz, and analysis of an RNAseH-defective RT mutant, we established that the first stiffness spike requires minus-strand strong stop DNA synthesis, with subsequent spikes requiring later stages of reverse transcription. Additional rapid AFM imaging experiments revealed repeated morphological changes in cores that were temporally correlated with the observed stiffness spikes. Our study reveals discrete mechanical changes in the viral core that are likely related to specific stages of reverse transcription. Our results suggest that reverse-transcription-induced changes in the capsid progressively remodel the viral core to prime it for temporally accurate uncoating in target cells.

biophysics↗

bioRxiv2020

RNF5 Regulation of RBBP4 Defines Acute Myeloid Leukemia Growth and Susceptibility to Histone Deacetylase Inhibitors

Acute myeloid leukemia (AML) remains incurable, largely due to its resistance to conventional treatments. Here, we found that increased expression and abundance of the ubiquitin ligase RNF5 contributes to AML development and survival. High RNF5 expression in AML patients correlated with poor prognosis. RNF5 inhibition decreased AML cell growth in culture and in vivo, and blocked development of MLL-AF9-driven leukemogenesis in mice, prolonging their survival. RNF5 inhibition led to transcriptional changes that overlapped with those seen upon HDAC1 inhibition. RNF5 induced the formation of K29 ubiquitin chains on the histone-binding protein RBBP4, promoting its recruitment and subsequent epigenetic regulation of genes involved in AML development and maintenance. Correspondingly, RNF5 or RBBP4 knockdown enhanced the sensitivity of AML cells to histone deacetylase (HDAC) inhibitors. Notably, low expression of RNF5 and HDAC coincided with a favorable prognosis. Our studies identified ERAD-independent role for RNF5, demonstrating that its control of RBBP4 constitutes an epigenetic pathway that drives AML while highlighting RNF5/RBBP4 as markers to stratify patients for treatment with HDAC inhibitors.

cancer biology↗

bioRxiv2020

Therapeutic activity of an inhaled potent SARS-CoV-2 neutralizing human monoclonal antibody in hamsters

SARS-CoV-2 infection results in viral burden in the upper and lower respiratory tract, enabling transmission and often leading to substantial lung pathology. Delivering the antiviral treatment directly to the lungs has the potential to improve lung bioavailability and dosing efficiency. As the SARS-CoV-2 Receptor Binding Domain (RBD) of the Spike (S) is increasingly deemed to be a clinically validated target, RBD-specific B cells were isolated from patients following SARS-CoV-2 infection to derive a panel of fully human monoclonal antibodies (hmAbs) that potently neutralize SARS-CoV-2. The most potent hmAb, 1212C2 was derived from an IgM memory B cell, has high affinity for SARS-CoV-2 RBD which enables its direct inhibition of RBD binding to ACE2. The 1212C2 hmAb exhibits in vivo prophylactic and therapeutic activity against SARS-CoV-2 in hamsters when delivered intraperitoneally, achieving a meaningful reduction in upper and lower respiratory viral burden and lung pathology. Furthermore, liquid nebulized inhale treatment of SARS-CoV-2 infected hamsters with as low as 0.6 mg/kg of inhaled dose, corresponding to approximately 0.03 mg/kg of lung deposited dose, mediated a reduction in respiratory viral burden that is below the detection limit, and mitigated lung pathology. The therapeutic efficacy achieved at an exceedingly low-dose of inhaled 1212C2 supports the rationale for local lung delivery and achieving dose-sparing benefits as compared to the conventional parenteral route of administration. Taken together, these results warrant an accelerated clinical development of 1212C2 hmAb formulated and delivered via inhalation for the prevention and treatment of SARS-CoV-2 infection.

immunology↗

bioRxiv2020

A JAK/STAT-Mediated Inflammatory Signaling Cascade Drives Oncogenesis In AF10-Rearranged AML

Leukemias bearing fusions of the AF10/MLLT10 gene are associated with poor prognosis, and therapies targeting these fusion proteins are lacking. To understand mechanisms underlying AF10 fusion-mediated leukemogenesis, we generated inducible mouse models of AML driven by the most common AF10 fusion proteins, PICALM/CALM-AF10 and KMT2A/MLL-AF10, and performed comprehensive characterization of the disease using transcriptomic, epigenomic, proteomic, and functional genomic approaches. Our studies provide a comprehensive map of gene networks and protein interactors associated with key AF10 fusions involved in leukemia. Specifically, we report that AF10 fusions activate a cascade of JAK/STAT-mediated inflammatory signaling through direct recruitment of JAK1 kinase. Inhibition of the JAK/STAT signaling by genetic Jak1 deletion or through pharmacological JAK/STAT inhibition elicited potent anti-oncogenic effects in mouse and human models of AF10 fusion AML. Collectively, our study identifies JAK1 as a tractable therapeutic target in AF10-rearranged leukemias. STATEMENT OF SIGNIFICANCEGene fusions of AF10/MLLT10 are recurrent in acute myeloid and lymphoid leukemia and are associated with extremely poor survival outcomes. We show that the JAK1 kinase is required for activation of the AF10 fusion oncotranscriptome and for leukemogenesis. Since a number of JAK/STAT pathways inhibitors are in clinical development or approved for use, our studies may help develop a therapeutic strategy for AF10-rearranged leukemias.

cancer biology↗

bioRxiv2020

Comparative analysis of genome-wide DNA methylation identifies patterns that associate with conserved transcriptional programs in osteosarcoma.

Osteosarcoma is an aggressive tumor of the bone that primarily affects young adults and adolescents. Osteosarcoma is characterized by genomic chaos and heterogeneity. While inactivation of tumor suppressor p53 TP53 is nearly universal other high frequency mutations or structural variations have not been identified. Despite this genomic heterogeneity, key conserved transcriptional programs associated with survival have been identified across human, canine and induced murine osteosarcoma. The epigenomic landscape, including DNA methylation, plays a key role in establishing transcriptional programs in all cell types. The role of epigenetic dysregulation has been studied in a variety of cancers but has yet to be explored at scale in osteosarcoma. Here we examined genome-wide DNA methylation patterns in 24 human and 44 canine osteosarcoma samples identifying groups of highly correlated DNA methylation marks in human and canine osteosarcoma samples. We also link specific DNA methylation patterns to key transcriptional programs in both human and canine osteosarcoma. Building on previous work, we built a DNA methylation-based measure for the presence and abundance of various immune cell types in osteosarcoma. Finally, we determined that the underlying state of the tumor, and not changes in cell composition, were the main driver of differences in DNA methylation across the human and canine samples. SignificanceThis is the first large scale study of DNA methylation in osteosarcoma and lays the ground work for the exploration of DNA methylation programs that help establish conserved transcriptional programs in the context of different genomic landscapes.

cancer biology↗

bioRxiv2020

Chromosomal Resistance to Metronidazole in Clostridioides difficile can be Mediated By Epistasis Between Iron Homeostasis and Oxidoreductases

Chromosomal resistance to metronidazole has emerged in clinical Clostridioides difficile, but the genetic mechanisms remain unclear. This is further hindered by the inability to generate spontaneous metronidazole-resistant mutants in the lab to aid genetic studies. We therefore constructed a mismatch repair mutator, in non-toxigenic ATCC 700057, to unbiasedly survey the mutational landscape for de novo resistance mechanisms. In separate experimental evolutions, the mutator adopted a deterministic path to resistance, with truncation of ferrous iron transporter FeoB1 as a first-step mechanism of low level resistance. Allelic deletion of feoB1 in ATCC 700057 reduced intracellular iron content, appearing to shift cells toward flavodoxin-mediated oxidoreductase reactions, which are less favorable for metronidazoles cellular action. Higher level resistance evolved from sequential acquisition of mutations to catalytic domains of pyruvate-ferredoxin oxidoreductase (PFOR encoded by nifJ); a synonymous codon change to xdhA1 (xanthine dehydrogenase subunit A), likely affecting its translation; and lastly, frameshift and point mutations that inactivated the iron-sulfur cluster regulator (IscR). Gene silencing of nifJ, xdhA1 or iscR with catalytically dead Cas9 revealed that resistance involving these genes only occurred when feoB1 was inactivated i.e. resistance was only seen in an feoB1-deletion mutant and not the isogenic wild-type parent. These findings show that metronidazole resistance in C. difficile is complex, involving multi-genetic mechanisms that could intersect with iron-dependent metabolic pathways.

microbiology↗

bioRxiv2019

The Dynamic Landscape of Transcription Initiation in Yeast Mitochondria

Controlling efficiency and fidelity in the early stage of mitochondrial DNA transcription is crucial for regulating cellular energy metabolism. Studies of bacteriophage and bacterial systems have revealed that transcription occurs through a series of conformational transitions during the initiation and elongation stages; however, how the conformational dynamics progress throughout these stages remains unknown. Here, we used single-molecule fluorescence resonance energy transfer techniques to examine the conformational dynamics of the two-component transcription system of yeast mitochondria with single-base resolution. We show that, unlike its single-component homologue in bacteriophages, the yeast mitochondrial transcription initiation complex dynamically transitions between closed, open, and scrunched conformations throughout the initiation stage, and then makes a sharp irreversible transition to an unbent conformation by promoter release at position +8. Remarkably, stalling the initiation complex revealed unscrunching dynamics without dissociating the RNA transcript, manifesting the existence of backtracking transitions with possible regulatory roles. The dynamic landscape of transcription initiation revealed here suggests a kinetically driven regulation of mitochondrial transcription.

biophysics↗

bioRxiv2019

Novel patterns of complex structural variation revealed across thousands of cancer genome graphs

Cancer genomes often harbor hundreds of somatic DNA rearrangement junctions, many of which cannot be easily classified into simple (e.g. deletion, translocation) or complex (e.g. chromothripsis, chromoplexy) structural variant classes. Applying a novel genome graph computational paradigm to analyze the topology of junction copy number (JCN) across 2,833 tumor whole genome sequences (WGS), we introduce three complex rearrangement phenomena: pyrgo, rigma, and tyfonas. Pyrgo are "towers" of low-JCN duplications associated with early replicating regions and superenhancers, and are enriched in breast and ovarian cancers. Rigma comprise "chasms" of low-JCN deletions at late-replicating fragile sites in esophageal and other gastrointestinal (GI) adenocarcinomas. Tyfonas are "typhoons" of high-JCN junctions and fold back inversions that are enriched in acral but not cutaneous melanoma and associated with a previously uncharacterized mutational process of non-APOBEC kataegis. Clustering of tumors according to genome graph-derived features identifies subgroups associated with DNA repair defects and poor prognosis.

genomics↗

bioRxiv2019

PopInf: An approach for reproducibly visualizing and assigning population affiliation in genomic samples of uncertain origin

Germline genetic variation contributes to cancer etiology, but self-reported race is not always consistent with genetic ancestry, and samples may not have identifying ancestry information. Here we describe a flexible computational pipeline, PopInf, to visualize principal components analysis output and assign ancestry to samples with unknown genetic ancestry, given a reference population panel of known origins. PopInf is implemented as a reproducible workflow in Snakemake with a tutorial on GitHub. We provide a pre-processed reference population panel that can be quickly and efficiently implemented in cancer genetics studies. We ran PopInf on TCGA liver cancer data and identify discrepancies between reported race and inferred genetic ancestry.\n\nSignificanceThe PopInf pipeline facilitates visualization and identification of genetic ancestry across samples, so that this ancestry can be accounted for in studies of disease risk. All code and a tutorial are available on Github: https://github.com/SexChrLab/PopInf.

genomics↗

bioRxiv2019

Phylogenetic Tree-based Pipeline for Uncovering Mutational Patterns during Influenza Virus Evolution

Various computational and statistical approaches have been proposed to uncover the mutational patterns of rapidly evolving influenza viral genes. Nonetheless, the approaches mainly rely on sequence alignments which could potentially lead to spurious mutations obtained by comparing sequences from different clades that coexist during particular periods of time. To address this issue, we propose a phylogenetic tree-based pipeline that takes into account the evolutionary structure in the sequence data. Assuming that the sequences evolve progressively under a strict molecular clock, considering a competitive model that is based on a certain Markov model, and using a resampling approach to obtain robust estimates, we could capture statistically significant single-mutations and co-mutations during the sequence evolution. Moreover, by considering the results obtained from analyses that consider all paths and the longest path in the resampled trees, we can categorize the mutational sites and suggest their relevance. Here we applied the pipeline to investigate the 50 years of evolution of the HA sequences of influenza A/H3N2 viruses. In addition to confirming previous knowledge on the A/H3N2 HA evolution, we also demonstrate the use of the pipeline to classify mutational sites according to whether they are able to enhance antigenic drift, compensate other mutations that enhance antigenic drift, or both.

evolutionary biology↗

bioRxiv2019

Network Inference with Granger Causality Ensembles on Single-Cell Transcriptomic Data

Advances in single-cell transcriptomics enable measuring the gene expression of individual cells, allowing cells to be ordered by their state in a dynamic biological process. Many algorithms assign pseudotimes to each cell, representing the progress along the biological process. Ordering the expression data according to such pseudotimes can be valuable for understanding the underlying regulator-gene interactions in a biological process, such as differentiation. However, the distribution of cells sampled along a transitional process, and hence that of the pseudotimes assigned to them, is not uniform. This prevents using many standard mathematical methods for analyzing the ordered gene expression states. We present Single-cell Inference of Networks using Granger Ensembles (SINGE), an algorithm for gene regulatory network inference from single-cell gene expression data. Given ordered single-cell data, SINGE uses kernel-based Granger Causality regression, which smooths the irregular pseudotimes and missing expression values. It then aggregates the predictions from an ensemble of regression analyses with a modified Borda count to compile a ranked list of candidate interactions between transcriptional regulators and their target genes. In two mouse embryonic stem cell differentiation case studies, SINGE outperforms other contemporary algorithms for gene network reconstruction. However, a more detailed examination reveals caveats about transcriptional network reconstruction with single-cell RNA-seq data. Network inference methods, including SINGE, may have near random performance for predicting the targets of many individual regulators even if the overall performance is good. In addition, including uninformative pseudotime values can hurt the performance of network reconstruction methods. A MATLAB implementation of SINGE is available at https://github.com/gitter-lab/SINGE.

bioinformatics↗

bioRxiv2019

Acute Myeloid Leukemia Driven by the CALM-AF10 Fusion Gene is Dependent on BMI1

A subset of acute myeloid and lymphoid leukemia cases harbor a t(10;11)(p13;q14) translocation resulting in the CALM-AF10 fusion gene. Standard chemotherapeutic strategies are often ineffective in treating patients with CALM-AF10 fusions. Hence, there is an urgent need to identify molecular pathways dysregulated in CALM-AF10-positive leukemias which may lay the foundation for novel targeted therapies. Here we demonstrate that the Polycomb Repressive Complex 1 gene BMI1 is consistently overexpressed in adult and pediatric CALM-AF10-positive leukemias. We demonstrate that genetic Bmi1 depletion abrogates CALM-AF10-mediated transformation of murine hematopoietic stem and progenitor cells (HSPCs). Furthermore, CALM-AF10-positive murine and human AML cells are profoundly sensitive to the small-molecule BMI1 inhibitor PTC209 as well as to PTC596, a compound in clinical development that has been shown to result in downstream degradation of BMI1 protein. PTC-596 significantly prolongs survival of mice injected with a human CALM-AF10 cell line in a xenograft assay. In summary, these results validate BMI1 as a bonafide candidate for therapeutic targeting in AML with CALM-AF10 rearrangements.

cancer biology↗