Biology subjects

Carroll, M. P.

Publications and source records attributed to Carroll, M. P..

7 recordsLinked to original sources

bioRxiv2026

Limits of marker information transfer]{Limits of marker information transfer in cross-panel cytometry imputation

Marker imputation can bridge cytometry datasets acquired with different panels and platforms. Its validity depends on whether common markers retain information about unmeasured target markers and whether those relationships transfer across assay contexts. We evaluated these limits in two paired flow cytometry-CyTOF cohorts comprising 134 patients and 257 specimens. A patient-held-out framework distinguished within-platform same-cell reconstruction from cross-platform distribution translation without cell correspondence. We compared conventional machine-learning and deep generative estimators with median imputation and used permutation controls to estimate the contributions of patient matching and source-exclusive markers. Evaluation covered marker values, specimen distributions, phenotype utility, and directional predictive relationships among markers. Within platforms, exact k-nearest neighbors reduced mean absolute error by 12.8-35.0% relative to median imputation. However, the median-based reconstructions were contracted, with a median ratio of predicted to observed interquartile range below 1 in every context and evaluable population. Patient matching improved cross-platform distribution recovery, whereas adding source-exclusive markers or higher-capacity estimators did not consistently produce net gains. In the independently annotated acute myeloid leukemia (AML) cohort, reconstructed markers largely preserved broad-lineage classification but did not recover fine-phenotype information available through direct measurement. In AML-CyTOF, the measured full panel outperformed the reconstructed representation by 10.25 percentage points for fine phenotypes. Predictive relationships among markers were context-specific. Most targets were better explained by several markers than by one. Marker selection based on these relationships showed a trade-off between panel size and pairwise coverage. Paired samples and imputation can therefore connect selected marker distributions across panels but should not be treated as substitutes for direct measurement. Cross-panel cytometry should be evaluated with patient-held-out tests matched to the resolution of available ground truth and the intended downstream use.

bioinformatics↗

bioRxiv2025

CCAAT-enhancer binding protein delta functions as a tumor suppressor gene in acute myeloid leukemia

There is a continued need for identification of novel disease drivers of acute myeloid leukemia as many patients experience relapse and have poor clinical outcomes. Analyses from our study and publicly available datasets predicted CEBPD as a novel tumor suppressor gene in acute myeloid leukemia. Consistent with the analyses, CEBPD knockdown experiments showed activation of MAPK signaling with concomitant increase in cell growth rate, while upregulation experiments suggested induction of myeloid differentiation marker CD14 expression in AML cell lines OCI-AML2 and OCI-AML5. Consistent with a previous report, our genomics analyses and azacytidine treatment experiments suggested a role for DNA methylation in downregulation of CEBPD expression during AML pathogenesis. Altogether, our results provide experimental evidence for a tumor suppressor function of CEBPD in AML.

cancer biology↗

bioRxiv2023

Targeting mitophagy in SRSF2 mutant hematologic malignancies

Splicing factor mutations are common in myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML), but how they alter cellular functions is unclear. We show that the pathogenic SRSF2P95H/+ mutation disrupts the splicing of mitochondrial mRNAs, impairs mitochondrial complex I function, and robustly increases mitophagy. We also identified a mitochondrial surveillance mechanism by which mitochondrial dysfunction modifies splicing of the mitophagy activator PINK1 to remove a poison intron, increasing the stability and abundance of PINK1 mRNA and protein. SRSF2P95H-induced mitochondrial dysfunction increased PINK1 expression through this mechanism, which is essential for survival of SRSF2P95H/+ cells. Inhibition of splicing with a glycogen synthase kinase 3 inhibitor promoted retention of the poison intron, impairing mitophagy and activating apoptosis in SRSF2P95H/+ cells. These data reveal a homeostatic mechanism for sensing mitochondrial stress through PINK1 splicing and identify increased mitophagy as a disease marker and a therapeutic vulnerability in SRSF2P95H mutant MDS and AML.

cancer biology↗

bioRxiv2023

Clonal evolution mediates Menin-inhibitor resistance in KMT2A-rearranged leukemias.

Inhibitors of the Menin-KMT2A interaction are promising agents for the treatment of KMT2A-rearranged (KMT2A-r) leukemias. We evaluated Menin inhibition in patient derived xenografts of KMT2A-r leukemias with high-risk features. Three AMLs with high-risk fusion partners (MLLT10, MLLT4) and two infant ALL samples were sensitive to Menin inhibition. We also evaluated serial samples from two patients with multiply relapsed ALL. We found that highly pretreated KMT2A-AFF1 ALL samples were much less sensitive compared to cells obtained earlier in the same patients disease course. Since none of the patients had been treated with a Menin inhibitor, resistance in these highly pretreated samples was acquired in the absence to Menin inhibitor exposure. Transcriptomic analysis documented sustained on-target efficacy towards the canonical targets in the Menin-inhibitor in resistant cells. Targeted genomic analysis documented the emergence of multiple co-mutations, including RAS pathway and TP53 mutations, although neither was sufficient to induce Menin-inhibitor resistance in vitro. Downregulation of KMT3D may account for resistance in one patients; inactivation of KMT2C/D had previously been reported to result in Menin inhibitor resistance. Future studies will need to clarify more broadly which genomic/epigenomic alterations drive upfront resistance. Regardless of mechanism, our data supports using Menin-inhibitors upfront or in early lines of therapy before substantial genomic or epigenomic evolution has occurred.

cancer biology↗

bioRxiv2022

Modeling clonal evolution and oncogenic dependency in vivo in the context of hematopoietic transformation

Cancer evolution is a multifaceted process involving the acquisition of somatic mutations and progressive epigenetic dysregulation of cellular fate. Both cell-intrinsic mechanisms and environmental interactions provide selective pressures capable of promoting clonal evolution and expansion, with single-cell and bulk DNA sequencing offering increased resolution into this process1-4. Advances in genome editing, single-cell biology and expressed lentiviral barcoding have enabled new insights into how transcriptional/epigenetic states change with clonal evolution5,6. Despite the extensive catalog of genomic alterations revealed by resequencing studies7,8, there remain limited means to functionally model and perturb this evolutionary process in experimental systems9. Here we integrated multi-recombinase (Cre, Flp, and Dre) tools for modeling reversible, sequential mutagenesis from premalignant clonal hematopoiesis to acute myeloid leukemia. We demonstrate that somatic acquisition of Flt3 activating mutations elicits distinct phases of acute and chronic activation resulting in differential cooperativity with Npm1 and Dnmt3a disease alleles. We next developed a generalizable allelic framework allowing for the reversible expression of oncogenic mutations at their endogenous loci. We found that reversal of mutant Flt3 resulted in rapid leukemic regression with distinct alterations in cellular compartments depending upon co-occurring mutations. These studies provide a path to model sequential mutagenesis and deterministically investigate mechanisms of transformation and oncogenic dependency in the context of clonal evolution.

cancer biology↗

bioRxiv2021

BCOR and BCORL1 mutations disrupt PRC1.1 repressive function in leukemia by unlinking the RING-PCGF1 enzymatic core from target genes

BCOR and its paralog BCORL1 encode subunits of the Polycomb repressive complex 1.1 (PRC1.1) and are recurrently mutated in myeloid malignancies. We show that leukemia-associated BCOR/BCORL1 mutations unlink the PRC1.1 RING-PCGF enzymatic core from the KDM2B-containing chromatin targeting auxiliary subcomplex, either by causing complete protein loss or expression of a C-terminally truncated protein lacking the PCGF Ub-like fold discriminator (PUFD) domain. By uncoupling PRC1.1 repressive function from target genes, BCOR/BCORL1 mutations activate aberrant cell signaling programs that confer acquired resistance to treatment. This study provides a mechanistic basis for Polycomb repressive dysfunction as a key oncogenic driver in myeloid malignancies and identifies a potential strategy for targeted therapy in BCOR-mutated cancer.

cancer biology↗

bioRxiv2020

Single cell mutational profiling delineates clonal trajectories in myeloid malignancies

Myeloid malignancies, including acute myeloid leukemia (AML), arise from the proliferation and expansion of hematopoietic stem and progenitor cells which acquire somatic mutations. Bulk molecular profiling studies on patient samples have suggested that somatic mutations are obtained in a step-wise fashion, where mutant genes with high variant allele frequencies (VAFs) are proposed to occur early in disease development and mutations with lower VAFs are thought to be acquired later in disease progression1-3. Although bulk sequencing informs leukemia biology and prognostication, it cannot distinguish which mutations occur in the same clone(s), accurately measure clonal complexity and clone size, or offer definitive evidence of mutational order. To elucidate the clonal framework of myeloid malignancies, we performed single cell mutational profiling on 146 samples from 123 patients. We found AML is most commonly comprised of a small number of dominant clones, which in many cases harbor co-occurring mutations in epigenetic regulators. Conversely, mutations in signaling genes often occur more than once in distinct subclones consistent with increasing clonal diversity. We also used these data to map the clonal trajectory of each patient and found that specific mutation combinations (FLT3-ITD + NPM1c) synergize to promote clonal expansion and dominance. We combined cell surface protein expression with single cell mutational analysis to map somatic genotype and clonal architecture with immunophenotype. Our studies of clonal architecture at a single cell level provide novel insights into the pathogenesis of myeloid transformation and how clonal complexity contributes to disease progression.

cancer biology↗