Biology subjects

Luskin, M. R.

Publications and source records attributed to Luskin, M. R..

5 recordsLinked to original sources

bioRxiv2025

Early persistence of recipient stem-cells and T-cell dysregulation are associated with relapse after transplant in AML/MDS

Hematopoietic stem cell transplantation (HSCT) offers the best curative option for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS), yet relapse remains common. Current relapse detection methods are often too late for effective intervention. To identify earlier predictors and therapeutic targets, we performed longitudinal single-cell RNA and T cell receptor (TCR) sequencing of bone marrow from 33 AML/MDS patients during post-transplant immune reconstitution, comparing those who relapsed to those who remained in remission. Persistence of recipient hematopoietic stem and progenitor cells (HSPCs) in the marrow was associated with relapse months later. These residual recipient HSPCs harbored copy number variations (CNVs), supporting their leukemic origin, and overexpressed PRAME and CALCRL compared to coexisting donor HSPCs. Further, in a subset of TP53-mutant disease, low TCR diversity with skewing toward dominant clonotypes foreshadowed relapse. These findings lay the groundwork for improved relapse prediction and nominate therapeutic targets for early post-transplant intervention.

cancer biology↗

bioRxiv2025

Dynamic BH3 profiling predicts clinical outcomes in acute myeloid leukemia

Predictive biomarkers can potentially meet the need for improved drug assignment in acute myeloid leukemia (AML). Fewer than half of AML patients have actionable mutations: consequently, targeted therapy achieves remission in only a fraction of those who have them. Dynamic BH3 Profiling (DBP), a functional assay, can measure changes in ex vivo drug-induced apoptotic priming in multiple cancers. To assess the feasibility and predictive capacity of DBP in AML, we prospectively tested DBP using a fixed-drug panel in myeloblasts from 92 patients. We generated a database combining genetic and functional annotation. Established AML clinical and genetic prognostic characteristics were associated with drug-induced apoptotic priming. We observed distinct interpatient sensitivities to single drugs or combinations with the BCL2-inhibitor venetoclax, and intrapatient apoptotic priming differences based on CD123-expression within distinct cell subpopulations. DBP further predicted the likelihood of remission to chemotherapy and targeted agents, supporting its use to identify optimal personalized therapy. Statement of significanceDynamic BH3 profiling provides patient-specific drug vulnerability data in real-time to inform prognosis and therapy selection. Key takeawaysO_LIDynamic BH3 profiling can be performed on bone marrow and leukemic blood from AML patients in 48 hours. C_LIO_LIKnown clinical prognostic factors associate with drug-induced apoptotic priming in AML. C_LIO_LIDrug-induced apoptotic priming identifies drug vulnerabilities in individual patients and predicts clinical response to chemotherapy and small molecule inhibitors. C_LI

cancer biology↗

bioRxiv2024

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease

Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples. HIGHLIGHTSO_LIRelapse after remission on TKI can harbor mutations in ABL1, RAS, or neither C_LIO_LIMutations and development-like cell state dictate fitness in residual disease C_LIO_LICo-targeting cell state and ABL1 markedly reduces MRD C_LIO_LIBiophysical measurements provide an integrative, rapid measurement of cell state C_LI

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

Reconstructing the lineage histories and differentiation trajectories of individual cancer cells in JAK2-mutant myeloproliferative neoplasms

Some cancers originate from a single mutation event in a single cell. For example, blood cancers known as myeloproliferative neoplasms (MPN) are thought to originate through the acquisition of a driver mutation (most commonly JAK2-V617F) in a hematopoietic stem cell (HSC). However, when the mutation first occurs in individual patients and how it impacts the behavior of HSCs in their native context is not known. Here we quantified the impact of the JAK2-V617F mutation on the proliferation dynamics of HSCs and the differentiation trajectories of their progenies in individual MPN patients. We reconstructed the lineage history of individual HSCs obtained from MPN patients using the patterns of spontaneous somatic mutations accrued in their genomes over time. Strikingly, we found that the JAK2-V617F mutation occurred in a single HSC several decades before MPN diagnosis -- at age 9{+/-}2 years in a 34-year-old patient, and at age 19{+/-}3 years in a 63-year-old patient. For each patient, we inferred the number of mutated HSCs over time and computed their fitness. The population of JAK2-mutated HSCs grew exponentially by 63{+/-}15% and 44{+/-}13% every year in the two patients, respectively. To contrast the differentiation trajectories of the JAK2-mutated HSCs with those of healthy HSCs, we simultaneously measured the full transcriptome and somatic mutations in single hematopoietic stem and progenitor cells (HSPCs). We found that the fraction of JAK2-mutant HSPCs varied significantly across different myeloid cell types within the same patient. The erythroid progenitor cells were often entirely JAK2-mutant, even when the peripheral blood JAK2-V617F allele burden was low. The novel biological insights uncovered by this work have implications for the prevention and treatment of MPN, as well as the accurate assessment of disease burden in patients. The technology platforms and computational frameworks developed here are broadly applicable to other types of hematological malignancies and cancers.

cancer biology↗