Biology subjects

Kennedy, V. E.

Publications and source records attributed to Kennedy, V. E..

4 recordsLinked to original sources

bioRxiv2025

RAS pathway activation drives clonal selection and monocytic differentiation in FLT3 and BCL2 inhibitor resistance

Despite efficacy of FLT3 and BCL2 inhibition in acute myeloid leukemia (AML), relapse limits survival. Mutation status and AML monocytic differentiation are implicated in resistance. On-treatment tumor evolution may select for genetically distinct clones or shifts in differentiation not resolvable by bulk sequencing. We performed multiomic single cell (SC) DNA/protein and RNA/protein profiling of patients treated on a clinical trial of the BCL2 inhibitor venetoclax and the FLT3 inhibitor gilteritinib (Ven/Git) to characterize immunophenotypic, transcriptional, and genetic clonal evolution on therapy. We found that while Ven/Gilt effectively eliminated FLT3 mutant clones, it selected for RAS mutations, RAS pathway activation and RAS-associated monocytic differentiation. In an in vitro model of monocytic differentiation associated with heightened RAS pathway activation, we demonstrated that MEK inhibition re-sensitized to Ven/Gilt. These data indicate RAS signaling is central to FLT3 and BCL2 inhibitor resistance, is tightly coupled to monocytic differentiation and can be overcome by RAS pathway inhibition. COIC.C.S. has provided educational talks for Astellas Pharma, served on advisory boards for Genentech/Abbvie and received research funding from Abbvie. B.C., Y.S. and J.H. are employees of Abbvie. M.S. and H.H. are or were previously employees of Genentech. FundingThis work was supported in part by Abbvie. C.C.S. is a Leukemia & Lymphoma Society Scholar in Clinical Research and a Damon Runyon-Richard Lumsden Foundation Clinical Investigator supported (in part) by the Damon Runyon Cancer Research Foundation (CI-99-18). Statement of SignificanceMutational and non-mutational RAS signaling activation drives clonal selection, monocytic differentiation and treatment resistance to FLT3 and BCL2 inhibition in AML. MEK inhibition can resensitize resistant AML cells, suggesting therapeutic potential for combined FLT3, BCL2 and RAS pathway inhibition in AML.

cancer biology↗

bioRxiv2024

Single Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting (SNACS): A tool for demultiplexing single-cell DNA sequencing data

MotivationRecently, single-cell DNA sequencing (scDNA-seq) and multi-modal profiling with the addition of cell-surface antibodies (scDAb-seq) have provided key insights into cancer heterogeneity. Scaling these technologies across large patient cohorts, however, is cost and time prohibitive. Multiplexing, in which cells from unique patients are pooled into a single experiment, offers a possible solution. While multiplexing methods exist for scRNAseq, accurate demultiplexing in scDNAseq remains an unmet need. ResultsHere, we introduce SNACS: Single-Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting. SNACS relies on a combination of patient-level cell-surface identifiers and natural variation in genetic polymorphisms to demultiplex scDNAseq data. We demonstrated the performance of SNACS on a dataset consisting of multi-sample experiments from patients with leukemia where we knew truth from single-sample experiments from the same patients. Using SNACS, accuracy ranged from 0.948 - 0.991 vs 0.552 - 0.934 using demultiplexing methods from the single-cell literature. Availability ImplementationSNACS is available at https://github.com/olshena/SNACS. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=83 SRC="FIGDIR/small/579345v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1e52aaorg.highwire.dtl.DTLVardef@c51d1dorg.highwire.dtl.DTLVardef@fa68a6org.highwire.dtl.DTLVardef@1ec6bd1_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Multiomic Single Cell Sequencing Identifies Stemlike Nature of Mixed Phenotype Acute Leukemia and Provides Novel Risk Stratification

Mixed phenotype acute leukemia (MPAL) is a leukemia whose biologic drivers are poorly understood, therapeutic strategy remains unclear, and prognosis is poor. We performed multiomic single cell (SC) profiling of 14 newly diagnosed adult MPAL patients to characterize the immunophenotypic, genetic, and transcriptional landscapes of MPAL. We show that neither genetic profile nor transcriptome reliably correlate with specific MPAL immunophenotypes. However, progressive acquisition of mutations is associated with increased expression of immunophenotypic markers of immaturity. Using SC transcriptional profiling, we find that MPAL blasts express a stem cell-like transcriptional profile distinct from other acute leukemias and indicative of high differentiation potential. Further, patients with the highest differentiation potential demonstrated inferior survival in our dataset. A gene set score, MPAL95, derived from genes highly enriched in this cohort, is applicable to bulk RNA sequencing data and was predictive of survival in an independent patient cohort, suggesting utility for clinical risk stratification.

cancer biology↗

bioRxiv2022

Microfluidics-free single-cell genomics with templated emulsification

Single-cell RNA sequencing is now a standard method used to reveal the molecular details of cellular heterogeneity, but current approaches have limitations on speed, scale, and ease of use that stem from the complex microfluidic devices or fluid handling steps required for sample processing. We, therefore, developed a method that does not require specialized microfluidic devices, expertise, or hardware. Our approach is based on particle-templated emulsification, which allows single-cell encapsulation and barcoding of cDNA in uniform droplet emulsions with only a vortexer. PIP-seq accommodates a wide range of emulsification formats, including microwell plates and large-volume conical tubes, enabling thousands of samples or millions of cells to be processed in minutes. We demonstrate that PIP-seq produces high-purity transcriptomes in mouse-human mixing studies, is compatible with multi-omics measurements, and can accurately characterize cell types in human breast tissue when compared to a commercial microfluidic platform. Single-cell transcriptional profiling of mixed phenotype acute leukemia using PIP-seq revealed the emergence of heterogeneity within chemotherapy-resistant cell subsets that were hidden by standard immunophenotyping. PIP-seq is a simple, flexible, and scalable next-generation workflow that extends single-cell sequencing to new applications, including screening, diagnostics, and disease monitoring.

genomics↗