Biology subjects

Rodriguez-Fraticelli, A. E.

Publications and source records attributed to Rodriguez-Fraticelli, A. E..

3 recordsLinked to original sources

bioRxiv2026

Leukemia stem cell expansion cultures reveal clonal drivers of leukemogenesis and therapy response

Leukemia stem cells (LSCs) contain the highest capacity for leukemia-reinitiation and therapy-resistance across all leukemic cells, but our understanding of their molecular and cellular properties remains limited due to their relative rarity and ineffective cell culture systems to maintain their purity at scale. Here, we develop Polymer-based Leukemic STem-cell Cultures (PLSTCs) and demonstrate their capacity to derive and propagate large numbers of Npm1cA/Flt3ITD acute myeloid leukemia (AML) stem cells at high purities. Compared to traditional cultures, PLSTCs show more than 1000-fold enrichment in functional LSCs based on single-cell gene expression signatures and leukemia-initiating assays. Tracing LSC clones with genomic LARRY barcodes during ex vivo expansion, we reveal that PLSTCs can sustain a diversity of self-renewing LSC states with stable, heritable transcriptional programs. Using dynamic state-fate analysis, we characterize clonal programs that are linked with enhanced ex vivo self-renewal, in vivo leukemia initiation, and therapeutic response to induction chemotherapy. LSC clones primed to resist treatment were enriched for a rare cell state that underwent a fate-switch and produced megakaryocytic-erythroid-like leukemic cells that expanded in the spleen. Targeting LSC programs through pooled CRISPR and single-cell sequencing (CROPseq) in PLSTCs, we reveal that chondroitin-sulfate synthesis is required to maintain a primitive LSC state and leukemic recovery from chemotherapy. In sum, our studies showcase the powerful application of scalable leukemic stem-cell expansion cultures and dynamic state-fate analysis of AML LSCs. We anticipate these systems will accelerate our understanding and interception of stem cell plasticity in cancer.

cancer biology↗

bioRxiv2024

Pre-existing stem cell heterogeneity dictates clonal responses to acquisition of cancer driver mutations

Cancer cells display wide phenotypic variation even across patients with the same mutations. Differences in the cell of origin provide a potential explanation, but these assays have traditionally relied on surface markers, lacking the clonal resolution to distinguish heterogeneous subsets of stem and progenitor cells. To address this challenge, we developed STRACK, an unbiased framework to longitudinally trace clonal gene expression and expansion dynamics before and after acquisition of cancer mutations. We studied two different leukemia driver mutations, Dnmt3a-R882H and Npm1cA, and found that the response to both mutations was highly variable across different stem cell states. Specifically, a subset of differentiation-biased stem cells, which normally become outcompeted with time, can efficiently expand with both mutations. Npm1c mutations surprisingly reversed the intrinsic bias of the clone-of-origin, with stem-biased clones giving rise to more mature malignant states. We propose a clonal "reaction norm", in which pre-existing clonal states dictate different cancer phenotypic potential. Highlights- Single cell tracing of cancer initiation at the clonal level (STRACK). - Ex vivo expansion cultures sustain intrinsic and heritable HSC heterogeneity. - Premalignant mutations enhance the self-renewal of high-output stem cells, increasing their survival probability. - Transforming mutations reprogram low-output stem cell fates to more mature malignant states.

cancer biology↗

bioRxiv2018

Lineage tracing on transcriptional landscapes links state to fate during differentiation

A challenge in stem cell biology is to associate molecular differences among progenitor cells with their capacity to generate mature cell types. Though the development of single cell assays allows for the capture of progenitor cell states in great detail, these assays cannot definitively link cell states to their long-term fate. Here, we use expressed DNA barcodes to clonally trace single cell transcriptomes dynamically during differentiation and apply this approach to the study of hematopoiesis. Our analysis identifies functional boundaries of cell potential early in the hematopoietic hierarchy and locates them on a continuous transcriptional landscape. We reconstruct a developmental hierarchy showing separate ontogenies for granulocytic subtypes and two routes to monocyte differentiation that leave a persistent imprint on mature cells. Finally, we use our approach to benchmark methods of dynamic inference from single-cell snapshots, and provide evidence of strong early fate biases dependent on cellular properties hidden from single-cell RNA sequencing.

systems biology↗