Biology subjects

Shaffer, S. M.

Publications and source records attributed to Shaffer, S. M..

16 recordsLinked to original sources

bioRxiv2026

SupeRJump: Determining normal and leukemic differentiation fate through semi-supervised jump diffusion modeling

Single cell RNA-seq (scRNA) has provided unprecedented resolution into cellular and clonal heterogeneity. Computational approaches have enabled recovery of differentiation dynamics, yet current approaches do not evaluate discontinuous differentiation processes present in malignant leukemia. To address these gaps, we developed SupeRJump: a jump-drift-diffusion based supervised cell-fate model (https://github.com/namwob44/SupeRJump/). We deploy this approach in human bone marrow, murine aging hematopoiesis, and lentivirally barcoded mouse models of acute myeloid leukemia. Our framework introduces a semi-supervised pseudotime strategy to fit a jump-drift-diffusion model and batch correction for lineage fate predictions from absorbing Markov chains. We introduce metrics to quantify a cells skewness toward particular lineages, transitions through intermediate progenitor states toward terminally differentiated states, and discontinuous transition dynamics. We use these metrics to identify cells preferentially biased for differentiation, their underlying transcriptional networks, and gene programs responsible for differentiation discontinuity.

bioinformatics↗

bioRxiv2026

Multiplexed enrichment and tracking of lineages with CloneSweeper

A fundamental challenge in studying therapy resistance is understanding whether it results from pre-existing cellular states ("priming") or drug-induced changes ("adaptation"). While lineage barcoding enables retrospective analysis of cells before and after treatment, current methods struggle to efficiently capture rare lineages in single-cell RNA sequencing (scRNA-seq) or isolate multiple specific lineages simultaneously for functional study. To overcome these limitations, we developed CloneSweeper, a multiplexed lineage tracking platform that pools enrichment libraries to isolate or enrich multiple rare lineages. CloneSweeper utilizes a dual-function barcode expressed as both a Cas9 gRNA for live-cell sorting and a 3 UTR transcript for high-recovery detection in 10x Genomics scRNA-seq. We applied CloneSweeper to a model of BRAF V600E melanoma, where we identified that resistance to targeted therapy emerges from a polyclonal population of rare, pre-existing lineages. By simultaneously targeting and enriching 21 distinct rare lineages prior to treatment, we defined a heritable, primed state characterized by de-differentiation and elevated mesenchymal markers. We demonstrate that these primed cells are not quiescent but instead exhibit upregulated inflammatory and stress response signaling, specifically via the AP-1 and NF-{kappa}B1 pathways. CloneSweeper thus provides a robust framework for dissecting the molecular mechanisms of rare biological phenomena through simultaneous, multiplexed lineage isolation.

bioengineering↗

bioRxiv2025

Gastric epithelium from BRCA1 and BRCA2 carriers harbors increased double-stranded DNA damage and augmented growth.

An accumulating body of evidence suggests carriers of a pathogenic germline variant (PGV) in BRCA1 or BRCA2 have increased gastric cancer (GC) risk. BRCA1 and BRCA2 are tumor suppressor genes involved in promoting homologous recombination to repair double-stranded DNA breaks. The aim of this investigation was to identify differences within the gastric epithelium and in patient-derived gastric organoids (PDGOs) between BRCA1 and BRCA2 carriers and non-carriers to determine if evidence of early gastric carcinogenesis exists amongst these carriers. First, using gastric epithelial biopsies, BRCA2 carriers were found to harbor higher expression of the proliferative marker Ki-67 within the antral gastric epithelium and strikingly, biopsies from both BRCA1 and BRCA2 carriers displayed a marked increase in double-stranded DNA damage. These results were further explored using PDGOs, where a growth advantage was observed for both BRCA1 and BRCA2 PDGOs compared to non-carrier PDGOs. Furthermore, both BRCA1 and BRCA2 PDGOs displayed a more pronounced enhancement of Ki-67 expression as well as increased double stranded DNA damage compared to non-carrier PDGOs. Importantly, none of the PDGOs showed signs of BRCA1 or BRCA2 loss of heterozygosity, potentially indicating a haploinsufficient phenotype. Taken together, these novel findings suggest that haploinsufficiency in BRCA1 and BRCA2 carriers may lead to DNA damage in the gastric epithelium, which may serve as an early event contributing to GC development.

cancer biology↗

bioRxiv2025

Deciphering Cell Fate and Clonal Dynamics via Integrative Single-Cell Lineage Modeling

Through natural or synthetic lineage barcodes, single-cell technologies now enable the joint measurement of molecular states and clonal identities, providing an unprecedented opportunity to study cell fate and dynamics. Yet, most computational methods for inferring cell development and differentiation rely exclusively on transcriptional similarity, overlooking the lineage information encoded by lineage barcodes. This limitation is exemplified by T cells, where subtle transcriptional differences mark divergent fates with distinct biological activity. Single-cell RNA and matched TCR sequencing is now ubiquitous in the analysis of clinical samples, where the TCR sequence provides an endogenous clonal barcode and could reveal clonal T cell responses. We present Clonotrace, a computational framework that jointly models gene expression and clonotype information to infer cell state transitions and fate biases with higher fidelity. While motivated by challenges in analyzing T cell populations, especially in the tumor microenvironment and immunotherapy settings, Clonotrace is broadly applicable to any lineage-barcoded single-cell dataset. Across diverse systems including T cells, hematopoietic differentiation, and cancer therapy resistance models, Clonotrace reveals differentiation hierarchies, distinguishes unipotent from multipotent states, and identifies candidate fate-determining genes driving lineage commitment.

bioinformatics↗

bioRxiv2025

Mitochondrial clone tracing within spatially intact human tissues

Understanding tissue development and intra-tissue evolution requires the ability to trace clones in intact tissues coupled with high-plex molecular profiling preserving spatial context. However, current lineage tracing tools are incompatible with spatial omics. Here, we present SUMMIT (Spatially Unveiling Mitochondrial Mutations In Tissues), a spatially-resolved lineage tracing technology that integrates gene expression profiling with mitochondrial mutation-based clone identification. Unlike synthetic lineage recording methods, SUMMIT relies only on endogenous mutations and thus can be applied to human tissues. To address the compositional mixing of cell types within spatial spots, SUMMIT includes a rigorous statistical framework to confidently assign variants to specific cell subpopulations and achieves high power for spatially localized clones by pooling information across neighboring spots. We validated SUMMIT using a controlled model in which we mixed two cancer cell lines in a mouse tumor, then demonstrated it on multiple human tissues including Barretts esophagus, gastric cardia, small bowel, and colorectal cancer. Across these samples, we distinguished between global mutations and mutations marking locally restricted clones. The coupled transcriptomic data allowed us to characterize the cell type composition within each clone and delineate their spatial configuration. This integrated approach provides a framework to understand spatially-defined clonal evolution in preserved human tissue.

genomics↗

bioRxiv2025

FOXM1 Modulation Alleviates Epithelial Remodeling and Inflammation in Eosinophilic Esophagitis

BackgroundEosinophilic esophagitis (EoE) is a chronic allergic disease characterized by esophageal epithelial remodeling, barrier dysfunction, and inflammation. Despite histologic remission, molecular and structural changes in the epithelium persist, contributing to ongoing symptoms and relapse. The transcription factor FOXM1 has been shown to be a key regulator of epithelial proliferation and inflammation in allergic asthma. ObjectiveTo investigate the role of FOXM1 in epithelial disruption in EoE and to evaluate the therapeutic potential of FOXM1 inhibition. DesignFOXM1 expression was analyzed in human esophageal biopsies, patient-derived organoids, and murine EoE models. IL-13 stimulation was used to model EoE in vitro. The effects of FOXM1 inhibition via the small molecule RCM-1 and siRNA-mediated knockdown were assessed by histology, gene expression profiling, organoid formation rates, and barrier integrity assays. RNA sequencing and chromatin immunoprecipitation were performed to elucidate molecular mechanisms. ResultsFOXM1 was significantly upregulated in patients with active EoE and localized to the basal epithelium. IL-13 increased FOXM1 expression, which impaired epithelial differentiation and enhanced basal cell hyperplasia. FOXM1 inhibition restored differentiation markers, reduced basal hyperplasia, and improved barrier function. In murine models, RCM-1 ameliorated epithelial changes and decreased eosinophil infiltration. Mechanistically, FOXM1 directly regulated cell cycle gene, CCNB1, which was upregulated in EoE and downregulated upon FOXM1 inhibition. FOXM1 expression was driven by an IL-13-PI3K/AKT axis. ConclusionFOXM1 plays a pivotal role in epithelial disruption in EoE by driving proliferation and impairing differentiation. Targeting FOXM1 restores epithelial homeostasis, mitigates inflammation, and offers a novel therapeutic approach for EoE. Key MessagesWhat is already known on this topic: Eosinophilic esophagitis is marked by epithelial remodeling and barrier dysfunction driven by Th2 inflammation. Despite remission, molecular and histologic changes in the esophageal epithelium persist, contributing to symptoms and relapse. The mechanisms underlying this epithelial dysregulation remain poorly understood. What this study adds: This study identifies FOXM1 as a key transcriptional regulator of epithelial disruption in EoE, demonstrating that FOXM1 inhibition restores epithelial differentiation, reduces basal cell hyperplasia, improves barrier integrity, and mitigates inflammation. How this study might affect research, practice, or policy: Targeting FOXM1 offers a novel therapeutic strategy to restore epithelial homeostasis and reduce inflammation in EoE. This dual approach, addressing both epithelial and immune dysregulation, may guide future therapeutic development and improve patient outcomes.

molecular biology↗

bioRxiv2025

The H3K36M oncohistone inhibits NSD2 to activate a SETD2-dependent antiviral-like immune response in KRAS-driven lung cancer

Mutations in histone 3 at or near lysine 36 (H3K36) have dominantly acting oncogenic effects in multiple tumor types by limiting H3K36-directed methyltransferases. Paradoxically, we find that expression of the H3K36M oncohistone unexpectedly inhibits tumor formation in KRAS-driven lung adenocarcinoma by inducing a potent immune-mediated tumor clearance. Mechanistically, oncohistone expression derepresses endogenous retroviral element transcription, results in the accumulation of double-stranded RNA (dsRNA), and activates an innate antiviral-like immune response that eradicates tumor growth. Surprisingly, while inactivation of the H3K36 di-methyltransferase NSD2 replicated all effects of oncohistone expression, inactivation of the H3K36 tri-methyltransferase SETD2 abolished element derepression and all associated downstream anti-cancer effects that are induced by oncohistone expression. These observations restructure our understanding of the roles of H3K36 methylation, the consequences of its deregulation in cancer, and shape our expectations for therapeutic interventions targeting H3K36 methyltransferases.

cancer biology↗

bioRxiv2023

Non-genetic differences underlie variability in proliferation among esophageal epithelial clones

The growth potential of individual epithelial cells is a key determinant of tissue development, homeostasis, and disease progression. Although it is known that epithelial progenitor cells vary in their proliferative capacity, the cell states underlying these differences are yet to be uncovered. Here we performed clonal tracing through imaging and cellular barcoding of an in vitro model of esophageal epithelial cells (EPC2-hTERT). We found that individual clones possess unique growth and differentiation capacities, with a subset of clones growing exponentially. Further, we discovered that this proliferative potential for a clone is heritable through cell division and can be influenced by extrinsic cues from neighboring cells. Combining barcoding with single-cell RNA-sequencing (scRNA-seq), we identified the cellular states associated with the highly proliferative clones, which include genes in the WNT and PI3K pathways. Importantly, we also identified a subset of cells resembling the highly proliferative cell state in the healthy human esophageal epithelium and, to a greater extent, in esophageal squamous cell carcinoma (ESCC). These findings highlight the physiological relevance of our cell line model, providing insights into the behavior of esophageal epithelial cells during homeostasis and disease.

systems biology↗

bioRxiv2023

Clonal differences underlie variable responses to sequential and prolonged treatment

Cancer cells exhibit dramatic differences in gene expression at the single-cell level which can predict whether they become resistant to treatment. Treatment perpetuates this heterogeneity, resulting in a diversity of cell states among resistant clones. However, it remains unclear whether these differences lead to distinct responses when another treatment is applied or the same treatment is continued. In this study, we combined single-cell RNA-sequencing with barcoding to track resistant clones through prolonged and sequential treatments. We found that cells within the same clone have similar gene expression states after multiple rounds of treatment. Moreover, we demonstrated that individual clones have distinct and differing fates, including growth, survival, or death, when subjected to a second treatment or when the first treatment is continued. By identifying gene expression states that predict clone survival, this work provides a foundation for selecting optimal therapies that target the most aggressive resistant clones within a tumor.

systems biology↗

bioRxiv2023

Clonal cell states link Barrett's esophagus and esophageal adenocarcinoma

Barretts esophagus is a common type of metaplasia and a precursor of esophageal adenocarcinoma. However, the cell states and lineage connections underlying the origin, maintenance, and progression of Barretts esophagus have not been resolved in humans. To address this, we performed single-cell lineage tracing and transcriptional profiling of patient cells isolated from metaplastic and healthy tissue. Our analysis revealed discrete lineages in Barretts esophagus, normal esophagus, and gastric cardia. Transitional basal progenitor cells of the gastroesophageal junction were unexpectedly related to both esophagus and gastric cardia cells. Barretts esophagus was polyclonal, with lineages that contained all progenitor and differentiated cell types. In contrast, precancerous dysplastic foci were initiated by the expansion of a single molecularly aberrant Barretts esophagus clone. Together, these findings provide a comprehensive view of the cell dynamics of Barretts esophagus, linking cell states along the full disease trajectory, from its origin to cancer.

genomics↗

bioRxiv2022

Disrupting cellular memory to overcome drug resistance

Plasticity enables cells to change their gene expression state in the absence of a genetic change. At the single-cell level, these gene expression states can persist for different lengths of time which is a quantitative measurement referred to as gene expression memory. Because plasticity is not encoded by genetic changes, these cell states can be reversible, and therefore, are amenable to modulation by disrupting gene expression memory. However, we currently do not have robust methods to find the regulators of memory or to track state switching in plastic cell populations. Here, we developed a lineage tracing-based technique to quantify gene expression memory and to identify single cells as they undergo cell state transitions. Applied to human melanoma cells, we quantified long-lived fluctuations in gene expression that underlie resistance to targeted therapy. Further, we identified the PI3K and TGF-{beta} pathways as modulators of these state dynamics. Applying the gene expression signatures derived from this technique, we find that these expression states are generalizable to in vivo models and present in scRNA-seq from patient tumors. Leveraging the PI3K and TGF-{beta} pathways as dials on memory between plastic states, we propose a " pretreatment" model in which we first use a PI3K inhibitor to modulate the expression states of the cell population and then apply targeted therapy. This plasticity informed dosing scheme ultimately yields fewer resistant colonies than targeted therapy alone. Taken together, we describe a technique to find modulators of gene expression memory and then apply this knowledge to alter plastic cell states and their connected cell fates.

systems biology↗

bioRxiv2022

IGF2BP1/IMP1 contributes to autophagy modulation directly via MAP1LC3B

Homeostatic tissue maintenance requires coordinated regulation of metabolic processes including macroautophagy/autophagy. Autophagy dysregulation underlies numerous human diseases. Our prior work revealed that the RNA binding protein IGF2BP1/IMP1 binds transcripts encoding autophagy-related proteins. Furthermore, Imp1 deletion in gastrointestinal epithelial cells in mice was associated with enhanced autophagy flux and improved recovery from tissue injury. In the current study, we evaluated molecular mechanisms underlying IMP1 modulation of autophagy. We provide a mechanism of direct IMP1 regulation of MAP1LC3B that is dependent upon IMP1 phosphorylation or cell stress, suggesting dynamic modulation of Imp1-mediated autophagy repression that facilitates tissue regeneration. More broadly, our study supports a new mechanism by which tissue regeneration is modulated post-transcriptionally via cell state rather than changes in stem or other cell lineages. This new mechanism may be particularly important in gastrointestinal epithelial cells, where autophagy is essential for tissue recovery following injury, or in diseases such as inflammatory bowel disease where defective autophagy is implicated.

cell biology↗

bioRxiv2021

Multiplexed detection of SARS-CoV-2 genomic and subgenomic RNA using in situ hybridization

The widespread Coronavirus Disease 2019 (COVID-19) is caused by infection with the novel coronavirus SARS-CoV-2. Currently, we have a limited toolset available for visualizing SARS-CoV-2 in cells and tissues, particularly in tissues from patients who died from COVID-19. Generally, single-molecule RNA FISH techniques have shown mixed results in formalin fixed paraffin embedded tissues such as those preserved from human autopsies. Here, we present a platform for preparing autopsy tissue for visualizing SARS-CoV-2 RNA using RNA FISH with amplification by hybridization chain reaction (HCR). We developed probe sets that target different regions of SARS-CoV-2 (including ORF1a and N) as well as probe sets that specifically target SARS-CoV-2 subgenomic mRNAs. We validated these probe sets in cell culture and tissues (lung, lymph node, and placenta) from infected patients. Using this technology, we observe distinct subcellular localization patterns of the ORF1a and N regions, with the ORF1a concentrated around the nucleus and the N showing a diffuse distribution across the cytoplasm. In human lung tissue, we performed multiplexed RNA FISH HCR for SARS-CoV-2 and cell-type specific marker genes. We found viral RNA in cells containing the alveolar type 2 (AT2) cell marker gene (SFTPC) and the alveolar macrophage marker gene (MARCO), but did not identify viral RNA in cells containing the alveolar type 1 (AT1) cell marker gene (AGER). Moreover, we observed distinct subcellular localization patterns of viral RNA in AT2 cells and alveolar macrophages, consistent with phagocytosis of infected cells. In sum, we demonstrate the use of RNA FISH HCR for visualizing different RNA species from SARS-CoV-2 in cell lines and FFPE autopsy specimens. Furthermore, we multiplex this assay with probes for cellular genes to determine what cell-types are infected within the lung. We anticipate that this platform could be broadly useful for studying SARS-CoV-2 pathology in tissues as well as extended for other applications including investigating the viral life cycle, viral diagnostics, and drug screening.

microbiology↗

bioRxiv2020

Retrospective identification of rare cell populations underlying drug resistance connects molecular variability with cell fate

Molecular differences between individual cells can lead to dramatic differences in cell fate, such as death versus survival of cancer cells upon drug treatment. These originating differences remain largely hidden due to difficulties in determining precisely what variable molecular features lead to which cellular fates. Thus, we developed Rewind, a methodology that combines genetic barcoding with RNA FISH to directly capture rare cells that give rise to cellular behaviors of interest. Applied to BRAFV600E melanoma, we trace drug-resistant cell fates back to single-cell gene expression differences in their drug-naive precursors (initial frequency of [~]1:1000-1:10,000 cells) and relative persistence of MAP-kinase signaling soon after drug treatment. Within this rare subpopulation, we uncover a rich substructure in which molecular differences between several distinct subpopulations predict future differences in phenotypic behavior, such as proliferative capacity of distinct resistant clones following drug treatment. Similarly, we show that treatments that modify the frequency of resistance can allow otherwise non-resistant cells in the drug-naive population to become resistant, and that these new populations are marked by the variable expression of distinct genes. Together, our results reveal the presence of hidden, rare-cell variability that can underlie a range of latent phenotypic outcomes upon drug exposure.

systems biology↗

bioRxiv2019

Genetic screening for single-cell variability modulators driving therapy resistance

Cellular plasticity describes the ability of cells to transition from one set of phenotypes to another. In the context of cancer therapeutics, plasticity refers to transient fluctuations in the molecular state of tumor cells, driving the formation of rare cells primed to survive drug treatment and ultimately reprogram into a stably resistant fate. However, the biological processes governing this cellular plasticity remain unknown. We used CRISPR/Cas9 genetic screens to reveal genes that affect cell fate decisions by altering cellular plasticity across a range of functional categories. We found that cellular plasticity and cell fate decision making can be decoupled in that factors can affect cell fate decisions in both plasticity-dependent and independent manners. We discovered a novel mode of altering resistance based on cellular plasticity that, contrary to known mechanisms, pushes cells towards a more differentiated state. We further confirmed our prediction that manipulating cellular plasticity before the addition of the main therapy would result in changes in therapy resistance more than concurrent administration. Together, our results indicate that identifying pathways modulating cellular plasticity has the potential to alter cell fate decisions and may provide a new avenue for treating drug resistance.

cell biology↗

bioRxiv2018

Memory sequencing reveals heritable single cell gene expression programs associated with distinct cellular behaviors

Non-genetic factors can cause individual cells to fluctuate substantially in gene expression levels over time. Yet it remains unclear whether these fluctuations can persist for much longer than the time of one cell division. Current methods for measuring gene expression in single cells mostly rely on single time point measurements, making the duration of gene expression fluctuations or cellular memory difficult to measure. Here, we report a method combining Luria and Delbrucks fluctuation analysis with population-based RNA sequencing (MemorySeq) for identifying genes transcriptome-wide whose fluctuations persist for several cell divisions. MemorySeq revealed multiple gene modules that are expressed together in rare cells within otherwise homogeneous clonal populations. Further, we found that these rare cell subpopulations are associated with biologically distinct behaviors, such as the ability to proliferate in the face of anti-cancer therapeutics, in different cancer cell lines. The identification of non-genetic, multigenerational fluctuations has the potential to reveal new forms of biological memory at the level of single cells and suggests that non-genetic heritability of cellular state may be a quantitative property.

systems biology↗