Biology subjects

Pe'er, D.

Publications and source records attributed to Pe'er, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Neoantigen-reactive CD8+ T cell engagement marks exceptional survivors of pancreatic cancer

Pancreatic cancer (PC) is largely refractory to immune checkpoint blockade (ICB), although homologous recombination-deficient (HRD) tumors may derive benefit. In the POLAR trial of maintenance pembrolizumab plus olaparib after platinum-based chemotherapy for metastatic PC, responses remained heterogeneous. To define determinants of productive antitumor immunity, we integrated longitudinal blood TCR sequencing with tumor single-cell and spatial profiling. Durable benefit was associated with rare tumor-infiltrating, peripherally expanding (TIE) CD8+ T cell clonotypes, a subset of which were functionally neoantigen-reactive. TIE patients showed markedly prolonged survival beyond established genomic and immune biomarkers. Conversely, resistance was associated with spatial T cell exclusion, myCAF-rich stromal remodeling, basal-like/KRAS-associated malignant-cell programs, and expansion of CTLA4 regulatory T cells linked to local immunosuppressive remodeling. These findings define a clonotype-resolved framework for immune monitoring and identify complementary stromal, tumor-intrinsic, and regulatory immune barriers that may guide rational combination immunotherapy in PC.

cancer biology↗

bioRxiv2026

IL-1β/IL-6 signaling circuit in the tumor microenvironment drives prostate cancer development

Despite considerable progress in elucidating mechanisms leading to castration-resistant prostate cancer (CRPC), insight into the early stages of prostate cancer initiation and progression remains limited. Genomic drivers of prostate cancer initiation have been defined through patient tumor sequencing, but the subsequent events responsible for local tissue invasion are poorly understood. Here we leverage a well-studied genetically engineered mouse prostate cancer model (Hi-Myc) that, based on robust and reproducible kinetics for transitioning from pre-invasive prostatic intraepithelial neoplasia (PIN) to invasive prostate adenocarcinoma (PCa), provides an ideal system to systematically address this question using single-cell analysis. Surprisingly, the transcriptomic profiles of early PIN lesions are indistinguishable from those of late-stage, highly invasive tumor cells, suggesting that MYC activation at the PIN stage establishes a transcriptional program that is fully capable of driving invasion but is restrained by the local tumor microenvironment (TME). Indeed, we find that progression to PCa is associated with progressive infiltration of IL-1{beta}+ tumor-infiltrating macrophages at the PIN stage that, based on immunodepletion and cytokine neutralization experiments, are required for the PIN-to-PCa transition. Mechanistically, IL-1{beta} from macrophages acts directly on prostate fibroblasts, leading to the release of IL-6, which drives invasion by activating IL-6R in tumor cells. Collectively, these findings identify a pro-tumorigenic IL-1{beta}/IL-6 signaling circuit mediated through local macrophages and fibroblasts that unleashes the full oncogenic potential of a cancer driver (MYC) activated at the PIN stage. We also find evidence of this circuit in other (non-MYC-driven) prostate cancer models as well as human prostate and lung adenocarcinoma, with implications for TME-specific targeted therapeutics in early-stage disease.

cancer biology↗

bioRxiv2026

The basal cell state maintains pancreatic cancers by controlling an immunosuppressive circuit

Intra-tumoral heterogeneity is a cardinal feature of solid tumors, yet how distinct cancer cell states functionally contribute to malignant and stromal diversity in situ remains poorly understood. Using mouse models to lineage-trace or genetically ablate the two predominant cancer cell states in autochthonous pancreatic ductal adenocarcinoma (PDAC), we discover that basal cancer cells are highly plastic, whereas classical cancer cells exhibit limited plasticity. Strikingly, ablation of the basal, but not the classical, state induced rapid and durable tumor collapse, driven by loss of immunosuppressive cancer-associated fibroblasts, macrophage repolarization, and reprogramming of the tumor cytokine milieu, culminating in tumor destruction by cytotoxic lymphocytes. Knockout of a single cytokine, GM-CSF, specifically in basal cells recapitulated macrophage repolarization and lymphocyte recruitment observed upon basal state ablation and shrank tumors. These results reveal the basal cell state controls an immunosuppressive cell circuit critical for PDAC maintenance, motivating therapeutic targeting of the basal cells.

cancer biology↗

bioRxiv2026

Scalable genotyping in fixed transcriptomes resolves clonal heterogeneity via single-cell sequencing

Despite the promise of single-cell transcriptomics for understanding cell states in heterogeneous populations, widely used platforms have limited ability to link transcriptional states to somatic mutations within the same cells. Here, we introduce Genotyping in Fixed Transcriptomes (GIFT) for the simultaneous detection of large numbers of targeted genetic variants with whole transcriptome profiles in single cells. The core innovation of GIFT is a rationally designed gapfilling reaction between adjacent single-stranded DNA (ssDNA) probes that barcodes native transcript sequence to enable highly-specific targeted mutation detection. GIFT achieves greater than 99% genotyping accuracy and flexible capture of hundreds of mutations per cell, including in formalin-fixed, paraffin-embedded (FFPE) tissue, enabling clonal lineage tracing in heterogeneous settings. We demonstrate the unique scalability of GIFT by profiling more than 700,000 cells from 35 donors with myeloproliferative neoplasms (MPN), revealing mutation-dependent hematopoietic responses to systemic inflammation associated with the characteristic JAK2V617 mutation, including an allelic dose gradient of interferon-associated transcriptional programs and priming of hematopoietic stem cells that develop into divergent disease states. The technical advantages of GIFT enable direct resolution of genotype-to-phenotype relationships via clonal tracing with comprehensive cell-state measurements at single-cell resolution.

genomics↗

bioRxiv2026

POLQ-driven repair scars shape the immunogenic landscape of homologous recombination-deficient pancreatic cancer

Pancreatic cancer (PC) is broadly resistant to immune checkpoint blockade, although a subset of homologous recombination-deficient (HRD) tumors exhibits durable immune engagement. The genomic features that distinguish these immune-responsive tumors from immune-inert HRD tumors remain poorly understood. Here we identify a microhomology-mediated end joining (MMEJ) repair scar, the MMEJ Deletion Footprint (MDF), as a genomic readout of POLQ-associated error-prone repair that enriches for frameshift indels. Across the multi-omic discovery cohort integrating tumor genomics, single-nucleus transcriptomics and spatial immune profiling, MDF-high HRD PC exhibited increased frameshift-indel-derived neoantigens and interferon programs. MDF was further associated with remodeling of the myeloid compartment toward MHC II-high dendritic cell-like antigen-presenting macrophage states and the immune synapse architecture marked by increased spatial interaction between APC-like macrophages and cytotoxic CD8+ T cells. These tissue-level features aligned with a functional trajectory shift of CD8+ T cells, consistent with effective anti-tumor immunity and was associated with favorable clinical outcomes of patients. Together, our findings position MMEJ-linked repair scarring as actionable biology that connects an HRD genotype to immune organization and suggests rational immunotherapy combinations that may enhance antigen presentation and myeloid activation to extend durable benefit in HRD-lineage cancers.

cancer biology↗

bioRxiv2025

Extracellular matrix regulates lineage plasticity in prostate cancer through YAP/TEAD

Treatment-related neuroendocrine prostate cancer (NEPC) is an increasingly frequent mechanism of resistance to androgen receptor pathway inhibitor (ARPI) therapy in prostate adenocarcinoma (PRAD). This lineage transition is dependent on upregulation of the NE-specifying transcription factor ASCL1, typically in a genetic background of RB1 and TP53 loss. Here we identify extracellular matrix-integrin-YAP1/TEAD signaling as a critical brake on NEPC lineage transition. Deletion of Itgb1, the shared B1 subunit required for collagen and laminin-mediated integrin activation, is sufficient to induce ASCL1 and NE lineage gene expression, by activating LATS1/2 kinases with subsequent inactivation of YAP1/TEAD signaling. Conversely, restoration of YAP1/TEAD signaling by pharmacological LATS1/2 inhibition, or by expression of constitutively active YAP1/TAZ mutants, prevents or reverts NEPC lineage transition. NOTCH and AR cooperate with YAP/TEAD to repress ASCL1, such that combined inhibition leads to complete reprograming of PRAD into NEPC in vitro, providing a dynamic platform to dissect the molecular events responsible for lineage transition over time. We find that lineage transition is accompanied by a redistribution of FOXA1 and TEAD cistromes from PRAD to NEPC-specific enhancers and requires the pioneering activity of FOXA1. Thus, extracellular matrix/integrin signaling in the PRAD tumor microenvironment restrains NE lineage plasticity, highlighting a potential path for pharmacological inhibitors in modulating treatment-induced lineage change.

cancer biology↗

bioRxiv2025

Oncogenic and tumor-suppressive forces converge on a progenitor-orchestrated niche to shape early tumorigenesis

The benign-to-malignant transition is a defining step in cancer progression. To investigate when and how malignancy initiation occurs and tissue reorganization proceeds, we combine single-cell and spatial transcriptomic profiling in mouse models of pancreatic ductal adenocarcinoma (PDAC) that capture spontaneous p53 loss. Among Kras-mutant cells, we find that oncogenic and tumor-suppressive programs, including those controlled by p53, CDKN2A, and SMAD4, are co-activated in a discrete progenitor-like population, engaging senescence-like responses. Using a framework we develop for spatial analysis, we show that a niche centered on these cells undergoes stepwise remodeling during tumor progression, mirroring invasive PDAC. Transient KRAS inhibition depletes progenitor-like cells and dismantles their niche, delaying malignancy initiation. Conversely, p53 suppression enables progenitor cell expansion, epithelial-mesenchymal reprogramming, and immune-privileged niche formation. These findings position the progenitor-like state at the convergence of cancer-driving mutations, plasticity and tissue remodeling, revealing a critical window for intercepting malignancy.

cancer biology↗

bioRxiv2025

Segger: Fast and accurate cell segmentation of imaging-based spatial transcriptomics data

The accurate assignment of transcripts to their cells of origin remains the Achilles heel of imaging-based spatial transcriptomics, despite being critical for nearly all downstream analyses. Current cell segmentation methods are prone to over- and under-segmentation, misassign transcripts to cells, require manual intervention, and suffer from low sensitivity and scalability. We introduce segger, a versatile graph neural network based on a heterogeneous graph representation of individual transcripts and cells, that frames cell segmentation as a transcript-to-cell link prediction task and can leverage single-cell RNA-seq information to improve transcript assignments. On multiple Xenium dataset benchmarks, segger exhibits superior sensitivity and specificity, while requiring orders of magnitude less compute time than existing methods. The user-friendly open-source software implementation has extensive documentation (https://elihei2.github.io/segger_dev/), requires little manual intervention, integrates seamlessly into existing workflows, and enables atlas-scale applications.

bioinformatics↗

bioRxiv2025

Transcriptomic plasticity is a hallmark of metastatic pancreatic cancer

Metastasis is the leading cause of cancer deaths; nonetheless, how tumor cells adapt to vastly different organ contexts is largely unknown. To investigate this question, we generated a transcriptomic atlas of primary tumor and diverse metastatic samples from a patient with pancreatic ductal adenocarcinoma who underwent rapid autopsy. Unsupervised archetype analysis identified both shared and site-specific gene programs, including lipid metabolism and gastrointestinal programs prevalent in peritoneum and stomach wall lesions, respectively. We developed a probabilistic approach for inferring clonal phylogeny from single-cell and matched whole-exome data. Distantly related genetic clones in the peritoneum express the lipid metabolism program, likely due to signaling by the adipocyte-rich peritoneum environment, and cells in most clones express multiple programs, suggesting that transcriptomic plasticity is a prevalent feature of metastatic cells. These deeply annotated analyses using a patient-centric platform provide a model for investigating metastatic mechanisms and plasticity in advanced cancer.

bioinformatics↗

bioRxiv2024

Engineering mtDNA Deletions by Reconstituting End-Joining in Human Mitochondria

Recent breakthroughs in the genetic manipulation of mitochondrial DNA (mtDNA) have enabled the precise introduction of base substitutions and the effective removal of genomes carrying harmful mutations. However, the reconstitution of mtDNA deletions responsible for severe mitochondrial myopathies and age-related diseases has not yet been achieved in human cells. Here, we developed a method to engineer specific mtDNA deletions in human cells by co-expressing end-joining (EJ) machinery and targeted endonucleases. As a proof-of-concept, we used mito-EJ and mito-ScaI to generate a panel of clonal cell lines harboring a [~]3.5 kb mtDNA deletion with the full spectrum of heteroplasmy. Investigating these isogenic cells revealed a critical threshold of [~]75% deleted genomes, beyond which cells exhibited depletion of OXPHOS proteins, severe metabolic disruption, and impaired growth in galactose-containing media. Single-cell multiomic analysis revealed two distinct patterns of nuclear gene deregulation in response to mtDNA deletion accumulation; one triggered at the deletion threshold and another progressively responding to increasing heteroplasmy. In summary, the co-expression of mito-EJ and programable nucleases provides a powerful tool to model disease-associated mtDNA deletions in different cell types. Establishing a panel of cell lines with a large-scale deletion at varying levels of heteroplasmy is a valuable resource for understanding the impact of mtDNA deletions on diseases and guiding the development of potential therapeutic strategies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=143 HEIGHT=200 SRC="FIGDIR/small/618543v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@ab900corg.highwire.dtl.DTLVardef@17e094dorg.highwire.dtl.DTLVardef@194a10corg.highwire.dtl.DTLVardef@d925e5_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LICombining prokaryotic end-joining with targeted endonucleases generates specific mtDNA deletions in human cells C_LIO_LIEngineering a panel of cell lines with a large-scale deletion that spans the full spectrum of heteroplasmy C_LIO_LI75% heteroplasmy is the threshold that triggers mitochondrial and cellular dysfunction C_LIO_LITwo distinct nuclear transcriptional programs in response to mtDNA deletions: threshold-triggered and heteroplasmy-sensing C_LI

molecular biology↗

bioRxiv2024

A single-cell atlas of spatial and temporal gene expression in the mouse cranial neural plate

The formation of the mammalian brain requires regionalization and morphogenesis of the cranial neural plate, which transforms from an epithelial sheet into a closed tube that provides the structural foundation for neural patterning and circuit formation. Sonic hedgehog (SHH) signaling is important for cranial neural plate patterning and closure, but the transcriptional changes that give rise to the spatially regulated cell fates and behaviors that build the cranial neural tube have not been systematically analyzed. Here we used single-cell RNA sequencing to generate an atlas of gene expression at six consecutive stages of cranial neural tube closure in the mouse embryo. Ordering transcriptional profiles relative to the major axes of gene expression predicted spatially regulated expression of 870 genes along the anterior-posterior and mediolateral axes of the cranial neural plate and reproduced known expression patterns with over 85% accuracy. Single-cell RNA sequencing of embryos with activated SHH signaling revealed distinct SHH-regulated transcriptional programs in the developing forebrain, midbrain, and hindbrain, suggesting a complex interplay between anterior-posterior and mediolateral patterning systems. These results define a spatiotemporally resolved map of gene expression during cranial neural tube closure and provide a resource for investigating the transcriptional events that drive early mammalian brain development.

developmental biology↗

bioRxiv2024

Artifacts in single-cell mitochondrial DNA mutation analyses misinform phylogenetic inference

Sequencing mitochondrial DNA (mtDNA) variants from single cells has resolved clonality and lineage in native human samples and clinical specimens. Prior work established that heteroplasmic mtDNA variants can be used to delineate clonality in hematopoiesis, but they have limited ability to reconstruct cellular phylogenies. However, a recent report by Weng et al. challenges the current paradigm by describing an unprecedented number of shared mtDNA variants between cells that reportedly resolve high-resolution phylogenetic trees. We re-examined the claims of Weng et al., and identified two major points of concern regarding this unprecedented connectedness. First, shared variants between cells are disproportionately detected in a single molecule per cell, and second, these variants are enriched 10-20-fold at the edges of mtDNA molecules, reminiscent of artifacts reported in other sequencing approaches. Further, our analyses show that pruning low support and likely artificial mtDNA variants removes nearly all of the reported phylogenetic structure. Thus, we strongly caution against using mtDNA variant calling workflows that rely on minimal evidence, including the computational pipeline introduced in Weng et al., as variants with high connectedness and low evidence are likely artifacts that lead to the construction of false phylogenies.

genomics↗

bioRxiv2024

Microbial cancer immunotherapy reprograms hematopoietic stem cells to enhance anti-tumor immunity

Mycobacterium bovis BCG is the vaccine against tuberculosis and an immunotherapy for bladder cancer. When administered intravenously, BCG reprograms bone marrow hematopoietic stem and progenitor cells (HSPCs), leading to heterologous protection against infections. Whether HSPC-reprogramming contributes to the anti-tumor effects of BCG administered into the bladder is unknown. We demonstrate that BCG administered in the bladder in both mice and humans reprograms HSPCs to amplify myelopoiesis and functionally enhance myeloid cell antigen presentation pathways. Reconstitution of naive mice with HSPCs from bladder BCG-treated mice enhances anti-tumor immunity and tumor control, increases intratumor dendritic cell infiltration, reprograms pro-tumorigenic neutrophils, and synergizes with checkpoint blockade. We conclude that bladder BCG acts systemically, reprogramming HSPC-encoded innate immunity, highlighting the broad potential of modulating HSPC phenotypes to improve tumor immunity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/586166v2_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@16b81a7org.highwire.dtl.DTLVardef@10cfebforg.highwire.dtl.DTLVardef@28bf93org.highwire.dtl.DTLVardef@1396184_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2024

Metastatic site influences driver gene function in pancreatic cancer

Driver gene mutations can increase the metastatic potential of the primary tumor1-3, but their role in sustaining tumor growth at metastatic sites is poorly understood. A paradigm of such mutations is inactivation of SMAD4 - a transcriptional effector of TGF{beta} signaling - which is a hallmark of multiple gastrointestinal malignancies4,5. SMAD4 inactivation mediates TGF{beta}s remarkable anti-to pro-tumorigenic switch during cancer progression and can thus influence both tumor initiation and metastasis6-14. To determine whether metastatic tumors remain dependent on SMAD4 inactivation, we developed a mouse model of pancreatic ductal adenocarcinoma (PDAC) that enables Smad4 depletion in the pre-malignant pancreas and subsequent Smad4 reactivation in established metastases. As expected, Smad4 inactivation facilitated the formation of primary tumors that eventually colonized the liver and lungs. By contrast, Smad4 reactivation in metastatic disease had strikingly opposite effects depending on the tumors organ of residence: suppression of liver metastases and promotion of lung metastases. Integrative multiomic analysis revealed organ-specific differences in the tumor cells epigenomic state, whereby the liver and lungs harbored chromatin programs respectively dominated by the KLF and RUNX developmental transcription factors, with Klf4 depletion being sufficient to reverse Smad4s tumor-suppressive activity in liver metastases. Our results show how epigenetic states favored by the organ of residence can influence the function of driver genes in metastatic tumors. This organ-specific gene-chromatin interplay invites consideration of anatomical site in the interpretation of tumor genetics, with implications for the therapeutic targeting of metastatic disease.

cancer biology↗

bioRxiv2023

Deep generative model deciphers derailed trajectories in acute myeloid leukemia

Biological insights often depend on comparing conditions such as disease and health, yet we lack effective computational tools for integrating single-cell genomics data across conditions or characterizing transitions from normal to deviant cell states. Here, we present Decipher, a deep generative model that characterizes derailed cell-state trajectories. Decipher jointly models and visualizes gene expression and cell state from normal and perturbed single-cell RNA-seq data, revealing shared and disrupted dynamics. We demonstrate its superior performance across diverse contexts, including in pancreatitis with oncogene mutation, acute myeloid leukemia, and gastric cancer.

bioinformatics↗

bioRxiv2023

Progressive plasticity during colorectal cancer metastasis

Metastasis is the principal cause of cancer death, yet we lack an understanding of metastatic cell states, their relationship to primary tumor states, and the mechanisms by which they transition. In a cohort of biospecimen trios from same-patient normal colon, primary and metastatic colorectal cancer, we show that while primary tumors largely adopt LGR5+ intestinal stem-like states, metastases display progressive plasticity. Loss of intestinal cell states is accompanied by reprogramming into a highly conserved fetal progenitor state, followed by non-canonical differentiation into divergent squamous and neuroendocrine-like states, which is exacerbated by chemotherapy and associated with poor patient survival. Using matched patient-derived organoids, we demonstrate that metastatic cancer cells exhibit greater cell-autonomous multilineage differentiation potential in response to microenvironment cues than their intestinal lineage-restricted primary tumor counterparts. We identify PROX1 as a stabilizer of intestinal lineage in the fetal progenitor state, whose downregulation licenses non-canonical reprogramming.

cancer biology↗

bioRxiv2023

Unified fate mapping in multiview single-cell data

Single-cell RNA sequencing allows us to model cellular state dynamics and fate decisions using expression similarity or RNA velocity to reconstruct state-change trajectories. However, trajectory inference does not incorporate valuable time point information or utilize additional modalities, while methods that address these different data views cannot be combined and do not scale. Here, we present CellRank 2, a versatile and scalable framework to study cellular fate using multiview single-cell data of up to millions of cells in a unified fashion. CellRank 2 consistently recovers terminal states and fate probabilities across data modalities in human hematopoiesis and mouse endodermal development. Our framework also allows combining transitions within and across experimental time points, a feature we use to recover genes promoting medullary thymic epithelial cell formation during pharyngeal endoderm development. Moreover, we enable estimating cell-specific transcription and degradation rates from metabolic labeling data, which we apply to an intestinal organoid system to delineate differentiation trajectories and pinpoint regulatory strategies.

bioinformatics↗

bioRxiv2023

The covariance environment defines cellular niches for spatial inference

The tsunami of new multiplexed spatial profiling technologies has opened a range of computational challenges focused on leveraging these powerful data for biological discovery. A key challenge underlying computation is a suitable representation for features of cellular niches. Here, we develop the covariance environment (COVET), a representation that can capture the rich, continuous multivariate nature of cellular niches by capturing the gene-gene covariate structure across cells in the niche, which can reflect the cell-cell communication between them. We define a principled optimal transport-based distance metric between COVET niches and develop a computationally efficient approximation to this metric that can scale to millions of cells. Using COVET to encode spatial context, we develop environmental variational inference (ENVI), a conditional variational autoencoder that jointly embeds spatial and single-cell RNA-seq data into a latent space. Two distinct decoders either impute gene expression across spatial modality, or project spatial information onto dissociated single-cell data. We show that ENVI is not only superior in the imputation of gene expression but is also able to infer spatial context to disassociated single-cell genomics data.

bioinformatics↗