Biology subjects

Keller, E. T.

Publications and source records attributed to Keller, E. T..

10 recordsLinked to original sources

bioRxiv2026

SPICE: A Robust Computational Framework for Identifying Copy Number Variations in Spatial Transcriptomics

Copy number variation (CNV), which alters the number of genomic segments, is a major driver of intratumor heterogeneity, characterized by spatially organized and genetically distinct cell populations. Recent advances in spatially resolved transcriptomic (SRT) technologies, which profile gene expression across thousands of spatially indexed tissue locations, offer a powerful opportunity to reconstruct the CNV architecture and dissect the spatial organization of cancer subclones. Here, we introduce SPICE (spatial inference of CNV events), a probabilistic method for identifying somatic CNVs and allele-specific copy number (ASCN) profiles from SRT data. A key feature of SPICE is its ability to integrate multiple complementary information available in SRT data, including gene expression, spatial coordinates, and heterozygous SNPs inferred from transcriptomic reads, to substantially enhance the accuracy and power of CNV detection. Using datasets generated across different SRT platforms, we first assess the reliability of SNPs derived from SRT data to ensure robust downstream inference. We then demonstrate that SPICE effectively integrates these modalities to deliver accurate and spatially coherent reconstruction of CNV landscapes and subclonal architecture, while maintaining excellent control of false discoveries. Together, SPICE provides a robust and effective solution for dissecting genomic heterogeneity in SRT studies of cancer.

genomics↗

bioRxiv2026

Multi-resolution Spatial Graphical Regression Models for Hierarchical Spatial Transcriptomics Data

Advances in spatial transcriptomics (ST) technologies enable systematic molecular characterization of tumor microenvironment, tumor gradients and gene regulatory networks. Cancer progression is known to vary along pathological gradients, yet existing network approaches for gene network inference typically ignore hierarchical spatial organization across the tumor. We develop a Bayesian multi-resolution spatial graphical regression (mSGR) framework to infer spatially varying gene networks from multi-resolution ST data. The proposed model allows precision matrices to vary across hierarchically structured spatial domains, capturing both local and global organization within the tumor. To identify spatially varying regulatory relationships, we introduce a spatially structured edge selection strategy that borrows strength across regions according to spatial proximity and pathological gradients, while Gaussian-process priors flexibly model spatial variation in edge strengths. Scalable inference is achieved through an augmented mean-field variational Bayes algorithm with node-wise parallel regressions, enabling efficient estimation in high-dimensional settings. Simulation studies demonstrate improved recovery of network structures compared with competing approaches. Applying mSGR to multi-resolution ST data from kidney cancer reveals stronger regulatory connectivity in transitional regions of epithelial-mesenchymal transition pathway and identifies hub genes along the tumor gradient, illustrating how spatially resolved network analysis can provide key insights into tumor microenvironment organization.

genomics↗

bioRxiv2026

STDrug enables spatially informed personalized drug repurposing from spatial transcriptomics

Drug repurposing offers a scalable route to accelerate therapeutic discovery, yet existing approaches based on single-cell RNA sequencing (scRNA-seq) often overlook spatial tissue context, limiting their ability to capture microenvironment-dependent drug responses. Here we present STDrug, a spatially informed computational framework that integrates spatial transcriptomics, graph-based modeling, and multimodal learning to enable patient-specific therapeutic prioritization. STDrug identifies and aligns disease and control spatial domains using graph convolutional networks and coherent point drift, and prioritizes candidate drugs through an integrative scoring scheme combining tumor-reversible gene signatures, perturbation-based reversal scores, and knowledge-guided gene weighting within a machine learning framework. By modeling spatial domain interactions alongside predicted drug efficacy and toxicity, STDrug generates robust patient-level drug scores. Across hepatocellular carcinoma and prostate cancer datasets, STDrug outperforms existing single-cell and spatial transcriptomics-based drug repurposing methods, achieving signficantly improved predictive accuracy (AUCs=0.81-0.82) across patients. Validation using large-scale electronic health records and in vitro assays further supports the translational relevance of top-ranked candidates. Taking together, STDrug establishes a generalizable framework for incorporating spatial omics into therapeutic discovery, advancing spatially informed and personalized drug repurposing.

bioinformatics↗

bioRxiv2026

Spatial multi-omics identify an immunosuppressive lipid-laden macrophage niche in primary CNS lymphoma

Primary central nervous system lymphoma (PCNSL) is histologically a subtype of diffuse large B-cell lymphoma (DLBCL), sharing genetic and transcriptomic similarity, but with distinct clinical features, particularly its confinement to the CNS and higher relapse risk. The microenvironmental basis for its divergence from systemic DLBCL remains unclear. Using spatial transcriptomic approaches (Xenium/GeoMx digital spatial profiling) in a comparative study of PCNSL (n=17) and DLBCL (n=76), we found that PCNSL, unlike systemic DLBCL, is dominated by an immunosuppressive macrophage compartment enriched for cholesterol-metabolism programs. In independent cohorts of PCNSL profiled by single-cell RNA sequencing, we validated the presence of a recurrent population of lipid-laden macrophages (LLMs): TREM2/GPNMB-expressing, lipid-remodeled cells transcriptionally distinct from resident microglia and consistent with an infiltrating monocyte origin, not previously characterized in CNS lymphoma. LLMs formed immunosuppressive niches with regulatory T cells, and using Cellscape hyperplex proteomic imaging we demonstrate that LLM-Treg spatial interactions are associated with chemotherapy response. To test whether LLMs are lymphoma-driven and functionally important, we developed an immunocompetent syngeneic PCNSL mouse model, driven by Myd88L252P and Cd79b mutations with Bcl2 overexpression. Monocyte-derived macrophages in lymphoma-bearing brain regions acquired an LLM-like state, not seen in lymphoma-free brain regions or in splenic tumors driven by the same oncogenic lesions. TREM2-SYK signaling sustained this state, and SYK inhibition reversed its tumor-supportive activity ex vivo. These findings identify the LLM program as a targetable immunosuppressive myeloid state in CNS lymphoma.

cancer biology↗

bioRxiv2025

Amoeboid-Mesenchymal Transition and the Proteolytic Control of Cancer Invasion Plasticity

Invasion plasticity allows malignant cells to toggle between collective, mesenchymal and amoeboid phenotypes while traversing extracellular matrix (ECM) barriers. Current dogma holds that collective and mesenchymal invasion programs trigger the mobilization of proteinases that digest structural barriers dominated by type I collagen, while amoeboid activity allows cancer cells to marshal mechanical forces to traverse tissues independently of ECM proteolysis. Here, we use cancer spheroid-3-dimensional matrix models, single-cell RNA sequencing, and human tissue explants to identify the mechanisms controlling mesenchymal versus amoeboid invasion. Unexpectedly, collective/mesenchymal- and amoeboid-type invasion programs - though distinct - are each characterized by active tunneling through ECM barriers, with expression of matrix-degradative metalloproteinases. CRISPR/Cas9-mediated targeting of a single membrane-anchored collagenase, MMP14/MT1-MMP, ablates tissue-invasive activity while co-regulating cancer cell transcriptional programs. Though changes in matrix architecture, nuclear rigidity, and metabolic stress as well as the presence of cancer-associated fibroblasts are proposed to support amoeboid activity, none of these changes restore invasive activity of MMP14-targeted cancer cells. While a requirement for MMP14 is bypassed in low-density collagen hydrogels, invasion by the proteinase-deleted cells is associated with nuclear envelope and DNA damage, highlighting a proteolytic requirement for maintaining nuclear integrity. Nevertheless, when cancer cells confront explants of live human breast tissue, MMP14 is again required to support invasive activity. Corroborating these results, spatial transcriptomic and immunohistological analyses of invasive human breast cancers identified clear expression of MMP14 in invasive cells that were further associated with degraded collagen, underlining the pathophysiologic importance of this proteinase in directing invasive activity in vivo.

cancer biology↗

bioRxiv2025

A spatiotemporal atlas of orchiectomy-induced androgen deprivation-mediated modulation of cellular composition and gene expression in the mouse prostate.

Androgen deprivation therapy (ADT) remains a cornerstone in the treatment of prostate cancer (PCa), yet most tumors eventually develop resistance. Murine models are widely used to study PCa progression and ADT response, but a detailed understanding of the prostates biological response to androgen deprivation in these models is lacking. Here, we present a comprehensive spatiotemporal analysis of cellular and transcriptional dynamics in the mouse prostate following orchiectomy (ORX)-induced androgen deprivation. We observed progressive involution across all prostate lobes (dorsal, ventral, lateral, and anterior) and distinct lobe-specific temporal gene expression changes post-ORX. Immune cell infiltration markedly increased over time, highlighting a shift in the prostates cellular landscape. Single-cell RNA sequencing uncovered a previously undescribed fibroblast subtype--termed ORX-induced fibroblast (OIF)-- characterized by high expression of Wnt2, Rorb, and Wif1, with distinct spatial localization. Pathway analysis revealed upregulation of amide and peptide binding functions, alongside suppression of peptidase and endopeptidase activity. Furthermore, dynamic changes in ligand-receptor interactions across lobes underscored the evolving intercellular communication in the post-ORX prostate. By integrating spatial transcriptomics with single-cell profiling, our study generates a high-resolution atlas of the murine prostates response to androgen deprivation. These findings provide a foundational resource for interpreting ADT responses in preclinical models of PCa.

cancer biology↗

bioRxiv2025

Spatial analysis reveals a novel inflammatory tumor transition state which promotes a macrophage-driven induction of sarcomatoid renal cell carcinoma

Sarcomatoid renal cell carcinoma (sRCC) is an aggressive transdifferentiation of epithelioid clear cell RCC (ccRCC) tumors that shows heightened response to immunotherapy. The underlying biology leading to sarcomatoid transformation and mechanisms contributing to immunotherapy response are not well understood. Novel single cell spatial techniques were used in ccRCC and sRCC tumors from 40 patients to understand the spatial sRCC transformation and corresponding immune changes. A transcriptional transition state in epithelioid ccRCC cells along a continuum to mesenchymal sRCC was identified which expresses high levels of pro-inflammatory cytokines and an immune infiltrate. In vitro studies demonstrated that M2-like macrophages, recruited to the tumor by the transition state, induce full transition to the sarcomatoid state. A combination of increased PD-L1 expression and T-cells recruited by the transition state was observed, consistent with the increased immunotherapy response. This study enriches our understanding of the mechanisms leading to development and immune responsiveness of sRCC paving the way for novel approaches to diminish RCC progression.

cancer biology↗

bioRxiv2024

Cellular cartography reveals mouse prostate organization and determinants of castration resistance

Inadequate response to androgen deprivation therapy (ADT) frequently arises in prostate cancer, driven by cellular mechanisms that remain poorly understood. Here, we integrated single-cell RNA sequencing, single-cell multiomics, and spatial transcriptomics to define the transcriptional, epigenetic, and spatial basis of cell identity and castration response in the mouse prostate. Leveraging these data along with a meta-analysis of human prostates and prostate cancer, we identified cellular orthologs and key determinants of ADT response and resistance. Our findings reveal that mouse prostates harbor lobe-specific luminal epithelial cell types distinguished by unique gene regulatory modules and anatomically defined androgen-responsive transcriptional programs, indicative of divergent developmental origins. Androgen-insensitive, stem-like epithelial populations - resembling human club and hillock cells - are notably enriched in the urethra and ventral prostate but are rare in other lobes. Within the ventral prostate, we also uncovered two additional androgen-responsive luminal epithelial cell types, marked by Pbsn or Spink1 expression, which align with human luminal subsets and may define the origin of distinct prostate cancer subtypes. Castration profoundly reshaped luminal epithelial transcriptomes, with castration-resistant luminal epithelial cells activating stress-responsive and stemness programs. These transcriptional signatures are enriched in tumor cells from ADT-treated and castration-resistant prostate cancer patients, underscoring their likely role in driving treatment resistance. Collectively, our comprehensive cellular atlas of the mouse prostate illuminates the importance of lobe-specific contexts for prostate cancer modeling and reveals potential therapeutic targets to counter castration resistance. Significance StatementAndrogen deprivation therapy is a mainstay in prostate cancer treatment, yet many patients eventually develop castration-resistant disease--a lethal progression driven by poorly understood cellular mechanisms. Our study provides a comprehensive cellular map of the prostate, identifying key determinants of normal organization and castration-induced remodeling. By pinpointing the cell types and molecular programs that confer ADT responsiveness or resistance, our findings offer new directions for prostate cancer modeling and pave the way toward novel therapeutic strategies aimed at enhancing ADT efficacy and preventing the emergence of castration-resistant prostate cancer.

cancer biology↗

bioRxiv2021

Macrophages induce inflammation by efferocytosis of apoptotic prostate cancer cells via HIF-1α stabilization

Clearance of apoptotic cancer cells by macrophages, known as efferocytosis, fuels the bone-metastatic growth of prostate cancer cells via pro-inflammatory and immunosuppressive processes. However, the exact molecular mechanisms remain unclear. In this study, single-cell transcriptomics of bone marrow macrophages undergoing efferocytosis of apoptotic prostate cancer cells revealed a significant enrichment of a cellular response to hypoxia. Here we show that efferocytic macrophages promote HIF-1 stabilization under normoxic conditions through interaction with phosphorylated STAT3. Inflammatory cytokine gene expression analysis of efferocytic HIF-1-mutant macrophages revealed a reduced expression of the pro-tumorigenic Mif. Furthermore, stabilization of HIF-1 using the HIF-prolyl-hydroxylase inhibitor, Roxadustat, enhanced MIF expression in macrophages. Finally, macrophages treated with recombinant MIF protein activated NF-{kappa}B (p65) signaling and increased the expression of pro-inflammatory cytokines. Altogether, these findings suggest that the clearance of apoptotic cancer cells by tumor-associated macrophages triggers p-STAT3/HIF-1/MIF signaling to enhance tumor-promoting inflammation in bone, suggesting this axis as a target for metastatic prostate cancer.

cancer biology↗

bioRxiv2018

Notch3 Promotes Prostate Cancer-Induced Bone Osteoblastic Metastasis in an MMP-3-Dependent Manner

Prostate cancer metastases primarily localize in the bone where they induce a unique osteoblastic response. Elevated Notch activity is associated with high-grade disease and metastasis. To address how Notch affects prostate cancer bone lesions, we manipulated Notch expression in mouse tibia xenografts and monitored tumor growth, lesion phenotype, and the bone microenvironment. Prostate cancer cell lines that induce mixed osteoblastic lesions in bone expressed 5-6 times more Notch3, than tumor cells that produce osteolytic lesions. Expression of active Notch3 (NICD3) in osteolytic tumors reduced osteolytic lesion area and enhanced osteoblastogenesis, while loss of Notch3 in osteoblastic tumors enhanced osteolytic lesion area and decreased osteoblastogensis. This was accompanied by a respective decrease and increase in the number of active osteoclasts and osteoblasts at the tumor-bone interface, without any effect on tumor proliferation. Conditioned medium from NICD3-expressing cells enhanced osteoblast differentiation and proliferation in vitro, while simultaneously inhibiting osteoclastogenesis. MMP-3 was specifically elevated and secreted by NICD3-expressing tumors, and inhibition of MMP-3 rescued the NICD3-induced osteoblastic phenotypes. Clinical osteoblastic bone metastasis samples had higher levels of Notch3 and MMP-3 compared to patient matched visceral metastases or osteolytic metastasis samples. We identified a Notch3-MMP-3 axis in human prostate cancer bone metastases that contributes to osteoblastic lesion formation by blocking osteoclast differentiation, while also contributing to osteoblastogenesis. These studies define a new role for Notch3 in manipulating the tumor microenvironment in bone metastases.

cancer biology↗