Biology subjects

Patel, A. G.

Publications and source records attributed to Patel, A. G..

9 recordsLinked to original sources

bioRxiv2026

Lineage-mixed neurodevelopmental programs in pediatric sarcomas nominate tumor-selective surface antigen pairs.

Pediatric solid tumors have low mutational burden, frequent oncogenic gene fusions, and developmental origins in arrested progenitor cells. Single-cell RNA-seq (scRNA-seq) could represent an ideal tool to assess whether these convergent biological features yield shared therapeutic vulnerabilities. However, while existing tools can extract gene expression programs for pan-tumor single-cell data, interpreting them requires domain expertise across many disciplines and diseases. Here, we analyzed a pan-pediatric scRNA-seq atlas of 266 patient- and xenograft-derived samples across 22 pediatric solid tumor types. To address the bottleneck between gene program identification and interpretation, we developed an AI agent framework built on off-the-shelf large language models (e.g., Gemini 2.5) to interpret gene expression programs at the level of human experts, but at much greater scale and speed. Our agent identified ectopic expression of neuronal marker genes as a unique feature of several fusion-driven sarcomas. This gene expression pattern resulted in tumor-specific co-expression of mixed mesenchymal/neuronal surface markers, providing a plausible therapeutic window to target these tumor types using emerging AND-gated therapeutic strategies, such as bispecific antibody-drug conjugates (ADCs) and bispecific CAR-T cells. As proof of principle, we nominated and validated STEAP1/NPTXR as a Ewing sarcoma candidate cell surface target pair. Together, this work delivers a pan-pediatric solid tumor scRNA-seq atlas, establishes a generalizable and accessible AI-based framework that complements existing single-cell methods by automating interpretation of pan-disease single-cell atlases, and nominates new bispecific ADC/CAR-T targets for catastrophic pediatric cancers.

cancer biology↗

bioRxiv2026

Integration of Neuroimaging and Histopathology in a Squirrel Monkey Model of Spontaneous Cerebral Amyloid Angiopathy and Amyloid-Related Imaging Abnormalities

Cerebral amyloid angiopathy (CAA) is a prevalent cerebrovascular pathology in AD and contributes to amyloid-related imaging abnormalities (ARIA), a major complication of current anti-amyloid immunotherapy. Despite its growing clinical importance, critical gaps remain in the development of reliable biomarkers for antemortem diagnosis of CAA. Squirrel monkeys (SQMs) are a valuable non-human primate model with translational relevance due to their universal propensity to develop abundant CAA and spontaneous ARIA in geriatric animals. The present study employed R2*, the apparent transverse relaxation rate, which is sensitive to susceptibility-related tissue properties, including iron content and blood oxygenation levels, to monitor age-related brain pathology in SQMs with varying CAA severity. Young, early geriatric, and late geriatric SQMs underwent 7T MRI using a dual-purpose T2*-w 3D multi-gradient-echo sequence for high-resolution anatomy and quantitative R2* mapping, alongside T2-w/FLAIR imaging. Whole-brain and gray matter R2* increased with age. In contrast, white matter R2* showed an initial increase followed by a late-life reversal, likely reflecting age-related changes in myelin integrity, tissue microstructure, and tissue water content. MRI-histopathology correlation linked T2*-w MRI hypointensities to CAA-positive iron-laden vessels associated with perivascular inflammation and, in some cases, hemosiderin deposits. Here we confirmed the occurrence of ARIA-H and ARIA-E events in geriatric animals. SQMs provided a valuable opportunity to examine the underlying pathology of spontaneous ARIA-E, revealing distinctive tissue signatures associated with its manifestation. ARIA-E hyperintensities were characterized by reactive gliosis and BBB disruption, whereas more advanced lesions exhibited perivascular lymphocytic infiltration and evidence of myelin and axonal injury. The current study presents compelling evidence linking R2* alterations with CAA severity and ARIA-related tissue injury, providing a foundation for further advancing early detection of CAA, ARIA risk assessment, and treatment strategies.

neuroscience↗

bioRxiv2026

Integrative Single-cell and Spatial Transcriptomic Analysis of Osteosarcoma Reveals Conserved and Distinct Ecosystems Across Sites and Species

Osteosarcoma is a heterogeneous malignancy, exhibiting significant variability among patients, individual cancer cells within a tumor, and the stromal cells that compose primary and metastatic lesions. To facilitate the study of this complex disease, we compiled a unique cross-species single-cell transcriptomic dataset totaling over a million cells/nuclei from human specimens, canine specimens, patient-derived xenografts/PDX, and syngeneic mouse models at both primary (bone) and metastatic (lung) sites. Using a rigorous process for multi-species alignment and annotation, we identified six conserved tumor cell transcriptional states organized along hierarchical differentiation trajectories from progenitor to differentiated phenotypes. Parallel analysis of tumor-associated cells identified conserved macrophage, fibroblast, and endothelial populations that exhibit species- and site-specific reprogramming. Validation by mapping cell types using spatial transcriptomics revealed structured neighborhood architectures that were reproduced across multiple samples. Cell-cell interaction analysis revealed similarities and differences in tumor-host networks across primary and metastatic sites and across species. This analysis enabled pathway-specific assessment of tumor-host communication fidelity across osteosarcoma model systems relative to humans, revealing canine osteosarcoma as a more faithful model. Metastatic lung lesions, counterintuitively, exhibited more intense and complex extracellular matrix (ECM) signaling than primary bone tumors. A key example was tumor-derived fibronectin (FN1), which engages integrin and syndecan receptors on lung epithelial cells, driving a pathological mesenchymal and profibrotic state that promotes fibrotic niche formation and metastatic lung colonization. Together, this cross-species resource delineates both conserved and divergent tumor microenvironment programs, demonstrates how model-aware analyses uncover previously unrecognized tumor-host interactions, and underscores the need for therapies that co-target tumor heterogeneity and its supportive metastatic niche. Statement of SignificanceWe show that the tumor microenvironment in human osteosarcoma patients has biological phenotypes that are conserved across both patients and species. This points towards underlying molecular mechanisms that could be therapeutically targeted.

cancer biology↗

bioRxiv2024

A spatial cell atlas of neuroblastoma reveals developmental, epigenetic and spatial axis of tumor heterogeneity

Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.

cancer biology↗

bioRxiv2023

Inferring therapeutic vulnerability within tumors through integration of pan-cancer cell line and single-cell transcriptomic profiles

Single-cell RNA sequencing greatly advanced our understanding of intratumoral heterogeneity through identifying tumor subpopulations with distinct biologies. However, translating biological differences into treatment strategies is challenging, as we still lack tools to facilitate efficient drug discovery that tackles heterogeneous tumors. One key component of such approaches tackles accurate prediction of drug response at the single-cell level to offer therapeutic options to specific cell subpopulations. Here, we present a transparent computational framework (nicknamed scIDUC) to predict therapeutic efficacies on an individual-cell basis by integrating single-cell transcriptomic profiles with large, data-rich pan-cancer cell line screening datasets. Our method achieves high accuracy, with predicted sensitivities easily able to separate cells into their true cellular drug resistance status as measured by effect size (Cohens d > 1.0). More importantly, we examine our methods utility with three distinct prospective tests covering different diseases (rhabdomyosarcoma, pancreatic ductal adenocarcinoma, and castration-resistant prostate cancer), and in each our predicted results are accurate and mirrored biological expectations. In the first two, we identified drugs for cell subpopulations that are resistant to standard-of-care (SOC) therapies due to intrinsic resistance or effects of tumor microenvironments. Our results showed high consistency with experimental findings from the original studies. In the third test, we generated SOC therapy resistant cell lines, used scIDUC to identify efficacious drugs for the resistant line, and validated the predictions with in-vitro experiments. Together, scIDUC quickly translates scRNA-seq data into drug response for individual cells, displaying the potential as a first-line tool for nuanced and heterogeneity-aware drug discovery.

bioinformatics↗

bioRxiv2023

Single cell transcriptomic profiling identifies tumor-acquired and therapy-resistant cell states in pediatric rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is a pediatric tumor that resembles undifferentiated muscle cells; yet the extent to which cell state heterogeneity and molecular features are shared with human development have not been fully ascribed. Here, we report a single-cell/nucleus RNA sequencing atlas derived from 72 datasets that includes patient tumors, patient-derived xenografts, primary in vitro cultures, and established cell lines. We report four dominant muscle-lineage cell states in RMS: progenitors, proliferative, differentiated, and ground cells. We stratify these RMS cells along the continuum of human muscle development and show that RMS cells share expression patterns with fetal/embryonal myogenic precursors rather than postnatal satellite cells. Indeed, fusion-negative RMS (FN-RMS) have a discrete stem cell hierarchy that faithfully recapitulates fetal muscle development. We also identify therapy-resistant FN-RMS progenitor cells that share transcriptomic similarity with bipotent skeletal mesenchymal cells, while a subset of fusion-positive (FP) RMS have tumor-acquired cells states, including a neuronal cell state, that are not found in development. Chemotherapy induced upregulation of progenitor signatures in FN-RMS while the neuronal gene programs were retained after therapy in FP-RMS. Taken together, this work identifies new cell state heterogeneity including unique treatment-resistant and tumor-acquired cell states that differ across RMS subtypes.

cancer biology↗

bioRxiv2021

Ly-6A-Induced Growth Inhibition and Cell death in a Transformed CD4+ T cell line: Role of Tumor Necrosis Factor-α (TNF-α)

Engaging the Ly-6A protein, an inhibitory signaling protein, on CD4+ T cell lines triggers apoptosis. Signaling through Ly-6A activates cell-intrinsic apoptotic cell death pathway as indicated by release of cytochrome C, activation of caspase 3 and 9. In addition Ly-6A induces cytokine production and growth inhibition. The mechanism underlying simultaneous distinct cellular responses has remained unknown. To examine the relatedness of distinct responses generated by engaging Ly-6A, we have quantified the secretion of TNF, TGF{beta} and a related protein GDF10, the three pro-apoptotic, growth inhibitory and tumor suppressive cytokines. While low levels of TGF{beta} and GDF10 were detected after engaging Ly-6A, the production of TNF- was elevated in cell cultures stimulated the Ly-6A protein. Blocking the biological activity of TNF resulted in reduced apoptosis induced by engaging Ly-6A. In contrast, growth inhibition/apoptosis in response to antigen receptor complex stimulation was not observed. Engaging the antigen receptor through activating the epsilon ({varepsilon}) chain of CD3 generated high levels of TGF-{beta} and GDF10 while decreasing TNF. These results suggest that the TNF- cytokine contributes to the Ly-6A-induced growth inhibitory and pro-apoptotic response in CD4+ T cells and provides mechanistic explanation of the observed biologically distinct responses initiated after engaging Ly-6A protein. These findings aid in understanding the inhibitory signaling initiated by Ly-6A protein, especially in the context of its potential immune checkpoint inhibitory role in T cells.

immunology↗

bioRxiv2021

The Myogenesis Program Drives Clonal Selection and Drug Resistance in Rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is a pediatric cancer with features of skeletal muscle; patients with unresectable or metastatic RMS fare poorly due to high rates of disease recurrence. Here, we use single cell and single nucleus RNA-sequencing to show that RMS tumors recapitulate the spectrum of embryonal myogenesis. Using matched patient samples from a clinical trial and orthotopic patient-derived xenografts (O-PDXs), we show chemotherapy eliminates the most proliferative component with features of myoblasts; after treatment, the quiescent immature population with features of paraxial mesoderm expands to reconstitute the developmental hierarchy of the original tumor. We discovered that this paraxial mesoderm population is dependent on EGFR signaling and is sensitive to EGFR inhibitors. Taken together, this data serves as a proof-of-concept that targeting each developmental state in RMS is an effective strategy for improving outcomes by preventing disease recurrence.

cancer biology↗

bioRxiv2019

A single-cell and single-nucleus RNA-seq toolbox for fresh and frozen human tumors

Single cell genomics is essential to chart the complex tumor ecosystem. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumor tissues, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each strategy requires modifications to fit the unique characteristics of different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We tested eight tumor types of varying tissue and sample characteristics (resection, biopsy, ascites, and orthotopic patient-derived xenograft): lung cancer, metastatic breast cancer, ovarian cancer, melanoma, neuroblastoma, pediatric sarcoma, glioblastoma, pediatric high-grade glioma, and chronic lymphocytic leukemia. Analyzing 212,498 cells and nuclei from 39 clinical samples, we evaluated protocols by cell quality, recovery rate, and cellular composition. We optimized protocols for fresh tissue dissociation for different tumor types using a decision tree to account for the technical and biological variation between clinical samples. We established methods for nucleus isolation from OCT embedded and fresh-frozen tissues, with an optimization matrix varying mechanical force, buffer, and detergent. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types and intrinsic expression profiles, but at different proportions. Our work provides direct guidance across a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

genomics↗