Biology subjects

Aparicio, L.

Publications and source records attributed to Aparicio, L..

5 recordsLinked to original sources

bioRxiv2026

Targeting CD73-A2aR-Mediated Adenosine Signaling at the Tumor-Immune Interface Overcomes Radioresistance

BackgroundRadiotherapy efficacy is constrained by an immunosuppressive tumor microenvironment (TME) enriched in extracellular adenosine and suppressive myeloid populations that attenuate cytotoxic T-cell responses. The CD73-adenosine-A2a/A2b receptor axis represents a key metabolic immune checkpoint; however, the relative contributions of tumor cell-intrinsic versus host-derived adenosine signaling to radiotherapy response remain incompletely defined. MethodsUsing orthotopic murine breast carcinoma models, we interrogated radiation-induced adenosine dynamics and downstream immune remodeling through quantitative adenosine measurements, bulk RNA sequencing, and multiparameter flow cytometry. Genetically engineered models were employed to dissect the roles of tumor-derived CD73 and host A2a/A2b receptors in regulating radiosensitivity. Therapeutic studies evaluated combinatorial targeting of CD73 and A2a/A2b receptors with radiotherapy and anti-PD-1, followed by comprehensive immune profiling in breast carcinomas. ResultsTumor cell-intrinsic CD73 and host A2A receptor signaling cooperatively drive radioresistance and tumor progression. Radiotherapy induces a rapid surge in intratumoral adenosine, triggering transcriptional and cellular programs consistent with myeloid-mediated immunosuppression and lymphocyte dysfunction. Although T-cell infiltration increases at later time point post-irradiation, effector function remains constrained. Pharmacologic inhibition of CD73 and A2a/A2b receptors partially restores T-cell functionality but is insufficient for durable tumor control as monotherapy. In contrast, concurrent blockade of adenosine signaling during radiotherapy, followed by adjuvant PD-1 inhibition, amplifies adaptive antitumor immunity and significantly enhances tumor control. ConclusionsThese findings define a mechanistic link between radiation-induced adenosine signaling and immune dysfunction in the TME. Targeting the CD73-A2a/A2b axis in combination with radiotherapy and checkpoint blockade represents a rational strategy to overcome radioresistance and improve antitumor immunity. STATEMENT OF SIGNIFICANCEThe tumor and immune cell contributions to adenosine signaling play a central role in shaping the therapeutic outcomes of tumor irradiation. Therapeutic targeting of the adenosine signaling axis improves radiosensitivity and efficacy of checkpoint blockade.

cancer biology↗

bioRxiv2024

Meta-analyses of mouse and human prostate single-cell transcriptomes reveal widespread epithelial plasticity in tissue regression, regeneration, and cancer

Recent advances in single-cell RNA-sequencing (scRNA-seq) technology have facilitated studies of cell states and plasticity in tissue maintenance and cancer, including in the prostate. Here we present meta-analyses of multiple new and published scRNA-seq datasets to establish reference cell type classifications for the normal mouse and human prostate. Our analyses demonstrate transcriptomic similarities between epithelial cell states in the normal prostate, in the regressed prostate after androgen-deprivation, and in primary prostate tumors. During regression in the mouse prostate, all epithelial cells shift their expression profiles towards a proximal periurethral (PrU) state, demonstrating an androgen-dependent plasticity that is restored to normal during androgen restoration and regeneration. In the human prostate, we find progressive rewiring of transcriptional programs across epithelial cell types in benign prostate hyperplasia and treatment-naive prostate cancer. Notably, we detect copy number variants predominantly within Luminal Acinar cells in prostate tumors, suggesting a bias in their cell type of origin, as well as a larger field of transcriptomic alterations in non-tumor cells. Finally, we observe that Luminal Acinar tumor cells in treatment-naive prostate cancer display heterogeneous androgen receptor (AR) signaling activity, including a split between high-AR and low-AR profiles with similarity to PrU-like states. Taken together, our analyses of cellular heterogeneity and plasticity provide important translational insights into the origin and treatment response of prostate cancer.

cancer biology↗

bioRxiv2022

Phenotypic dissection of epithelial lineages and therapeutic manipulation of differentiation programs in human Adenoid Cystic Carcinomas

Adenoid Cystic Carcinoma (ACC) is a rare and aggressive form of salivary gland cancer, characterized by the co-existence within tumor tissues of two distinct populations of malignant cells, phenotypically similar to the myoepithelial and ductal lineages of normal salivary glands. Using a novel computational approach for single-cell RNA-seq analysis, we identified two cell-surface markers (CD49f, KIT) that enable the differential purification of myoepithelial-like (CD49fhigh/KITneg) and ductal-like (CD49flow/KIT+) cells from ACC patient derived xenografts (PDX). Using prospective xeno-transplantation experiments, we demonstrate that myoepithelial-like cells act as progenitors of ductal-like cells. Using three-dimensional (3D) organoid cultures, we demonstrate that agonists of retinoic acid (RA) signaling promote differentiation of myoepithelial-like cells into ductal-like cells, while inhibitors of RA signaling selectively kill ductal-like cells. Finally, we demonstrate that BMS493, an inverse agonist of RA signaling, can be successfully leveraged for the in vivo treatment of human ACCs.

cancer biology↗

bioRxiv2020

A single-cell atlas of the mouse and human prostate reveals heterogeneity and conservation of epithelial progenitors

Understanding the cellular constituents of the prostate is essential for identifying the cell of origin for benign prostatic hyperplasia and prostate adenocarcinoma. Here we describe a comprehensive single-cell atlas of the adult mouse prostate epithelium, which demonstrates extensive heterogeneity. We observe distinct lobe-specific luminal epithelial populations (LumA, LumD, LumL, and LumV) in the distal region of the four prostate lobes, a proximally-enriched luminal population (LumP) that is not lobe-specific, as well as a periurethral population (PrU) that shares both basal and luminal features. Functional analyses suggest that LumP and PrU cells have multipotent progenitor activity in organoid formation and tissue reconstitution assays. Furthermore, we show that mouse distal and proximal luminal cells are most similar to human acinar and ductal populations, that a PrU-like population is conserved between species, and that the mouse lateral prostate is most similar to the human peripheral zone. Our findings elucidate new prostate epithelial progenitors, and help resolve long-standing questions about the anatomical relationships between the mouse and human prostate.

developmental biology↗

bioRxiv2018

Quasi-universality in single-cell sequencing data

The development of single-cell technologies provides the opportunity to identify new cellular states and reconstruct novel cell-to-cell relationships. Applications range from understanding the transcriptional and epigenetic processes involved in metazoan development to characterizing distinct cells types in heterogeneous populations like cancers or immune cells. However, analysis of the data is impeded by its unknown intrinsic biological and technical variability together with its sparseness; these factors complicate the identification of true biological signals amidst artifact and noise. Here we show that, across technologies, roughly 95% of the eigenvalues derived from each single-cell data set can be described by universal distributions predicted by Random Matrix Theory. Interestingly, 5% of the spectrum shows deviations from these distributions and present a phenomenon known as eigenvector localization, where information tightly concentrates in groups of cells. Some of the localized eigenvectors reflect underlying biological signal, and some are simply a consequence of the sparsity of single cell data; roughly 3% is artifactual. Based on the universal distributions and a technique for detecting sparsity induced localization, we present a strategy to identify the residual 2% of directions that encode biological information and thereby denoise single-cell data. We demonstrate the effectiveness of this approach by comparing with standard single-cell data analysis techniques in a variety of examples with marked cell populations.

systems biology↗