Biology subjects

Garcia, S. G.

Publications and source records attributed to Garcia, S. G..

3 recordsLinked to original sources

bioRxiv2026

Fluorescence-based sorting of extracellular vesicles enables detection and omics

Extracellular vesicles (EVs) are nanosized, lipid bilayer-enclosed particles that mediate intercellular communication and hold considerable promise as biomarkers and therapeutic agents. However, their functional heterogeneity remains incompletely understood, largely due to the absence of reliable methods for isolating specific EV subpopulations. Here, we established a Nanoscale Flow sorting (NanoFACS) workflow and evaluated its potential for EV detection, sorting, and molecular characterization. We assessed critical parameters, including fluorescent staining and labeling approaches, background signal discrimination, dilution and flow-rate effects, and scatter triggering. We achieved high-purity sorting of CFSE-stained and antibody-labeled EVs, preserving vesicle integrity and sufficient RNA yields for small RNA sequencing of sorted populations. We identified EV subtype-specific small RNAs despite partial cargo overlap in single-marker sorted populations. Our results establish a reproducible antibody-based NanoFACS workflow that defines key operational parameters for reliable EV detection and sorting, with potential adaptability across conventional and spectral flow cytometry platforms. By reducing background and non-EV-associated events, the workflow enables the isolation of phenotypically defined EV subpopulations suitable for downstream molecular analysis, providing a practical approach to investigate EV heterogeneity.

cell biology↗

bioRxiv2026

Molecular Characterization of the Progressive Landscape of Depression

Major Depressive Disorder (MDD) frequently follows a recurrent trajectory of episodes and remissions, often culminating in treatment-resistance. Molecular differences defining state-specific changes during episode and remission have been explored. However, progressive differences--defined here as cross-sectional linear trends across clinical stages from first to recurrent episodes or remissions, reflecting increasing illness burden over time--remain poorly understood, limiting sustained therapeutic outcomes. Here, we analyzed RNA-seq data from postmortem sgACC to identify progressive differences across MDD episodes or remission relative to state-specific differences, using an integrative assessment of molecular and cellular specificity, genetic-risk, disease-comorbidity and potential therapeutic targets. Differential expression analysis showed greater overlap between progressive and state-specific differences during remission than episode. Pathway enrichment highlighted disruptions in extracellular-matrix pathways shared by state-specific and progressive episodes, while metabolic and catalytic pathways were restored during remission. Cell-type-specific analyses showed that progressive changes were linked to superficial-layer intra-telencephalic neurons, whereas state-specific changes were enriched in pyramidal neuron subtypes and deeper layer SST-positive interneurons. Genome-wide association-informed enrichment analysis further linked these transcriptomic changes to genetic risk factors and symptom dimensions. Anhedonia was associated with both state-specific episode and progressive-remission signatures, suggesting that it is a persistent trait-like feature of MDD. Finally, an integrative pharmacological analysis revealed shared molecular mechanisms between pro-disease and therapeutic targets, highlighting pleiotropic effects of key pathways depending on disease state and dosage. Together, these findings provide a novel perspective on biological underpinnings of MDD progression over episodes or remissions and identify pharmacological targets that account for pathological and/or compensatory/therapeutic processes.

neuroscience↗

bioRxiv2021

Photoimmunotherapy retains its anti-tumor efficacy with increasing stromal content in heterotypic pancreatic cancer spheroids

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease characterized by increased levels of desmoplasia that contributes to reduced drug delivery and poor treatment outcomes. In PDAC, the stromal content can account for up to 90% of the total tumor volume. The complex interplay between stromal components, including pancreatic cancer associated fibroblasts (PCAFs), and PDAC cells in the tumor microenvironment (TME) have a significant impact on prognoses and thus needs to be recapitulated in vitro when evaluating various treatment strategies. This study is a systematic evaluation of photodynamic therapy (PDT) in 3D heterotypic coculture models of PDAC with varying ratios of patient derived PCAFs that simulate heterogenous PDAC tumors with increasing stromal content. The efficacy of antibody-targeted PDT (photoimmunotherapy; PIT) using cetuximab photoimmunoconjugates (PICs) of benzoporphyrin derivative (BPD) is contrasted with that of liposomal BPD (Visudyne(R)), which is currently in PDT clinical trials for PDAC. We demonstrate that both Visudyne(R)-PDT and PIT were effective in heterotypic PDAC 3D spheroids with a low stromal content. However, as the stromal content increases above 50% in the 3D spheroids, the efficacy of Visudyne(R)-PDT is reduced by up to 10-fold, while PIT retains its efficacy. PIT was found to be 10-fold, 19-fold and 14-fold more phototoxic in spheroids with 50%, 75% and 90% PCAFs, respectively, as compared to Visudyne(R)-PDT. This marked difference in efficacy is attributed to the ability of PICs to penetrate and distribute within spheroids with a higher stromal content, whereas Visudyne(R) is restricted to the spheroid periphery. This study thus demonstrates how the stromal content in PDAC spheroids directly impacts their responsiveness to PDT and proposes PIT to be a highly suited treatment option for desmoplastic tumors with particularly high degrees of stromal content.

cancer biology↗