Biology subjects

Spasic, M.

Publications and source records attributed to Spasic, M..

4 recordsLinked to original sources

bioRxiv2026

A Single-Cell Peripheral Immune Atlas Spanning High-Risk Lesions to Invasive Breast Cancer in Black and White Women

Black women are at risk for breast cancer nearly a decade before women of other racial groups for unclear reasons. Because immune responses influence cancer initiation and progression, we performed single-cell RNA sequencing of peripheral blood mononuclear cells from non-Hispanic Black (NHB) and non-Hispanic White (NHW) women with high-risk breast lesions, ductal carcinoma in-situ, and invasive breast cancer. Race-associated transcriptional differences were observed across all disease states and were most pronounced in invasive disease. Computational analyses, supported by flow cytometric protein analysis, revealed enrichment of chronic inflammation, immune regulatory programs, and immune aging pathways in NHB cancer patients, particularly in monocytes, dendritic cells, CD4+ T cells, and B cells. From these data, we derived a population-level immune signature (IMM-POP) comprising genes differentially enriched in this subset of immune cells from NHB breast cancer patients. IMM-POP correlates with an immunosuppressive signature in external breast cancer datasets. We thus provide a single-cell peripheral immune atlas integrating race and breast disease state. SignificanceThis study revealed race-specific peripheral immunity features in precancerous and invasive breast cancers: Black patients exhibited features of chronic inflammation and immune aging compared with White patients, suggesting immune weathering and providing insights for studying early onset of breast cancer in Black patients.

cancer biology↗

bioRxiv2025

Platelet-Mediated Suppression of T Cell Function Drives Immune Evasion in Triple Negative Breast Cancer through the P-Selectin / PSGL-1 Pathway

Immune checkpoint inhibitors (ICIs) have demonstrated clinical promise in triple-negative breast cancer (TNBC), yet their effectiveness is often limited by acquired resistance and immune refractoriness. This underscores the urgent need to improve strategies that restore or enhance anti-tumor immunity. Platelets--long recognized for their role in hemostasis--have emerged as key immunomodulators in cancer by interacting with circulating tumor cells, shielding them from sheer stress and immune clearance while actively promoting immune evasion. Here, we uncover a previously unrecognized immunoregulatory pathway whereby platelet-derived P-selectin engages P-selectin glycoprotein ligand-1 (PSGL-1) on T cells, triggering immunosuppressive signaling and promoting T-cell exhaustion. This interaction, identified using in vitro co-culture systems and validated in in vivo mouse models of TNBC, reveals a targetable form of platelet-mediated immune suppression that contributes to ICI resistance. PSGL-1, traditionally known for mediating leukocyte trafficking, functions here as an immune checkpoint receptor, further underscoring the therapeutic relevance of this axis. Together, our findings highlight the P-selectin-PSGL-1 interaction as a novel and targetable mechanism of immune evasion and provide preclinical evidence that its disruption may enhance ICI responsiveness and improve outcomes in TNBC. Key PointsO_LITumor-associated platelets (TAPs) exhaust T-cells through P-selectin/P-selectin glycoprotein ligand-1 binding C_LIO_LIPharmaceutical blockade of P-selectin using Crizanlizumab, prevents exhaustion and allows T-cell function C_LI

cancer biology↗

bioRxiv2025

Unpaired Image-to-Image Translation for Segmentation and Signal Unmixing

This work introduces Ui2i, a novel model for unpaired image-to-image translation, trained on content-wise unpaired datasets to enable style transfer across domains while preserving content. Building on CycleGAN, Ui2i incorporates key modifications to better disentangle content and style features, and preserve content integrity. Specifically, Ui2i employs U-Net-based generators with skip connections to propagate localized shallow features deep into the generator. Ui2i removes feature-based normalization layers from all modules and replaces them with approximate bidirectional spectral normalization--a parameter-based alternative that enhances training stability. To further support content preservation, channel and spatial attention mechanisms are integrated into the generators. Training is facilitated through image scale augmentation. Evaluation on two biomedical tasks--domain adaptation for nuclear segmentation in immunohistochemistry (IHC) images and unmixing of biological structures superimposed in single-channel immunofluorescence (IF) images--demonstrates Ui2is ability to preserve content fidelity in settings that demand more accurate structural preservation than typical translation tasks. To the best of our knowledge, Ui2i is the first approach capable of separating superimposed signals in IF images using real, unpaired training data.

bioinformatics↗

bioRxiv2021

SunCatcher: Clonal Barcoding with qPCR-Based Detection Enables Functional Analysis of Live Cells and Generation of Custom Combinations of Cells for Research and Discovery

Over recent decades, cell lineage tracing, clonal analyses, molecular barcoding, and single cell "omic" analysis methods have proven to be valuable tools for research and discovery. Here, we report a clonal molecular barcoding method, which we term SunCatcher, that enables longitudinal tracking and retrieval of live barcoded cells for further analysis. Briefly, single cell-derived clonal populations are generated from any complex cell population and each is infected with a unique, heritable molecular barcode. One can combine the barcoded clones to recreate the original parental cell population or generate custom pools of select clones, while also retaining stocks of each individual barcoded clone. We developed two different barcode deconvolution methods: a Next-Generation Sequencing method and a highly sensitive, accurate, rapid, and inexpensive quantitative PCR-based method for identifying and quantifying barcoded cells in vitro and in vivo. Because stocks of each individual clone are retained, one can analyze not only the positively selected clones but also the negatively selected clones result from any given experiment. We used SunCatcher to barcode individual clones from mouse and human breast cancer cell lines. Heterogeneous pools of barcoded cells reliably reproduced the original proliferation rates, tumor-forming capacity, and disease progression as the original parental cell lines. The SunCatcher PCR-based approach also proved highly effective for detecting and quantifying early spontaneous metastases from orthotopic sites that would otherwise have not been detected by conventional methods. We envision that SunCatcher can be applied to any cell-based studies and hope it proves a useful tool for the research community.

cancer biology↗