Biology subjects

Schmolze, D.

Publications and source records attributed to Schmolze, D..

5 recordsLinked to original sources

bioRxiv2026

Spatial context of cellular heterogeneity in triple-negative breast cancer reveals actionable subtypes

Triple-negative breast cancer (TNBC) is an aggressive, heterogeneous disease with limited targeted treatment options. Leveraging bulk and spatial transcriptomics and cellular mapping of breast tissue from a large patient cohort, we identified three reproducible TNBC ecosystem subtypes that encode distinct spatial tumor-microenvironment architectures and clinically relevant treatment-response phenotype. Our analyses define: (1) an immune-exhausted subtype associated with immune checkpoint therapy (ICT); (2) a highly fibrotic/hypoxic subtype; and (3) a metabolically reprogrammed subtype characterized by nuclear-receptor and fatty-acid signaling. Spatial profiling further revealed subtype-specific organization of epithelial, immune, and stromal programs across tumor centers and invasive edges. Multiplexed imaging independently supported the contrasting immune-infiltrated and stromal-excluded architectures of the immune-engaged and fibrotic subtypes. The unique markers associated with the subtypes also provide the basis for subtyping and candidate therapeutic vulnerabilities. Our study provides a robust framework for personalized medicine, highlighting that targeting specific spatio-cellular architectures is critical to improving clinical outcomes.

cancer biology↗

bioRxiv2026

Spatial Landscape of Pregnancy-Associated Triple Negative Breast Cancer and Mammary Gland Involution

Pregnancy-associated triple negative breast cancer (PA-TNBC) is one of the highest-risk breast cancers, marked by an aggressive phenotype that lacks targeted treatment options. Studies have shown that post-lactational mammary gland involution plays a role in this increased risk. To delineate the underlying mechanisms, our study characterized the transcriptional state of the epithelia and surrounding microenvironment in women with PA-TNBC, comparing those diagnosed pre-involution (PRE) and post-involution (POST, <3 years after delivery). Spatial transcriptomics using the GeoMx Digital Spatial Profiler was performed on treatment-naive PA-TNBC tissues from 33 women (10 PRE, 23 POST). Regions of interest were segmented with pan-cytokeratin staining. We found that the most prominent transcriptional differences between PRE and POST epithelia occurred in the adjacent non-invasive regions and during the transition into invasive TNBC. POST non-invasive epithelia uniquely showed inflammatory and developmental pathway activation, while the transition into TNBC involved increased chromatin remodeling and cell migration pathways. Further, the tumor microenvironment (TME) in POST showed the highest proportion of immune cells and the highest prevalence of tumor- and immune exhaustion-associated cell states. Finally, a pseudotime analysis of POST transcriptional dynamics found that women diagnosed 1-2 years after delivery exhibited the strongest evidence for inflammatory signaling across the tissue. Our results highlight biological mechanisms distinguishing PRE and POST PA-TNBC across tissue regions and cell types. We emphasize the importance of early detection of malignant molecular signatures in morphologically normal epithelium in post-involution women and suggest that targeting the TME may improve treatment efficacy in post-involution PA-TNBC.

cancer biology↗

bioRxiv2025

Spatially distinct cellular and molecular landscapes define prognosis in triple negative breast cancer

BackgroundTriple-negative breast cancer is a prevalent breast cancer subtype with the lowest 5-year survival. Several factors contribute to its treatment response, but the inherent molecular and cellular tumor heterogeneity are increasingly acknowledged as crucial determinants. MethodsSpatial transcriptomic profiling was performed on FFPE tissues from a retrospective, treatment-naive group of women with differential prognoses (17 with >15 years survival-good prognosis (GPx) and 15 with <3 years survival-poor prognosis (PPx)) using GeoMX(R) Digital Spatial Profiler. Regions of interest were segmented on pan-cytokeratin and analyzed for tumor and stromal components, probed using GeoMx human whole transcriptome atlas (WTA) panel. Data quality control, normalization, and differential analysis was performed in R using GeomxTools and linear mixed models. Additional analyses including cell-type deconvolution, spatial entropy, functional enrichment, TF-target / ligand-receptor analysis and convolution neural networks were employed to identify significant gene signatures contributing to differential prognosis. ResultsHere we report on the spatial and molecular heterogeneity underlying differential prognosis. We observe that the state of the epithelia and its microenvironment (TME) are transcriptionally distinct between the two groups. Invasive epithelia in GPx show a significant increase in immune transcripts with the TME exhibiting increased immune cell presence (via IF), while in PPx they are more metabolically and translationally active, with the TME being more mesenchymal/fibrotic. Specifically, pre-cancerous epithelia in PPx display a prescience of aggressiveness as evidenced by increased EMT-signaling. We identify distinct epithelial gene signatures for PPx and GPx, that can, with high accuracy, classify samples at the time of diagnosis and likely inform therapy. ConclusionsTo the best of our knowledge, this is the first study to leverage spatial transcriptomics for an in-depth delineation of the cellular and molecular underpinnings of differential prognosis in TNBC. Our study highlights the potential of spatial transcriptomics to not only uncover the molecular drivers of differential prognosis in TNBC but also to pave the way for precision diagnostics and tailored therapeutic strategies, transforming the clinical landscape for this aggressive breast cancer subtype.

cancer biology↗

bioRxiv2022

Profile of the somatic mutational landscape in breast tumors from Hispanic/Latina women

Breast cancer causes the most cancer deaths among Hispanic/Latinas (H/L). However, limited tumor-sequencing data from H/L are available to guide treatment. To address this gap, we performed whole-exome sequencing of DNA from 140 HL germline and 146 matched breast tumors and RNA-seq for the tumors. We generated somatic-mutation profiles, identified copy-number alterations (CNAs), and compared results to non-Hispanic White (White) women in The Cancer Genome Atlas. Similar to Whites, PIK3CA and TP53 were the most commonly mutated genes in breast tumors from H/L. We found 4 common COSMIC mutation signatures (1, 2, 3, 13) and signature 16 not previously reported in other breast-cancer datasets. We observed recurrent amplifications in breast-cancer drivers including MYC, FGFR1, CCND1, and ERBB2, and a recurrent amplification on 17q11.2 associated with high KIAA0100 gene expression, implicated in breast-cancer aggressiveness. Expanded research is required to determine how these characteristics of H/L tumors impact treatment response and survival.

cancer biology↗

bioRxiv2019

Fractal dimension, occupancy and hotspot analyses of B cell spatial distribution predict clinical outcome in breast cancer

While the density of tumor-infiltrating lymphocytes (TILs) is now well known to correlate with clinical outcome, the clinical significance of spatial distribution of TILs is not well characterized. We have developed novel statistical techniques (including fractal dimension differences, a hotspot analysis, a box counting method that we call occupancy and a way to normalize cell density that we call thinning) to analyze the spatial distribution (at different length scales) of various types of TILs in triple negative breast tumors. Consistent with prior reports, the density of CD20+ B cells within tumors is not correlated with clinical outcome. However, we found that their spatial distribution differs significantly between good clinical outcome (no recurrence within at least 5 years of diagnosis) and poor clinical outcome (recurrence with 3 years of diagnosis). Furthermore, CD20+ B cells are more spatially dispersed in good outcome tumors and are more likely to infiltrate into cancer cell islands. Lastly, we found significant correlation between the spatial distributions of CD20+ B cells and CD8+ (cytotoxic) T cells (as well as CD3+ T cells), regardless of outcome. These results highlight the significance of the spatial distribution of TILs, especially B cells, within tumors.\n\nSignificance StatementImmune cells can fight cancer. For example, a patient has a good prognosis when a high density of killer T cells, a type of immune cell that can kill cancer cells, infiltrates into a tumor. However, there is no clear association between prognosis and the density of B cells, another type of immune cell, in a tumor. We developed several statistical techniques to go beyond cell density and look at the spatial distribution, i.e., the pattern or arrangement of immune cells, in tumors that have been removed from patients with triple negative breast cancer. We find that B cells and killer T cells tend to be more spread out in the tumors of patients whose cancer did not recur.

cancer biology↗