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Quist, J.

Publications and source records attributed to Quist, J..

3 recordsLinked to original sources

Lactate Blocks Tertiary Lymphoid Structure Formation by Inhibiting B Cell Chemotaxis

Tertiary lymphoid structures (TLS) and B cell infiltration are strong predictors of immunotherapy success across cancers, including triple-negative breast cancer (TNBC). However, immune-cold TNBCs often lack both features. Here, we identify a tumor-intrinsic mechanism that actively suppresses B cell recruitment. Despite evidence of B cell responses in cancer-associated lymph nodes (cLNs), B cells fail to infiltrate TNBC tumors or form TLS. This exclusion is not simply due to chemokine deficiency as exogenous chemokine addition fails to restore B cell migration. Using fractionation and metabolic profiling, we identify lactate as a dominant tumor-secreted metabolite that directly impairs B cell chemotaxis by disrupting mitochondrial metabolism. In vivo, combining lactate inhibition with engineered chemokine secretion promotes cLN-derived B cell infiltration and enables TLS formation, particularly when coupled with CD40 stimulation. Transcriptomics analyses across several human cancer datasets strengthen the association between high glycolytic activity with poor B-cell infiltration in chemokine-rich tumors. Together, our findings reveal lactate as a key metabolic barrier to B cell trafficking and TLS induction, suggesting that metabolic reprogramming may provide an avenue to convert "immune-cold" tumors into TLS-rich, immunologically responsive microenvironments.

cancer biology↗

SMART: A Spatio-Molecular Atlas of Response Trajectories in Triple-Negative Breast Cancer

A major challenge in treating Triple-Negative Breast Cancer (TNBC) lies in its molecular, morphological and clinical heterogeneity, which hampers accurate prediction of responses to neoadjuvant treatment. To address this, we introduce SMART: Spatio-Molecular Atlas of Response Trajectories, a comprehensive, multimodal resource compiled from 129 TNBC samples across 89 patients, obtained before, during, and after neoadjuvant chemotherapy (NACT). SMART comprises of 5,096 high quality manually selected spatial transcriptomic profiles enriched for epithelial, immune, or stromal compartments; paralleled with histological annotations, imagebased network analysis and protein expression. Seven novel spatial epithelial archetypes (EAs), seven tumour-immune microenvironments (TIMEs) and their co-localisation patterns were defined, revealing an opposing prevalence of functionally divergent EAs between response groups and the prognostic significance of B-cell enriched TIMEs, in particular those surrounding histologically normal epithelium adjacent to the tumour. The SMART dataset and analytical tools are publicly available via the PharosAI platform, providing the research community with the most comprehensive, manually annotated spatio-molecular transcriptomics atlas of NACT-treated TNBC to date.

cancer biology↗

NoButter: An R package for reducing transcript dis-persion in CosMx Spatial Molecular Imaging Data

MotivationAdvances in spatial transcriptomics technologies at single-cell resolution have high-lighted the need for innovative quality assessment approaches and improved analytical tools. Imaging-based spatial transcriptomics technologies, such as the CosMx Spatial Molecular Imager (SMI), provide the location and abundance of transcripts through multifocal imaging. Optical sections (or Z-slices) form a Z-stack that represents the tissue depth. Transcript dispersion can be observed across these Z-slice and introduce considerable levels of technical noise to the data that can negatively impact downstream analysis. Package FunctionalityNoButter is an R package designed to evaluate transcript dispersion in CosMx SMI spatial transcriptomics data. Using the raw data, the transcript distribution is assessed for each Z-slice of a Z-stack across multiple fields of views (FOVs). To systematically identify transcript dispersion, the percentage of transcripts located outside cell boundaries is calculated. Z-slices exhibiting high levels of transcript dispersion can be excluded, while high-confidence transcripts are preserved. Usage ScenarioTo demonstrate the functionalities of NoButter, spatial transcriptomics data was generated using the CosMx SMI for lymph node tissue, a lung sample, and two triple-negative breast cancers (TNBCs). Use cases illustrate substantial transcript dispersion in optical planes closer to the glass slide. In these Z-slices, on average, an additional 10% of the transcripts were discarded using NoButter. Cleaning such Z-slices with high dispersion rates reduces technical noise and improves the overall quality of the spatial transcriptomics data. AvailabilityThe package can be accessed at https://github.com/cancerbioinformatics/NoButter.

bioinformatics↗