Biology subjects

Strell, C.

Publications and source records attributed to Strell, C..

6 recordsLinked to original sources

bioRxiv2025

A comprehensive molecular atlas of the cell types in the mouse liver

The liver plays a crucial role in essential physiological processes, and its impaired function due to liver fibrosis from various causes is an increasingly significant health issue. The livers functionality relies on the precise arrangement of its cellular structures, yet the molecular architecture of these units remains only partially understood. We created a comprehensive molecular atlas detailing all the major cell types present in the adult mouse liver through deep single-cell RNA sequencing. Our analysis offers new insights into hepatic endothelial and mesenchymal cells, specifically highlighting the differences between the cells of the periportal microvasculature, the sinusoids, and the portal vein, the latter exhibiting a mixed arterio-venous phenotype. We identified distinct subpopulations of hepatic stellate cells, fibroblasts, and vascular mural cells located in different anatomical regions. Comparisons with transcriptomic data from disease models indicate that a previously unrecognized capsular population of hepatic stellate cells expands in response to fibrotic disease. Our findings reveal that various fibroblast subpopulations respond differently to pathological insults. This data resource will be invaluable for advancing therapeutic interventions targeting hepatic diseases.

cell biology↗

bioRxiv2025

TCR clonality and TCR clonal expansion in the in situ microenvironment of non-small cell lung cancer

T-cell activation and clonal expansion are essential for the efficacy of immunotherapy in non-small cell lung cancer (NSCLC) patients. Since the distribution of T-cell clones might provide insights into immunogenic mechanisms, we determined the /{beta} TCR clonality using RNA-sequencing from frozen tumor tissue of 182 NSCLC patients and paired the results with extensive in situ image and sequence analyses of the immune microenvironment of NSCLC. TCR clonality (Gini index) patterns ranged from high T-cell clone diversity with high evenness (Gini index low) to clonal dominance with low evenness (Gini index high). TCR clonality in cancer tissue was lower than in matched normal lung (p=0.021). High Gini index correlated strongly with distinct mutations (EGFR, P53), tumor mutation burden (p<0.001), and inflamed tumor phenotypes (PRF1, GZMA, GZMB, INFG) with exhaustion signatures (LAG3, TIGIT, IDO1, PD-1, PD-L1). Correspondingly, PD-1+, CD3+, CD8A+, CD163+, and CD138+ immune cells infiltrated cancer tissue with high TCR clonality. In situ sequencing revealed that dominant T-cell clones were more often of CD8-subtype and tended to approximate the tumor cell compartment (p<0.03). In a checkpoint inhibitor-treated NSCLC patient cohort, high TCR clonality was associated with therapy response (p=0.016) and prolonged survival (p=0.003, median survival 13.8 vs 2.9 months). Our robust analysis pipeline revealed diverse TCR repertoires related to genotypes and immune phenotypes. The in situ positioning of expanded T-cell clones indicated functional impact, which was clinically confirmed in NSCLC patients receiving immunotherapy. One sentence summaryT-cell clone expansion in NSCLC is associated with genetic mutations, immune phenotypes, immunotherapy response, and patient survival.

cancer biology↗

bioRxiv2024

A distinctive tumor compartment in pancreatic lobules defined by nascent stroma and classical tumor cell phenotype

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive tumor type characterized by a particularly extensive stroma. While different types of cancer-associated fibroblasts (CAFs) in this desmoplastic stroma have been described, areas of early invasion and nascent stroma are understudied. Here, we identify a distinctive PDAC niche within the pancreatic lobules, a compartment dominated by pancreatic exocrine cells and slender stroma. Cellular interaction profiling using machine learning on whole slide images of human PDAC reveals that the tumor invasion front in the lobules is dominated by specific interactions of tumor cells and exocrine cells that have undergone acinar-to-ductal metaplasia (ADM). Multiplex protein and mRNA stains confirm that tumor growth in the lobules is closely linked to ADM in the lobules, and reveal stromal protein gradients from the gracile lobular stroma to the characteristic desmoplastic stroma. We identify nascent CAFs (nCAFs), co-expressing expressing nerve growth factor receptor (NGFR) and platelet-derived growth factor receptor alpha (PDGFRa) that are absent in the mature, desmoplastic stroma. Lobular invasion and nCAFs are intertwined with phenotypic changes of the cancer cells, such that tumor cells in lobules express classical subtype markers, while those embedded in the desmoplastic are on the basal end of the phenotypic continuum. In mice, the PDAC subtype - basal or classical - similarly depends on tissue location, suggesting microenvironmental factors rather than clonal selection as important drivers of tumor phenotype identity. Clinically, our results mandate factoring in tumor tissue location when calling PDAC subtypes. Biologically, they identify pancreatic lobules as a distinctive tissue niche associated with nascent stroma, and they suggest that lobular colonization by tumor cells is a significant route of PDAC progression.

cancer biology↗

bioRxiv2021

PoSTcode: Probabilistic image-based spatial transcriptomics decoder

Realising the full potential of novel image-based spatial transcriptomic (IST) technologies requires robust and accurate algorithms for decoding the hundreds of thousand fluorescent signals each derived from single molecules of mRNA. In this paper, we introduce PoSTcode, a probabilistic method for transcript decoding from cyclic multi-channel images, whose effectiveness is demonstrated on multiple large-scale datasets generated using different versions of the in situ sequencing protocols. PoSTcode is based on a re-parametrised matrix-variate Gaussian mixture model designed to account for correlated noise across fluorescence channels and imaging cycles. PoSTcode is shown to recover up to 50% more confidently decoded molecules while simultaneously decreasing transcript mislabeling when compared to existing decoding techniques. In addition, we demonstrate its increased stability to various types of noise and tuning parameters, which makes this new approach reliable and easy to use in practice. Lastly, we show that PoSTcode produces fewer doublet signals compared to a pixel-based decoding algorithm.

bioinformatics↗

bioRxiv2021

Spatial genomics maps the structure, character and evolution of cancer clones

Subclonality is a universal feature of cancers yet how clones grow, are spatially organised, differ phenotypically or influence clinical outcome is unclear. To address this, we developed base specific in situ sequencing (BaSISS). In fixed tissues, transcripts harbouring clone-defining mutations are detected, converted into quantitative clone maps and characterised through multi-layered data integration. Applied to 8 samples from key stages of breast cancer progression BaSISS localised 1.42 million genotype informative transcripts across 4.9cm2 of tissue. Microscopic clonal topographies are shaped by resident tissue architectures. Distinct transcriptional, histological and immunological features distinguish coexistent genetic clones. Spatial lineage tracing temporally orders clone features associated with the emergence of aggressive clinical traits. These results highlight the pivotal role of spatial genomics in deciphering the mechanisms underlying cancer progression.

cancer biology↗

bioRxiv2021

Basal-to-classical phenotypic switch of pancreatic cancer cells upon integration into the duodenal epithelium

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive solid tumors. Based on transcriptomic classifiers, basal-like and classical PDAC subtypes can be defined that differ in prognosis. Single-cell sequencing has recently revealed that these subtypes coexist in individual tumors. However, the contribution of either clonal heterogeneity or microenvironmental cues to subtype heterogeneity is unclear. Here, we report the tumor phenotype dynamics in a cohort of patients in whom PDAC infiltrated the duodenal wall. Using multiplex immunohistochemistry, we show that PDAC cells revert to non-destructive growth and undergo differentiation towards the classical subtype upon integration into the duodenal epithelium. Our results tightly link microenvironmental cues to the PDAC molecular subtype and open the door to a systematic investigation of microenvironmental control in human pancreatic cancer.

cancer biology↗