Biology subjects

Heidegger, I.

Publications and source records attributed to Heidegger, I..

3 recordsLinked to original sources

bioRxiv2025

Optimised dissociation and multimodal profiling of prostate cancer stroma reveal fibromuscular cell heterogeneity with clinical correlates

BackgroundDynamic remodelling of the tumour microenvironment (TME) plays a central role in prostate cancer (PCa) progression, immune evasion and therapy resistance. However, the co-existence of both tumour-promoting and tumour-restraining stromal elements necessitates extensive characterisation of the TME for effective targeting. Fibromuscular cell heterogeneity in PCa remains poorly characterised, in part due to challenges in isolating cells embedded within the desmoplastic stroma. This study therefore aimed to better characterise fibroblast and smooth muscle cell (SMC) populations as the major tissue-resident stromal cell subtypes within the PCa TME. MethodsA PCa single-cell RNA sequencing (scRNA-seq) dataset was re-analysed to define fibromuscular subtypes. Due to low fibroblast yields, an optimised tissue dissociation protocol was developed and benchmarked against two commercial kits via flow cytometry, immunostaining of clinical specimens and ex vivo culture. Dimensionality reduction and clustering were applied to the CD31- stromal fraction using a multiparameter surface marker panel. Annotation of the resulting clusters based on their surface marker profile was supported by integrating scRNA-seq and immuno-histological findings. ResultsThe optimised protocol yielded over twice the viable cells/mg tissue compared to two commercial kits, preserved surface marker integrity, enhanced successful cultivation of mesenchymal cells and recovered diverse stromal subpopulations from benign and malignant samples. Dimensionality reduction and clustering of flow cytometry counts identified 11 distinct CD31- stromal populations. Integration with transcriptomic data and immunofluorescence of clinical specimens identified spatially- and prognostically-distinct fibroblast subtypes, including inflammatory and myofibroblastic cancer-associated fibroblasts, pericytes linked to poor prognosis and a novel SMC subset associated with stromal activation. ConclusionThis study presents a robust workflow for improved isolation and characterisation of fibromuscular stromal cells in PCa. The multimodal approach enabled refined characterisation of phenotypically distinct and clinically-relevant stromal subpopulations within their spatial context providing a foundation for future TME-targeted therapies.

cancer biology↗

bioRxiv2023

Comparative Analysis of Whole Transcriptome Single-Cell Sequencing Technologies in Complex Tissues

The development of single-cell omics tools has enabled scientists to study the tumor microenvironment (TME) in unprecedented detail. However, each of the different techniques may have its unique strengths and limitations. Here we directly compared two commercially available high-throughput single-cell RNA sequencing (scRNA-seq) technologies - droplet-based 10X Chromium vs. microwell-based BD Rhapsody - using paired samples from patients with localized prostate cancer (PCa) undergoing a radical prostatectomy. Although high technical consistency was observed in unraveling the whole transcriptome, the relative abundance of cell populations differed. Cells with low-mRNA content such as T cells were underrepresented in the droplet-based system, at least partly due to lower RNA capture rates. In contrast, microwell based scRNA-seq recovered less cells of epithelial origin. Moreover, we discovered platform-dependent variabilities in mRNA quantification and cell-type marker annotation. Overall, our study provides important information for selection of the appropriate scRNA-seq platform and for the interpretation of published results. SYNOPSISO_LIComparison of scRNA-seq protocols uncovers disparities in RNA-to-library conversion C_LIO_LIMicrowell-based scRNA-seq technology excels in capturing low-mRNA content cells C_LIO_LIBiased transcriptomes due to gene specific RNA detection efficacies by both platforms C_LIO_LIThe study guides in informed scRNA-seq platform selection and data interpretation C_LI

cancer biology↗

bioRxiv2022

STAT3 restricts prostate cancer metastasis and antiandrogen resistance by controlling LKB1/CREB signaling pathway

Prostate cancer (PCa) lethality is driven by its progression to a metastatic castration-resistant state, yet the signaling mechanisms underlying metastatic spread remain unknown. Here we show that STAT3 converges with the LKB1/mTORC1 and CREB to control metastatic disease in PCa mouse models. Unexpectedly, STAT3 was found to be upregulated in diabetic PCa patients undergoing metformin therapy with a concomitant reduction in mTORC1 expression. In preclinical mouse models of PCa, genetic ablation or activation of STAT3 had opposing effects on LKB1/AMPK/mTORC1- dependent tumorigenesis. Using genetic and pharmacological approaches, we identified LKB1 as a direct STAT3 target while repressing CREB. Furthermore, PCa patients with high CREB expression had inferior clinical outcome with significantly increased risk of disease and metastatic recurrence. We observe that castration state lowers STAT3 abundance and increases AR and CREB levels, leading to castration-resistant PCa (CRPC). Our findings revealed that STAT3 controls mTORC1 and CREB in metastatic disease, suggesting CREB as a promising target for lethal CRPC.

cancer biology↗