Biology subjects

Thalmann, G. N.

Publications and source records attributed to Thalmann, G. N..

6 recordsLinked to original sources

bioRxiv2026

Spatial single-cell proteomics defines multicellular niches in the primary prostate cancer microenvironment

Prostate cancer displays substantial clinical and histopathological heterogeneity which is not fully captured by conventional Gleason grading. To resolve the spatial and phenotypic complexity of the prostate tumor microenvironment, we performed imaging mass cytometry using a prostate-tailored 34-plex antibody panel on a clinically annotated tissue microarray cohort of 195 patients of primary stage disease after radical prostatectomy (523 regions of interest; 2.19 million cells). We identified 34 distinct cell types spanning epithelial, endothelial, stromal and immune compartments, and further organized into 18 epithelial-dominated, cancer associated fibroblast-dominated, and immune-rich spatial niches. Within the epithelial compartment, we detected an ERGp53 luminal population whose abundance is independently associated with poor overall and progression-free survival. In the stroma, we defined extracellular matrix remodeling-related cancer associated fibroblast and smooth muscle cell lineages, including a periglandular CD105high niche with strong stromal-immune connectivity that is selectively associated with worse clinical outcome. Finally, cumulative immune niche burden correlated with histological inflammation and stratifies for worse patient survival. Together, these data provide a spatially resolved single-cell atlas of primary PCa and reveal stromal-immune-epithelial niches with prognostic relevance beyond Gleason grade.

cancer biology↗

bioRxiv2023

Identifying drug sensitivity of multifocal primary prostate cancer

The pronounced intra-patient variability in multifocal primary prostate cancer (PCa) has curtailed the efficacy of current treatment options. Patient-derived organoids (PDOs) have emerged as a pivotal model for functional testing due to their capability to retain the histopathological and molecular characteristics of parental tissues, allowing timely acquisition of drug response outcomes. In our study, employing twin biopsies from multiple lesions with matched PDO models in vitro, we investigated the molecular heterogeneity of PCa, and how it is linked to in vitro PDO pharmacological heterogeneity. Our functional testing approach leverages PDOs to screen standard-of-care treatment and FDA-approved compounds for other malignancies, aiming to repurpose their use in PCa and explore alternatives to androgen deprivation therapy. By integrating gene expression data from parental tissue with drug response results from PDOs, we have established a transcriptomics-based drug prediction models. The machine learning-based prediction model can predict the experimental PDO response to a specific drug, for the majority of screened drugs. This study offers a preclinical approach to potentially procure drug prediction outcomes and validate them in PDO models, as a prior step to clinical trial investigations or for selection of targeted therapeutic options.

cancer biology↗

bioRxiv2023

Mechano-signaling of prostate tumor initiating cells facilitates their tropism to stiff metastatic niche

Analysis of clinical datasets indicate that cancer stem-like cells/tumor-initiating cells (CSCs/TICs) derived from prostate cancer (PCa) patients display an elevated expression of genes for cell-matrix interactions, cell adhesion proteins and of the putative mechanotransducer TAZ. Here we combined measurements on the cellular mechano-responses to matrix stiffness, including cell-generated forces, zebrafish and PDX-derived organoid models, to show that mechanotransduction serves as a key determinant for PCa CSC maintenance during metastatic onset. The {beta}1-integrin-ILK-CDC42-N-Wasp dependent cytoskeletal tension and TAZ nucleus-translocation mediate this mechano-signaling axis. As a result, expression of the stemness genes NANOG and OCT4 are induced, leading to metastatic tumor initiation. It is further demonstrated that pharmaceutical perturbation of this mechano-signaling using a novel YAP/TAZ inhibitor K975 constrains PCa metastasis in zebrafish, and development of PDX-derived organoids. Our data highlights the essential role of mechanotransduction in PCa aggressiveness, thereby underlying this pathway as a therapeutic target for future studies.

cancer biology↗

bioRxiv2022

Bladder cancer organoids as a functional system to model different disease stages and therapy response

Bladder Cancer (BLCa) inter-patient heterogeneity is considered the primary cause of tumor reoccurrence and treatment failure, suggesting that BLCa patients could benefit from a more personalized treatment approach. Patient-derived organoids (PDOs) have been successfully used as a functional model for predicting drug response in different cancer types. In our study, we established BLCa PDO cultures from different BLCa stages. BLCa PDOs preserve the histological and molecular heterogeneity of the parental tumors, including their multiclonal genetic landscapes. BLCa PDOs consistently share key genetic alterations detected in parental tumors, mirroring tumor evolution in longitudinal sampling. Our drug screening pipeline was implemented using BLCa PDOs, testing both standard-of-care and additional FDA-approved compounds for other solid tumors. Integrative analysis of drug response profiles with matched PDO genomic analysis was used to determine enrichment thresholds for candidate markers of therapy resistance and sensitivity. By assessing the clinical history of longitudinally sampled cases, the clonal evolution of the disease could be determined and matched with drug response profiles. In conclusion, we have developed a clinically relevant pipeline for drug response profile assessment and discovery of candidate markers of therapy resistance.

cancer biology↗

bioRxiv2020

Stroma transcriptomic and proteomic profile of prostate cancer metastasis xenograft models reveals conservation of bonemicroenvironment signatures

Prostate cancer (PCa) is the second leading cause of cancer-associated death in men with therapy resistance acquisition to androgen deprivation treatment and metastasis progression. Understanding the mechanisms of tumor progression to metastatic stage is necessary for the design of therapeutic and prognostic schemes. The main objective of the current study is to determine, using transcriptomic and proteomic analyses on patient derived-xenograft models, whether differentially aggressive PCa tumors predispose their microenvironment (stroma) to a metastatic gene expression pattern, and how this information could be applied in prognostics. Transcriptomic profiling (RNA Sequencing) was performed on PCa PDX models representing different disease stages; BM18 (androgen dependent bone metastasis) and LAPC9 (androgen independent bone metastasis). Using organism-specific reference databases, the human-specific transcriptome, representing the tumor, was identified and separated from the mouse-specific transcriptome (representing the contributing stroma counterpart) from the same PDX tumor samples. To identify proteome changes in the tumor (human) versus the stroma (mouse), we performed human and mouse cell separation using the MACS mouse depletion sorting kit, and subjected protein lysates to quantitative TMT labeling and mass spectrometry. We show that tenascin C is one of the most abundant stromal genes in bone metastasis PCa PDXs, is modulated by androgen levels in vivo and is highly expressed in castration resistant LAPC9 PDX compared to castration sensitive BM18 PDX. Tissue microarray of primary PCa samples (N=210) was used to evaluate the potential of TNC to act as a metastasis prognosis marker. Low number of TNC-positive cells were associated with statistically significant clinical progression to local recurrence or metastasis, compared to high TNC-positive group. Our data showed that metastatic PCa PDXs that differ in androgen sensitivity trigger a differential stroma response suggesting that stroma was influenced by tumor cues. Selected stromal markers of osteoblastic PCa induced bone metastases, were induced in the microenvironment of the host organism in metastatic xenografts, although implanted in a non-bone site, indicating a conserved mechanism of tumor cells to induce a stromal pre-metastatic signature with high potential prognostic or diagnostic value.

cancer biology↗

bioRxiv2020

Patient-derived xenografts and organoids model therapy response in prostate cancer

Therapy resistance and metastatic processes in prostate cancer (PCa) remain undefined, due to lack of experimental models that mimic different disease stages. We describe a novel androgen-dependent PCa patient-derived xenograft (PDX) model from treatment-naive, soft tissue metastasis (PNPCa). RNA and whole-exome sequencing of the PDX tissue and organoids confirmed transcriptomic and genomic similarity to primary tumor. PNPCa harbours BRCA2 and CHD1 somatic mutations, shows an SPOP/FOXA1-like transcriptomic signature and microsatellite instability, which occurs in 3% of advanced PCa and has never been modelled in vivo. Comparison of the treatment-naive PNPCa with additional metastatic PDXs (BM18, LAPC9), in a medium-throughput organoid screen of FDA-approved compounds, revealed differential drug sensitivities. Multikinase inhibitors (ponatinib, sunitinib, sorafenib) were broadly effective on all PDX- and patient-derived organoids from advanced cases with acquired resistance to standard-of-care compounds. This proof-of-principle study may provide a preclinical tool to screen drug responses to standard-of-care and newly identified, repurposed compounds.

cancer biology↗