Biology subjects

Feuerhake, F.

Publications and source records attributed to Feuerhake, F..

3 recordsLinked to original sources

bioRxiv2025

Spatial Transcriptomics Expression Prediction from Histopathology Based on Cross-Modal Mask Reconstruction and Contrastive Learning

Spatial transcriptomics is a technology that captures gene expression levels at different spatial locations, widely used in tumor microenvironment analysis and molecular profiling of histopathology, providing valuable insights into resolving gene expression and clinical diagnosis of cancer. Due to the high cost of data acquisition, large-scale spatial transcriptomics data remain challenging to obtain. In this study, we develop a contrastive learning-based deep learning method to predict spatially resolved gene expression from whole-slide images. Evaluation across six different disease datasets demonstrates that, compared to existing studies, our method improves Pearson Correlation Coefficient (PCC) in the prediction of highly expressed genes, highly variable genes, and marker genes by 6.27%, 6.11%, and 11.26% respectively. Further analysis indicates that our method preserves gene-gene correlations and applies to datasets with limited samples. Additionally, our method exhibits potential in cancer tissue localization based on biomarker expression.

pathology↗

bioRxiv2024

The Role of Biopsy Position and Tumor-Associated Macrophages for Predictions on Recurrence of Malignant Gliomas: An In Silico Study

Predicting the biological behavior and time to recurrence (TTR) of high-grade diffuse gliomas (HGG) after the maximum safe neurosurgical resection and combined radiation and chemotherapy plays a pivotal role in planning the clinical follow-up, the choice of potentially necessary second-line treatment, and the quality of life of patients faced with the diagnosis of a malignant brain tumor. The current standard-of-care (SoC) for HGG includes follow-up neuroradiological imaging to detect recurrence as early as possible and several clinical, neuropathological, and radiological prognostic factors with limited accuracy toward predicting TTR. Herein, using an in-silico analysis, we aim to improve predictive power towards TTR considering the role of (i) prognostically relevant information available by diagnostics used in current SoC, (ii) advanced image-based information that is currently not part of the standard diagnostic workup, such as interface of tumor and normal tissue (edge) features and quantitative data specific for the position of biopsies within the tumor, and (iii) information on tumor-associated macrophages. In particular, we introduce a state-of-the-art spatio-temporal model of tumor-immune interactions, emphasizing the interplay between macrophages and glioma cells. This model serves as a synthetic reality for assessing the predictive value of various features. We generate a cohort of virtual patients based on our mathematical model. Each patients dataset includes simulated T1 and FLAIR MRI volumes, and simulated results on macrophage density and proliferative activity either in a specified part of the tumor, namely tumor core or edge ("localized"), or unspecified ("non-localized"). We impose different levels of noise to enhance the realism of our synthetic data. Our findings reveal that macrophage density at the tumor edge contributes to a high predictive value of feature importance for the selected regression model. Moreover, there is a lower MSE and higher R2 for the "localized" biopsy in prediction accuracy toward recurrence post-resection compared with "non-localized" specimens. In conclusion, the results show us that localized biopsies can bring more information about the tumor behavior, especially at the interface of tumor and normal tissue (Edge).

systems biology↗

bioRxiv2024

Enhancement of colorectal cancer therapy through interruption of the HSF1-HSP90 axis by p53 activation or cell cycle inhibition

The stress-associated molecular chaperone system is an actionable target in cancer therapies. It is ubiquitously upregulated in cancer tissues and enables tumorigenicity by stabilizing hundreds of oncoproteins and disturbing the stoichiometry of protein complexes. Most inhibitors target the key component heat-shock protein 90 (HSP90). However, although classical HSP90 inhibitors are highly tumor-selective, they fail in phase 3 clinical oncology trials. These failures are at least partly due to an interference with a negative feedback loop by HSP90 inhibition, known as heat-shock response (HSR): in response to HSP90 inhibition there is compensatory synthesis of stress-inducible chaperones, mediated by the transcription factor heat-shock factor 1 (HSF1). We recently identified that wildtype p53 (p53) actively reduces the HSR by repressing HSF1 via a p21-CDK4/6-MAPK-HSF1 axis. Here we test the hypothesis that in HSP90-based therapies simultaneous p53 activation or direct cell cycle inhibition interrupts the deleterious HSF1-HSR axis and improves the efficiency of HSP90 inhibitors. Indeed, we find that the clinically relevant p53 activator Idasanutlin suppresses the HSF1-HSR activity in HSP90 inhibitor-based therapies. This combination synergistically reduces cell viability and accelerates cell death in p53-proficient colorectal cancer (CRC) cells, murine tumor-derived organoids and patient-derived organoids (PDOs). Mechanistically, upon combination therapy human CRC cells strongly upregulate p53-associated pathways, apoptosis, and inflammatory immune pathways. Likewise, in the chemical AOM/DSS CRC model in mice, dual HSF1-HSP90 inhibition strongly represses tumor growth and remodels immune cell composition, yet displays only minor toxicities in mice and normal mucosa-derived organoids. Importantly, inhibition of the cyclin dependent kinases 4 and 6 (CDK4/6) under HSP90 inhibition phenocopies synergistic repression of the HSR in p53-proficient CRC cells. Even more important, in p53-deficient (mutp53-harboring) CRC cells, an HSP90 inhibition in combination with CDK4/6 inhibitors similarly suppresses the HSF1-HSR system and reduces cancer growth. Likewise, p53-mutated PDOs strongly respond to dual HSF1-HSP90 pathway inhibition and thus, providing a strategy to target CRC independent of the p53 status. In sum, activating p53 (in p53-proficient cancer cells) or inhibiting CDK4/6 (independent of the p53 status) provide new options to improve the clinical outcome of HSP90-based therapies and to enhance colorectal cancer therapy.

cancer biology↗