June 12 - 14
Leipzig, DE
Visit our booth
Meet Lunaphore
Mark your calendars for the 108th Annual Meeting of the German Society of Pathology in Leipzig!
Join us and engage directly with our expert scientists to discover spatial multiomics on COMET™️. Experience firsthand how you can simultaneously detect RNA and proteins within the same section, all at a subcellular level of detail.
Our protease-free, fully-automated workflow enables multiomics scalability for all stages of research. Are you interested in elevating your spatial biology projects with our multiomics solutions? Contact us now to arrange a detailed discussion with our dedicated team.
Workshops
June 13 | 12:00 PM - 12:20 PM SPONSORED SESSION
Advances in Spatial Biology for Enhanced Biomarker Discovery and Tissue Characterization
Better biomarkers are required to refine biopsy-level assessment in rectal, particularly to improve the prediction of response to neoadjuvant treatment and guide patient selection for tailored treatment regimens. High-plex methods such as sequential Immunofluorescence (seqIF™) streamlined and increased the throughput of molecular biomarker discovery substantially. However, tumor morphology is often overlooked in this process. In this talk, we will emphasize how pathologists’ expertise can drive biomarker discovery, using the established morphological feature of tumor budding (TB) as an example.
In this talk, we will give insight into the requirements of a seqIF™ pipeline, and present examples of the morphological and molecular features that can be extracted from such images. Specifically, we will discuss the concepts of epithelial cluster size and epithelial-mesenchymal transition (EMT) in the context of rectal cancer. Our findings show that EMT processes are most pronounced in TB but are also evident in slightly larger clusters and fibril-like structures of the tumor. Finally, we will demonstrate how these features together can inform disease-free patient survival.
Speaker
Mauro Gwerder
PhD Candidate
Institute of Tissue Medicine and Pathology, University of Bern
Spatial biology techniques aid in biomarker discovery and clinical target identification by preserving tissue architecture. Lunaphore introduces an integrated solution comprising COMET™, a fully-automated spatial multiomics platform, and HORIZON™ image analysis software for interpreting hyperplex immunofluorescent images efficiently. Here, we will walk through the integrated workflow from COMET™ images to biological insights to characterize the tissue architecture and identify relevant biomarkers.
Speaker
Müge Akpinar-Puchalla, Ph.D.
Field Application Specialist Manager
Lunaphore
June 14 | 10:30 AM - 12:00 PM SYMPOSIUM SESSION
WG Informatics, Digital pathology, biobanking 2
June 14
11:00 AM - 11:12 AM
Saal 4
1. Institute of Tissue Medicine and Pathology, University of Bern, Bern, Switzerland, 2. Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland, 3. Lunaphore Technologies, Tolochenaz, Switzerland, 4. Department of Oncology, Geneva University Hospitals, Geneva, Switzerland, 5. Department of Medical Oncology, Inselspital, Bern University Hospital, Bern, Switzerland, 6. Center for Scalable Data Analytics and AI (ScaDS.AI), Dresden/Leipzig, Germany, 7. Faculty of Computer Science, TU Dresden, Dresden, Germany, 8. Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Background
In rectal cancer, most patients receive neo-adjuvant therapy. To better predict patient outcome from biopsies better tools are needed. Histological features such as intratumoral budding (ITB) and immune infiltration[Ref1] have been proven to predict patient response. However, Cancer-Associated Fibroblasts (CAFs) are underexplored in rectal cancer biopsies. In this work, we investigate the potential of five fibroblast markers to predict Disease-Free Survival (DFS) in rectal biopsies.
Methods
A tissue Micro-Array (TMA) cohort consisting of 160 rectal cancer biopsy cores (1A) underwent seqIF™ protocol[Ref2]. 31 markers were applied iteratively to the cohort (1B). The Pixie-pipeline[Ref3], which applies a self-organizing map (SOM) to create meta-clusters for each pixel, was used for tissue classification (1C). The tissue was further split into stromal areas using Voronoi tessellation (1D). We identified stromal areas interacting with the epithelium using Delaunay triangulation (1E). We subsequently extracted quantitative features for univariate (KM estimator) and multivariate survival analysis (CoxPH model).
Fig. 1: Tissue profiling approach: (A) H&E-stained example core (sequential cut), (B) seqIFTM-stained example cores (31-plex), (C) Pixie tissue classification results, (D) Tissue classification after voronoi-tesselation of the stromal compartment, (E) Extraction of stromal areas that are directly interacting with the epithelium (highlighted)
Results
A total of four CAF meta-clusters were identified, namely “FAP+ CAFs”, “IDO1+ CAFs”, “myoCAFs” and “CD90+ CAFs”, along with eight immune meta-clusters. We found CD8+ T-cells and M1-macrophage infiltration as favorable features for DFS in a univariate setting (p=0.072 and p=0.005 respectively). Notably, CD90+ CAFs were associated with improved DFS (HR=0.43, p= 0.007; Fig. 2), indicative of a protective role in rectal cancer progression.
Multivariate Cox proportional Hazard model for Disease-Free Survival (DFS), including the following variables: Fraction of CD90+ CAF areas interacting with epithelial tissue (split in two groups using the median); Age of the patient; Treatment received after resection (yes / no); ypTNM staging (I / II / III / IV); Mandard regression grade (1-5)
Conclusion
In this work, we profiled the stromal compartment in rectal cancer biopsies and identified predictive immune and fibroblast subtypes. These findings provide the computational and biological foundations for further investigations into the relationship between CAFs and other histological features in rectal cancer. CAF subtypes, in combination with ITB counts and immune infiltration patterns, could enhance current prognostic models for rectal cancer.
References:
- [Ref1] Shuhei Sano et al., (2023), Intratumoral Budding and CD8-Positive T-Cell Density in Pretreatment Biopsies as a Predictor of Response to Neoadjuvant Chemoradiotherapy in Advanced Rectal Cancer, Clinical Colorectal Cancer, 411-420, 22/4, https://doi.org/10.1016/j.clcc.2023.07.004
- [Ref2] François Rivest et al., (2023), Fully Automated Sequential Immunofluorescence (seqIF) for Hyperplex Spatial Proteomics, Scientific Reports, 13, https://doi.org/10.1038/s41598-023-43435-w
- [Ref3] Candace C. Liu et al., (2023), Robust Phenotyping of Highly Multiplexed Tissue Imaging Data Using Pixel-Level Clustering, Nature Communications, 14/1, https://doi.org/10.1038/s41467-023-40068-5
Speaker
Mauro Gwerder
PhD Candidate
Institute of Tissue Medicine and Pathology, University of Bern
June 13 | 12:00 PM - 12:20 PM SPONSORED SESSION
Advances in Spatial Biology for Enhanced Biomarker Discovery and Tissue Characterization
Better biomarkers are required to refine biopsy-level assessment in rectal, particularly to improve the prediction of response to neoadjuvant treatment and guide patient selection for tailored treatment regimens. High-plex methods such as sequential Immunofluorescence (seqIF™) streamlined and increased the throughput of molecular biomarker discovery substantially. However, tumor morphology is often overlooked in this process. In this talk, we will emphasize how pathologists’ expertise can drive biomarker discovery, using the established morphological feature of tumor budding (TB) as an example.
In this talk, we will give insight into the requirements of a seqIF™ pipeline, and present examples of the morphological and molecular features that can be extracted from such images. Specifically, we will discuss the concepts of epithelial cluster size and epithelial-mesenchymal transition (EMT) in the context of rectal cancer. Our findings show that EMT processes are most pronounced in TB but are also evident in slightly larger clusters and fibril-like structures of the tumor. Finally, we will demonstrate how these features together can inform disease-free patient survival.
Speaker
Mauro Gwerder
PhD Candidate
Institute of Tissue Medicine and Pathology, University of Bern
Spatial biology techniques aid in biomarker discovery and clinical target identification by preserving tissue architecture. Lunaphore introduces an integrated solution comprising COMET™, a fully-automated spatial multiomics platform, and HORIZON™ image analysis software for interpreting hyperplex immunofluorescent images efficiently. Here, we will walk through the integrated workflow from COMET™ images to biological insights to characterize the tissue architecture and identify relevant biomarkers.
Speaker
Müge Akpinar-Puchalla, Ph.D.
Field Application Specialist Manager
Lunaphore
June 14 | 10:30 AM - 12:00 PM SYMPOSIUM SESSION
WG Informatics, Digital pathology, biobanking 2
June 14
11:00 AM - 11:12 AM
Saal 4
References:
- [Ref1] Shuhei Sano et al., (2023), Intratumoral Budding and CD8-Positive T-Cell Density in Pretreatment Biopsies as a Predictor of Response to Neoadjuvant Chemoradiotherapy in Advanced Rectal Cancer, Clinical Colorectal Cancer, 411-420, 22/4, https://doi.org/10.1016/j.clcc.2023.07.004
- [Ref2] François Rivest et al., (2023), Fully Automated Sequential Immunofluorescence (seqIF) for Hyperplex Spatial Proteomics, Scientific Reports, 13, https://doi.org/10.1038/s41598-023-43435-w
- [Ref3] Candace C. Liu et al., (2023), Robust Phenotyping of Highly Multiplexed Tissue Imaging Data Using Pixel-Level Clustering, Nature Communications, 14/1, https://doi.org/10.1038/s41467-023-40068-5
Speaker
Mauro Gwerder
PhD Candidate
Institute of Tissue Medicine and Pathology, University of Bern