Three-dimensional analysis of the patterns of growth and mechanisms of evading therapy of pancreatic cancer in whole organs and thick slabs of tissue using active and passive SHANEL technology
Pathology
Final Report Abstract
Pancreatic carcinoma is one of the most aggressive types of cancer and is expected to become the third leading cause of cancer-related death by the end of this decade. Advances in therapy always depend on a profound understanding of the underlying mechanisms of tumor growth and metastasis. Compared to other tumors in the gastrointestinal tract, pancreatic carcinoma quite frequently invades the vessels and nerves that run through the pancreas. This characteristic is associated with the aggressiveness of the tumor, since the spread through the vascular and nerve pathways likely facilitates metastasis and promotes the local growth of the cancer cells. Therefore, the aim of my project was to investigate the growth of pancreatic carcinoma cells in human surgical specimens at the microscopic level in 3D. Previous investigations of vessel and nerve infiltration in surgical specimens have been based primarily on conventional twodimensional histological sections, as are also used for the daily diagnosis of cancer diseases. These sections are about 4-6µm (0.0004 – 0.0006cm) thick and vary in length and width from less than 0.5cm to about 1.5cm. For comparison, a tumor in the head of the pancreas is about 2.5 – 3.0cm in diameter. Thus, a single slide represents only 0.01 – 0.02% of the total diameter of the tumor. This is often sufficient for most clinical-diagnostic questions, but poses significant limitations for the scientific investigation of growth patterns. Vessels and nerves, as well as partly tubular growing cancer cells, are only partially sectioned. We were able to examine tissue up to a thickness of 0.4 – 0.5cm by further developing so-called tissue clearing methods combined with three-dimensional imaging in a special microscope. The visualization of cancer cells and nerves was achieved by their labeling with nano-antibodies and conventional antibodies. Following the principles of immunofluorescence, these were labeled with fluorophores that emitted light at different wavelengths when excited by the laser during lightsheet microscopy. This allowed us to optically section these thicker pieces of tissue into individual images 3µm thick, which we could then digitally reassemble into three-dimensional images. In a further step, we were able to render these target structures and thus convert them into a computer-interpretable format, which allows us to perform standardized analyses. We were able to optimize existing algorithms of 3D image analysis (skeletonization). We defined invasive protrusions of cancer cells based on their width and length. We can now place these in a spatial relationship to the nerves. The overarching goal here is to distinguish directional growth of the cancer cells towards the nerves from random growth and to investigate the influence of preoperative chemotherapy on the growth of the cancer cells in 3D. We were able to create the prerequisites for this through our preliminary work, and currently, 30 tumor samples that have already been microscoped and are available in 3D are being processed through the analysis pipeline.
Publications
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Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions.
Braxton, Alicia M.; Kiemen, Ashley L.; Grahn, Mia P.; Forjaz, André; Babu, Jaanvi Mahesh; Zheng, Lily; Jiang, Liping; Cheng, Haixia; Song, Qianqian; Reichel, Rebecca; Graham, Sarah; Damanakis, Alexander I.; Fischer, Catherine G.; Mou, Stephanie; Metz, Cameron; Granger, Julie; Liu, Xiao-Ding; Bachmann, Niklas; Almagro-Pérez, Cristina ... & Wood, Laura D.
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Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer. Med, 4(2), 75-91.
Kiemen, Ashley L.; Damanakis, Alexander Ioannis; Braxton, Alicia M.; He, Jin; Laheru, Daniel; Fishman, Elliot K.; Chames, Patrick; Pérez, Cristina Almagro; Wu, Pei-Hsun; Wirtz, Denis; Wood, Laura D. & Hruban, Ralph H.
