Dive into Pancreatic Cancer Research with the Big Data Viewer

Explore the pancreatic cancer spatial proteome with Cell DIVE and see the power of multiplexed imaging with the Minerva image viewer

Pancreatic Ductal Adenocarcinoma with 11 Aerobic Glycolysis/Warburg Effect biomarkers shown – BCAT, Glut1, HK2, HTR2B, LDHA, NaKATPase, PCAD, PCK26, PKM2, SMA1, and Vimentin. Pancreatic_Ductal_Adenocarcinoma_11_Aerobic_Glycolysis_Markers_ROI4.jpg

Pancreatic cancer, with a mortality rate near 40%, is challenging to treat due to its proximity to major organs. This story explores the complex biology of pancreatic ductal adenocarcinoma (PDAC), examining molecular and spatial determinants of tumor aggression in metabolism, apoptosis, and immunity. Access the full Cell DIVE dataset in your browser to delve deeper into these findings.

Key learnings:

  • Discover how whole-tissue multiplexed imaging using Cell DIVE can map pancreatic cancer tissues.
  • Explore metabolism, apoptosis, and immune cell activity in this complex cancer.
  • Learn how Cell DIVE can power your next spatial immune-oncology study.
  • Discover how to explore Cell DIVE datasets directly in your browser through the Minerva image viewer.

Challenges in therapy of pancreatic cancer

Pancreatic cancer is a hard-to-treat cancer with a mortality rate close to 40%. The pancreas' close proximity to many major organ systems makes this cancer particularly dangerous. Moreover, the highly heterogenous nature of pancreatic cancers, such as pancreatic ductal adenocarcinoma (PDAC) poses a special challenge to therapy development. Some of the more invasive and aggressive regions of the tumor are especially refractory to novel treatments. Understanding the sources of this tumor heterogeneity is critical to therapeutic research, and multiplexed imaging approaches like Cell DIVE offer the ability to interrogate multiple biological pathways within a single tumor. By analyzing these pathways, researchers can see how tumor regions that differ in terms of aggression and disease impact are established.

Examine full, real datasets in your web browser, helping to identify key findings in a PDAC sample

To facilitate this evaluation process, we have integrated Minerva image viewing technology, which allows researchers to examine full, real Cell DIVE datasets in a standard web browser. Minerva is a lightweight, narrative-based image browser developed by scientists at Harvard University, designed to simplify the demonstration and sharing of histopathology datasets among researchers1. Using Minerva, we have created a series of guided narrations that illustrate different biological contexts. These narrations highlight various areas of interest within the tissues, explaining staining patterns and the rationale for selecting specific biomarkers. This approach provides a framework for how users might construct a Cell DIVE study and perform subsequent analysis. With this tool, users can evaluate the capabilities of Cell DIVE imaging, explore different strategies for multiplexed imaging, and understand how analysis can transform images into quantitative data.

In this Minerva story, we identify several key findings in a PDAC sample. First, we find that a major source of PDAC tumor heterogeneity is choice of metabolic pathway used by different tumor regions. In tumors and other highly proliferating populations, cells can occasionally shift their metabolic activity away from full electron transport chain-mediated respiration and towards a direct fermentation of glucose, in a shift known as the Warburg effect. GLUT1, a glucose transporter, marks cells in the PDAC tissue undergoing this effect, and experiencing a condition known as hypoxia - a reduction of oxygen levels in the tissue. BCAT, HTR2B, and LDHA also mark conditions of altered metabolism. Hypoxic regions of the tumor are known to be sources of aggressive cancer cells.

Choosing an imaging-based spatial biology solution depends on a large number of factors, including initial costs, reagent costs, throughput, and ease-of-use, but perhaps the most critical deciding point is the quality of the images produced. By directly evaluating Cell DIVE images using the Minerva image viewer, researchers can appreciate the power of the Cell DIVE approach and technologies.

Seeing is believing, explore the interactive date set:

 Explore the interactive data set

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