Identifying Spatial Expression Patterns in the Tumor Microenvironment, New Webinar Hosted by Xtalks

TORONTO, September 24, 2018 (Newswire.com) - Join industry expert Dr. Lorenz Rognoni, Senior Consultant of Datafication at Definiens AG, for an insightful and interactive webinar. There will be two live broadcasts on Tuesday, Oct. 9, 2018 at 9am EDT (2pm BST/UK) and 2pm EDT (11am PDT).

Advancement in cancer immunotherapy is associated with unraveling the complexities of immune suppressive mechanisms across different cancers. Quantification on multispectral multiplex-immunofluorescence (mIF) images allows detection of several biomarkers in a single section. In addition, new evidence using mIF techniques suggests that spatial analysis reveals novel insights in the tumor microenvironment. However, multispectral imaging is tile-based due to long scanning periods, which leads to insufficient data acquisition for significant spatial analysis. In this webinar, our featured speaker will present an automated workflow to study the spatial patterns of infiltrating cells in the tumor microenvironment based on multispectral mIF whole-slide scans. This was used to study the relationship between tumor proliferation and immune-response in non-small cell lung cancer (NSCLC) resections.

Formalin-fixed, paraffin-embedded NSCLC resection samples were stained by MedImmune with a custom-developed 7-plex mIF panel (CD68, CD8, Ki67, PD1, PD-L1, pancytokeratins-CK & DAPI) using the Opal method (PerkinElmer) in combination with an automated staining platform to ensure high throughput and consistent sample processing. Tiled scans were acquired with a Vectra Polaris (PerkinElmer) multispectral imaging system. Definiens developed a workflow which composes the tiled unmixed multispectral data to a whole-slide image and optimizes the layers for screen display and automated image analysis. Furthermore, images were shared on Definiens collaboration platform along with a chromogenic-IHC pseudocolor of the IF CK/DAPI signals and co-registered H&E section for pathologist annotations. These annotations were used in defining tumor center and invasive margin. The image analysis includes single-cell detection on the complete slide along with classification of subpopulations based on multi-marker positivity of individual cells. Part of the analysis is a high-quality tumor stroma separation based on the CK signal. The single-cell readouts were used to construct spatial biomarker expression patterns.

To learn more about this event visit: Identifying Spatial Expression Patterns in the Tumor Microenvironment.

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Contact:

Nima Rajan

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Email: [email protected]

Source: Xtalks