10129 - CD68 & CD163, Breast Cancer, TME
Breast cancer development and progression could be affected by its tumour-associated macrophages (TAMs). More specifically, a disbalance between TAM subtypes: M1-like and M2-like macrophages might lead to unfavourable outcome.
The present APP works on serial section TMAs stained with CD68 and CD163. The APP quantifies the number of positive cells for both stains, which enables the calculation of the M2/M1 ratio as #CD163/(#CD68 - #CD163).
CD68, CD163, Breast cancer, Digital pathology, TMA, Image analysis, Cell quantification, TME
First, a pre-processing step enhances the nuclear stain by hematoxylin color deconvolution. Then a blob filter is applied to identify the individual nuclei. During post-processing the individual nuclei are classified as negative or positive based on the amount of surrounding CD68 and CD163 stain. Also, the size of the nuclei is taken into account to exclude tumor cells.
QUANTITATIVE OUTPUT VARIABLES
The output variables obtained from this protocol are:
- #Mtotal: Number of CD68 positive nuclei
- #M2: Number of CD163 positive nuclei
From which #M1 can be calculated as:
- #M1: The number of #Mtotal - #M2
APP1: “01 CD68 quantification”
APP2: “02 CD163 quantification”
Step 1: De-array the CD68 and CD163 TMAs using the Tissuearray™ module
Step 2: Load and run the APP “01 CD68 quantification” as a batch process on the CD68 cores
Step 3: Load and run the APP “02 CD163 quantification” as a batch process on the CD163 cores
There is no staining protocol available.
The APP utilizes the Visiopharm Engine™ and Viewer software modules, where Engine™ offers an execution platform to expand processing capability and speed of image analysis. The Viewer allows a fast review together with several types of image adjustment properties ex. outlining of regions, annotations and direct measures of distance, curve length, radius, etc.
By adding the AuthorTM module the APP can be customized to fit other purposes. AuthorTM offers a comprehensive and dedicated set of tools for creating new fit-for-purpose analysis APPs, and no programming experience is required. For an optimized workflow the Tissuearray™ module is recommended as it facilitates easy and fast de-arraying of the cores.
There are no references avalible.
This APP was developed for Dr. Bert Van Der Vegt, University Medical Center Groningen, Netherlands.