After After
Before Before

10133 - COX2, Melanoma, TME

INTRODUCTION

The inducible isoform of cyclooxygenase-2 (COX2) is upregulated during both inflammation and cancer, and is described to modulate cell proliferation and apoptosis mainly in solid tumors.

The "10133 - COX2, Melanoma, TME" APP detects nuclei and classifies them as either negative, 1+, 2+ or 3+ based on the COX2 staining expression present in each nucleus' vicinity.


KEYWORDS
COX2, cyclooxygenase, melanoma, skin, cancer, oncology, IHC, tumor micro environment


METHODS
To identify the nuclei, the APP performs a two-stage polynomial blob filtering on a blue-enhanced feature image and delimits them using local linear filtering. Each pixel with DAB staining is classified as low, mid and high based on the intensity and grouped together locally. Each nucleus is then classified based on its surroundings in the order of 3+, 2+, 1+ and negative to emphasize the strongest staining present in each nucleus’ vicinity.


QUANTITATIVE OUTPUT VARIABLES
The output variables obtained from this protocol include:

  • Number and percentage of negative, 1+, 2+, and 3+ cells in both stromal and tumor tissue
  • H-score = (% of 3+)x3 + (% of 2+)x2 + (% of 1+) for both stromal and tumor tissue

AUXILIARY APPs
APP: “01 Detect TumorStroma”
The auxiliary APP: “01 Detect TumorStroma” is used for automatic tumor and stromal tissue detection. The analysis APP will then provide results for tumor and stromal tissue separately.

WORKFLOW
Step 1: Load and run the APP “01 Detect TumorStroma” for tumor and stromal tissue identification. Manually correct the result if needed.
Step 2: Load and run the APP “02 COX2 Analysis” for the quantification of cells.

STAINING PROTOCOL
There is no staining protocol available.

ADDITIONAL INFORMATION
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 Author™ module the APP can be customized to fit other purposes. Author™ offers a comprehensive and dedicated set of tools for creating new fit-for-purpose analysis APPs, and no programming experience is required.

REFERENCES
There are no references available.

RUO
Figure 1
Figure 1
Nuclei surrounded by mixed COX2 staining.
Figure 2
Figure 2
Nuclei in figure 1 classified by APP as negative (blue), 1+ (yellow), 2+ (orange), or 3+ (red) based on the COX2 staining of each nucleus' surroundings.
Figure 3
Figure 3
Nuclei surrounded by intermediate and strong COX2 staining.
Figure 4
Figure 4
Classification of nuclei surrounded by intermediate and strong COX2 staining.
Figure 5
Figure 5
Nuclei surrounded by negative COX2 staining.
Figure 6
Figure 6
Classification of nuclei surrounded by negative COX2 staining.
Figure 7
Figure 7
Sample with stromal and tumor tissue.
Figure 8
Figure 8
Tumor and stroma identification by auxiliary APP. Stroma regions are outlined by a red region of interest (ROI) and tumor regions by a blue ROI. Quantitative output variables such as H-score is given for stroma and tumor region individually.