DEVELOPED FOR MOTiF™ PD-1/PD-L1 Panel: Auto Lung Cancer Kit 50 Slides




Akoya Biosciences has developed a rules-based phenotyping algorithm for use in inForm when analyzing multiplex-immunofluorescence slides stained with Akoya’s MOTiF™ PD-1/PD-L1 Lung Panel Kit. This biomarker panel for lung cancer contains the 6 most clinically relevant markers and can be utilized to understand immune infiltration in the face of a PD-L1 blockade. The algorithm includes pre-defined marker-dye pairings and rules for excluding non-biological marker co-positivity.



  • Markers: FoxP3, PD-L1, PanCK, PD-1, CD8, CD68
  • Tissue Type: Lung Cancer


VECTRA POLARIS IMAGING PROTOCOL
The Pre-Developed Polaris imaging protocol includes exposure times optimized for use with the MOTiF™ PD-1/PD-L1 Panel: Auto Lung Cancer Kit 50 Slides.

  1. Install MOTiF PD-1-PDL1 20x Polaris imaging protocol onto your Polaris computer from the following link:

    MOTiF PD-1-PDL1 20x.ppr
  2. Save file to the Vectra Polaris Study Folder associated with tissues stained using the MOTiF™ PD-1/PD-L1 Panel: Auto Lung Cancer Kit 50 Slides
  3. Open Polaris software and load protocol in the "Edit Protocol" window

INFORM ALGORITHM
The Pre-configured Rules-based Lung Cancer algorithm is ONLY compatible with the latest inForm version 2.4.10 release.

  1. Install inForm version 2.4.10 onto your computer from the following link:

    inForm 2.4.10
  2. Down the Pre-configured Rules-based Lung Cancer algorithm from the following link:

    MOTiF PD-1-PDL1 Rules Phenotyping - Lung Algorithm


WORKFLOW INSTRUCTIONS
Guidance for how to use the Pre-configured Rules-based Lung Cancer algorithm can be downloaded from the following link:
         
          MOTiF PD-1-PDL1 Rules Phenoptyping - Lung.ifp
         


ALGORITHM INCLUDES
The Pre-configured Rules-based Lung Cancer algorithm developed by Akoya includes the following processing steps:
  • Prepare Images (Spectral Unmixing)
  • for use with either synthetic or user-generated libraries
  • Segment Tissue (AI-enabled Trainable Classifier)
  • optional and can be removed if you do not need it. Keep in mind that some phenoptrReports functionality (like cell density calculation) requires tissue segmentation results.
  • Segment Cells (Adaptive Cell Segmentation)
  • Phenotype Cells (Rules-Based Phenotyping).
  • If desired, a Scoring step can be added


QUANTITATIVE OUTPUT VARIABLES
The output variables obtained from this algorthim are:

  • Identifies regions of Tumor, Non-tumor, and Other (non-tissue areas)
  • Reports the area of each tissue region
  • Segments individual cells into their nuclei, cytoplasm and membrane compartments
  • Reports fluorescent signal presence (above a threshold) within each cell's cellular compartment
  • Reports the measurement of fluorescent intensities within each cell’s cellular compartment
  • Identifies the location of the following cellular phenotypes:
              CD8+
              PD-1+
              CD8+/PD-1+
              CK+
              PD-1+/FoxP3+
              CD8+/PD-1+/FoxP3+
              CD68+
  • Reports the prevalence (number and density) of each phenotype within each individual tissue region

Tissue analysis results are output in .csv table for downstream data analysis using phenoptrReports