Practical Approaches to Tumor Xenograft Analysis

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Practical Approaches to Tumor Xenograft Analysis. Frank Voelker, Flagship Biosciences LLC Trevor Johnson, Flagship Biosciences LLC Veronica Traviglone, Infinity Pharmaceuticals Igor Deyneko, Infinity Pharmaceuticals. Outline. Introduction Anatomy of a Xenograft - PowerPoint PPT Presentation

Text of Practical Approaches to Tumor Xenograft Analysis

  • Practical Approaches to Tumor Xenograft AnalysisFrank Voelker, Flagship Biosciences LLCTrevor Johnson, Flagship Biosciences LLCVeronica Traviglone, Infinity PharmaceuticalsIgor Deyneko, Infinity Pharmaceuticals

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    OutlineIntroductionAnatomy of a XenograftDefining the Approach to the AnalysisAnalytical StrategiesExamples of CasesPresenting FACTS for Target Tissue Analysis

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    General Anatomy of a XenograftCD-31 Stain for Microvessels

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    Chronic Inflammation and Peripheral Adipose TissueAdjacent tissue frequently contains host responses such as inflammation, adipose tissue or adnexal structures that need to be excluded from the analysis

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    Extensive Necrosis and DegenerationNecrosis and neoplastic cells in various stages of degeneration are common features of a xenograft.CD31 Immunostain

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    Host Response of Vascular Ingrowth Demonstrated with CD31 Immunostain Even the smallest microvessels may be enclosed in adventitial tissue as an extension of stromal ingrowths

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    Compare H&E and IHC StainsH&ECD31

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    Compare Corresponding Areas of H&E and CD31 StainsCompare microscopic characteristics of an H&E- stained section with comparable regions of an IHC CD31-stained sectionThis will provide valuable perspective regarding IHC target tissue staining and will allow more accurate identification of tissue classes.H&ECD31

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    Significant Xenograft Tissue ComponentsNeoplastic CellsTissue BiomarkerConnective Tissue StromaNecrosis and DegenerationCystic or Secretory Vacuoles Artifactual Space

    Which of these do you want to include in your analysis?

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    Some Examples of Analytical EndpointsNeoplastic Cell AreaTotal Xenograft AreaMarker Area or Score Neoplastic Cell AreaA function of neoplastic cell abundance versus necrosis and/or stromal prominenceImmunohistochemistry expression of marker metabolism within neoplastic cell population Number of Neoplastic NucleiNeoplastic Cell AreaAn indication of mean neoplastic cell size Targeted Cell NumberTotal Xenograft AreaCell frequency within measured areaNumber of MicrovesselsNeoplastic Cell + Stromal AreaMicrovessel analysis

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    What aspects of a marker determine treatment effect?(Nwp/Ntotal)x(100) + Np/Ntotal)x(200) + Nsp/Ntotal)x(300) = H Score (For a maximum of 300)Staining variation in tumors or other tissues frequently raises the question of whether to measure either percent area or average intensity of an immunostain. In some cases, a solution to this problem is to measure score as an output convention encompassing both percent area and stain intensity.

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    * Manual Use of Positive and Negative Pen Tools Similar IHC staining of fibronectin and secretion droplets in this xenograft tumor with subsequent poor differentiation by the Genie classifier required the use of the negative pen tool to assist in quantitating fibronectin using the IHC deconvolution algorithm.

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    Manual Use of Positive and Negative Pen Tools Use of a 21UX Cintiq Wacom drawing board facilitates the use of positive and negative pen tools in manually delineating critical features of the xenograft.

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    Using Genie to Segregate Neoplasm from Nontarget Tissue in a Xenograft Stained for Phospho-Histone 3Central regions of the xenograft contain an interdigitating pattern of necrosis and connective tissue trabeculae too complex for manual exclusion .Accurate segregation of neoplasm (green) from necrosis and connective tissue (red) was accomplished using Genie

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    The Rationale Behind Histology Feature Recognition

    Using software to preprocess an image with the purpose of segregating target tissue components from nontarget tissue.Aperio GenieVisiopharmSubsequent analysis yields accurate data only from the target tissue component, and omits erroneous nonspecific results from nontarget tissue.Feature recognition is valuable in xenograft analysis when target and nontarget regions are too intricately interwoven for manual exclusion.

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    Strategy for Analyzing Successive SamplesProgression of analysis through sample seriesRed = 1st ClassifierBlue = 2nd ClassifierGreen = 3rd Classifier* = Points when a new classifier was developed during the analysis ***Xenograft neoplasms within a study are surprisingly heterogeneous even though derived from the same source, and it is difficult and time consuming to derive a common pattern recognition classifier appropriate for all neoplasms within a study. It is more expeditious and also yields more accuracy to develop new classifiers as the analysis progresses.

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    Consistent Analysis of Study Samples Using GenieSubsequent Uniform Analysis of Segregated Target Tissue for area/intensity Even though multiple classifiers are constructed for successive samples, the final analyses of target tissue components will be accurate and comparable if the same algorithm threshold values are constantly maintained.

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    Using Genie to Segregate Neoplasm from Nontarget Tissue in a Xenograft Stained for Phospho-Histone 3Higher magnification reveals accurate separation of target from nontarget tissue.The grayed-out nontarget tissue class consists of a mixture of connective tissue trabeculae and necrotic tumor cells.

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    Assessing Fibronectin in a Xenograft Using Several Software ProgramsAssessing the intensity and quantity of fibronectin as a marker in xenograft stromaAperio Deconvolution Mark-upVisiopharm Mark-upOriginal IHC Image

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    *Assessing Angiogenesis in a Xenograft Using Several Software Programs Use of the microvessel analysis algorithm to assess angiogenesis in a xenograft neoplasm in a mouse Microvessel analysis provides important information regarding potential antineoplastic effects of pharmaceutical compoundsOriginal CD31-Stained Image Aperio Microvessel Algorithm Mark-upVisiopharm Mark-up

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    Using the Microvessel Analysis Algorithm to Count Cyclin B1-Positive Target Cells in a Xenograft Use of the microvessel analysis algorithm to assess macrophage populations in mouse xenograft neoplasms Threshold algorithm parameters are modified to accommodate the smaller size and shape characteristics of the cells

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    Use of Visiopharm Software to Analyze a Marker Separately in Cytoplasm and Nuclei of a NeoplasmDiscriminating between nuclear and cytoplasmic regions of a neoplasm allows separate biomarker intensity measurement for both nuclear and cytoplasmic markers (analysis with Visiopharm software).

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    Distinctive or Special Staining Facilitates Target Tissue Pattern RecognitionH&EH&E ClassifierCD31CD31 ClassifierFirst pass accuracy is much greater for the H&E-stained section than for the hematoxylin- counterstained IHC sectionCurrent histology pattern recognition programs often have difficulty distinguishing target tissue profiles because of low contrast /nonspecific counterstaining

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    Feature Analysis on Consecutive Tissue Sections (FACTS)4. QC and pathologist review3. Image and ROI registration2. AutomatedfeaturerecognitionConsecutive tissue sectioning

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    Image and ROI RegistrationRegister images with v(x,y)

    Rotation: x = xcos() - ysin() y = xsin() + ycos() Translation:x -> xy -> y

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    Example of Slide Registration

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    Annotated Feature to Feature RegistrationMore complex due to biological and histological differences between serial sectionsUsually Elastic to count for these differencesImportant to note that the actual images are never morphed, just the annotationsLet the application determine the methodPhase Registration: xp(2 i (u x + v y)) = (f) (g) / | (f) (g) |Mutual Information:MI(X,Y) = H(Y) H(Y | X) = H(X) H(Y) H(X,Y)where H(X) = Ex(log(P(X))

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    Annotation Feature to Feature Registration (cont.)Wavelet Transform:Decompose image into collection of appropriate wavelet (Spline, Haar, Etc.)

    Filter image along rows and columns (high and low pass)Find frequency coefficients and apply differential measurements

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    Example of Feature Registration

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    Acknowledgments

    Dr. Steven Potts, Flagship Biosciences LLCDr. David Young, Flagship Biosciences LLCMs. Charlotte Aagaard Johnson, Visiopharm Inc.Mr. Rob Diller, Flagship Biosciences LLCMr Erik Hagendorn, Flagship Biosciences LLCQuestions? Email contact: frank@flagshipbio.com trevor@flagshipbio.com

    *New Targets CommitteePage **