tristatehs multiplexing victoria duckworthmsfh.wildapricot.org/resources/documents/tristatehs... ·...

4/29/2019

1

Multiplex Immunohistochemistry Assays: Best Practices, Techniques, and TroubleshootingVictoria Duckworth, MS | Product Manager, Opal Reagents | Akoya Biosciences, Inc. 68 Elm St Hopkinton, MA 01748 [email protected]

Objectives

Upon completion of this workshop, participants will be responsible to:

• Discuss the detection methods and strategies for multiplex IHC

• Explain the importance of in-house antibody validation

• Design an effective multiplex protocol

2 2019 Tri-State

Agenda

• Why Multiplex IHC?

• Pre-analytical considerations

• Antibody Validation

• Multiplex Development and Optimization

• Troubleshooting

• Multispectral Imaging and Image Analysis

2019 Tri-State 3

4/29/2019

2

Why Multiplex IHC?

Emergence of immuno oncology has created a paradigm shift in cancer treatment

2019 Tri-State

Targeted tumor mutationShort-term therapeutic benefits

Immune system engagedClinical biomarker complexity

Tumor cell

Nucleus

EGFR

KRASBRAF

MEK

ERKTumor cell

CD8+ T Cell

PD-1PD-L1

Macrophage

T Reg

T Helper

APCTumor cell

Nucleus

EGFR

KRASBRAF

MEK

ERKTumor

cell

CD8+ T Cell

PD-1PD-L1

Macrophage

T Reg

T Helper

APC

5

But immunotherapies have brought new complexity challenges into the clinic

2019 Tri-State

• How do we predict which patients should receive the therapy?

• Can different PD-L1 tests be used for different PD-1/PD-L1 therapies?

• Only 1 of the 4 FDA approved PD-L1 assays received a Companion Dx designation

• PD-L1 testing demonstrates some benefit for therapy decisions, but overall predictive values are still poor

PD-L1+

Responders

Non-responders

Response to Keytruda® in Previously Treated NSCLC Patients (PD-L1 tumor proportion score cutoff over ≥50%)*

41%

59%

More than half of patients testing positive for this biomarker did not respond to treatment

PD-L1-

Responders

Non-responders

13%

87%

6

4/29/2019

3

Challenges extend into the translational research space

2019 Tri-State

Critical Attributes for Research

Solution

• Tissue integrity for spatial context

• Multiplexing to capture immune response complexity

• Reliably detecting cell types and their functional markers

• Multi-parametric analytical capability

• Implementing a robust and efficient workflow

Trends in I-O and Clinical Biomarker

Research

• New checkpoint inhibitors

• Immuno profiling patients based on TME (eg immune desert, exclusion, infiltration)

• Determining the best combination of therapies for cancer patients

A tool that lets us explore the complex cell-cell biology in a tumor to discover and validate predictive

biomarkers

7

8 2019 Tri-State

Low-plex tissue based

Traditional IHC, FISH, and RNA-ISH

Manually determines the expression of specific target

within a tissue sample

Challenges

1. Lack of quantitation

2. Inability to phenotype cells

3. Limited data available from sample

High-plex non-tissue-based

NGS, Gene expression; and Flow cytometry

DNA, RNA or protein analysis from homogenized samples

Challenges

1. Lack of spatial context within tumor micro environment

2. Sequencing approaches do not provide direct evidence on mechanism of action

High-plex tissue-based

CyTOF; MIBI; serial staining

Alternative approaches for high-plex tissue analysis

Challenges

1. Workflow not fit-for-purpose for large scale translational work

2. Extremely costly for implementation

8

Key Components of IHC Assays

• Primary antibodies, labeled or unmodified, to the target of interest

• Variation in species; most commonly mouse, rabbit, rat

• Secondary Antibodies

• Interact with primary antibodies or probe labels

• Are themselves labeled in some way (enzymes, fluorophores, haptens)

• Chromogens/Fluorophores

• Substrate that reacts enzymatically with the labeled secondary antibody to visually denote where there is positivity for the target of interest in the tissue sample

• Counterstains/Post Counterstains

• Staining reagents applied after the completion of IHC to provide morphological context to the reader. Frequently a nuclear stain.

2019 Tri-State 9

4/29/2019

4

Key Components of IHC Assays

• Retrieval/Incubation/Reaction Buffers

• For antigen retrieval, antibody denaturing, and long incubation steps

• Usually citrate‐based pH 6, TRIS/EDTA based pH 9

• Antibody Diluents

• For the dilution of stocks to working concentration. Formulated to aid in the binding process.

• Enzymes

• Sometimes required for antigen unmasking, particularly with ISH

• Inhibitor/Blockers

• Peroxidase inhibitor used to quench endogenous peroxidase enzymes that may create background/false positives

• High‐ionic strength or high‐protein concentration blocking reagents that can be used to decrease background or signal‐to‐noise ratio in IHC

2019 Tri-State

Pre-Analytical Considerations

Garbage In, Garbage Out

2019 Tri-State O'Hurley, Gillian, et al. “Garbage in, Garbage out: A Critical Evaluation of Strategies Used for Validation of Immunohistochemical Biomarkers.” Molecular Oncology, vol. 8, 2014, pp. 783–798.

12

4/29/2019

5

Pre-Analytical Summary

• Tissue preservation and handling is key!

• Ensure fixative is appropriate for IHC (formalin), and was fixed for the appropriate time

• Sections are fresh or stored desiccated -80 C

• Antigen retrieval: correct for your target and fixation type

2019 Tri-State 13

Antibody Validation



15

4/29/2019

6

Antibody Validation Techniques

2019 Tri-State

• IHC comparison of staining patterns

• Human Protein Atlas, SPOCTOPUS, OMIM

• Paired antibodies, PLA, IP

• Isotype controls

• Competitive assays

• Positive and Negative cell/tissue controls

• Western Blots

• RNA

• sequencing data

• RNA ISH

16

Gorris, Mark A. J., et al. “Eight-Color Multiplex Immunohistochemistry for Simultaneous Detection of Multiple Immune Checkpoint Molecules within the Tumor Microenvironment.” The Journal of Immunology, 15 Nov. 2017.

Example Ideal Validation Workflow

2019 Tri-State Bordeaux, Jennifer, et al. “Antibody Validation.” BioTechniques ‐ Antibody Validation, Biotechniques, Mar. 2010.

17

Multiplex Development and Optimization

4/29/2019

7

General Procedure after Antibody Validation

Step 1

• Decide your method of detection

Step 2

• Decide your method of execution (manual vs auto)

Step 3

• Choose your panel order and detection pairings

Step 4

• Run DAB singles as reference for appropriate signal and dynamic range

Step 5

• Run monoplexesas though they are in the multiplex

• Assess staining against standard

Step 5

• Run multiplex

2019 Tri-State 19

Challenges with Multiplex Staining

• Antibody species cross-reactivity• Standard assumption is 1 target per species

• Antigen sheltering• Detection of 1st target obscures 2nd

• Fluorophore/chromogen cross-talk

• Low signals – weakly expressed or inaccessible targets; low affinity Ab• Results in long exposure times and photobleaching

• Imbalanced signals• reduces effectiveness of unmixing, especially when imbalances get to > 10x

• Poor dynamic range

• Background staining

• Autofluorescence from FFPE – masks marker signals

2019 Tri-State 20

Multiplex IHC Methods

• Directly labeled primaries

• Species/Species directly labeled secondaries

• Covalent Binding Strategies

2019 Tri-State 21

4/29/2019

8



22

Directly labeled primaries

Pros:

• Species-independent

• Quick incubations; cocktailing antibodies

Cons:

• No amplification

• Limited antibody selection/must conjugate

• Newer direct label techniques expensive

Species anti-target antibody

Fluorophore

Target on tissue

23

Species/Species directly labeled secondaries

Anti-species multimer (HRP or AP)

Species anti-target antibody

HRP/AP HRP/AP

Target on tissue

Pros:

• Unmodified primary antibodies

• Standard secondary antibodies

Cons:

• Limit in antibody species choice

• Little amplification

• Lower plexing limit

24

4/29/2019

9

CD20

CD4

PD-1

Anti-CD20 (Rabbit)

Anti-CD8 (Rabbit)

Anti-CD4 (Rabbit)HRP-Anti-Rabbit

Opal 540

Opal 570

Opal 690

Tissue Section

MicrowaveTreatmentMicrowaveTreatmentMicrowaveTreatment

CD8

MicrowaveTreatment

Anti-PD-1 (Rabbit)

Opal 520

Covalent Binding Strategies

Pros:

• Unmodified primary antibodies

• Any species antibody

• Amplification

• Dynamic Range

• High-plexing

Cons:

• Assay development and optimization time

25



26

Brightfield Staining

• Gold standard in diagnostics

• Familiar and easily/widely obtainable substrates

• DAB, Fast Red, AEC, NBT/BCIP, Silver

• Pathologists are used to it

• Standard microscopes apply

2019 Tri-State 27

4/29/2019

10

Qualitative vs. Quantitative

Quantitative, multi-analyte, per-cellVisual Protein Assessment

The tissue is the issue• Still the gold standard – primary diagnosis and most directly connected

to disease • Information not presently being accessed with conventional approaches• Samples are getting smaller and less available

needs new imaging and staining methods

2019 Tri-State 28

Immunofluorescence Staining

• Improve sensitivity by10 to 100‐fold

• Excellent resolution with low background

• 2 to 4 logs of dynamic range versus 1 log for chromogenic

• Reduce antibody consumption

• Signal is more linear

• Increase plexing for multiple biomarker detection strategies

• Add signal amplification to almost any immunoassay

Standard detection

TSA detection

2019 Tri-State 29



30

4/29/2019

11

Automated vs. Manual Staining

• Things to consider:

• Time

• Days vs overnight

• Reproducibility

• Operator variability

• Throughput

• Higher slide volume needs

• Cost

• Man hours vs budget

Remember: If you intend to run an assay either manually or automated, develop and optimize your assay the same way!

2019 Tri-State 31

Choosing antibody parameters

2019 Tri-State

• Optimize retrieval conditions for your antigen/antibody

• Assess staining completeness, correctness, and dynamic range

• 1, 3, and 6th

32

Deciding Substrate-Antibody Pairing and Staining Order

2019 Tri-State

Step Three: Important factors to keep in mind:

• Colocalization of markers

• Expression patterns (ie dynamic range)

• Epitope retrieval conditions

33

4/29/2019

12

Creating Monoplex Slides

2019 Tri-State

Include appropriate MWT/Denaturing steps: ie, your antibody going first will have 5 denatures after it, your second antibody should have one denature before and 4 after, etc

• Titering Substrate concentration

• 1:50, 1:100, 1:150

• Create simulated brightfield view if applicable, compare against initial DAB stain

34

Simulated IHC views for TIL assay applied to breast cancer

H&E view Foxp3 view

CD20Opal540

CD8Opal570

CD4Opal520

Foxp3Opal620

DAPI

Cytokeratin view

CD20 view CD8 view CD4 view

CD68Opal650

CKOpal690

Spectrally separated

CD68 view2019 Tri-State 35

Creating Monoplex Slides

2019 Tri-State

• Brightness counts: 10-30, or no more than a factor of 3 between neighboring channels. S:B 10:1

• Alternatively, ensure exposure times are equivalent/appropriate

• If MWT/Denaturing significantly impacts signal sensitivity/specificity:

• Re-order staining

• Increase substrate concentration

36

4/29/2019

13

Example Paper

• 8-Plex Fluorescent Assay:

• Gorris, Mark A. J., et al. “Eight-Color Multiplex Immunohistochemistry for Simultaneous Detection of Multiple Immune Checkpoint Molecules within the Tumor Microenvironment.” The Journal of Immunology, 15 Nov. 2017.

2019 Tri-State 37

Example Paper: Ab Validation

38 2019 Tri-State



2019 Tri-State 39

4/29/2019

14

40 2019 Tri-State


Troubleshooting

Troubleshooting: It’s just like IHC!

No Staining

• Primary antibody is the wrong species

• Primary antibody is not specific or sensitive to the exposed epitope

• Depar/AR is insufficient

• AR/fixation modified the epitope

• Your target isn’t there

Background

• Primary antibody concentration is too high

• Run isotype controls for secondary antibody activity

• Blocking is insufficient• Incubations are too

hot/long• Substrate

concentration is too high

Non-Specific Staining

• Antibody concentration is too high

• Tissue is dry• Blocking is insufficient• Endogenous enzymes

2019 Tri-State 42

4/29/2019

15

Common Reasons for New Assays to Fail

• MONOPLEXES ARE NOT DEVELOPED AS IN THE MULTIPLEX

• Remember: Always include denaturing steps into your monoplexes

• Antibody is not specific or sensitive enough

• Includes incorrect primary diluent or blocking strategies

• Pre-analytic issues (over/under fixation)

• Control/development tissue (ie tonsil) has extremely different expression pattern than study tissue

2019 Tri-State 43

Common Reasons for Established Assays to Fail

• New tissue source/type

• Even small variations or inconsistencies in fixation or processing protocols can change the effectiveness of retrieval or deparaffinization!

• New operator

• Aging of halide-based light sources

• Degradation or contamination of antibodies/substrate/diluent

• The sample simply isn’t positive for your marker!

• When in doubt: go back to your monoplexes

2019 Tri-State 44

Drop-Out Controls for Automation

2019 Tri-State

Drop‐Out Control Slides to Assess Automated Stripping Efficiency

Slide 1: First complete sequence, denature. Second sequence, without primary antibody (but with secondary and detection.)

Slide 2: Second complete sequence, denature. Third sequence, without primary antibody (but with secondary and detection.)

Slide 3: Third complete sequence, denature. Fourth sequence, without primary antibody (but with secondary and detection.)

Slide 4: Fourth complete sequence, denature. Fifth sequence, without primary antibody (but with secondary and detection.)

Slide 5: Fifth complete sequence, denature. Sixth sequence, without primary antibody (but with secondary and detection.)

If signal appears in the subsequent channel:

- Change order of application, Increase temperature to 100 C (BOND RX) or 95 C (DISCOVERY ULTRA), Increase number of denaturing cycles

Note: This workflow assumes the use of a cocktailed secondary antibody.

45

4/29/2019

16

Multispectral Imaging and Image Analysis



47

Why do we need image analysis?

2019 Tri-State

• Too much data for the human eye

• Understanding complex phenotypes

• Spatial relationships (immune cells in the tumor v stroma)

4/29/2019

17

Emerging Digital Pathology: Multispectral Imaging

2019 Tri-State

• With the aid of references, spectrally separate signals

• Remove autofluorescence

• Minimal bleedthrough/cross talk

• Distinct spectral layers aid in analysis

Traditional RGB Image

2019 Tri-State

Fluorophore signals bleed between filter cubes

Overlapping signals are indistinguishable

DAPICD68 (Opal 520)CD4 (Opal 540)CD8 (Opal 570)CK (Opal 620)PD-L1 (Opal 650)FoxP3 (Opal 690)Colon Cancer50

Multispectral Image with Autofluorescence

2019 Tri-State Colon Cancer51

4/29/2019

18

Underlying Autofluorescence Signal

2019 Tri-State

Autofluorescence pervasive due to fixation

Potential to block important signal

Colon Cancer52

Multispectral Image with AutofluorescenceRemoved

2019 Tri-State

DAPICD68 (Opal 520)CD4 (Opal 540)CD8 (Opal 570)CK (Opal 620)PD-L1 (Opal 650)FoxP3 (Opal 690)

Individual Signals Balanced and Unmixed

Autofluorescence not blocking important signal

Colon Cancer53

Trainable classifiers to Automate Detection and Segmentation of Tissue Morphologies

Tissue Segmentation

2019 Tri-State 54

4/29/2019

19

Cell Segmentation

2019 Tri-State

Identify and Segment Individual cells and their compartments

Accommodate densely packed cells and complex morphologies

Quantitate Per‐cell and per‐cell‐compartment expression levels

55

Cellular Phenotyping

2019 Tri-State

Visualize, analyze, quantify and phenotype immune and other cells

Phenotype low expressing epitopes

Analyze low phenotypic expressors

56

Cellular Scoring

2019 Tri-State

Access percent positivity via quantification of stain levels

Calculate H‐score

57

4/29/2019

20

Spatial Analytics

Nearest Phenotypic Neighbor Analysis

Count Cells within a fixed radius

Find, Count and Visualize touching cells

2019 Tri-State 58

Image Analysis Companies for mIHC

• PerkinElmer, Inc.: inForm Image Analysis Software

• Indicia Labs: HALO and HALO Link

• Visiopharm

• Analytical platforms:

• R

• MATLAB

• ImageJ

2019 Tri-State 59

Works Cited

• O'Hurley, Gillian, et al. “Garbage in, Garbage out: A Critical Evaluation of Strategies Used for Validation of Immunohistochemical Biomarkers.” Molecular Oncology, vol. 8, 2014, pp. 783–798.

• Bordeaux, Jennifer, et al. “Antibody Validation.” BioTechniques - Antibody Validation, Biotechniques, Mar. 2010.

• Gorris, Mark A. J., et al. “Eight-Color Multiplex Immunohistochemistry for Simultaneous Detection of Multiple Immune Checkpoint Molecules within the Tumor Microenvironment.” The Journal of Immunology, 15 Nov. 2017.

2019 Tri-State 60

4/29/2019

21

Questions?Thank you!

tristatehs multiplexing victoria duckworthmsfh.wildapricot.org/resources/documents/tristatehs... ·...

Documents