Analytic Response Curves of Clinical Breast Cancer IHC Tests

Quantitative comparison of immunohistochemical HER2-low detection in an interlaboratory study

AIMS

Recently, human epidermal growth factor 2 (HER2)-low (i.e. HER2 score 1+ or 2+ without amplification) breast cancer patients became eligible for trastuzumab-deruxtecan treatment. To improve assay standardisation and detection of HER2-low in a quantitative manner, we conducted an external quality assessment-like study in the Netherlands. Dynamic range cell lines and immunohistochemistry (IHC) calibrators were used to quantify HER2 expression and to assess interlaboratory variability.

METHODS AND RESULTS

Three blank slides with a dynamic range cell line and an IHC calibrator were stained with routine HER2 assays by 35 laboratories. Four different antibody clones were used: 19 (54.3%) 4B5, six (17.1%) A0485, five (14.3%) DG44 (HercepTest) and five (14.3%) SP3. Laboratories used two different detection kits for 4B5 assays: 14 (73.7%) ultraView and five (26.3%) OptiView. Variability of HER2 expression in cell lines, measured with artificial intelligence software, was median (min-max) = negative core 0.5% (0.0-57.0), 1+ core 4.3% (1.6-71.3), 2+ core 42.8% (30.4-92.6) and 3+ core 96.2% (91.8-98.8). The calibrators DG44 and 4B5 OptiView had the highest analytical sensitivity, closely followed by 4B5 ultraView. SP3 was the least sensitive. Calibrators of A0485 assays were not analysable due to background staining.

CONCLUSIONS

As assays were validated for detecting HER2-amplified tumours, not all assays and antibodies proved suitable for HER2-low detection. Some tests showed distinct expression in the negative cell line. Dynamic range cell line controls and quantitative analysis using calibrators demonstrated more interlaboratory variability than commonly appreciated. Revalidation of HER2 tests by laboratories is needed to ensure clinical applicable HER2-low assays.

Digital Image Analysis and Quantitative Bead Standards in Root Cause Analysis of Immunohistochemical Staining Variability: A Real-world Example

Assessment of automated immunohistochemical staining platform performance is largely limited to the visual evaluation of individual slides by trained personnel. Quantitative assessment of stain intensity is not typically performed. Here we describe our experience with 2 quantitative strategies that were instrumental in root cause investigations performed to identify the sources of suboptimal staining quality (decreased stain intensity and increased variability). In addition, these tools were utilized as adjuncts in validation of a new immunohistochemical staining instrument. The novel methods utilized in the investigation include quantitative assessment of whole slide images (WSI) and commercially available quantitative calibrators. Over the course of ~13 months, these methods helped to identify and verify correction of 2 sources of suboptimal staining. One root cause of suboptimal staining was insufficient/variable power delivery from our building's electrical circuit. This led us to use uninterruptible power managers for all automated immunostainer instruments, which restored expected stain intensity and consistency. Later, we encountered one instrument that, despite passing all vendor quality control checks and not showing error alerts was suspected of yielding suboptimal stain quality. WSI analysis and quantitative calibrators provided a clear evidence that proved critical in confirming the pathologists' visual impressions. This led to the replacement of the instrument, which was then validated using a combination of standard validation metrics supplemented by WSI analysis and quantitative calibrators. These root cause analyses document 2 variables that are critical in producing optimal immunohistochemical stain results and also provide real-world examples of how the application of quantitative tools to measure automated immunohistochemical stain output can provide a greater objectivity when assessing immunohistochemical stain quality.

Quantitative comparison of PD-L1 IHC assays against NIST standard reference material 1934

Companion diagnostic immunohistochemistry (IHC) tests are developed and performed without incorporating the tools and principles of laboratory metrology. Basic analytic assay parameters such as lower limit of detection (LOD) and dynamic range are unknown to both assay developers and end users. We solved this problem by developing completely new tools for IHC-calibrators with units of measure traceable to National Institute of Standards & Technology (NIST) Standard Reference Material (SRM) 1934. In this study, we demonstrate the clinical impact and opportunity for incorporating these changes into PD-L1 testing. Forty-one laboratories in North America and Europe were surveyed with newly-developed PD-L1 calibrators. The survey sampled a broad representation of commercial and laboratory-developed tests (LDTs). Using the PD-L1 calibrators, we quantified analytic test parameters that were previously only inferred indirectly after large clinical studies. The data show that the four FDA-cleared PD-L1 assays represent three different levels of analytic sensitivity. The new analytic sensitivity data explain why some patients' tissue samples were positive by one assay and negative by another. The outcome depends on the assay's lower LOD. Also, why previous attempts to harmonize certain PD-L1 assays were unsuccessful; the assays' dynamic ranges were too disparate and did not overlap. PD-L1 assay calibration also clarifies the exact performance characteristics of LDTs relative to FDA-cleared commercial assays. Some LDTs' analytic response curves are indistinguishable from their predicate FDA-cleared assay. IHC assay calibration represents an important transition for companion diagnostic testing. The new tools will improve patient treatment stratification, test harmonization, and foster accuracy as tests transition from clinical trials to broad clinical use.

Tissue Multiplex Analyte Detection in Anatomic Pathology - Pathways to Clinical Implementation

Background: Multiplex tissue analysis has revolutionized our understanding of the tumor microenvironment (TME) with implications for biomarker development and diagnostic testing. Multiplex labeling is used for specific clinical situations, but there remain barriers to expanded use in anatomic pathology practice.

Methods: We review immunohistochemistry (IHC) and related assays used to localize molecules in tissues, with reference to United States regulatory and practice landscapes. We review multiplex methods and strategies used in clinical diagnosis and in research, particularly in immuno-oncology. Within the framework of assay design and testing phases, we examine the suitability of multiplex immunofluorescence (mIF) for clinical diagnostic workflows, considering its advantages and challenges to implementation.

Results: Multiplex labeling is poised to radically transform pathologic diagnosis because it can answer questions about tissue-level biology and single-cell phenotypes that cannot be addressed with traditional IHC biomarker panels. Widespread implementation will require improved detection chemistry, illustrated by InSituPlex technology (Ultivue, Inc., Cambridge, MA) that allows coregistration of hematoxylin and eosin (H&E) and mIF images, greater standardization and interoperability of workflow and data pipelines to facilitate consistent interpretation by pathologists, and integration of multichannel images into digital pathology whole slide imaging (WSI) systems, including interpretation aided by artificial intelligence (AI). Adoption will also be facilitated by evidence that justifies incorporation into clinical practice, an ability to navigate regulatory pathways, and adequate health care budgets and reimbursement. We expand the brightfield WSI system “pixel pathway” concept to multiplex workflows, suggesting that adoption might be accelerated by data standardization centered on cell phenotypes defined by coexpression of multiple molecules.

Conclusion: Multiplex labeling has the potential to complement next generation sequencing in cancer diagnosis by allowing pathologists to visualize and understand every cell in a tissue biopsy slide. Until mIF reagents, digital pathology systems including fluorescence scanners, and data pipelines are standardized, we propose that diagnostic labs will play a crucial role in driving adoption of multiplex tissue diagnostics by using retrospective data from tissue collections as a foundation for laboratory-developed test (LDT) implementation and use in prospective trials as companion diagnostics (CDx).

Development and Validation of Measurement Traceability for In Situ Immunoassays

BACKGROUND

Immunoassays for protein analytes measured in situ support a $2 billion laboratory testing industry that suffers from significant interlaboratory disparities, affecting patient treatment. The root cause is that immunohistochemical testing lacks the generally accepted tools for analytic standardization, including reference standards and traceable units of measure. Until now, the creation of these tools has represented an insoluble technical hurdle.

METHODS

We address the need with a new concept in metrology-that is, linked traceability. Rather than calculating analyte concentration directly, which has proven too variable, we calculate concentration by measuring an attached fluorescein, traceable to NIST Standard Reference Material 1934, a fluorescein standard.

RESULTS

For validation, newly developed estrogen receptor (ER) calibrators were deployed in tandem with an array of 80 breast cancer tissue sections in a national external quality assessment program. Laboratory performance was assessed using both the ER standards and the tissue array. Similar to previous studies, the tissue array revealed substantial discrepancies in ER test results among the participating laboratories. The new ER calibrators revealed a broad range of analytic sensitivity, with the lower limits of detection ranging from 7310 to 74 790 molecules of ER. The data demonstrate, for the first time, that the variable test results correlate with analytic sensitivity, which can now be measured quantitatively.

CONCLUSIONS

The reference standard enables precise interlaboratory alignment of immunohistochemistry test sensitivity for measuring cellular proteins in situ. The introduction of a reference standard and traceable units of measure for protein expression marks an important milestone.

Synthetic Antigen Gels as Practical Controls for Standardized and Quantitative Immunohistochemistry

Optimization and standardization of immunohistochemistry (IHC) protocols within and between laboratories requires reproducible positive and negative control samples. In many situations, suitable tissue or cell line controls are not available. We demonstrate here a method to incorporate target antigens into synthetic protein gels that can serve as IHC controls. The method can use peptides, protein domains, or whole proteins as antigens, and is compatible with a variety of fixation protocols. The resulting gels can be used to create tissue microarrays (TMAs) with a range of antigen concentrations that can be used to objectively quantify and calibrate chromogenic, fluorescent, or mass spectrometry-based IHC protocols. The method offers an opportunity to objectively quantify IHC staining results, and to optimize and standardize IHC protocols within and between laboratories. (J Histochem Cytochem 58:XXX-XXX, 2019).

A Root Cause Analysis Into the High Error Rate in Clinical Immunohistochemistry

The field of Clinical Immunohistochemistry (IHC) is beset with a high error rate, an order of magnitude higher than in other types of clinical laboratory testing. Despite the many improvements in the field, these errors have persisted over the last 2 decades. The improvements over the years include an extensive literature describing the potential causes of errors and how to avoid them. More stringent regulatory guidelines have also been implemented. These measures reflect the standard view is that fixing the broad confluence of causes of error will address the problem. This review takes a different tack. To understand the high error rates, this review compares Clinical IHC laboratory practice to practices of other clinical laboratory disciplines. What aspects of laboratory testing that minimize errors in other clinical laboratory disciplines are not found in Clinical IHC? In this review, we seek to identify causal factors and underlying root causes that are unique to the field of Clinical IHC in comparison to other laboratory testing disciplines. The most important underlying root cause is the absence of traceable units of measure, international standards, calibrators that are traceable to standards, and quantitative monitoring of controls. These tools and practices (in other clinical laboratory disciplines) provide regular accurate feedback to laboratory personnel on analytic test performance.

Selecting an Optimal Positive IHC Control for Verifying Antigen Retrieval

Positive immunohistochemistry (IHC) controls are intended to detect problems in both immunostaining and heat-induced epitope retrieval (HIER). However, it is not known what features in a control are important for verifying HIER. Contrary to expectation, the fact that a tissue is formalin-fixed does not necessarily render it suitable in verifying proper HIER. Some tissue controls, for some immunostains, strongly stain even without HIER. Consequently, the control may verify the immunostain but provide little or no information regarding the HIER step. To sort this out, we used formalin-fixed peptide epitopes, a model that provides for precise definition of analyte concentration, epitope composition, and degree of fixation. Our data demonstrate that formalin fixation generates a variable level of protein epitope masking, depending on the epitope recognized by the primary antibody. Some epitopes are highly masked while others hardly at all. Furthermore, the ability of amino acids in the epitope to react with formaldehyde can, at least in part, account for this variability. Most important, we demonstrate the importance of selecting a positive control with a low or intermediate analyte concentration (relative to the immunostain's analytic sensitivity). High analyte concentrations can be insensitive in verifying the HIER step.

Quantitative Assessment of Immunohistochemistry Laboratory Performance by Measuring Analytic Response Curves and Limits of Detection

Context.—

Numerous studies highlight interlaboratory performance variability in diagnostic immunohistochemistry (IHC) testing. Despite substantial improvements over the years, the inability to quantitatively and objectively assess immunostain sensitivity complicates interlaboratory standardization.

Objective.—

To quantitatively and objectively assess the sensitivity of the immunohistochemical stains for human epidermal growth factor receptor type 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) across IHC laboratories in a proficiency testing format. We measure sensitivity with parameters that are new to the field of diagnostic IHC: analytic response curves and limits of detection.

Design.—

Thirty-nine diagnostic IHC laboratories stained a set of 3 slides, one each for HER2, ER, and PR. Each slide incorporated a positive tissue section and IHControls at 5 different concentrations. The IHControls comprise cell-sized clear microbeads coated with defined concentrations of analyte (HER2, ER, and/or PR). The laboratories identified the limits of detection and then mailed the slides for quantitative assessment.

Results.—

Each commercial immunostain demonstrated a characteristic analytic response curve, reflecting strong reproducibility among IHC laboratories using the same automation and reagents prepared per current Good Manufacturing Practices. However, when comparing different commercial vendors (using different reagents), the data reveal up to 100-fold differences in analytic sensitivity. For proficiency testing purposes, quantitative assessment using analytic response curves was superior to subjective interpretation of limits of detection.

Conclusions.—

Assessment of IHC laboratory performance by quantitative measurement of analytic response curves is a powerful, objective tool for identifying outlier IHC laboratories. It uniquely evaluates immunostain performance across a range of defined analyte concentrations.

The Importance of Epitope Density in Selecting a Sensitive Positive IHC Control

Clinical Immunohistochemistry (IHC) laboratories face unique challenges in performing accurate and reproducible immunostains. Among these challenges is the use of homemade controls derived from pathological discard samples. Such positive controls have an unknown number of analyte molecules per cell (epitope density). It is unclear how the lack of defined analyte concentrations affects performance of the control. To address this question, we prepared positive IHC controls ( IHControls) for human epidermal growth factor receptor type II (HER-2), estrogen receptor (ER), or progesterone receptor (PR) with well-defined, homogeneous, and reproducible analyte concentrations. Using the IHControls, we examined the effect of analyte concentration on IHC control sensitivity. IHControls and conventional tissue controls were evaluated in a series of simulated primary antibody reagent degradation experiments. The data demonstrate that the ability of a positive IHC control to reveal reagent degradation depends on (1) the analyte concentration in the control and (2) where that concentration falls on the immunostain's analytic response curve. The most sensitive positive IHC controls have analyte concentrations within or close to the immunostain's concentration-dependent response range. Strongly staining positive controls having analyte concentrations on the analytic response curve plateau are less sensitive. These findings emphasize the importance of selecting positive IHC controls that are of intermediate (rather than strong) stain intensity.