Tissue microarrays: leaping the gap between research and clinical adoption

Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging

Tissues and organs are composed of distinct cell types that must operate in concert to perform physiological functions. Efforts to create high-dimensional biomarker catalogs of these cells have been largely based on single-cell sequencing approaches, which lack the spatial context required to understand critical cellular communication and correlated structural organization. To probe in situ biology with sufficient depth, several multiplexed protein imaging methods have been recently developed. Though these technologies differ in strategy and mode of immunolabeling and detection tags, they commonly utilize antibodies directed against protein biomarkers to provide detailed spatial and functional maps of complex tissues. As these promising antibody-based multiplexing approaches become more widely adopted, new frameworks and considerations are critical for training future users, generating molecular tools, validating antibody panels, and harmonizing datasets. In this Perspective, we provide essential resources, key considerations for obtaining robust and reproducible imaging data, and specialized knowledge from domain experts and technology developers.

A new tool for technical standardization of the Ki67 immunohistochemical assay

Ki67, a nuclear proliferation-related protein, is heavily used in anatomic pathology but has not become a companion diagnostic or a standard-of-care biomarker due to analytic variability in both assay protocols and interpretation. The International Ki67 Working Group in breast cancer has published and has ongoing efforts in the standardization of the interpretation of Ki67, but they have not yet assessed technical issues of assay production representing multiple sources of variation, including antibody clones, antibody formats, staining platforms, and operators. The goal of this work is to address these issues with a new standardization tool. We have developed a cell line microarray system in which mixes of human Karpas 299 or Jurkat cells (Ki67⁺) with Sf9 (Spodoptera frugiperda) (Ki67^-) cells are present in incremental standardized ratios. To validate the tool, six different antibodies, including both ready-to-use and concentrate formats from six vendors, were used to measure Ki67 proliferation indices using IHC protocols for manual (bench-top) and automated platforms. The assays were performed by three different laboratories at Yale and analyzed using two image analysis software packages, including QuPath and Visiopharm. Results showed statistically significant differences in Ki67 reactivity between each antibody clone. However, subsets of Ki67 assays using three clones performed in three different labs show no significant differences. This work shows the need for analytic standardization of the Ki67 assay and provides a new tool to do so. We show here how a cell line standardization system can be used to normalize the staining variability in proliferation indices between different antibody clones in a triple negative breast cancer cohort. We believe that this cell line standardization array has the potential to improve reproducibility among Ki67 assays and laboratories, which is critical for establishing Ki67 as a standard-of-care assay.

Antibody validation for protein expression on tissue slides: a protocol for immunohistochemistry

Antibodies play a crucial role in basic research and clinical decision-making. However, there are no standardized algorithms or guidelines to ensure their accuracy and validity. There have been efforts to generate consensus, but, with the exception of clinical labs, antibody validation remains variable in the literature and sometimes in clinical practice. Here we focus on immunohistochemistry, an example of a scientific and clinical tool where validation of antibodies is critical. We describe a protocol that we use to validate antibodies specifically for immunohistochemistry, including some of the pillars of antibody validation from Uhlen et al. 2016, as an example of a rigorous approach to build antibody-based tests for both basic and translational science labs and for the clinic.

Cross-Platform Comparison of Computer-assisted Image Analysis Quantification of In Situ mRNA Hybridization in Investigative Pathology

Although availability of automated platforms has proliferated, there is no standard practice for computer-assisted generation of scores for mRNA in situ hybridization (ISH) visualized by brightfield microscopic imaging on tissue sections. To address this systematically, an ISH for peptidylprolyl isomerase B (PPIB) (cyclophilin B) mRNA was optimized and applied to a tissue microarray of archival non-small cell lung carcinoma cases, and then automated image analysis for PPIB was refined across 4 commercially available software platforms. Operator experience and scoring results from ImageScope, HALO, CellMap, and Developer XD were systematically compared with each other and to manual pathologist scoring. Markup images were compared and contrasted for accuracy, the ability of the platform to identify cells, and the ease of visual assessment to determine appropriate interpretation. Comparing weighted scoring approaches using H-scores (Developer XD, ImageScope, and manual scoring) a correlation was observed (R value=0.7955), and association between the remaining 2 approaches (HALO and CellMap) was of similar value. ImageScope showed the highest R value in comparison with manual scoring (0.7377). Mean-difference plots showed that HALO produced the highest relative normalized values, suggesting higher relative sensitivity. ImageScope overestimated PPIB ISH signal at the high end of the range scores; however, this tendency was not observed in other platforms. HALO emerged with the highest number of favorable observations, no apparent systematic bias in score generation compared with the other methods, and potentially higher sensitivity to detect ISH. HALO may serve as a tool to empower teams of investigative pathology laboratory scientists to assist pathologists readily with quantitative scoring of ISH.

The Society for Immunotherapy of Cancer statement on best practices for multiplex immunohistochemistry (IHC) and immunofluorescence (IF) staining and validation

OBJECTIVES

The interaction between the immune system and tumor cells is an important feature for the prognosis and treatment of cancer. Multiplex immunohistochemistry (mIHC) and multiplex immunofluorescence (mIF) analyses are emerging technologies that can be used to help quantify immune cell subsets, their functional state, and their spatial arrangement within the tumor microenvironment.

METHODS

The Society for Immunotherapy of Cancer (SITC) convened a task force of pathologists and laboratory leaders from academic centers as well as experts from pharmaceutical and diagnostic companies to develop best practice guidelines for the optimization and validation of mIHC/mIF assays across platforms.

RESULTS

Representative outputs and the advantages and disadvantages of mIHC/mIF approaches, such as multiplexed chromogenic IHC, multiplexed immunohistochemical consecutive staining on single slide, mIF (including multispectral approaches), tissue-based mass spectrometry, and digital spatial profiling are discussed.

CONCLUSIONS

mIHC/mIF technologies are becoming standard tools for biomarker studies and are likely to enter routine clinical practice in the near future. Careful assay optimization and validation will help ensure outputs are robust and comparable across laboratories as well as potentially across mIHC/mIF platforms. Quantitative image analysis of mIHC/mIF output and data management considerations will be addressed in a complementary manuscript from this task force.

Multiplexed (18-Plex) Measurement of Signaling Targets and Cytotoxic T Cells in Trastuzumab-Treated Patients using Imaging Mass Cytometry

PURPOSE

Imaging mass cytometry (IMC) uses metal-conjugated antibodies to provide multidimensional, objective measurement of protein targets. We used this high-throughput platform to perform an 18-plex assessment of HER2 ICD/ECD, cytotoxic T-cell infiltration and other structural and signaling proteins in a cohort of patients treated with trastuzumab to discover associations with trastuzumab benefit.

EXPERIMENTAL DESIGN

An antibody panel for detection of 18 targets (pan-cytokeratin, HER2 ICD, HER2 ECD, CD8, vimentin, cytokeratin 7, β-catenin, HER3, MET, EGFR, ERK 1-2, MEK 1-2, PTEN, PI3K p110 α, Akt, mTOR, Ki67, and Histone H3) was used with a selection of trastuzumab-treated patients from the Hellenic Cooperative Oncology Group 10/05 trial (n = 180), and identified a case-control series.

RESULTS

Patients that recurred after adjuvant treatment with trastuzumab trended toward a decreased fraction of HER2 ECD pixels over threshold compared with cases without recurrence (P = 0.057). After exclusion of the lowest HER2 expressers, 5-year recurrence events were associated with reduced total extracellular domain (ECD)/intracellular domain (ICD) ratio intensity in tumor (P = 0.044). These observations are consistent with our previous work using quantitative immunofluorescence, but represent the proof on identical cell content. We also describe the association of the ECD of HER2 with CD8 T-cell infiltration on the same slide.

CONCLUSIONS

The proximity of CD8 cells as a function of the expression of the ECD of HER2 provides further evidence for the role of the immune system in the mechanism of action of trastuzumab.

Signaling protein signature predicts clinical outcome of non-small-cell lung cancer

BACKGROUND

Non-small-cell lung cancer (NSCLC) is characterized by abnormalities of numerous signaling proteins that play pivotal roles in cancer development and progression. Many of these proteins have been reported to be correlated with clinical outcomes of NSCLC. However, none of them could provide adequate accuracy of prognosis prediction in clinical application.

METHODS

A total of 384 resected NSCLC specimens from two hospitals in Beijing (BJ) and Chongqing (CQ) were collected. Using immunohistochemistry (IHC) staining on stored formalin-fixed paraffin-embedded (FFPE) surgical samples, we examined the expression levels of 75 critical proteins on BJ samples. Random forest algorithm (RFA) and support vector machines (SVM) computation were applied to identify protein signatures on 2/3 randomly assigned BJ samples. The identified signatures were tested on the remaining BJ samples, and were further validated with CQ independent cohort.

RESULTS

A 6-protein signature for adenocarcinoma (ADC) and a 5-protein signature for squamous cell carcinoma (SCC) were identified from training sets and tested in testing sets. In independent validation with CQ cohort, patients can also be divided into high- and low-risk groups with significantly different median overall survivals by Kaplan-Meier analysis, both in ADC (31 months vs. 87 months, HR 2.81; P <  0.001) and SCC patients (27 months vs. not reached, HR 9.97; P <  0.001). Cox regression analysis showed that both signatures are independent prognostic indicators and outperformed TNM staging (ADC: adjusted HR 3.07 vs. 2.43, SCC: adjusted HR 7.84 vs. 2.24). Particularly, we found that only the ADC patients in high-risk group significantly benefited from adjuvant chemotherapy (P = 0.018).

CONCLUSIONS

Both ADC and SCC protein signatures could effectively stratify the prognosis of NSCLC patients, and may support patient selection for adjuvant chemotherapy.

Larger core size has superior technical and analytical accuracy in bladder tissue microarray

The construction of tissue microarrays (TMAs) with cores from a large number of paraffin-embedded tissues (donors) into a single paraffin block (recipient) is an effective method of analyzing samples from many patient specimens simultaneously. For the TMA to be successful, the cores within it must capture the correct histologic areas from the donor blocks (technical accuracy) and maintain concordance with the tissue of origin (analytical accuracy). This can be particularly challenging for tissues with small histological features such as small islands of carcinoma in situ (CIS), thin layers of normal urothelial lining of the bladder, or cancers that exhibit intratumor heterogeneity. In an effort to create a comprehensive TMA of a bladder cancer patient cohort that accurately represents the tumor heterogeneity and captures the small features of normal and CIS, we determined how core size (0.6 vs 1.0 mm) impacted the technical and analytical accuracy of the TMA. The larger 1.0 mm core exhibited better technical accuracy for all tissue types at 80.9% (normal), 94.2% (tumor), and 71.4% (CIS) compared with 58.6%, 85.9%, and 63.8% for 0.6 mm cores. Although the 1.0 mm core provided better tissue capture, increasing the number of replicates from two to three allowed with the 0.6 mm core compensated for this reduced technical accuracy. However, quantitative image analysis of proliferation using both Ki67+ immunofluorescence counts and manual mitotic counts demonstrated that the 1.0 mm core size also exhibited significantly greater analytical accuracy (P=0.004 and 0.035, respectively, r²=0.979 and 0.669, respectively). Ultimately, our findings demonstrate that capturing two or more 1.0 mm cores for TMA construction provides superior technical and analytical accuracy over the smaller 0.6 mm cores, especially for tissues harboring small histological features or substantial heterogeneity.

Validation of tumor protein marker quantification by two independent automated immunofluorescence image analysis platforms

Protein marker levels in formalin-fixed, paraffin-embedded tissue sections traditionally have been assayed by chromogenic immunohistochemistry and evaluated visually by pathologists. Pathologist scoring of chromogen staining intensity is subjective and generates low-resolution ordinal or nominal data rather than continuous data. Emerging digital pathology platforms now allow quantification of chromogen or fluorescence signals by computer-assisted image analysis, providing continuous immunohistochemistry values. Fluorescence immunohistochemistry offers greater dynamic signal range than chromogen immunohistochemistry, and combined with image analysis holds the promise of enhanced sensitivity and analytic resolution, and consequently more robust quantification. However, commercial fluorescence scanners and image analysis software differ in features and capabilities, and claims of objective quantitative immunohistochemistry are difficult to validate as pathologist scoring is subjective and there is no accepted gold standard. Here we provide the first side-by-side validation of two technologically distinct commercial fluorescence immunohistochemistry analysis platforms. We document highly consistent results by (1) concordance analysis of fluorescence immunohistochemistry values and (2) agreement in outcome predictions both for objective, data-driven cutpoint dichotomization with Kaplan-Meier analyses or employment of continuous marker values to compute receiver-operating curves. The two platforms examined rely on distinct fluorescence immunohistochemistry imaging hardware, microscopy vs line scanning, and functionally distinct image analysis software. Fluorescence immunohistochemistry values for nuclear-localized and tyrosine-phosphorylated Stat5a/b computed by each platform on a cohort of 323 breast cancer cases revealed high concordance after linear calibration, a finding confirmed on an independent 382 case cohort, with concordance correlation coefficients >0.98. Data-driven optimal cutpoints for outcome prediction by either platform were reciprocally applicable to the data derived by the alternate platform, identifying patients with low Nuc-pYStat5 at ~3.5-fold increased risk of disease progression. Our analyses identified two highly concordant fluorescence immunohistochemistry platforms that may serve as benchmarks for testing of other platforms, and low interoperator variability supports the implementation of objective tumor marker quantification in pathology laboratories.

"Score the Core" Web-based pathologist training tool improves the accuracy of breast cancer IHC4 scoring

Hormone receptor status is an integral component of decision-making in breast cancer management. IHC4 score is an algorithm that combines hormone receptor, HER2, and Ki-67 status to provide a semiquantitative prognostic score for breast cancer. High accuracy and low interobserver variance are important to ensure the score is accurately calculated; however, few previous efforts have been made to measure or decrease interobserver variance. We developed a Web-based training tool, called "Score the Core" (STC) using tissue microarrays to train pathologists to visually score estrogen receptor (using the 300-point H score), progesterone receptor (percent positive), and Ki-67 (percent positive). STC used a reference score calculated from a reproducible manual counting method. Pathologists in the Athena Breast Health Network and pathology residents at associated institutions completed the exercise. By using STC, pathologists improved their estrogen receptor H score and progesterone receptor and Ki-67 proportion assessment and demonstrated a good correlation between pathologist and reference scores. In addition, we collected information about pathologist performance that allowed us to compare individual pathologists and measures of agreement. Pathologists' assessment of the proportion of positive cells was closer to the reference than their assessment of the relative intensity of positive cells. Careful training and assessment should be used to ensure the accuracy of breast biomarkers. This is particularly important as breast cancer diagnostics become increasingly quantitative and reproducible. Our training tool is a novel approach for pathologist training that can serve as an important component of ongoing quality assessment and can improve the accuracy of breast cancer prognostic biomarkers.

Quantitative measurement of cancer tissue biomarkers in the lab and in the clinic

Detection of biomolecules in tissues provides contextual information and the possibility to assess the interaction of different cell types and markers. Routine qualitative assessment of immune- and oligonucleotide-based methods in research and the clinic has been associated with assay variability because of lack of stringent validation and subjective interpretation of results. As a result, the vast majority of in situ assays in clinical usage are nonquantitative and, although useful, often of questionable scientific validity. Here, we revisit the reporters and methods used for single- and multiplexed in situ visualization of protein and RNA. Then we examine methods for the use of quantitative platforms for in situ measurement of protein and mRNA levels. Finally, we discuss the challenges of the transition of these methods to the clinic and their potential role as tools for development of companion diagnostic tests.

The future of laboratory medicine - a 2014 perspective

Predicting the future is a difficult task. Not surprisingly, there are many examples and assumptions that have proved to be wrong. This review surveys the many predictions, beginning in 1887, about the future of laboratory medicine and its sub-specialties such as clinical chemistry and molecular pathology. It provides a commentary on the accuracy of the predictions and offers opinions on emerging technologies, economic factors and social developments that may play a role in shaping the future of laboratory medicine.