Flow Cytometry for Non-Hodgkin and Hodgkin Lymphomas

Multiparametric flow cytometry is a powerful diagnostic tool that permits rapid assessment of cellular antigen expression to quickly provide immunophenotypic information suitable for disease classification. This chapter describes a general approach for the identification of abnormal lymphoid populations by flow cytometry, including B, T, NK, and Hodgkin lymphoma cells suitable for the clinical and research environment. Knowledge of the common patterns of antigen expression of normal lymphoid cells is critical to permit identification of abnormal populations at disease presentation and for minimal residual disease assessment. We highlight an overview of procedures for processing and immunophenotyping non-Hodgkin B- and T-cell lymphomas and also describe our strategy for the sensitive and specific diagnosis of classic Hodgkin lymphoma, nodular lymphocyte predominant Hodgkin lymphoma, and T-cell/histiocyte-rich large B-cell lymphoma.

Utility of CCR7 to differentiate classic Hodgkin lymphoma and other B-cell lymphomas by flow cytometry and immunohistochemistry

OBJECTIVES

Classic Hodgkin lymphoma (CHL) is characterized by infrequent neoplastic Hodgkin and Reed-Sternberg (HRS) cells in an inflammatory background. The diagnostic utility of CC-chemokine receptor 7 (CCR7) in CHL was explored using flow cytometry and immunohistochemistry (IHC).

METHODS

Neoplastic specimens and non-neoplastic lymph nodes were immunophenotyped and CCR7 expression was measured semiquantitatively by flow cytometry (clone 3D12) and IHC (clone 150503).

RESULTS

Our results showed that CCR7 was expressed on HRS cells in the vast majority of CHL cases (45/48 by flow cytometry, 57/59 by IHC) but rarely expressed in neoplastic cells in diffuse large B-cell lymphoma, not otherwise specified (1/25 by flow cytometry, 2/40 by IHC) and nodular lymphocyte predominant Hodgkin lymphoma (0/4 by flow cytometry, 1/13 by IHC). Primary mediastinal large B-cell lymphoma (PMLBCL) revealed weak CCR7 expression by flow cytometry in most cases (8/10) but only occasionally by IHC (2/12). Both cases (2/2) of T-cell/histiocyte-rich large B-cell lymphoma (THRLBCL) also showed CCR7 expression detected by flow cytometry compared with IHC (0/7). The HRS cells demonstrated a greater percentage of positive cells and greater antigen intensity than the other B-cell lymphomas by IHC. The expression identified by flow cytometry in PMLBCL and THRLBCL but not by IHC suggests that there may be differences in the detection capabilities of the 2 techniques or the 2 CCR7 clones used.

CONCLUSIONS

The expression of CCR7 in HRS cells suggests its potential utility in differentiating CHL from other B-cell lymphomas. Incorporating CCR7 into flow cytometry and IHC panels may further enhance the diagnostic sensitivity of CHL.

Implicit Flow Cytometric Diagnosis of Classic Hodgkin Lymphoma Using CD3+CD4+CD26- T-Cells

BACKGROUND

Flow cytometry is not routinely performed in clinical laboratories for the diagnosis of classic Hodgkin lymphoma (CHL).

METHODS

Fourteen cases of CHL and 132 cases of the control group were studied by 10-color flow cytometry, with markers including CD3, CD4, CD7, CD8, and CD26, as well as calculated parameters such as the CD4:CD8 ratio, percent CD3+CD4+CD26- T-cells of CD3+CD4+ T-cells, percent CD3+CD4+CD26- T-cells of total events, CD7 coefficient of variation among CD3+CD4+CD26- T-cells, and CD7 median fluorescence intensity of CD3+CD4+CD26- T-cells relative to CD3+CD8+ T-cells.

RESULTS

CHL cases showed a median percent CD3+CD4+CD26- of CD3+CD4+ T-cells of 72.3% with range from 41.1% to 94.4%, median percent CD3+CD4+CD26- T-cells of total events of 17.4% with range from 4.6% to 52.5%, CD7 coefficient of variation among CD3+CD4+CD26- T-cells less than 100%, and CD7 median fluorescence intensity of CD3+CD4+CD26- T-cells relative to CD3+CD8+ T-cells of 1.7 with range from 0.4 to 3.5. In the control group, every entity showed some degree of overlap with CHL in terms of these parameters. A "Hodgkin score" was thus constructed to enhance separation of CHL from other entities. A threshold Hodgkin score of 15.35 achieved a sensitivity of 78.6% and specificity of 96.2% in the diagnosis of CHL. Incorporating the Hodgkin score into a simple algorithm raises the specificity to 100%.

CONCLUSION

In this study, we used flow cytometry to demonstrate increased CD3+CD4+CD26- T-cells in CHL, and derived a Hodgkin score for the diagnosis of CHL.

A Review of the Flow Cytometric Findings in Classic Hodgkin Lymphoma, Nodular Lymphocyte Predominant Hodgkin Lymphoma and T Cell/Histiocyte-Rich Large B Cell Lymphoma

Classic Hodgkin lymphoma, nodular lymphocyte predominant Hodgkin lymphoma, and T cell/histiocyte-rich large B cell lymphoma form a unique set of lymphomas with similar morphologic growth patterns (occasional neoplastic cells within a prominent cellular cell background) that are pathobiologically related. Distinguishing these entities has been historically difficult by flow cytometry; however, our laboratory has developed antibody-fluorochrome combinations capable of immunophenotyping these lymphomas. Additionally, characterization of the background reactive lymphocytes can aid in narrowing the differential diagnosis. This review summarizes the immunophenotypic features and insights of the neoplastic and reactive populations found in this unique group of lymphomas.

Flow cytometry assessment of reactive T-cells distinguishes classic Hodgkin lymphoma from benign lymphadenopathy in children

Background

Detection of classic Hodgkin lymphoma (cHL) neoplastic cells using flow cytometric immunophenotyping (FCI) remains limited. We hypothesized that characterization of the reactive infiltrates could assist in diagnosing cHL in children.

Methods

FCI using four‐color staining approaches was performed on 156 lymph node specimens with the following histopathologic diagnoses: cHL (25 cases), reactive lymphoid hyperplasia (RLH, 44 cases), and non‐Hodgkin lymphoma (87 cases).

Results

The overall concordance of FCI data with the histopathologic results of these cases was 81.4%. A reactive expansion of T‐cells with increased expression of CD45RO was present in the reactive infiltrate of cHL (CD45RO/CD3, 67.5%) and Epstein–Barr virus (EBV) infected RLH (62.7%) but not in EBV‐negative RLH (28.0%). The mean fluorescence intensity (MFI) of CD7 was higher for cHL and differed significantly from EBV‐positive RLH (138.5 vs. 63.8). A proposed diagnostic algorithm markedly elevated the overall concordance rate from 81.4% to 97.4%.

Conclusions

Immunophenotyping the reactive infiltrate of lymphoid tissue using flow cytometry is a reliable supplement to histopathology for the rapid diagnosis of pediatric cHL.

A comparison and review of the flow cytometric findings in classic Hodgkin lymphoma, nodular lymphocyte predominant Hodgkin lymphoma, T cell/histiocyte rich large B cell lymphoma, and primary mediastinal large B cell lymphoma

The "Hodgkin-like" lymphomas including classic Hodgkin lymphoma, nodular lymphocyte predominant Hodgkin lymphoma, T cell/histiocyte rich large B cell lymphoma, and primary mediastinal large B cell lymphoma have been shown to be pathobiologically related. With the exception of primary mediastinal large B cell lymphoma, these lymphomas have similar morphologic growth patterns with occasional neoplastic cells within a prominent reactive cell background. Historically, distinguishing these entities was difficult by flow cytometry; however, over the past 15 years, our laboratory has developed antibody-fluorochrome combinations capable of accurately distinguishing these entities by their immunoprofile. Additionally, an algorithmic approach based on characterization of the background reactive B-cell and T-cell populations can aid in narrowing the differential diagnosis. This review summarizes both the morphologic and immunophenotypic features and the current flow cytometric insights of the neoplastic and reactive populations found in this unique subset of lymphomas.

De Novo Identification and Visualization of Important Cell Populations for Classic Hodgkin Lymphoma Using Flow Cytometry and Machine Learning

OBJECTIVES

Automated classification of flow cytometry data has the potential to reduce errors and accelerate flow cytometry interpretation. We desired a machine learning approach that is accurate, is intuitively easy to understand, and highlights the cells that are most important in the algorithm's prediction for a given case.

METHODS

We developed an ensemble of convolutional neural networks for classification and visualization of impactful cell populations in detecting classic Hodgkin lymphoma using two-dimensional (2D) histograms. Data from 977 and 245 clinical flow cytometry cases were used for training and testing, respectively. Seventy-eight nongated 2D histograms were created per flow cytometry file. Shapley additive explanation (SHAP) values were calculated to determine the most impactful 2D histograms and regions within histograms. SHAP values from all 78 histograms were then projected back to the original cell data for gating and visualization using standard flow cytometry software.

RESULTS

The algorithm achieved 67.7% recall (sensitivity), 82.4% precision, and 0.92 area under the receiver operating characteristic. Visualization of the important cell populations for individual predictions demonstrated correlations with known biology.

CONCLUSIONS

The method presented enables model explainability while highlighting important cell populations in individual flow cytometry specimens, with potential applications in both diagnosis and discovery of previously overlooked key cell populations.

Role of Flow Cytometric Immunophenotyping for Classic Hodgkin Lymphoma in Small Biopsy and Cytology Specimens

CONTEXT.—

The diagnosis of classic Hodgkin lymphoma (CHL) traditionally requires surgical tissue biopsy because of the paucity of diagnostic Hodgkin and Reed-Sternberg cells. Diagnosis can be challenging in small core needle and cytologic biopsies, which are increasingly used because of reduced costs and minimal invasiveness. Flow cytometric (FC) identification of Hodgkin and Reed-Sternberg cells is possible, but FC test efficacy is not well studied outside of validation settings, especially in small specimens.

OBJECTIVE.—

To assess the testing efficacy of FC performed on small biopsy and cytology specimens for the diagnosis of CHL.

DESIGN.—

We reviewed 131 patients with CHL and 459 patients without CHL during a 3-year period who underwent a small biopsy procedure, including core biopsy and/or cytology evaluation, with concurrent routine clinical FC testing for CHL, assessing performance of FC in small specimens.

RESULTS.—

Evaluating testing efficacy, sensitivity was 95.4% and specificity was 98.2%, whereas positive and negative predictive values were 92.2% and 99.0%, respectively. Although there were more false-positive results than compared with published validation studies, expert review identified distinct diagnostic pitfalls; awareness of these may improve testing efficacy.

CONCLUSIONS.—

Although FC diagnosis of CHL was historically considered unfeasible, our findings in a real-world clinical setting suggest that FC adds diagnostic value to small biopsy evaluation, reducing time to treatment, costs, and invasive excisional procedures.

Flow Cytometry for Non-Hodgkin and Hodgkin Lymphomas

Multiparametric flow cytometry is a powerful diagnostic tool that permits rapid assessment of cellular antigen expression to quickly provide immunophenotypic information suitable for disease classification. This chapter describes a general approach for the identification of abnormal lymphoid populations by flow cytometry, including B, T, NK, and Hodgkin lymphoma cells suitable for the clinical and research environment. Knowledge of the common patterns of antigen expression of normal lymphoid cells is critical to permit identification of abnormal populations at disease presentation and for minimal residual disease assessment. We highlight an overview of procedures for processing and immunophenotyping non-Hodgkin B- and T-cell lymphomas and also describe our strategy for the sensitive and specific diagnosis of classical Hodgkin lymphoma and nodular lymphocyte predominant Hodgkin lymphoma.

Diagnosis of Hodgkin lymphoma in the modern era

The Hodgkin lymphomas are a family of unique lymphoma subtypes, in which the nature of the neoplastic cell was enigmatic for many years. Much of the mystery has been solved, with all forms now considered to be of B-cell origin, in most cases of germinal centre derivation. Today we recognize Hodgkin lymphoma as an eponym that encompasses multiple entities. One of the unifying themes is the major contribution from the tumour microenvironment. Both the character of the neoplastic cells and the nature of the immune environment are critical to accurate diagnosis. Moreover, an understanding of the molecular alterations that characterize both the neoplastic cells and their microenvironment have led to therapeutic advances, targeting both neoplastic and reactive components. Other conditions may foster a similar inflammatory milieu and lead to lymphoproliferations that mimic the Hodgkin lymphomas. In this review we provide an update on the diagnostic features of the various subtypes and include additional information relevant for prognostic evaluation and investigation of potential therapeutic targets. Additionally, we also discuss those conditions that often cause confusion in diagnosis and need to be distinguished from the Hodgkin lymphomas.

Flow cytometry for assessment of the tumor microenvironment in pediatric Hodgkin lymphoma

BACKGROUND

The role of flow cytometry in diagnosis and management of Hodgkin lymphoma (HL) remains limited. As knowledge emerges of the tumor microenvironment in this disease, various methods are being evaluated in its study. This study examines the microenvironment using flow cytometry to assess differences between subtypes and clinicopathologic correlates.

PROCEDURE

A retrospective cross-sectional study was performed analyzing the tumor immunophenotype, by flow cytometry, for 31 children with classical HL. Correlation was made with patient information, including outcome.

RESULTS

The makeup of the tumor microenvironment varies across subtype of HL, with T cells predominating in nodular sclerosis (NS), and similar proportions of B and T cells in mixed cellularity (MC). CD4 cells predominate in NS, whereas CD8 more so in MC subtype. The rate of continuous complete remission is significantly higher in the MC subgroup. Last, the proportion of HLA-DR/CD38 copositive lymphocytes was an independent prognostic factor for relapse/refractoriness.

CONCLUSIONS

This study indicates that flow cytometry can be used to examine the tumor microenvironment in HL and that percentage of HLA-DR/CD38 copositive lymphocytes may be a biomarker for relapse and refractoriness in pediatric HL.

Use of flow cytometry in the phenotypic diagnosis of hodgkin's lymphoma

Hodgkin's lymphoma (HL) has a unique immunophenotype derived from immunohistochemistry (positive for CD15, CD30, and Pax-5; negative for CD3, CD20 in most cases, and CD45). The knowledge gained over recent years enables better diagnosis, prognosis, and treatment of HL. Flow cytometry as a tool for the diagnosis of classic HL has not been useful in the past due to the difficulty in isolating Reed-Sternberg cells as they are admixed in a rich inflammatory background which consists mainly of T cells, B cells, eosinophils, histiocytes, and plasma cells. However, in the recent past, several studies have tried to identify Reed-Sternberg cells using flow cytometry on fine needle aspiration or tissue biopsy of lymph nodes to confirm or supplement immunohistochemistry staining in diagnosis. Newer and more sensitive tools such as flow cytometry can be used for diagnosis, technology that may have been difficult in the past for diagnosis of this lymphoma subtype. Using flow cytometry, diagnosis is faster and could lead to point-of-care technology especially where we have typical immunophenotype signatures. © 2018 International Clinical Cytometry Society.

Computer-aided detection of rare tumor populations in flow cytometry: an example with classic Hodgkin lymphoma

OBJECTIVES

Diagnosing classical Hodgkin lymphoma (cHL) by flow cytometry (FC) relies on an observer gating rare populations of Hodgkin/Reed Sternberg (HRS) cells. Here, we apply machine-learning methods to aid in the detection of rare tumor cell populations using data derived from clinical FC analysis of cHL as a model disease.

METHODS

FC data from 144 clinical cases using a nine-color FC reagent panel were analyzed using Python 2.7 and the "scikit-learn" module.

RESULTS

Seventy-eight 50 × 50 two-dimensional histograms were generated from routine FC data and a reciprocal power function applied to favor rare events. Data were classified by support vector machine (SVM), gradient boosting, and random forest classifiers. All three classifiers showed no statistical difference in performance, with 89%-92% accuracy on cross-validation. Nearly all classifiers misclassified the same set of cases, with more false-positive than false-negative cases. Dimensionality reduction by ensemble methods selected for data points in a CD5+/ CD40+/CD64- region.

CONCLUSIONS

All classifiers provide probabilistic confidences for each result, and diagnostic cutoffs can be chosen to minimize false negatives and serve as a screening tool. Computational exclusion of manually gated HRS cells had little impact on the overall performance of selected support vectors in SVM or dimensionality reduction, suggesting that features of the immune response in cHL may dictate the method accuracy. We hypothesize there are distinct inflammatory cells that suggest cHL.

A six-color flow cytometry assay for immunophenotyping classical Hodgkin lymphoma in lymph nodes

OBJECTIVES

We have recently demonstrated that classical Hodgkin lymphoma (CHL) can be immunophenotyped by flow cytometry (FC), thus obviating the need for immunohistochemistry in many cases. The previously described nine-color assay, however, cannot be used by laboratories that do not have access to a nine- or ten-color flow cytometer. Therefore, a six-color FC tube was designed employing the following combination: CD64-FITC/CD30-PE/CD40-PeCy5.5/CD20-PECy7/CD95-APC/CD3-APC-H7.

METHODS

To validate this assay, we analyzed 408 tissue specimens (including 55 CHL cases, 26 of which had been previously cryopreserved). Specimen inclusion criteria included the identification of an abnormal population by FC or (if no abnormal population was identified) greater than 50,000 viable events and specimen age less than 4 days. All FC studies were examined blinded to any clinical, laboratory, or histologic information.

RESULTS

The diagnostic sensitivity and specificity of the six-color FC assay was 85.4% and 99.7%, respectively.

CONCLUSIONS

Taken together, these results suggest that the six-color FC assay has acceptable sensitivity and specificity for clinical use, allowing more FC laboratories to immunophenotype CHL by this method.

Flow cytometry for non-Hodgkin and classical Hodgkin lymphoma

Multiparametric flow cytometry is a powerful diagnostic tool that permits rapid assessment of cellular antigen expression to quickly provide immunophenotypic information suitable for disease classification. This chapter describes a general approach for the identification of abnormal lymphoid populations by flow cytometry, including B, T, and Hodgkin lymphoma cells suitable for the clinical and research environment. Knowledge of the common patterns of antigen expression of normal lymphoid cells is critical to permit identification of abnormal populations at disease presentation and for minimal residual disease assessment. We highlight an overview of procedures for processing and immunophenotyping non-Hodgkin B- and T-cell lymphomas and also describe our strategy for the sensitive and specific diagnosis of classical Hodgkin lymphoma.

Strategies for immunophenotyping and purifying classical Hodgkin lymphoma cells from lymph nodes by flow cytometry and flow cytometric cell sorting

Flow cytometry is an established technique to immunophenotype hematopoietic neoplasms. While the diagnosis of classical Hodgkin lymphoma (CHL) has commonly been made using paraffin sections, we have recently demonstrated that the neoplastic Hodgkin and Reed-Sternberg (HRS) cells of CHL can be identified by flow cytometry. Using 6- and 9-color flow cytometric assays, CHL can be immunophenotyped with 85-90% sensitivity and nearly 100% specificity. Analysis of this data requires using established gating strategies to help in the identification of putative HRS cell populations. Interestingly, HRS cells bind to reactive T cells (HRS-T cell rosetting) and this phenomenon can be identified and utilized diagnostically by flow cytometry. In addition, the reactive T cells of CHL show characteristic immunophenotypic changes by flow cytometry and these changes can suggest a diagnosis of CHL. Finally, these principles can be employed to rapidly purify HRS cells using flow cytometric cell sorting. This manuscript provides experimental protocols for immunophenotyping CHL by flow cytometry as well as purifying the HRS cells via flow cytometric cell sorting.

Flow cytometric detection of the classical hodgkin lymphoma: clinical and research applications

Classical Hodgkin lymphoma (CHL) is a relatively uncommon B cell-derived neoplasm that presents with rare malignant cells in an abundant reactive background. The diagnosis of CHL currently relies on a combination of morphologic findings and immunohistochemical stains. With the exception of rare cases with dramatically increased malignant populations, isolation of pure viable tumor cells has not been historically possible. Recently, a reliable flow cytometric assay for direct detection and isolation of the malignant cells in this disease has been developed. This assay has proven useful diagnostically and has been clinically validated to have a very high sensitivity and nearly absolute specificity for the diagnosis of CHL in routine clinical samples. This paper describes the methodology for the flow cytometric detection of CHL in clinical samples as well as current state of evaluation of background lymphocytes as an adjunct diagnostic test. Also discussed are exciting research applications of the direct isolation of viable tumor cells in CHL. The current state of flow cytometric evaluation of nodular lymphocyte predominant Hodgkin lymphoma and T cell-rich large B cell lymphoma is also briefly discussed.