Gene expression profiling of microdissected Hodgkin Reed-Sternberg cells correlates with treatment outcome in classical Hodgkin lymphoma

Blood ◽  
2012 ◽  
Vol 120 (17) ◽  
pp. 3530-3540 ◽  
Author(s):  
Christian Steidl ◽  
Arjan Diepstra ◽  
Tang Lee ◽  
Fong Chun Chan ◽  
Pedro Farinha ◽  
...  

Abstract In classical Hodgkin lymphoma (CHL), 20%-30% of patients experience relapse or progressive disease after initial treatment. The pathogenesis and biology of treatment failure are still poorly understood, in part because the molecular phenotype of the rare malignant Hodgkin Reed-Sternberg (HRS) cells is difficult to study. Here we examined microdissected HRS cells from 29 CHL patients and 5 CHL-derived cell lines by gene expression profiling. We found significant overlap of HL-specific gene expression in primary HRS cells and HL cell lines, but also differences, including surface receptor signaling pathways. Using integrative analysis tools, we identified target genes with expression levels that significantly correlated with genomic copy-number changes in primary HRS cells. Furthermore, we found a macrophage-like signature in HRS cells that significantly correlated with treatment failure. CSF1R is a representative of this signature, and its expression was significantly associated with progression-free and overall survival in an independent set of 132 patients assessed by mRNA in situ hybridization. A combined score of CSF1R in situ hybridization and CD68 immunohistochemistry was an independent predictor for progression-free survival in multivariate analysis. In summary, our data reveal novel insights into the pathobiology of treatment failure and suggest CSF1R as a drug target of at-risk CHL.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 266-266 ◽  
Author(s):  
Enrico Tiacci ◽  
Verena Brune ◽  
Susan Eckerle ◽  
Wolfram Klapper ◽  
Ines Pfeil ◽  
...  

Abstract Abstract 266 Background. Previous gene expression profiling studies on cHL have been performed on whole tissue sections (mainly reflecting the prominent reactive background in which the few HRS cells are embedded), or on cHL cell lines. However, cultured HRS cells do not likely reflect primary HRS cells in all aspects, being derived from end-stage patients and from sites (e.g. pleural effusions or bone marrow) which are not typically involved by cHL and where HRS cells lost their dependence on the inflammatory microenvironment of the lymph node. Methods. ∼1000–2000 neoplastic cells were laser-microdissected from hematoxylin/eosin-stained frozen sections of lymph nodes taken at disease onset from patients with cHL (n=16) or with various B-cell lymphomas (n=35), including primary mediastinal B-cell lymphoma (PMBL) and nodular lymphocyte-predominant Hodgkin lymphoma (nLPHL). After two rounds of in vitro linear amplification, mRNA was hybridized to Affymetrix HG-U133 Plus 2.0 chips. Expression profiles were likewise generated from sorted cHL cell lines and several normal mature B-cell populations. Results. Primary and cultured HRS cells, although sharing hallmark cHL signatures such as high NF-kB transcriptional activity and lost B-cell identity, showed considerable transcriptional divergence in chemokine/chemokine receptor activity, extracellular matrix remodeling and cell adhesion (all enriched in primary HRS cells), as well as in proliferation (enriched in cultured HRS cells). Unsupervised and supervised analyses indicated that microdissected HRS cells of cHL represent a transcriptionally unique lymphoma entity, overall closer to nLPHL than to PMBL but with differential behavior of the cHL histological subtypes, being HRS cells of the lymphocyte-rich and mixed-cellularity subtypes close to nLPHL cells while HRS cells of NS and LD exhibited greater similarity to PMBL cells. HRS cells downregulated a large number of genes involved in cell cycle checkpoints and in the maintenance of genomic integrity and chromosomal stability, while upregulating gene and gene signatures involved in various oncogenic signaling pathways and in cell phenotype reprogramming. Comparisons with normal B cells highlighted the lack of consistent transcriptional similarity of HRS cells to bulk germinal center (GC) B cells or plasma cells and, interestingly, a more pronounced resemblance to CD30+ GC B cells and CD30+ extrafollicular B cells, two previously uncharacterized subsets that are transcriptionally distinct from the other mature B-cell types. Conclusions. Gene expression profiling of primary HRS cells provided several new insights into the biology and pathogenesis of cHL, its relatedness to other lymphomas and normal B cells, and its enigmatic phenotype. Disclosures: No relevant conflicts of interest to declare.


Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4553-4553
Author(s):  
Matthew W. Andres ◽  
Robin A. Roberts ◽  
Debbie J. Mustacich ◽  
Randy D. Gascoyne ◽  
Deborah A. Fuchs ◽  
...  

Abstract Background: Determining monotypia of surface immunoglobulin (SIg) is often an important step in the diagnosis of B-cell lymphomas. Many competing methods have been developed and are commonly used in clinical practice. The role of gene expression profiling (GEP) in determining light chain restriction is yet to be clarified. The goal of this study was to compare 4 methods by which light chain restriction can be determined: frozen section immunohistochemistry (FS-IHC), paraffin section IHC (PS-IHC), in-situ hybridization (ISH), and GEP. Design: 40 cases of DLBCL, part of a previous GEP study of DLBCL (Rosenwald et al, NEJM 2002), were made into a tissue microarray (TMA). FS-IHC slides, previously stained using by-hand streptavidin and diaminobenzidine, were re-examined for κ:λ restriction. PS-IHC was done on the TMA using the Benchmark system according to manufacturer’s protocols for κ/λ staining (Ventana Medical Systems VMSI, Tucson, AZ). ISH was performed on the TMA with a newly developed sensitive ISH procedure from VMSI which uses a purified streptavidin reagent to reduce background and increase sensitivity. The FS-IHC, PS-IHC, and ISH arrays were reviewed and scored as κ/λ monotypic, SIg-negative or indeterminate by 3 pathologists. The averaged gene expression ratios for microarray elements probing for κ and λ on each case were plotted on a log2 scale. Monoclonality was determined using 2 different GEP criteria: (1) κ-monoclonal if κ:λ expression was >2log2 or λ-monoclonal if expression was λ>κ or (2) κ and λ light chain relative expression on either side of the median. These data from all 4 techniques were used to determine a consensus clonality in which the majority of the results agreed. The results for each technique were then compared to the consensus for that case. Results: 7 Cases had a 4/4 consensus, 9 cases a 3/4, 11 cases a 3/3, 7 cases a 2/3, and 1 case a 2/2. 5 cases were excluded from the study because there was no majority consensus. 19 cases (47.5%) were κ monoclonal, 10 (25%) λ monoclonal, 6 (15%) SIg-negative, and 5 cases (12.5%) indeterminate. Compared to the consensus clonality FS-IHC was accurate in 21/26 (81%), PS-IHC in 28/32 (87%), sensitive ISH in 29/29 (100%) cases. GEP was accurate in 31/35 (89%) cases using either criteria (1) or (2); in 27/35 (77%) using criterion (1) alone, in 28/35 (80%) using criterion (2) alone, and 24/35 (69%) of cases when both criteria (1) and (2) were met. 6 SIg-negative cases failed all GEP criterion, but were considered correctly classified as neitherκ nor λ monoclonal. Discussion: The technique with the highest accuracy compared to consensus was the sensitive ISH assay, in part because samples were eliminated if the mRNA control (polyT probe) staining was suboptimal. GEP was also accurate using either of our criteria. The SIg-negative cases were not classified as either κ or λ monoclonal using any of our criteria. Given the increasing role GEP is likely to play in hematopathology, the application of GEP to B cell clonality may have diganostic utility.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1437-1437
Author(s):  
Ralph Schwiebert ◽  
Sharon Barrans ◽  
Jan Taylor ◽  
Andrew S Jack ◽  
Cathy H Burton

Abstract Introduction A challenge in the management of classical Hodgkin lymphoma (CHL) is selecting treatment which will maximise success while minimising treatment side effects. The international Response Adapted Therapy in Hodgkin Lymphoma (RATHL) trial (NCT00678327) demonstrated that treatment may be successfully adapted based on positron emission tomography (PET-CT) scan results after 2 cycles (PET2) of ABVD chemotherapy in advanced CHL. This approach however delays risk stratification meaning some patients may be over or under treated and therefore a baseline predictor is highly desirable. A gene expression-based model performed on RNA from formalin-fixed paraffin-embedded tissue (FFPET) biopsies on the Nanostring platform (Scott et al, J Clin Oncol 2013; 31:692-700) has been published. In addition Steidl et al used gene expression profiling (GEP) to correlate tumour-associated macrophages with survival in CHL (Steidl et al, NEJM 2010; 10:875-885). In order to explore whether GEP at baseline could be used in combination with PET2 results to predict outcome, these published gene signatures were explored on the DASL platform in a series of CHL cases and correlated with PET2 response. Recently, PD-1 ligand (PD-L1) on the cell surface of Reed-Sternberg cells (the hallmark cells of CHL) has been demonstrated to co-opt the PD-1 pathway allowing immune evasion (Green et al, Blood 2010;116:3268-77). Therefore this was also performed by immunohistochemistry (IHC) and GEP as well as assessment of EBV status. Methods 50 patients with CHL were identified, with at least 2 years of follow up, diagnosed between 2008 and 2013. Deauville scores at PET2 were determined. IHC consistent with CHL, including: CD3, CD19, CD20, CD30, CD79, BOB-1, OCT-2, MUM1 and TARC was performed on 3mm FFPET lymph node sections, and reported by two independent observers. Latent Epstein-Barr virus (EBV) infection was determined by IHC for LMP-1 expression and in-situ hybridisation using fluorescein-labelled peptide nucleic acid probes (Dako, K5201). PD-L1 expression was determined by IHC using a rabbit monoclonal antibody (Cell Signaling Technology, E1L3N, #13684). Three to five 5mm sections of FFPET were used for RNA extraction using the Ambion RecoverAll™ kit standard protocol. GEP was quantified using Illumina's whole genome cDNA-mediated annealing, selection, extension, and ligation Assay (WG-DASL). 61 genes of interest were analysed for significance in the difference in gene expression between groups and included genes from the two recently reported GEP predictor tools in CHL (Steidl et al, 2010, Scott et al 2013) as well as PD-1 and PD-L1. The Mann-Whitney test was used to assess the significance in the difference between means (significant if p<0.05). Results A statistically significant difference in EBV status was found between PET negative (Deauville scores 1-3) and PET positive (Deauville scores 4-5) groups (Fisher's exact test: P-Value = 0.028). All patients who were EBV positive had a negative PET2 scan. GEP using WG-DASL revealed that only 2 genes of those reported in recent predictor models (Steidl et al 2010, Scott et al 2013) were expressed at significantly different levels between PET negative and PET positive patients (GLUL, RNF144B), both with increased expression in the PET2 positive group. There was no significant difference between PD-L1 expression and PET scores, CD274 gene expression and outcome. Assessment as to whether samples would cluster into groups according to PET positivity or PD-L1 expression status by unsupervised cluster analysis using four recently reported B cell lymphoma gene signatures (Monti et al, Blood 2005; 5:1851-61, Care et al, PloS one 2013; 2: e55895) was performed, but no significant grouping was found. Conclusion GEP on the DASL platform was not able to predict PET response. The original models were trained on outcome and therefore retraining of the GEP model based on PET response is likely to be required. EBV status was found to be predictive of PET response but this could not be correlated with other biomarkers to predict outcome. Although PD-1 and PD-L1 targeted therapy has shown exciting results in patients with CHL, PD-L1 IHC expression and CD274 gene expression, did not correlate with PET2 response or outcome. Baseline biomarkers capable of identifying patients likely to benefit from targeted treatment needs to be further investigated in proposed clinical trials. Disclosures No relevant conflicts of interest to declare.


2011 ◽  
Vol 139 (suppl. 2) ◽  
pp. 84-89 ◽  
Author(s):  
Dirk Hose ◽  
Anja Seckinger ◽  
Anna Jauch ◽  
Thierry Reme ◽  
Jerome Moreaux ◽  
...  

Multiple myeloma patients? survival under treatment varies from a few months to more than 15 years. Clinical prognostic factors, especially beta2-microglobulin (B2M) and the international staging system (ISS), allow risk assessment to a certain extent, but do not identify patients at very high risk. As malignant plasma cells are characterized by a variety of chromosomal aberrations and changes in gene expression, a molecular characterization of CD138-purified myeloma cells by interphase fluorescence in situ hybridization (iFISH) and gene expression profiling (GEP) can be used for improved risk assessment. iFISH allows a risk stratification with presence of a translocation t(4;14) and/or deletion of 17p13 being the best documented adverse prognostic factors. A deletion of 13q14 is no longer considered to define adverse risk. Patients harbouring a t(4;14) seems to benefit from a bortezomib- or lenalidomide containing regimen, whereas patients with deletion 17p13 seem only to benefit from a high dose therapy approach using long term bortezomib (in induction and maintenance) and autologous tandem-transplantation as used in the GMMG-HD4 trial, or the total therapy 3 concept. Gene expression profiling allows the assessment of high risk scores (IFM, UAMS), remaining prognostic despite treatment with novel agents, and prognostic surrogates of biological factors (e.g. proliferation) and (prognostic) target gene expression (e.g. Aurora-kinase A). Thus, assessment of B2M and ISS-stage, iFISH, and GEP is considered extended routine diagnostics in therapy requiring multiple myeloma patients for risk assessment and, even now, to a certain extent selection of treatment.


2017 ◽  
Vol 35 (32) ◽  
pp. 3722-3733 ◽  
Author(s):  
Fong Chun Chan ◽  
Anja Mottok ◽  
Alina S. Gerrie ◽  
Maryse Power ◽  
Marcel Nijland ◽  
...  

Purpose Our aim was to capture the biology of classical Hodgkin lymphoma (cHL) at the time of relapse and discover novel and robust biomarkers that predict outcomes after autologous stem-cell transplantation (ASCT). Materials and Methods We performed digital gene expression profiling on a cohort of 245 formalin-fixed, paraffin-embedded tumor specimens from 174 patients with cHL, including 71 with biopsies taken at both primary diagnosis and relapse, to investigate temporal gene expression differences and associations with post-ASCT outcomes. Relapse biopsies from a training cohort of 65 patients were used to build a gene expression–based prognostic model of post-ASCT outcomes (RHL30), and two independent cohorts were used for validation. Results Gene expression profiling revealed that 24% of patients exhibited poorly correlated expression patterns between their biopsies taken at initial diagnosis and relapse, indicating biologic divergence. Comparative analysis of the prognostic power of gene expression measurements in primary versus relapse specimens demonstrated that the biology captured at the time of relapse contained superior properties for post-ASCT outcome prediction. We developed RHL30, using relapse specimens, which identified a subset of high-risk patients with inferior post-ASCT outcomes in two independent external validation cohorts. The prognostic power of RHL30 was independent of reported clinical prognostic markers (both at initial diagnosis and at relapse) and microenvironmental components as assessed by immunohistochemistry. Conclusion We have developed and validated a novel clinically applicable prognostic assay that at the time of first relapse identifies patients with unfavorable post-ASCT outcomes. Moving forward, it will be critical to evaluate the clinical use of RHL30 in the context of positron emission tomography–guided response assessment and the evolving cHL treatment landscape.


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