B-Cell Scaffold Protein with Ankyrin Repeats (BANK1) Is Differentially Expressed in ZAP-70 Negative Compared to ZAP-70 Positive Chronic Lymphocytic Leukemia Cells.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 2938-2938
Author(s):  
Frank Dicker ◽  
Susanne Schnittger ◽  
Claudia Schoch ◽  
Alexander Kohlmann ◽  
Wei-Min Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cells ◽  
Chronic Lymphocytic Leukemia ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Differentially Expressed Genes ◽  
Expression Profiling ◽  
Lymphocytic Leukemia ◽  
Differentially Expressed ◽  
Cell Scaffold

Abstract The lack of somatic mutations of the immunoglobulin variable heavy chain (IgVH) gene has been established as poor prognostic marker for chronic lymphocytic leukemia (CLL) patients at early stage disease. Expression of the non receptor tyrosine kinase zeta chain associated protein (ZAP-70) was proposed as a surrogate marker for an unmutated IgVH, however, up to 30% discordant samples have been reported depending on the respective study. B cell receptor (BCR) mediated signaling is enhanced by ZAP-70 expression in CLL cells in vitro and ZAP-70 expression also tends to decrease the time from diagnosis to treatment irrespective of the IgVH status. Therefore, we wanted to identify differentially expressed genes between the ZAP-70 positive and negative CLLs by gene expression profiling of peripheral blood mononuclear cells (PBMCs) using Affymetrix microarrays (HG-U133 Plus 2.0). ZAP-70 expression was analyzed by quantitative real time PCR of CD19 purified (purity > 99%) PBMCs (n=62) using a LightCycler instrument. Expression of ZAP-70 mRNA was normalized against the housekeeping gene ABL and a relative quantitation against Jurkat T cells as a calibrator was performed. Results are expressed as normalized ratio and a cut-off of 0.5 normalized ratio gave the best correlation to the IgVH status with 77% concordant samples between ZAP-70 expression and the IgVH status. The discordant samples consisted of 5 unmutated IgVHs in the ZAP-70 negative group and 9 mutated in the ZAP-70 positive group. In a second step PBMCs of the same samples were analyzed by gene expression profiling and differentially expressed genes were identified by t-test. Among the two best genes that could be used in a classification algorithm (SVM) to distinguish between the 2 subsets with 92% accuracy were ZAP-70 and B cell scaffold protein with ankyrin repeats (BANK1). The expression of BANK1 was increased 3–4-fold in the ZAP-70 negative compared to the ZAP-70 positive CLL subset (P = 0,001). In the literature, BANK1 has been identified in human BCR expressing B cells and seems to be B cell restricted. In B cells the scaffolding protein BANK1 enhances BCR-mediated Ca2+-signaling, a signaling pathway that is also enhanced by ZAP-70 expression in CLL B cells. Based on these data we show that increased BANK1 expression correlates with a ZAP-70 negative status in CLL B cells. The functional consequences of BANK1 expression in the ZAP-70 negative subset of CLL B cells, which are usually associated with a more favorable prognosis, still need to be established further.

Microarray Gene Expression Profiling of B-Cell Chronic Lymphocytic Leukemia Subgroups Defined by Genomic Aberrations and VH Mutation Status

2004 ◽  
Vol 22 (19) ◽  
pp. 3937-3949 ◽  
Author(s):  
Christian Haslinger ◽  
Norbert Schweifer ◽  
Stephan Stilgenbauer ◽  
Hartmut Döhner ◽  
Peter Lichter ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Lymphocytic Leukemia ◽  
B Cell ◽  
Differentially Expressed Genes ◽  
Expression Profiling ◽  
Lymphocytic Leukemia ◽  
Differentially Expressed ◽  
Mutational Status ◽  
Genomic Aberrations ◽  
Cell Chronic Lymphocytic Leukemia

Purpose Genomic aberrations and mutational status of the immunoglobulin variable heavy chain (VH) gene have been shown to be among the most important predictors for outcome in patients with B-cell chronic lymphocytic leukemia (B-CLL). In this study, we report on differential gene expression patterns that are characteristic for genetically defined B-CLL subtypes. Materials and Methods One hundred genetically well-characterized B-CLL samples, together with 11 healthy control samples, were analyzed using oligonucleotide arrays, which test for the expression of some 12,000 human genes. Results Aiming at microarray-based subclassification, class predictors were constructed using sets of differentially expressed genes, which yielded in zero or low misclassification rates. Furthermore, a significant number of the differentially expressed genes clustered in chromosomal regions affected by the respective genomic losses/gains. Deletions affecting chromosome bands 11q22-q23 and 17p13 led to a reduced expression of the corresponding genes, such as ATM and p53, while trisomy 12 resulted in the upregulation of genes mapping to chromosome arm 12q. Using an unsupervised analysis algorithm, expression profiling allowed partitioning into predominantly VH-mutated versus unmutated patient groups; however, association of the expression profile with the VH mutational status could only be detected in male patients. Conclusion The finding that the most significantly differentially expressed genes are located in the corresponding aberrant chromosomal regions indicates that a gene dosage effect may exert a pathogenic role in B-CLL. The significant difference in the partitioning of male and female B-CLL samples suggests that the genomic signature for the VH mutational status might be sex-related.

Gene Expression Profiling of Highly Purified Malignant and Non-Malignant Cells: Characterization of the Tumor-Microenvironment Cellular Synapse in De Novo Follicular Lymphoma (FL).

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 355-355 ◽  
Author(s):  
Karin Tarte ◽  
Céline Pangault ◽  
John de Vos ◽  
Philippe Ruminy ◽  
Fabienne Sauvee ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
B Cells ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
De Novo ◽  
Differentially Expressed ◽  
Malignant Cells ◽  
Activated T Cell

Abstract Genetic and functional studies have demonstrated that FL cells retain the major features of normal germinal center (GC)-derived B cells, in particular the dependency on an active crosstalk with their specialized microenvironment. In agreement, microarray analyses have recently revealed that FL patient outcome is primarily predicted by molecular characteristics of tumor-infiltrating immune cells instead of tumor cells. However, our knowledge of the crucial interactions between malignant and non-malignant cells in FL remains limited by the use of whole biopsy specimen to perform gene expression profiling (GEP). We thus conducted GEP on both CD19pos B cells and CD19negCD22neg non-B cells purified from lymph nodes of 17 patients with de novo FL & 4 normal donors (CD20pos >94.5%, median=98.2%) and 9 de novo FL patients & 5 normal donors (CD20pos<6.7%, median=0.5%), respectively. Biotinylated cRNA were amplified according to the small sample labelling protocol and hybridized onto HGU133 Plus 2.0 arrays (Affymetrix). Raw data were normalized using GC-RMA methodology (ArrayAssist, Stratagene) and finally, based on a CV>80, 10870 probesets were selected for further analyses. Unsupervised hierarchical clustering (Eisen’s software) allowed the correct classification of the 35 samples into the 4 groups: FL B-cell, Normal B-cells, FL non-B cells, and Normal non-B cells. Supervised analyzes were done using asymptotic non-parametric Mann-Whitney U-test (fold change ≥2, P<0.01) and confirmed by permutation analysis (500 permutations, false discovery rate <5%) using SAM software. We first established the list of the 841 probesets that were differentially expressed between FL and normal B-cells containing, 355 probesets overexpressed in malignant B cells including genes involved in GC B-cell biology (BCL6, MTA3, ID2, CD80, SDC4) and oncogenes as well (BCL2, AURK2) and conversely, 486 probesets downregulated in malignant B cells involving several interferon-stimulated genes for example. We then looked for the FL-specific microenvironment signature and pointed out the 1206 probesets that were differentially expressed between FL and normal non-B cells. Interestingly, all these genes were upregulated in the lymphoma context. Among them, we identified a striking follicular helper T-cell (TFH) signature (CXCR5, ICOS, CXCL13, CD200, PDCD1, SH2D1A) and an activated T-cell signature (IFNG, FASLG, GZMA, ZAP70, CD247). Notably, the TFH and activated T-cell signatures were not merely a surrogate for the number of T cells since many standard T-cell genes (i.e. CD2, CD4, CD7, LEF1, CD8A) were not induced in the FL microenvironment. Finally, in order to draw an overview of the FL-specific synapse between B and non-B cell compartments, we isolated a group of 2323 probesets that were differentially expressed between both compartments in FL and not in normal context. Using Ingenuity Pathway Analysis software we then identified among them FL-specific functional networks, including an IL-4- & an IL-15-centered pathway. Altogether, these data shed new light on our understanding of FL biology and could be a source of new therapeutics targeting the interplay between B cells and their microenvironment.

B-Cell Chronic Lymphocytic Leukemia Cells Exposed to the Non-Genotoxic p53 Activator Nutlin-3 Are Characterized by a Specific Gene Expression Signature.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 4374-4374
Author(s):  
Michele Dal-Bo ◽  
Paola Secchiero ◽  
Massimo Degan ◽  
Riccardo Bomben ◽  
Dania Benedetti ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Lymphocytic Leukemia ◽  
B Cell ◽  
Differentially Expressed Genes ◽  
Chemotherapeutic Agents ◽  
Lymphocytic Leukemia ◽  
Differentially Expressed ◽  
Specific Gene ◽  
P53 Mutations ◽  
Cell Chronic Lymphocytic Leukemia

Abstract Abstract 4374 Introduction p53 plays a key role in determining the clinical features of B cell chronic lymphocytic leukemia (CLL). Disruption of p53 by point mutations, deletion at 17p13, or both, occurs in a fraction of cases at diagnosis and predicts poor survival and chemorefractoriness. In cells with functional p53, p53 activity is inhibited through interaction with MDM2. In fact, p53 can be activated upon exposure of cells to inhibitors of p53/MDM2 interaction, like Nutlins. Exposure of CLL cells to Nutlin-3 is effective in raising the levels of p53 protein with subsequent induction of cell cycle arrest and/or apoptosis, independently of the most relevant prognostic markers. The aim of the present study was to analyze the gene expression profile (GEP) induced by Nutlin-3 exposure in primary CLL cells from p53wt and p53del/mut cases. Patients and methods purified cells from 24 PB CLL samples, all characterized for IGHV mutational status, CD38 and ZAP-70 and p53 mutations (16 p53wt CLL, 8 p53del/mut CLL of which 6 with del17p13 and p53 mutations, 1 with del17p13 alone, and 1 with p53 mutations alone), were exposed to 10 mM Nutlin-3 for 24 hours. GEP was performed using a dual labelling strategy; the differential expression of the below reported genes were validated by quantitative real-time PCR. Results i) signature of Nutlin-3 exposure in p53wt CLL: 144 differentially expressed genes (143 up-regulated, 1 down-regulated) were correlated with response to Nutlin-3. Among the over-expressed genes, several genes were related to apoptosis (e.g. BAX, BBC3, E124, IKIP, FAS, LRDD, FLJ11259, TRIAP1, GADD45, TP53INP1, ISG20L1, ZMAT3, TNFRS10C, TNFRSF10B/TRAIL-R2), while other genes (e.g. MDM2, CDKN1A, PCNA) were up-regulated by Nutlin-3 as a part of a negative feed-back mechanism. Of note, this signature was not shared by 3/16 p53wt cases (identified as “non-responder” p53wt CLL) and 7/8 p53del/mut cases (identified as “non-responder” p53del/mut CLL); consistently, cells from these cases were also significantly resistant to the in-vitro cytotoxic effects of Nutlin-3; ii) signature of Nutlin-3 “non-responder” p53wt CLL: by comparing the constitutive GEP of 13 “responder” versus 3 “non-responder” p53wt CLL, we obtained 278 differentially expressed genes, 149 up-regulated and 129 down-regulated in “non-responder” p53wt CLL. Among up-regulated genes, we focused on MDM4/MDMX, a gene whose product was known to have an inhibitor activity of p53-dependent transcription and to form Nutlin-3 resistant complexes with p53. Among down-regulated genes, validations were made for BIRC4BP, whose product is known to act as an antagonist of the anti-apoptotic protein XIAP; iii) signature of Nutlin-3 “non-responder” p53del/mut CLL: by comparing the constitutive GEP of 13 “responder” versus 7 “non-responder” p53del/mut cases, we obtained 72 differentially expressed genes, 26 up-regulated and 46 down-regulated (31/46 located at the 17p segment) in “non-responder” p53del/mut CLL. Validations were made for several genes whose products display pro-apoptotic activities (e.g. PSMB6, RPL26 and ZBTB4, located at 17p segment, and GNAZ located at chromosome 22) among down-regulated genes, and ARHGDIA, whose gene product displays anti-apoptotic activities and mediates cellular resistance to chemotherapeutic agents, among up-regulated genes. Notably, CLL cells (n=43) displayed constitutively higher levels of MDM4/MDMX (p<0.0001) and ARHGDIA (p=0.0002) transcripts than purified normal B cells (n=15), irrespectively to the major biologic prognosticators. Conclusions specific gene-sets and GEP were documented to be associated with response or resistance to Nutlin-3 exposure in p53wt or p53del/mut CLL. These findings may help to identify novel molecular targets for CLL therapy. Disclosures: No relevant conflicts of interest to declare.

Gene Expression Profiling of B-Lymphocyte and Plasma Cell Populations from Waldenström’s Macroglobulinemia. Comparison with Expression Patterns of the Same Cell-Counterparts from Other B-Cell Neoplasms.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 503-503
Author(s):  
Norma C. Gutierrez ◽  
Enrique M. Ocio ◽  
Patricia Maiso ◽  
Encarna Ferminan ◽  
Manuel Delgado ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Patterns ◽  
Lymphocytic Leukemia ◽  
Differentially Expressed ◽  
Multiparameter Flow Cytometry ◽  
Cell Populations ◽  
Expression Levels

Abstract The tumoral clone of Waldenström’s macroglobulinemia (WM) shows a wide morphological heterogeneity which ranges from B lymphocytes (BL) to plasma cells (PC), including a lymphoplasmacytic population that defines the disease. The differences between these cell compartments and their cell-counterpart in other lymphoproliferative disorders have not yet been sufficiently explored. We compared the gene expression profiling (GEP) of BL and PC from patients diagnosed with WM, with clonal BL and PC from patients with chronic lymphocytic leukemia (CLL) and multiple myeloma (MM) respectively. Bone marrow samples from 10 WM and 10 MM patients and peripheral blood from 10 CLL patients were used for the analysis. The isolation of the different cell populations was carried out by multiparameter flow cytometry sorting with the following monoclonal antibodies combination: Kappa or Lambda-FITC, CD10-PE, CD38-PerCP-Cy5.5, CD19-PE-Cy7, CD34-APC and CD45-APC-Cy7. Total RNA (100–500 ng) was amplified and labeled using the “GeneChip Two-Cycle cDNA Synthesis Kit” and hybridized to “Human Genome U133A” microarray (Affymetrix). Processing of genechip data was carried out using the Robust Multi-chip Average (RMA) and the Affymetrix Microarray Suite v.5 (MAS5) gene expression algorithms. Two-way hierarchical cluster analysis showed that GEP was able to classify PC from WM and PC from MM in two different groups. In a similar way, BL from WM and CLL were grouped in different clusters. The Significance Analysis of Microarrays (SAM) algorithm identified gene expression changes in a total of 163 genes (103 up and 60 down-regulated) when MW PC were compared with MM PC. Some of these genes were related to regulation of PC development: PAX5 was overexpressed and IRF4 infraexpressed in WM PC. PC from WM displayed high expression levels of MYB and DEK oncogenes while MM PC showed an elevated expression level of v-MAF oncogene. Regarding gene functional categories, “immune response” and “signal transduction” were the biological process more active in WM PC. Comparison between BL from WM and BL from CLL revealed that 31 genes were differentially expressed: IL4 receptor, LEF1 (WNT/b-catenin pathway), fibromodulin (modulator of TGF-b activity) and FGR oncogene (tyrosine kinase protein) showed very low expression levels in WM BL compared to CLL BL. In contrast, the growth factor IL6 was over-expressed in WM BL. These results indicate that both PC and BL from WM are genetically different from the MM and CLL cell-counterpart. The differentially expressed genes have important functions in the B-cell differentiation and oncogenesis. Supported by Spanish Myeloma Network (G03/136) and “Ministerio de Ciencia y Tecnología” (SAF04/06587) and “Junta de Castilla y León” grants (SA032/04)

scholarly journals Digital Gene Expression Profiling Analysis of Aged Mice under Moxibustion Treatment

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Nan Liu ◽  
Yunyao Jiang ◽  
Min Xing ◽  
Baixiao Zhao ◽  
Jincai Hou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Gene Expression Profiling ◽  
Differentially Expressed Genes ◽  
Pathway Analysis ◽  
Expression Profiling ◽  
Digital Gene Expression ◽  
Differentially Expressed ◽  
Aged Mice ◽  
Digital Gene Expression Profiling

Aging is closely connected with death, progressive physiological decline, and increased risk of diseases, such as cancer, arteriosclerosis, heart disease, hypertension, and neurodegenerative diseases. It is reported that moxibustion can treat more than 300 kinds of diseases including aging related problems and can improve immune function and physiological functions. The digital gene expression profiling of aged mice with or without moxibustion treatment was investigated and the mechanisms of moxibustion in aged mice were speculated by gene ontology and pathway analysis in the study. Almost 145 million raw reads were obtained by digital gene expression analysis and about 140 million (96.55%) were clean reads. Five differentially expressed genes with an adjusted P value < 0.05 and |log⁡2(fold  change)| > 1 were identified between the control and moxibustion groups. They were Gm6563, Gm8116, Rps26-ps1, Nat8f4, and Igkv3-12. Gene ontology analysis was carried out by the GOseq R package and functional annotations of the differentially expressed genes related to translation, mRNA export from nucleus, mRNA transport, nuclear body, acetyltransferase activity, and so on. Kyoto Encyclopedia of Genes and Genomes database was used for pathway analysis and ribosome was the most significantly enriched pathway term.

Gene Expression Profiling of Peripheral T-Cell Lymphoma (PTCL, NOS) and Comparison to Diffuse Large B-Cell Lymphoma (DLBCL).

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2277-2277
Author(s):  
Daruka Mahadevan ◽  
Catherine Spier ◽  
Kimiko Della Croce ◽  
Susan Miller ◽  
Benjamin George ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
T Cell ◽  
B Cells ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Real Time ◽  
Expression Profiling ◽  
Cell Lymphoma ◽  
Rt Pcr

Abstract Background: WHO classifies NHL into B (~85%) and T (~15%) cell subtypes. Of the T-cell NHL, peripheral T-cell NHL (PTCL, NOS) comprises ~6–10% with an inferior response and survival to chemotherapy compared to DLBCL. Gene Expression Profiling (GEP) of DLBCL has provided molecular signatures that define 3 subclasses with distinct survival rates. The current study analyzed transcript profiling in PTCL (NOS) and compared and contrasted it to GEP of DLBCL. Methods : Snap frozen samples of 5 patients with PTCL (NOS) and 4 patients with DLBCL were analyzed utilizing the HG-U133A 2.0 Affymetrix array (~18,400 transcripts, 22,000 probe sets) after isolating and purifying total RNA (Qiagen, RNAeasy). The control RNA samples were isolated from normal peripheral blood (PB) B-cell (AllCell, CA), normal PB T-cell (AllCell, CA) and normal lymph node (LN). Immunohisto-chemistry (IHC) confirmed tumor lineage and quantitative real time RT-PCR was performed on selected genes to validate the microarray study. The GEP data were processed and analyzed utilizing Affymetrix MAS 5.0 and GeneSpring 5.0 software. Our data were analyzed in the light of the published GEP of DLBCL (lymphochip and affymtrix) and the validated 10 prognostic genes (by IHC and real time RT-PCR). Results : Data are represented as “robust” increases or decreases of relative gene expression common to all 5 PTCL or 4 DLBCL patients respectively. The table shows the 5 most over-expressed genes in PTCL or DLBCL compared to normal T-cell (NT), B-cell (NB) and lymph node (LN). PTCL vs NT PTCL vs LN DLVCL vs NB DLBCL vs LN COL1A1 CHI3L1 CCL18 CCL18 CCL18 CCL18 VNN1 IGJ CXCL13 CCL5 UBD VNN1 IGFBP7 SH2D1A LYZ CD52 RARRES1 NKG7 CCL5 MAP4K1 Of the top 20 increases, 3 genes were common to PTCL and DLBCL when compared to normal T and B cells, while 11 were common when compared to normal LN. Comparison of genes common to normal B-cell and LN Vs DLBCL or PTCL and normal T-cell and LN Vs PTCL or DLBCL identified sets of genes that are commonly and differentially expressed in PTCL and/or DLBCL. The 4 DLBCL patients analyzed express 3 of 10 prognostic genes compared to normal B-cells and 7 of 10 prognostic genes compared to normal LN and fall into the non-germinal center subtype. Quantitative real time RT-PCR on 10 functionally distinct common over-expressed genes in the 5 PTCL (NOS) patients (Lumican, CCL18, CD14, CD54, CD106, CD163, α-PDGFR, HCK, ABCA1 and Tumor endothelial marker 6) validated the microarray data. Conclusions: GEP of PTCL (NOS) and DLBCL in combination with quantitative real time RT-PCR and IHC have identified a ‘molecular signature’ for PTCL and DLBCL based on a comparison to normal (B-cell, T-cell and LN) tissue. The categorization of the GEP based on the six hallmarks of cancer identifies a ‘tumor profile signature’ for PTCL and DLBCL and a number of novel targets for therapeutic intervention.

New Pathogenetic Insights Into Classical Hodgkin Lymphoma Revealed by Gene Expression Profiling of Microdissected Hodgkin/Reed-Sternberg Cells.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 266-266 ◽  
Author(s):  
Enrico Tiacci ◽  
Verena Brune ◽  
Susan Eckerle ◽  
Wolfram Klapper ◽  
Ines Pfeil ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cells ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Hodgkin Lymphoma ◽  
Cell Lines ◽  
Expression Profiling ◽  
Expression Profiles ◽  
B Cell Lymphoma ◽  
Cell Phenotype

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.

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