Array CGH Analysis of Nodal T-Cell Lymphomas: Identification of Genomic Alterations Specific to Angioimmunoblastic and Unspecified Subtypes, and Correlation with Transcriptomic Data.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3567-3567
Author(s):  
Laurence de Leval ◽  
David Rickman ◽  
Emilie Thomas ◽  
Louis Huang ◽  
Aurélien de Reynies ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Dna Microarrays ◽  
Genetic Alterations ◽  
Differentially Expressed ◽  
Genomic Alterations ◽  
Genomic Imbalances ◽  
T Cell Lymphomas ◽  
Genomic Aberrations ◽  
The Mean

Abstract Genetic alterations underlying angioimmunoblastic and unspecified peripheral T-cell lymphomas (AITL and PTCL-u) are largely unknown. Seventeen AITL and 16 PTCL-u previously characterized by gene expression profiling, were analyzed by CGH on DNA microarrays comprising 4434 BAC clones with a resolution of about 600 KB. In the PTCL-u group, the mean number of chromosomal aberrations per case was 302 (range, 55 to 892). Gains (n=237, 41 to 587) were more frequent than losses (n=65, 8 to 305). AITL samples had, on average, a lesser number of genomic alterations than PTCL-u cases (n=243, range, 55 to 485), comprising more gains (n=201, 42 to 541) than losses (n=42, 9 to 262). Overall, the most frequent recurrent gains, present in 50% of all samples, were observed at 1p36.1; 1p36.3 ; 1q32 ; 2q37 ; 4p16 ; 5p15.3 ; 6q12 ; 7p22 ; 7p12 ; 7p11.2 ; 7q35-36 ; 8q24.3 ; 9q34 ; 11p15 ; 11q13 ; 16p13.3 ; 16q24 ; 17q12,q21,q25 ; 19p13.3 ; 19q13.2-q13.3 ; 20q11.2-q13.3 ; 22q11.1-q11.2 ; Xp11 ; Xp21-22 ; Xq27-28. The comparison of the genomic profiles of AITL and PTCL-u identified 73 genomic alterations (at clones or zones of clones) significantly associated with either group of tumors (Fisher test, p < 0,05). Six genomic gains mapping at 5p15 and 22q11 were associated with the AITL subtype. Thirty-four gains (mapping at 6p25, 7p1, 7q3, 8q24, 11p14, 14q32, 17q, 22q) and 33 losses (mapping at 6q, 10p and 13q), were overrepresented in PTCL-u. The coordinate analysis of the transcriptomic and CGH array data identified 10 regions with genomic imbalances containing genes differentially expressed in AITL versus PTCL-u. Seven regions amplified in PTCL-u contained genes overexpressed in PTCL-u, mostly related to metabolic pathways. Conversely, loss of genomic material at 13q12 correlated with decreased expression in PTCL-u of a few genes of the AITL signature. In AITL tumors, gain at 22q11 correlated with increased transcription of the LIF gene, previosuly characterized as part of the tumor cell signature in AITL. CD30+ PTCL-u samples had on average a higher number of genomic aberrations than CD30-negative cases (n=408 versus 238). Thirty-three genomic gains and 22 losses were exclusively seen in CD30+ tumors, and regions with chromosomal imbalances at 1q, 6q, 10p contained genes differentially expressed in CD30+ and CD30− tumors. For example, reduced transcription of FYN in CD30+ PTCL-u correlated with deletion of the corresponding chromosomal region. In conclusion, all 33 nodal PTCL analyzed harbor genomic imbalances (gains>losses), of which many are common to both AITL and PTCL-u subgroups; the pattern of genomic aberrations differs between the two subgroups, with certain aberrations being overrepresented in PTCL-u, and only a few specific for AITL; coordinate appraisal of transcriptomic and genomic data highlights correlations between genomic imbalances and gene expression signatures in subgroups of tumors.

Oncogenomic analysis of mycosis fungoides reveals major differences with Sézary syndrome

Blood ◽  
2009 ◽  
Vol 113 (1) ◽  
pp. 127-136 ◽  
Author(s):  
Remco van Doorn ◽  
Marloes S. van Kester ◽  
Remco Dijkman ◽  
Maarten H. Vermeer ◽  
Aat A. Mulder ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Mycosis Fungoides ◽  
Genetic Alterations ◽  
Comparative Genomic ◽  
Sézary Syndrome ◽  
Sezary Syndrome ◽  
Chromosomal Alterations ◽  
T Cell Lymphomas ◽  
Skin Homing

Abstract Mycosis fungoides (MF), the most common cutaneous T-cell lymphoma, is a malignancy of mature, skin-homing T cells. Sézary syndrome (Sz) is often considered to represent a leukemic phase of MF. In this study, the pattern of numerical chromosomal alterations in MF tumor samples was defined using array-based comparative genomic hybridization (CGH); simultaneously, gene expression was analyzed using microarrays. Highly recurrent chromosomal alterations in MF include gain of 7q36, 7q21-7q22 and loss of 5q13 and 9p21. The pattern characteristic of MF differs markedly from chromosomal alterations observed in Sz. Integration of data from array-based CGH and gene-expression analysis yielded several candidate genes with potential relevance in the pathogenesis of MF. We confirmed that the FASTK and SKAP1 genes, residing in loci with recurrent gain, demonstrated increased expression. The RB1 and DLEU1 tumor suppressor genes showed diminished expression associated with loss. In addition, it was found that the presence of chromosomal alterations on 9p21, 8q24, and 1q21-1q22 was associated with poor prognosis in patients with MF. This study provides novel insight into genetic alterations underlying MF. Furthermore, our analysis uncovered genomic differences between MF and Sz, which suggest that the molecular pathogenesis and therefore therapeutic requirements of these cutaneous T-cell lymphomas may be distinct.

Biological Differences in Peripheral T-Cell Lymphomas Identified by DNA Microarrays.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3012-3012
Author(s):  
Beatriz Martinez-Delgado ◽  
Manisha Bahl ◽  
Marta Cuadros ◽  
Victoria Fernandez ◽  
Javier Benitez ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
B Cell ◽  
Dna Microarrays ◽  
Expression Profiles ◽  
Resting Cells ◽  
T Cell Lymphomas ◽  
Infiltrating Cells ◽  
Peripheral T Cell Lymphomas

Abstract Peripheral T-cell lymphomas (PTCL) constitute a heterogeneous and aggressive group of tumors whose pathogenic alterations remain largely unknown. They show great morphologic, immunophenotypic and clinical differences. Expression profiling has been demonstrated to be a useful tool for the molecular classification of tumours. We used DNA microarrays (Affymetrics, Lymph_DX) to look for molecular differences in peripheral T-cell lymphomas. We analysed the expression of 19 pathologically confirmed PTCL (11 PTCL, unspecified (u) and 8 angioimmunoblastic, AILT). A time-course of stimulation with anti-CD3 and anti-CD28 was performed in CD4+ and CD8+ isolated peripheral blood lymphocytes, and the gene expression of tumors was compared with resting and stimulated normal T-cells. Cases of classical Hodgkin’s lymphoma, with which PTCL may be confused, were included. Gene expression of PTCL revealed several clusters of genes with biological significance showing differential expression within the tumors. We defined a “Cytotoxic Response” cluster characterized by the expression of cytotoxic molecules PRF1 and GZMB and GZMH, a “B-cell-related genes” cluster which included B-cell specific genes PAX5 or CD19, and an interesting “Resting-cells genes” cluster. These three clusters were negatively correlated with a “Proliferation” signature. On the other hand, the “Proliferation” signature significantly correlated with the expression of TNFRSF8 (CD30) (r=0.63, p=0.003) and the expression of CD3G (r=0.51, p=0.022). Other interesting genes were also found associated specifically to the proliferation of PTCL. Comparison between PTCLu and AILT showed differences in the expression of CD21 and other genes reflecting the higher presence of dendritic cells in AILT, and also revealed differences in expression of relevant chemokines, such us CXCL5, CXCL13 and CCL19. Intriguingly, compared with normal CD4 and CD8 T-cells, PTCL showed lower expression of most of the typical genes associated with T-cell biology, suggesting that PTCL often lose the common genetic program of T-cells. PTCL expression profiles are difficult to interpret due to the significant proportion of other infiltrating cells accompanying the tumor. Our results showed that microarrays are a helpful tool to dissect the PTCL expression profile, identifying those genes expressed by infiltrating cells and those expressed by tumor cells.

scholarly journals 953 Transcriptional analysis of leukocytes from COVID convalescent donors reveals persistent activation of the innate and adaptive immune system

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A1002-A1003
Author(s):  
Mallikarjuna Gedda ◽  
Patrick Danaher ◽  
Lipei Saho ◽  
Martin Ongkeko ◽  
Leonard Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
T Cell ◽  
T Cell Receptor ◽  
Time Windows ◽  
Cell Receptor ◽  
Differentially Expressed ◽  
Tcr Diversity ◽  
The Mean ◽  
Over Time

BackgroundCoronavirus disease 2019 (COVID-19) results in robust but dysregulated acute immune response characterized by pro-inflammatory cytokine production and T-cell exhaustion, but little is known concerning immune response following recovery. We assessed immune function in convalescent plasma donors (CCD) who had recovered from COVID-19.MethodsThe cellular immune response and T-cell receptor (TCR) diversity in CCD was investigated using the nCounter host response and TCR diversity panels. 270 CCD and 40 healthy donor (HD) blood samples collected 11 to 193 days after diagnosis were analyzed. The CCD samples were from 162 donors, 69 donated more than once. All HD donated only once.ResultsMany genes were differentially expressed for months following infection. Analysis of samples collected 0 to 90 days post-diagnosis found that 19 of 773 genes were differentially expressed among CCD and HD (FDR < 0.05) (figure 1a). At 90 to 120 days, 120 to 150 and >150 post-diagnosis, 13, 58 and 4 genes were differentially expressed respectively (FDR < 0.05) (figures 1b-d). At 120 to 150 days the differentially expressed genes included those in Treg differentiation, type III interferon signaling and chemokine signaling pathways. 76 genes were differently expressed at least once during the time windows described above. (Figure 1e). Among CCD, the expression of CTLA-4, ICOS, ICOSLG, OSM and CXCR4 were initially elevated but fell to HD levels at the end of the study period. The expression of LILRA6, CCR2 and CX3CR1 increased or remained elevated throughout (figure 1f).A subset of samples departed notably from the average trend. The transcriptome of each CCD sample was scored by its similarity to the mean transcriptome of HD samples. This analysis revealed 21 CCD samples from 19 unique donors were highly perturbed from HD samples (figure 2a). Among these highly perturbed samples 80% were collected > 90 days post-diagnosis. The perturbed samples clustered into two groups, labelled P1 and P2 (figure 2b) and displayed dysregulation of distinct gene sets (figures 2c, 2d). The P1 were characterized by increased expression of genes in myeloid inflammation, type 1 interferon and innate immune signaling pathways, lower COVID antibody levels and increased T-cell receptor diversity. P2 were characterized by highly up-regulated CD44, BCL2, TGFB1, IL18BP, IL27RA, and IL11RA.Abstract 953 Figure 1Longitudinal trends in CCD gene expression. a-d: Differential expression results in HD vs. 4 time windows of CCD. Genes with FDR <0.1 are labeled; e: average CCD log2 fold-changes from HD over time. Color is only given for times where the Loess regression is different from the mean HD with p < 0.05; f: longitudinal results for selected genes. Orange lines connect CCD samples over time. Blue lines show inner 95% quantiles of HD samplesAbstract 953 Figure 2CCD with more severe departure from HD gene expression. a: CCD samples (in orange) were scored for perturbation from the mean HD (in blue), and 21 highly perturbed sample subsets emerged; b: clustering of the 21 highly perturbed patients. The dendrogram was cut to define two groups. c: volcano plots comparing expression in P1 (left) and P2 (right) vs. CCD; d: longitudinal trends of selected genes perturbed in P1 and P2ConclusionsImmune dysregulation in CCD continues at least 6 months post-infection. Some CCDs experienced marked transcriptional changes which may be the result of COVID-19 reactivation and could be responsible for long-haul syndrome.AcknowledgementsN/ATrial RegistrationNCT04360278ReferencesN/A Ethics ApprovalN/AConsentN/A

scholarly journals Comprehensive high-throughput meta-analysis of differentially expressed microRNAs in transcriptomic datasets reveals significant disruption of MAPK/JNK signal transduction pathway in Adult T-cell leukemia/lymphoma

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Shahrzad Shadabi ◽  
Nargess Delrish ◽  
Mehdi Norouzi ◽  
Maryam Ehteshami ◽  
Fariba Habibian-Sezavar ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signal Transduction ◽  
T Cell ◽  
Network Analysis ◽  
High Throughput ◽  
Target Gene ◽  
Differentially Expressed ◽  
Cell Leukemia ◽  
Adult T Cell Leukemia ◽  
Healthy Donors

Abstract Background Human T-lymphotropic virus 1 (HTLV-1) infection may lead to the development of Adult T-cell leukemia/lymphoma (ATLL). To further elucidate the pathophysiology of this aggressive CD4+ T-cell malignancy, we have performed an integrated systems biology approach to analyze previous transcriptome datasets focusing on differentially expressed miRNAs (DEMs) in peripheral blood of ATLL patients. Methods Datasets GSE28626, GSE31629, GSE11577 were used to identify ATLL-specific DEM signatures. The target genes of each identified miRNA were obtained to construct a protein-protein interactions network using STRING database. The target gene hubs were subjected to further analysis to demonstrate significantly enriched gene ontology terms and signaling pathways. Quantitative reverse transcription Polymerase Chain Reaction (RTqPCR) was performed on major genes in certain pathways identified by network analysis to highlight gene expression alterations. Results High-throughput in silico analysis revealed 9 DEMs hsa-let-7a, hsa-let-7g, hsa-mir-181b, hsa-mir-26b, hsa-mir-30c, hsa-mir-186, hsa-mir-10a, hsa-mir-30b, and hsa-let-7f between ATLL patients and healthy donors. Further analysis revealed the first 5 of DEMs were directly associated with previously identified pathways in the pathogenesis of HTLV-1. Network analysis demonstrated the involvement of target gene hubs in several signaling cascades, mainly in the MAPK pathway. RT-qPCR on human ATLL samples showed significant upregulation of EVI1, MKP1, PTPRR, and JNK gene vs healthy donors in MAPK/JNK pathway. Discussion The results highlighted the functional impact of a subset dysregulated microRNAs in ATLL on cellular gene expression and signal transduction pathways. Further studies are needed to identify novel biomarkers to obtain a comprehensive mapping of deregulated biological pathways in ATLL.

Tumor Necrosis Factor-p Gene Expression and Its Relationship to the Clinical Features and Histopathogenesis of Peripheral T-Cell Lymphomas

1994 ◽  
Vol 16 (1-2) ◽  
pp. 125-133 ◽  
Author(s):  
Hirokazu Kato ◽  
Tetsuro Nagasaka ◽  
Atsushi Ichikawa ◽  
Tomohiro Kinoshita ◽  
Takashi Murate ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Tumor Necrosis Factor ◽  
Clinical Features ◽  
Tumor Necrosis ◽  
P Gene ◽  
T Cell Lymphomas ◽  
Necrosis Factor ◽  
Peripheral T Cell Lymphomas

Genetic alterations and oxidative stress in T cell lymphomas

2022 ◽  
pp. 108109
Author(s):  
Sushant Kumar ◽  
Bhavuk Dhamija ◽  
Diksha Attrish ◽  
Vinanti Sawant ◽  
Manju Sengar ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
T Cell ◽  
Genetic Alterations ◽  
T Cell Lymphomas ◽  
And Oxidative Stress

scholarly journals HOXC4, HOXC5, and HOXC6 Expression in Non-Hodgkin's Lymphoma: Preferential Expression of the HOXC5 Gene in Primary Cutaneous Anaplastic T-Cell and Oro-Gastrointestinal Tract Mucosa-Associated B-Cell Lymphomas

Blood ◽  
1997 ◽  
Vol 90 (10) ◽  
pp. 4116-4125 ◽  
Author(s):  
Janet J. Bijl ◽  
Johan W. van Oostveen ◽  
Jan M.M. Walboomers ◽  
Anja Horstman ◽  
Adriaan J.C. van den Brule ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
B Cell ◽  
Expression Pattern ◽  
Gene Expression Pattern ◽  
Lymphoid Cells ◽  
B Cell Lymphomas ◽  
Preferential Expression ◽  
T Cell Lymphomas ◽  
Hodgkin's Lymphomas

Abstract Most of the 39 members of the homeobox (HOX) gene family are believed to control blood cell development. HOXC4 and HOXC6 gene expression levels increase with differentiation of lymphoid cells. In contrast, HOXC5 is not expressed in the lymphoid lineage, but was found in lymphoid cell lines, representing the neoplastic equivalents of various differentiation stages of T and B lymphocytes. In the present study, we investigated the HOXC4, HOXC5, and HOXC6 gene expression pattern in 89 non-Hodgkin's lymphomas (NHLs) of different histologic subtypes and originating from different sites. Using RNA in situ hybridization and semiquantitative reverse transcription-polymerase chain reaction, we found expression of HOXC4 in 83 of 88 and HOXC6 in 77 of 88 NHLs and leukemias investigated. In contrast, HOXC5 expression was found in only 26 of 87 NHLs and appeared to be preferentially expressed by two specific subsets of lymphomas, ie, primary cutaneous anaplastic T-cell lymphomas (9 of 9) and extranodal marginal zone B-cell lymphomas (maltomas; 7 of 9). These results indicate that, in contrast to HOXC4 and HOXC6, HOXC5 shows a type- and site-restricted expression pattern in both T- and B-cell NHLs.

scholarly journals Clonal hematopoiesis in angioimmunoblastic T-cell lymphoma with divergent evolution to myeloid neoplasms

2020 ◽  
Vol 4 (10) ◽  
pp. 2261-2271 ◽  
Author(s):  
Natasha E. Lewis ◽  
Kseniya Petrova-Drus ◽  
Sarah Huet ◽  
Zachary D. Epstein-Peterson ◽  
Qi Gao ◽  
...  
Keyword(s):  
Bone Marrow ◽  
T Cell ◽  
Genetic Alterations ◽  
Divergent Evolution ◽  
Tissue Samples ◽  
Clonal Hematopoiesis ◽  
Follicular Helper ◽  
Myeloid Neoplasms ◽  
T Cell Lymphomas ◽  
Genomic Studies

Abstract TET2 and DNMT3A mutations are frequently identified in T-cell lymphomas of T follicular helper cell origin (TCL-TFH), clonal hematopoiesis (CH), and myeloid neoplasms (MNs). The relationships among these 3 entities, however, are not well understood. We performed comprehensive genomic studies on paired bone marrow and tissue samples as well as on flow cytometry–sorted bone marrow and peripheral blood subpopulations from a cohort of 22 patients with TCL-TFH to identify shared CH-type mutations in various hematopoietic cell compartments. Identical mutations were detected in the neoplastic T-cell and myeloid compartments of 15 out of 22 patients (68%), including TET2 (14/15) and DNMT3A (10/15). Four patients developed MNs, all of which shared CH-type mutations with their TCL-TFH; additional unique genetic alterations were also detected in each patient’s TCL-TFH and MN. These data demonstrate that CH is prevalent in patients with TCL-TFH and that divergent evolution of a CH clone may give rise to both TCL-TFH and MNs.

Biomarkers of Vorinostat Resistance in Cutaneous T-Cell Lymphoma.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 1381-1381
Author(s):  
Chunlei Zhang ◽  
Baoqiang Li ◽  
Rakhshandra Talpur ◽  
C. Cameron Yin ◽  
Madeleine Duvic
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Mononuclear Cells ◽  
Cell Lymphoma ◽  
T Cell Lymphoma ◽  
Differentially Expressed ◽  
Cytokine Signaling ◽  
Cutaneous T Cell Lymphoma ◽  
Phase Ii Studies

Abstract Profiling gene expression with DNA microarray technology has elucidated novel therapeutic targets and led the approval of a number of targeted therapeutic agents for the treatment of cancer. Vorinostat (suberoylanilide hydroxamic acid, SAHA) is a pan-histone deacetylase (HDAC) inhibitor that has demonstrated an overall response rate of approximately 24–30% in two phase II studies of cutaneous T cell lymphoma (CTCL) patients. There are currently no known specific biomarkers to indicate resistance to vorinostat. To identify genes resistant to vorinostat we compared profiles using the Aligent whole human genome oligo microarrays containing ∼41,000 genes/transcripts in vitro in vorinostat-resistant MJ and -sensitive HH CTCL cell lines treated with 1 μM of vorinostat for 24 hours and compared them to patients’ peripheral blood mononuclear cells (PBMCs) before and during oral therapy. There were 3151 (7.7%) genes/transcripts differentially expressed in vitro in treated resistant MJ cells compared to untreated vehicle control (p < 0.001). We also studied differential gene expression in two clinically resistant Sézary patients’ PBMCs taken at baseline and four weeks after oral vorinostat (400 mg daily or 300 mg bid 3 days/wk). In patients’ PBMCs, 585 (1.4%) and 2744 (6.7%) differentially expressed genes/transcripts (p < 0.001) were identified, respectively. Genes that were up-regulated both in vitro and in vivo included a tumor necrosis factor receptor super-family member 11a (TNFRSF11a or RANK), matrix metallopeptidase 9 (MMP9), suppressor of cytokine signaling 3 (SOCS3), vinculin (VCL) and KIAA1840. Genes that were down-regulated in both included adenylate kinase 3-like 1 (AK3L1), leucine rich repeat and fibronectin type III domain containing 4 (LRFN4), and AL359650. Increased RANK, MMP9 and SOCS3 mRNA expression in MJ compared to HH cells and in three resistant versus three vorinostat responding Sézary patients’ PBMCs was confirmed using quantitative real-time PCR. In conclusion, our results suggest that oligonucleotide microarray analysis may identify biomarkers of resistance to vorinostat which would be helpful to select patients who may not benefit from treatment. These findings provide the rationale for future functional studies and development of more effective use of HDAC inhibitors for CTCL patients.

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