Impact of Tumor Infiltrating T Cells in Patients with Diffuse Large B-Cell Lymphoma

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 1572-1572
Author(s):  
Shahryar Kiaii ◽  
Andrew James Clear ◽  
John G Gribben
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
B Cell ◽  
Immune Cells ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Treated Group ◽  
Prognostic Impact ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Abstract Abstract 1572 Previous studies have demonstrated the importance of the non-malignant tumor-infiltrating immune cells in the tumor microenvironment at diagnosis in patients with non-Hodgkin's lymphoma (NHL). We aimed to investigate the molecular mechanisms whereby tumor infiltrating T cells (TILs) are altered in follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL). We used gene expression profiling of highly purified CD4 and CD8 infiltrating T-cells (TILs) from FL patients and reported that PMCH, ETV1 and NAMPT are highly expressed in both CD4 and CD8 TILs and showed in tissue microarrays (TMA) that expression of pro-melanin-concentrating hormone (PMCH), ets variant 1 (ETV1) and nicotinamide phosphoribosyltransferase (NAMPT) in T-cells have prognostic impact in disease specific survivals (DSS) and time to transformation (TT) in patients with FL. In addition, PMCH and NAMPT were shown to be independently significant in TT in multivariate analysis. We next examined expression of these gene products in T cells in FL samples before and after transformation to DLBCL (n=29). Comparing total number of positive cells for expression of proteins of interest, we demonstrate there is a significant decline in PMCH (p=0.035), EVT1 (p=0.018) and NAMPT (p=0.0136) expressing cells after transformation. We further investigated the prognostic impact of expression of these proteins in T cells in patients with DLBCL in two treatment groups, those receiving rituximab (n=68) and in a historic non-rituximab (n=130) treated cohort. By assessing the number of positive cells and the impact on survival using Kaplan-Meier analysis, we now show that the T-cell expressed genes PMCH, ETV1 and NAMPT have prognostic significance for overall survival (OS) in patients with DLBCL. Patients with higher number of PMCH expressing T-cells showed significant longer survivals in both rituximab (p=0.027) and non-rituximab (p=0.033) treated groups. In contrast to PMCH, and in line with our previous data in FL, patients with higher number of NAMPT expressing cells showed significantly shorter OS in the rituximab (p=0.046) treated group, with a trend towards shorter OS in non-rituximab (p=0.064) treated group. Patients with higher percentage of ETV1 expressing cells had longer OS in the non-Rituximab group (p=0.008), with only a trend towards OS with rituximab treatment (p=0.067). We are examining this further in a larger cohort of rituximab treated patients. Our previous data has indicated that TILs in patients with FL are abnormal in terms of their gene expression and function. We now show that changes in protein expression in TILs have an impact on transformation in patients with FL and on survival in both FL and DLBCL. We are further characterizing the mechanisms of gene expression alteration in TILs of patients with FL and DLBCL and its functional consequences in the biology and of the disease. It appears that altered gene expression in TILs plays a fundamental role in transformation and may be important in the survivals and biology of NHL. Since non-malignant infiltrating immune cells have a crucial role in the outcome of patients with FL and DLBCL, understanding the nature and impact of the abnormalities induced in TILs in these patients is crucial before any immunotherapeutic strategies can be implemented to attempt to alter the immune microenvironment in NHL. Disclosures: Gribben: Celgene: Honoraria.

scholarly journals Gene expression profiling-based risk prediction and profiles of immune infiltration in diffuse large B-cell lymphoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Selin Merdan ◽  
Kritika Subramanian ◽  
Turgay Ayer ◽  
Johan Van Weyenbergh ◽  
Andres Chang ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
B Cell ◽  
Risk Prediction ◽  
Expression Profiling ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Gene Signatures ◽  
Large B Cell Lymphoma ◽  
Large B Cell

AbstractThe clinical risk stratification of diffuse large B-cell lymphoma (DLBCL) relies on the International Prognostic Index (IPI) for the identification of high-risk disease. Recent studies suggest that the immune microenvironment plays a role in treatment response prediction and survival in DLBCL. This study developed a risk prediction model and evaluated the model’s biological implications in association with the estimated profiles of immune infiltration. Gene-expression profiling of 718 patients with DLBCL was done, for which RNA sequencing data and clinical covariates were obtained from Reddy et al. (2017). Using unsupervised and supervised machine learning methods to identify survival-associated gene signatures, a multivariable model of survival was constructed. Tumor-infiltrating immune cell compositions were enumerated using CIBERSORT deconvolution analysis. A four gene-signature-based score was developed that separated patients into high- and low-risk groups. The combination of the gene-expression-based score with the IPI improved the discrimination on the validation and complete sets. The gene signatures were successfully validated with the deconvolution output. Correlating the deconvolution findings with the gene signatures and risk score, CD8+ T-cells and naïve CD4+ T-cells were associated with favorable prognosis. By analyzing the gene-expression data with a systematic approach, a risk prediction model that outperforms the existing risk assessment methods was developed and validated.

Gene Expression Signature of Host Immune Response Is Predictive of Follicular Lymphoma Patient Survival in Independent Cohorts, and Correlates with Transformation to Diffuse Large B-Cell Lymphoma.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2951-2951
Author(s):  
Ash A Alizadeh ◽  
Andrew J Gentles ◽  
Sylvia K Plevritis ◽  
Ronald Levy
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Follicular Lymphoma ◽  
B Cell ◽  
Immune Cells ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Large B Cell Lymphoma ◽  
Large B Cell ◽  
Independent Cohort

Abstract Abstract 2951 Poster Board II-927 Background: Expression signatures of infiltrating immune cells [1] have been shown to predict survival in follicular lymphoma (FL), but have not been cross-validated in independent patient cohorts [2,3]. These signatures may relate biologically to the frequency of infiltrating including T-cells and macrophages, or to specific transcription programs within tumor cells and/or the tumor microenvironment. We sought to evaluate the validity of this model in an independent cohort of patients with FL, assessing its relationship to outcomes including histological transformation and death. Methods: The immune response (IR) predictor score proposed by Dave et al. [1] was applied to gene expression data from an independent cohort of 88 FL patients [4] with known survival outcomes and history of transformation to diffuse large B-cell lymphoma (DLBCL). Genes (n=66) corresponding to IR1 and IR2 signatures were mapped from Affymetrix microarrays [1] to a custom cDNA array [4] via Entrez Gene ID, and the composite IR score was calculated per the scheme proposed by Dave et al. Results: The IR score was predictive of patient outcome in the 88 patient test set as a continuous variable (p=0.001, HR=2.01, 95% CI 0.50-1.30). Partitioning of patients into high and low risk groups based on the median IR score across the cohort robustly separated survival curves (Figure A). The IR score was significantly higher in FL patients known to undergo transformation to DLBCL (Figure B: mean IR score of -0.6 in non-transforming FL vs. -0.2 in transforming FL; p∼10-11, t-test). Conclusions: The IR score of Dave et al. was highly significant as a predictor of survival in the independent patient cohort [4]. Moreover, the score was significantly associated with propensity of FL to transform to DLBCL. To our knowledge, immune cell infiltration has not previously been implicated in transformation. 1. Dave SS et al. (2004) Prediction of survival in follicular lymphoma based on molecular features of tumor-infiltrating immune cells. N Engl J Med 351(21): 2159-2169. 2. Tibshirani R (2005) Immune signatures in follicular lymphoma. N Engl J Med 352: 1496-1497. 3. Chu G Hong WJ, Warnke R, Chu G (2005). Immune Signatures in Follicular Lymphoma (Corres). N Engl J Med. 352: 1496-1497. 4. Glas AM et al. (2005) Gene expression profiling in follicular lymphoma to assess clinical aggressiveness and to guide the choice of treatment. Blood 105(1): 301-307. Disclosures: No relevant conflicts of interest to declare.

Prognostic Impact of Tumor Infiltrating FOXP3 Positive Regulatory T Cells in Diffuse Large B-Cell Lymphoma at Diagnosis.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 1565-1565
Author(s):  
Jae-Yong Kwak ◽  
Na-Ri Lee ◽  
Eun-Kee Song ◽  
Kyu Yun Jang ◽  
Ha Na Choi ◽  
...  
Keyword(s):  
T Cells ◽  
Regulatory T Cells ◽  
B Cell ◽  
Cell Lymphoma ◽  
International Prognostic Index ◽  
Prognostic Significance ◽  
B Cell Lymphoma ◽  
Prognostic Impact ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Abstract Tumor infiltrating immune cells play an important role in host immune reactions against diffuse large B-cell lymphoma (DLBCL). In the present study, we have identified a subset of tumor infiltrating FOXP3-positive regulatory T cells (Tregs) in the initial DLBCL biopsy specimens and evaluated its prognostic significance. Ninety-six patients with DLBCL were retrospectively evaluated. Expression pattern of FOXP3 protein was examined using standard immunohistochemistry in paraffin-embedded tissue samples. The median overall survival (OS) was 28 months. Compared to the others, the patients with higher percentage of FOXP3-positive Tregs in the initial tumor biopsy, showed a significantly longer OS (p=0.003). When prognostic factors were evaluated in a multivariate model, the international prognostic index and the percentage of infiltrating FOXP3-positive Tregs in the initial biopsy were shown to be independent predictors of OS. In conclusion, the presence of increased percentage of FOXP3-positive Tregs in DLBCL predicts a better prognosis. Figure Figure

Applicability of Different Immunohistochemistry Algorithms to Assess Gene Expression Profile In Patients with Diffuse Large B-Cell Lymphoma

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 4134-4134
Author(s):  
Gonzalo Gutierrez-Garcia ◽  
Teresa Cardesa ◽  
Luis Colomo ◽  
Fina Climent ◽  
Santiago Mercadal ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Conflicts Of Interest ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Prognostic Impact ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Abstract Abstract 4134 Gene expression profile (GEP) allows to distinguish two groups with different origin in patients with diffuse large B-cell lymphoma (DLBCL): germinal-center (GC) and activated (ABC), with the latter having a significantly poorer outcome. However, GEP is a technique not available in current clinical practice. For this reason, attempts to reproduce GEP data by immunophenotyping algorithms have been made. The aim of this study was to apply the most popular algorithms in a series of patients with DLBCL homogeneously treated with immunochemotherapy, in order to assess the correlation with GEP data and their usefulness to predict response and outcome of the patients. One hundred fifty seven patients (80M/77F; median age 65 years) diagnosed with DLBCL in 5 institutions of the Grup per l'Estudi dels Limfomes de Catalunya I Balears (GELCAB) during a 5-year period, treated with Rituximab-containing regimens (in most cases, R-CHOP), in whom histological material to construct a tissue microarrays (TMA) was available, constituted the subjects of the present study. Four algorithms were applied: Colomo (Blood 2003, 101:78) using CD10, bcl-6 and MUM1/IRF4; Hans (Blood 2004, 103:275) using CD10, bcl-6 and MUM1/IRF4; Muris (J Pathol 2006, 208:714) using CD10 and MUM1/IRF4, and Choi (Clin Cancer Res 2009, 15:5494), using CD10, bcl-6, GCET1, FOXP1 and MUM1/IRF4. The thresholds used were those previously described. GEP studies were performed in 62 patients in whom fresh frozen material was available. Main clinical and evolutive data were recorded and analyzed. The proportion of positive cases for the different single antigens was as follows: CD10 26%, bcl-6 64%, GCET1 46%, FOXP1 78% and MUM1/IRF4 28%. The distribution of cases (GC vs. non-GC) according to the algorithms is detailed in the table. In 88 of 110 patients (80%) with all the antigens available, the patients were allocated in the same group (either GC or non-GC). When the immunochemistry was compared with GEP data, the sensitivity in the GC group was 59%, 52%, 70% and 40% for Colomo, Hans, Muris and Choi algorithms, respectively. The sensitivity in the non-GC group was 81%, 85%, 62% and 84%, respectively. On the other hand, the positive predictive value (PPV) in the GC group was 81%, 83%, 72% and 77%, respectively. In non-GC subset the PPV for the different algorithms was 59%, 55%, 72% and 52%, respectively. We observed a higher percentage of misclassified cases in the GC-phenotype subset than in the non-GC subgroup. None of the immunohistochemical algorithms showed a significant superiority as surrogate of GEP information among the others. The ability of GEP groups as well as of groups defined by the algorithms to predict complete response (CR) rate, progression-free survival (PFS) and overall survival (OS) of the patients is showed in the table. Thus, whereas the GEP groups showed significant prognostic value for CR rate, PFS and OS, none of the immunohistochemical algorithms were able to predict the outcome. In conclusion, in a homogeneous series of DLBCL patients treated with immunochemotherapy, the different immunohistochemical algorithms were not able to mimic the GEP information. The prognostic impact of the groups defined by immunohistochemistry (GC vs. non-GC) was particularly low. N (%) CR rate N (%) 5-year PFS (%) 5-year OS (%) Colomo algorithm GC 53 (44) 39 (74) 48 54 Non-GC 68 (56) 53 (78) 55 62 Hans algorithm GC 61 (41) 47 (77) 54 60 Non-GC 88 (59) 67 (76) 52 59 Muris algorithm GC 87 (57) 63 (72) 48 57 Non-GC 65 (43) 51 (78) 56 63 Choi algorithm GC 45 (33) 32 (71) 48 54 Non-GC 90 (67) 70 (78) 52 61 Gene expression profile 30 (58) 25 (83) 76* 80** GC Activated 22 (42) 17 (77) 31* 45** * p=0.005, ** p=0.03. Disclosures: No relevant conflicts of interest to declare.

Alteration of the gene expression profile of T-cell receptor αβ-modified T-cells with diffuse large B-cell lymphoma specificity

Hematology ◽  
2013 ◽  
Vol 18 (3) ◽  
pp. 138-143 ◽  
Author(s):  
Xianfeng Zha ◽  
Qingsong Yin ◽  
Huo Tan ◽  
Chunyan Wang ◽  
Shaohua Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
B Cell ◽  
T Cell Receptor ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Cell Receptor ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Prognostic impact of tumor infiltrating FOXP3 positive regulatory T cells in diffuse large B-cell lymphoma at diagnosis

2008 ◽  
Vol 49 (2) ◽  
pp. 247-256 ◽  
Author(s):  
Na-Ri Lee ◽  
Eun-Kee Song ◽  
Kyu Yun Jang ◽  
Ha Na Choi ◽  
Woo Sung Moon ◽  
...  
Keyword(s):  
T Cells ◽  
Regulatory T Cells ◽  
B Cell ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Prognostic Impact ◽  
Large B Cell Lymphoma ◽  
Large B Cell

scholarly journals LAG3: a novel immune checkpoint expressed by multiple lymphocyte subsets in diffuse large B-cell lymphoma

2020 ◽  
Vol 4 (7) ◽  
pp. 1367-1377 ◽  
Author(s):  
Colm Keane ◽  
Soi C. Law ◽  
Clare Gould ◽  
Simone Birch ◽  
Muhammed B. Sabdia ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
B Cells ◽  
B Cell ◽  
Cell Lymphoma ◽  
International Prognostic Index ◽  
B Cell Lymphoma ◽  
Large B Cell Lymphoma ◽  
The Impact ◽  
Large B Cell

Abstract Blockade of the PD-1 axis has modest efficacy in diffuse large B-cell lymphoma (DLBCL), but data regarding LAG3 are sparse. The impact of LAG3 digital gene expression was tested in 309 patients with DLBCL treated with standard chemoimmunotherapy. Cellular distribution of LAG3 protein was determined by immunohistochemistry and flow cytometry. In tumor-infiltrating lymphocytes (TILs), LAG3 expression was highest on CD4+ regulatory T cells (Tregs) and was also highly expressed on CD8+ T cells compared with CD4+ non-Tregs (both P = .008). LAG3high TILs were enriched in PD-1 and TIM-3. LAG3 was also expressed on a proportion of malignant B cells, and these patients had significantly higher LAG3 messenger RNA in their biopsies (P = .03). LAG3high gene expression was associated with inferior survival in discovery/validation cohorts, independent of cell of origin and the international prognostic index. Patients who were PD-L1high were fivefold more likely to be LAG3high (P < .0001). Patients who were LAG3high/PD-L1high had an inferior progression-free survival (P = .011) and overall survival (P = .005) compared with patients who were LAG3low/PD-L1high. Digital spatial protein analysis confirms LAG3 expression on T cells and, surprisingly, tumor-associated macrophages (TAMs) at higher levels than found on CD20+ B cells in the tumor microenvironment. LAG3 is frequently expressed on CD4+ Tregs and CD8+ TILs, typically with other immune checkpoints, and is also present in a proportion of malignant B cells in DLBCL and in areas enriched for TAMs. LAG3high expression is associated with poor outcome independent of conventional prognosticators. 

scholarly journals Adverse prognostic impact of regulatory T‐cells in testicular diffuse large B‐cell lymphoma

2020 ◽  
Vol 105 (6) ◽  
pp. 712-721
Author(s):  
Marjukka Pollari ◽  
Teijo Pellinen ◽  
Marja‐Liisa Karjalainen‐Lindsberg ◽  
Pirkko‐Liisa Kellokumpu‐Lehtinen ◽  
Suvi‐Katri Leivonen ◽  
...  
Keyword(s):  
T Cells ◽  
Regulatory T Cells ◽  
B Cell ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Prognostic Impact ◽  
Large B Cell Lymphoma ◽  
Large B Cell

scholarly journals OCT1 gene Expression Is an Independent Prognostic Factor in Diffuse Large B Cell Lymphoma

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 5185-5185
Author(s):  
Gisele Rodrigues Gouveia ◽  
Suzete Cleusa Ferreira ◽  
Sheila Siqueira ◽  
Juliana Pereira
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Cell Lymphoma ◽  
International Prognostic Index ◽  
B Cell Lymphoma ◽  
Prognostic Impact ◽  
Large B Cell Lymphoma ◽  
Significant Difference ◽  
The Impact ◽  
Large B Cell

Abstract Background: Transcription factors associated with the POU domain modulate the expression of several genes of B lymphoid differentiation, including the IgH. The study of these factors allowed to better understand the pathogenesis of lymphomas and to establish the lineage and the differentiation stage of the malignant cell. The silencing of OCT1 in tumor cell lines reduced its malignant transformation, but its ectopic expression enhanced the tumorigenesis ability. However, few studies has been evaluated the role of the OCT1 gene expression in lymphoma. In this study we assessed the impact of the OCT1 gene expression in the survival of patients with Diffuse Large B Cell Lymphoma (DLBCL). Methods: From January 2006 to January 2011 were evaluated 77 patients with DLBCL treated with R-CHOP at Clinical Hospital and Cancer Institute of Sao Paulo University. The RNA was extracted from the paraffin block at lymphoma diagnosis and gene expression analysis was performed by relative quantification method by Real-Time PCR (qRT-PCR). After the data normalization using two different reference genes, the median expression of OCT1 was obtained. The overall survival (OS) and progression-free survival (PFS) were estimated by the Kaplan-Meier method. The relative risks were obtained by Cox regression bivariate intervals with 95% of confidence. The significance level of 5% was accepted and the IBM SPSS Statistics software version 20.0 was used. Results: Patients showing OCT1 expression < the median presented higher OS (p = 0.010) and PFS (p = 0.016) than patients with OCT1 expression ≥ median with a hazard rate (HR) for OS and PFS of 2.45 and 1.14, respectively. In multivariate analysis the PFS was also higher in patients with OCT1 expression < the median (p = 0.035). The stratification by the international prognostic index (IPI) and age showed that the expression of OCT1 < median showed a statistically significant difference in the OS (p = 0.048) in IPI intermediate-high (HI) and high (HR) patients (p = 0.048), with a HR of 2.32 in HI plus HR group. The PFS (p = 0.025) and OS (p = 0.025) were lower in patients ≥ 60 years and OCT1 expression ≥ the median. Conclusion: Our data suggest that the expression of OCT1 showed a predictive prognostic impact in DLBCL independently of IPI. Patients with lower expression of OCT1 presented a better OS and PFS. Figure 1 SG curve for the OCT1 gene expression. Figure 1. SG curve for the OCT1 gene expression. Figure 2 SLP curve for the OCT1 gene expression. Figure 2. SLP curve for the OCT1 gene expression. Figure 3 SG curve for to expression of OCT1 gene for subgroup IPI intermediate-high and high. Figure 3. SG curve for to expression of OCT1 gene for subgroup IPI intermediate-high and high. Disclosures No relevant conflicts of interest to declare.

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