Prognostic role of regulatory T cells in lymphoma: a systematic review and meta-analysis

Peng, Fei; Qin, You; Mu, Shidai; Li, Jingwen; Ai, Lisha; Hu, Yu

doi:10.1007/s00432-020-03398-1

Cited by 15 publications

(23 citation statements)

References 56 publications

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“…Considerable data indicate the cancer microenvironment is important in the growth, invasion and spread of lymphomas including DLBCL 3–7 . However, the IPI and R‐IPI do not consider the lymphoma microenvironment which consists of immune and stromal cells.…”

Section: Introductionmentioning

confidence: 99%

A prognostic immune risk score for diffuse large B‐cell lymphoma

Tian

Cai

et al. 2021

Br J Haematol

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Summary We constructed a prognostic score for persons with diffuse large B‐cell lymphoma (DLBCL) based on infiltrating immune cells. Data of 956 consecutive subjects were retrieved from the Gene Expression Omnibus database and assigned to training (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10846, n = 305) or validation (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE87371 n = 206 and http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE117556 n = 445 combined) cohorts. Proportions of non‐lymphoma cells in the sample were inferred using the ESTIMATE algorithm. An immune risk score was constructed comprised of eight types of non‐lymphoma immune cells calculated using the CIBERSORT algorithm. Five‐year survival of subjects with an immune risk score ≤ 0·45 in the training cohort was better than that of subjects with a score > 0·45 (hazard ratio [HR] = 3·99; 95% confidence interval [CI] = 2·74, 5·82; P < 0·001). HR in the validation cohort was HR = 2·17 (1·47, 3·21; P < 0·001). Enrichment analyses indicated correlations with genes controlling immune‐related biological processes and pathways. A nomogram comprised of the immune risk score and most covariates including age, lactate dehydrogenase concentration (LDH), lymphoma‐type (germinal centre B cell [GCB] versus non‐GCB), Eastern Cooperative Oncology Group performance status (ECOG‐PS) and rituximab therapy had a C‐statistic of 0·76 compared with C‐statistics of 0·69 and 0·69 for the International Prognostic Index (IPI) and Revised International Prognostic Index (R‐IPI). These data indicate the immune risk score is an accurate, independent survival predictor in persons with DLBCL.

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Section: Introductionmentioning

confidence: 99%

A prognostic immune risk score for diffuse large B‐cell lymphoma

Tian

Cai

et al. 2021

Br J Haematol

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“…It is generally accepted that cytotoxic CD8 + T cells, following successful priming, recognize tumor-specific (neoantigens) or tumor-associated antigens and exert antitumor function primarily via the release of cytotoxic molecules such as perforin and granzymes (35)(36)(37). However, Tregs suppress CD8 + T cells by direct cell contact and secretion of inhibitory cytokines including IL-10 and TGF-b (36,38). TAMs have been shown to mediate antibody-dependent cellular phagocytosis of rituximab in malignant B cells, limit CD8 + T cell activity through PD-L1 expression, and release IL-10 and TGF-b or inhibiting enzymes, thus regulating antitumor immunity and response to therapy (39).…”

Section: Discussionmentioning

confidence: 99%

International Prognostic Index-Based Immune Prognostic Model for Diffuse Large B-Cell Lymphoma

Shi

et al. 2021

Front. Immunol.

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BackgroundThe International Prognostic Index (IPI) is widely used to discriminate the prognosis of patients with diffuse large B-cell lymphoma (DLBCL). However, there is a significant need to identify novel valuable biomarkers in the context of targeted therapy, such as immune checkpoint blockade (ICB).MethodsGene expression data and clinical DLBCL information were obtained from The Cancer Genome Atlas and Gene Expression Omnibus datasets. A total of 371 immune-related genes in DLBCL patients associated with different IPI risk groups were identified by weighted gene co-expression network analysis, and eight genes were selected to construct an IPI-based immune prognostic model (IPI-IPM). Subsequently, we analyzed the somatic mutation and transcription profiles of the IPI-IPM subgroups as well as the potential clinical response to immune checkpoint blockade (ICB) in IPI-IPM subgroups.ResultsThe IPI-IPM was constructed based on the expression of CMBL, TLCD3B, SYNDIG1, ESM1, EPHA3, HUNK, PTX3, and IL12A, where high-risk patients had worse overall survival than low-risk patients, consistent with the results in the independent validation cohorts. The comprehensive results showed that high IPI-IPM risk scores were correlated with immune-related signaling pathways, high KMT2D and CD79B mutation rates, and upregulation of inhibitory immune checkpoints, including PD-L1, BTLA, and SIGLEC7, indicating a greater potential response to ICB therapy.ConclusionThe IPI-IPM has independent prognostic significance for DLBCL patients, which provides an immunological perspective to elucidate the mechanisms of tumor progression and sheds light on the development of immunotherapy for DLBCL.

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“…It’s generally accepted that cytotoxic CD8 + T cells, following successful priming, recognize tumor-specific (neoantigens) or tumor-associated antigens and exert anti-tumor function primarily via the release of cytotoxic molecules such as perforin and granzymes 73-75 . However, Tregs suppress CD8 + T cells by direct cell contact and secretion of inhibitory cytokines including IL-10 and TGF-β 74, 76 . TAMs have been shown to mediate antibody-dependent cellular phagocytosis of rituximab engaged malignant B cells, but limit CD8 + T cells activity through PD-L1 expression, as well as releasing IL-10 and TGF-β or inhibiting enzymes, thus regulating anti-tumor immunity and response to therapy 77 .…”

Section: Discussionmentioning

confidence: 99%

An IPI based immune prognostic model for diffuse large B-cell lymphoma

Shi

et al. 2021

Preprint

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Background: An enhanced International Prognostic Index (NCCN-IPI) was built to better discriminate diffuse large B-cell lymphoma (DLBCL) patients in the rituximab era. However, there is an urgent need to identify novel valuable biomarkers in the context of targeted therapies, such as immune checkpoint blockade (ICB) therapy. Methods: Gene expression data and clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. 73 immune-related hub genes in DLBCL patients with different IPI levels were identified by weighted gene co-expression network analysis (WGCNA), and 4 genes were selected to construct an IPI-based immune-related prognostic model (IPI-IPM). Afterward, the genetic, somatic mutational and molecular profiles of IPI-IPM subgroups were analyzed, as well as the potential clinical response of ICB in different IPI-IPM subgroups. Results: The IPI-IPM was constructed base on the expression of LCN2, CD5L, NLRP11 and SERPINB2, where high-risk patients had shorter overall survival (OS) than low-risk patients, consistent with the results in the GEO cohorts. The comprehensive results showed that a high IPI-IPM risk score was correlated with immune-related signaling pathways, high KMT2D and CD79B mutation rates, high infiltration of CD8+ T cells and macrophages (M1, M2), as well as up-regulation of inhibitory immune checkpoints including PD-L1, LAG3 and BTLA, indicating more potential response to ICB therapy. Conclusion: The IPI-IPM has independent prognostic significance for DLBCL patients, which provides an immunological perspective to elucidate the mechanisms on tumor progression and drug resistance, also sheds a light on developing immunotherapy for DLBCL.

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Prognostic role of regulatory T cells in lymphoma: a systematic review and meta-analysis

Cited by 15 publications

References 56 publications

A prognostic immune risk score for diffuse large B‐cell lymphoma

A prognostic immune risk score for diffuse large B‐cell lymphoma

International Prognostic Index-Based Immune Prognostic Model for Diffuse Large B-Cell Lymphoma

An IPI based immune prognostic model for diffuse large B-cell lymphoma

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