Inflammatory Cells in Diffuse Large B Cell Lymphoma

Tamma, Roberto; Ranieri, Girolamo; Ingravallo, Giuseppe; Annese, Tiziana; Oranger, Angela; Gaudio, Francesco; Musto, Pellegrino; Specchia, Giorgina; Ribatti, Doménico

doi:10.3390/jcm9082418

Cited by 37 publications

(33 citation statements)

References 113 publications

(122 reference statements)

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“…Thus, a better understanding of the interactions between the TME and the immune response may provide new approaches to improve the efficiency of current immunotherapies, especially immune checkpoint inhibitor and chimeric antigen receptor (CAR) T cell therapies ( 8 ). Several studies have considered the latent role of the TME in the occurrence and development of DLBCL, but their results were controversial ( 9 ).…”

Section: Introductionmentioning

confidence: 99%

Identification and Validation of a Prognostic Gene Signature for Diffuse Large B-Cell Lymphoma Based on Tumor Microenvironment-Related Genes

Chen

Pei

et al. 2021

Front. Oncol.

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Diffuse large B-cell lymphoma (DLBCL) is an extremely heterogeneous tumor entity, which makes prognostic prediction challenging. The tumor microenvironment (TME) has a crucial role in fostering and restraining tumor development. Consequently, we performed a systematic investigation of the TME and genetic factors associated with DLBCL to identify prognostic biomarkers for DLBCL. Data for a total of 1,084 DLBCL patients from the Gene Expression Omnibus database were included in this study, and patients were divided into a training group, an internal validation group, and two external validation groups. We calculated the abundance of immune–stromal components of DLBCL and found that they were related to tumor prognosis and progression. Then, differentially expressed genes were obtained based on immune and stromal scores, and prognostic TME‐related genes were further identified using a protein–protein interaction network and univariate Cox regression analysis. These genes were analyzed by the least absolute shrinkage and selection operator Cox regression model to establish a seven-gene signature, comprising TIMP2, QKI, LCP2, LAMP2, ITGAM, CSF3R, and AAK1. The signature was shown to have critical prognostic value in the training and validation sets and was also confirmed to be an independent prognostic factor. Subgroup analysis also indicated the robust prognostic ability of the signature. A nomogram integrating the seven-gene signature and components of the International Prognostic Index was shown to have value for prognostic prediction. Gene set enrichment analysis between risk groups demonstrated that immune-related pathways were enriched in the low-risk group. In conclusion, a novel and reliable TME relevant gene signature was proposed and shown to be capable of predicting the survival of DLBCL patients at high risk of poor survival.

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Section: Introductionmentioning

confidence: 99%

Identification and Validation of a Prognostic Gene Signature for Diffuse Large B-Cell Lymphoma Based on Tumor Microenvironment-Related Genes

Chen

Pei

et al. 2021

Front. Oncol.

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“…TNFAIP3 is poorly expressed in DLBCL. DLBCL is the most common histological subtype of NHL (17)(18)(19) and generally responds well to treatment with rituximab (20,21). TNFAIP3 is an established tumor suppressor in lymphoma (22)(23)(24), but its drug resistance has been reported in various types of cancer (25,26).…”

Section: Resultsmentioning

confidence: 99%

Potential of the tumor‑derived extracellular vesicles carrying the miR‑125b‑5p target TNFAIP3 in reducing the sensitivity of diffuse large B cell lymphoma to rituximab

Zhang

Zhou

et al. 2021

Int J Oncol

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Diffuse large B-cell lymphoma (DLBCL) is the most common and aggressive form of non-Hodgkin's lymphoma. Extracellular vesicles (EVs) derived from cancer cells are known to modify the tumor microenvironment. The aim of the present study was to investigate the role of miR-125b-3p carried by EVs in DLBCL in vitro and in vivo. TNFAIP3 expression in patient lesions was measured and the upstream miR that regulates TNFAIP3 was predicted using the starBase database. EVs were isolated from DLBCL cells and identified. DLBCL cells were transfected with pcDNA to overexpress TNFAIP3 or inhibit miR-125b-5p expression, incubated with EVs, and treated with rituximab to compare cell growth and TNFAIP3/CD20 expression. DLBCL model mice were administered EVs, conditioned medium, and rituximab to observe changes in tumor size, volume, and weight. TNFAIP3 was downregulated in patients with DLBCL and its levels further decreased in patients with drug-resistant DLBCL. Overexpression of TNFAIP3 in DLBCL cells enhanced the inhibitory effect of rituximab and increased CD20 expression. miR-125b-5p targeted TNFAIP3. Inhibition of miR-125b-5p enhanced the inhibitory effect of rituximab in DLBCL cells. The EV-carried miR-125b-5p reduced the sensitivity of DLBCL cells to rituximab, which was averted by overexpression of TNFAIP3. EVs reduced the sensitivity of DLBCL model mice to rituximab via the miR-125b-5p/TNFAIP3 axis. The study findings indicate that the tumor-derived EVs carrying miR-125b-5p can enter DLBCL cells and target TNFAIP3, thus reducing the sensitivity of DLBCL to rituximab, which may provide a novel therapeutic approach for DLBCL.

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“…GSVA, GO, and KEGG enrichment results showed that cluster B, which had an abundance almost the same as that of immune cells, was strongly associated with cytokine activity and the chemokine pathway. This phenomenon may be related to the fact that immune cells are capable of producing multiple types of cytokines and chemokines (Tamma et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Characterization of Cachexia-Inducing Factors in Diffuse Large B-Cell Lymphoma Reveals a Molecular Subtype and a Prognosis-Related Signature

Kuang

Liu

et al. 2021

Front. Cell Dev. Biol.

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BackgroundCachexia is defined as an involuntary decrease in body weight, which can increase the risk of death in cancer patients and reduce the quality of life. Cachexia-inducing factors (CIFs) have been reported in colorectal cancer and pancreatic adenocarcinoma, but their value in diffuse large B-cell lymphoma (DLBCL) requires further genetic research.MethodsWe used gene expression data from Gene Expression Omnibus to evaluate the expression landscape of 25 known CIFs in DLBCL patients and compared them with normal lymphoma tissues from two cohorts [GSE56315 (n = 88) and GSE12195 (n = 136)]. The mutational status of CIFs were also evaluated in The Cancer Genome Atlas database. Based on the expression profiles of 25 CIFs, a single exploratory dataset which was merged by the datasets of GSE10846 (n = 420) and GSE31312 (n = 498) were divided into two molecular subtypes by using the method of consensus clustering. Immune microenvironment between different subtypes were assessed via single-sample gene set enrichment analysis and the CIBERSORT algorithm. The treatment response of commonly used chemotherapeutic drugs was predicted and gene set variation analysis was utilized to reveal the divergence in activated pathways for distinct subtypes. A risk signature was derived by univariate Cox regression and LASSO regression in the merged dataset (n = 882), and two independent cohorts [GSE87371 (n = 221) and GSE32918 (n = 244)] were used for validation, respectively.ResultsClustering analysis with CIFs further divided the cases into two molecular subtypes (cluster A and cluster B) associated with distinct prognosis, immunological landscape, chemosensitivity, and biological process. A risk-prognostic signature based on CCL2, CSF2, IL15, IL17A, IL4, TGFA, and TNFSF10 for DLBCL was developed, and significant differences in overall survival analysis were found between the low- and high-risk groups in the training dataset and another two independent validation datasets. Multivariate regression showed that the risk signature was an independently prognostic factor in contrast to other clinical characteristics.ConclusionThis study demonstrated that CIFs further contribute to the observed heterogeneity of DLBCL, and molecular classification and a risk signature based on CIFs are both promising tools for prognostic stratification, which may provide important clues for precision medicine and tumor-targeted therapy.

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Inflammatory Cells in Diffuse Large B Cell Lymphoma

Cited by 37 publications

References 113 publications

Identification and Validation of a Prognostic Gene Signature for Diffuse Large B-Cell Lymphoma Based on Tumor Microenvironment-Related Genes

Identification and Validation of a Prognostic Gene Signature for Diffuse Large B-Cell Lymphoma Based on Tumor Microenvironment-Related Genes

Potential of the tumor‑derived extracellular vesicles carrying the miR‑125b‑5p target TNFAIP3 in reducing the sensitivity of diffuse large B cell lymphoma to rituximab

Comprehensive Characterization of Cachexia-Inducing Factors in Diffuse Large B-Cell Lymphoma Reveals a Molecular Subtype and a Prognosis-Related Signature

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