Single nucleotide variants in immune-response genes and the tumor microenvironment composition predict progression of mantle cell lymphoma

Assis‐Mendonça, Guilherme Rossi; Fattori, André; Lourenço, Gustavo Jacob; Delamain, Márcia Torresan; Nonogaki, Suely; Lima, Vladmir Cláudio Cordeiro de; Colleoni, Gisele Wally Braga; Souza, Cármino Antônio de; Soares, Fernando Augusto; Lima, Carmen Sílvia Passos; Vassallo, José

doi:10.1186/s12885-021-07891-9

Cited by 7 publications

(4 citation statements)

References 65 publications

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“…Thus, we conclude that there is an active infiltration of cytotoxic T cells in MCL TIME. The frequency and ratios of T cells in late differentiation stage have not been reported before, but TH and TC frequencies were in line with previous studies using IHC by ourselves [26] and Vasallo et al [62].…”

Section: Discussionsupporting

confidence: 91%

Quantification and Profiling of Early and Late Differentiation Stage T Cells in Mantle Cell Lymphoma Reveals Immunotherapeutic Targets in Subsets of Patients

Lokhande,

Nilsson,

de Matos Rodrigues

et al. 2024

Cancers

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With the aim to advance the understanding of immune regulation in MCL and to identify targetable T-cell subsets, we set out to combine image analysis and spatial omic technology focused on both early and late differentiation stages of T cells. MCL patient tissue (n = 102) was explored using image analysis and GeoMx spatial omics profiling of 69 proteins and 1812 mRNAs. Tumor cells, T helper (TH) cells and cytotoxic (TC) cells of early (CD57−) and late (CD57+) differentiation stage were analyzed. An image analysis workflow was developed based on fine-tuned Cellpose models for cell segmentation and classification. TC and CD57+ subsets of T cells were enriched in tumor-rich compared to tumor-sparse regions. Tumor-sparse regions had a higher expression of several key immune suppressive proteins, tentatively controlling T-cell expansion in regions close to the tumor. We revealed that T cells in late differentiation stages (CD57+) are enriched among MCL infiltrating T cells and are predictive of an increased expression of immune suppressive markers. CD47, IDO1 and CTLA-4 were identified as potential targets for patients with T-cell-rich MCL TIME, while GITR might be a feasible target for MCL patients with sparse T-cell infiltration. In subgroups of patients with a high degree of CD57+ TC-cell infiltration, several immune checkpoint inhibitors, including TIGIT, PD-L1 and LAG3 were increased, emphasizing the immune-suppressive features of this highly differentiated T-cell subset not previously described in MCL.

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Section: Discussionsupporting

confidence: 91%

Quantification and Profiling of Early and Late Differentiation Stage T Cells in Mantle Cell Lymphoma Reveals Immunotherapeutic Targets in Subsets of Patients

Lokhande,

Nilsson,

de Matos Rodrigues

et al. 2024

Cancers

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“…In recent years, several studies have underlined the potential role of interindividual genetic differences in shaping treatment response and toxicity in lymphoma. 23 , 24 Nonetheless, to date, little pharmacogenetic knowledge is available in the MCL literature, 25 , 26 , 27 , 28 and no data relative to lenalidomide treatment in MCL have been published. In contrast, several pharmacogenetic studies have been published, mainly in MM, assessing the relation of lenalidomide activity with polymorphisms of CRBN , one of lenalidomide’s most investigated molecular targets.…”

Section: Discussionmentioning

confidence: 99%

Candidate germline biomarkers of lenalidomide efficacy in mantle cell lymphoma: the Fondazione Italiana Linfomi MCL0208 trial

et al. 2023

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In the FIL MCL0208 phase III trial, lenalidomide maintenance (LEN) after transplantation (ASCT) in mantle cell lymphoma (MCL) improved progression-free survival (PFS) vs observation (OBS). The host pharmacogenetic background was analyzed to decipher whether single nucleotide polymorphisms (SNPs) of genes encoding transmembrane transporters, metabolic enzymes, or cell surface receptors might predict drug efficacy. Genotypes were obtained by real-time polymerase chain reaction (RT-PCR) in peripheral blood (PB) germ line DNA. Polymorphisms of either ABCB1 or VEGF were found in 69% and 79% of 278 patients and predicted favorable PFS vs homozygous wild type (WT) in the LEN arm: 3-year PFS 85% vs 70% (p < 0.05) and 85% vs 60% (p < 0.01), respectively. Patients carrying both ABCB1 and VEGF WT had the poorest 3-year PFS (46%) and overall survival (OS, 76%): in fact, in these patients LEN did not improve PFS vs OBS (3-year PFS 44% vs 60%, p = 0.62). Moreover, CRBN polymorphism (n = 28) was associated with lenalidomide dose reduction or discontinuation. Finally, ABCB1, NCF4, and GSTP1 polymorphisms predicted lower hematological toxicity during induction, while ABCB1 and CRBN polymorphisms predicted lower risk of grade ≥3 infections. This study demonstrates that specific SNPs represent candidate predictive biomarkers of immunochemotherapy toxicity and LEN efficacy after ASCT in MCL. This trial is registered at eudract.ema.europa.eu as 2009-012807-25.

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“…In MCL, the effects of various immune checkpoint inhibitors (ICIs) are inconclusive, and the expressions of programmed death 1 (PD-1) and its ligands are almost undetectable (13,14). Moreover, the immune-response genes and stromal microenvironments have confirmed the major roles in the survival, progression, and chemoresistance of MCL (15)(16)(17). Therefore, understanding the immune landscape and molecular variations in MCL is essential for the development of immunotherapy.…”

Section: Introductionmentioning

confidence: 99%

Identification of immune-related genes and development of a prognostic model in mantle cell lymphoma

Zhang¹,

Shi²,

Wang³

et al. 2022

Ann Transl Med

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Background: The immune landscape, prognostic model, and molecular variations of mantle cell lymphoma (MCL) remain unclear. Hence, an integrated bioinformatics analysis of MCL datasets is required for the development of immunotherapy and the optimization of targeted therapies.Methods: Data were obtained from the Gene Expression Omnibus (GEO) database (GSE32018, GSE45717 and GSE93291). The differentially expressed immune-related genes were selected, and the hub genes were screened by three machine learning algorithms, followed by enrichment and correlation analyses. Next, MCL molecular clusters based on the hub genes were identified by K-Means clustering, the probably approximately correct (PAC) algorithm, and principal component analysis (PCA). The landscape of immune cell infiltration and immune checkpoint molecules in distinct clusters was explored by single-sample gene-set enrichment analysis (ssGSEA) as well as the CIBERSORT and xCell algorithms. The prognostic genes and prognostic risk score model for MCL clusters were identified by least absolute shrinkage and selection operator (LASSO)-Cox analysis and cross-validation for lambda. Correlation analysis was performed to explore the correlation between the screened prognostic genes and immune cells or immune checkpoint molecules.Results: Four immune-related hub genes (CD247, CD3E, CD4, and GATA3) were screened in MCL, mainly enriched in the T-cell receptor signaling pathway. Based on the hub genes, two MCL molecular clusters were recognized. The cluster 2 group had a significantly worse overall survival (OS), with downregulated hub genes, and a variety of activated immune effector cells declined. The majority of immune checkpoint molecules had also decreased. An efficient prognostic model was established, including six prognostic genes (LGALS2, LAMP3, ICOS, FCAMR, IGFBP4, and C1QA) differentially expressed between two MCL clusters. Patients with a higher risk score in the prognostic model had a poor prognosis.Furthermore, most types of immune cells and a range of immune checkpoint molecules were positively correlated with the prognostic genes.Conclusions: Our study identified distinct molecular clusters based on the immune-related hub genes, and showed that the prognostic model affected the prognosis of MCL patients. These hub genes, modulated immune cells, and immune checkpoint molecules might be involved in oncogenesis and could be potential prognostic biomarkers in MCL.

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Single nucleotide variants in immune-response genes and the tumor microenvironment composition predict progression of mantle cell lymphoma

Cited by 7 publications

References 65 publications

Quantification and Profiling of Early and Late Differentiation Stage T Cells in Mantle Cell Lymphoma Reveals Immunotherapeutic Targets in Subsets of Patients

Quantification and Profiling of Early and Late Differentiation Stage T Cells in Mantle Cell Lymphoma Reveals Immunotherapeutic Targets in Subsets of Patients

Candidate germline biomarkers of lenalidomide efficacy in mantle cell lymphoma: the Fondazione Italiana Linfomi MCL0208 trial

Identification of immune-related genes and development of a prognostic model in mantle cell lymphoma

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