Single-cell spatial analysis of tumor immune architecture in diffuse large B-cell lymphoma

Colombo, Anthony; Hav, Monirath; Singh, Mohan; Xu, Alexander M.; Gamboa, Alicia; Lemos, Tucker; Gerdtsson, Erik; Chen, Denaly; Houldsworth, Jane; Shaknovich, Rita; Aoki, Tomohiro; Chong, Lauren C.; Takata, Katsuyoshi; Chavez, Elizabeth A.; Hicks, James; Kühn, Peter; Siddiqi, Imran; Merchant, Akil

doi:10.1182/bloodadvances.2022007493

Cited by 26 publications

(14 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This finding is consistent with reports of increased TIM-3 expression on T-cells in other neoplasms compared with healthy donors, including in colon cancer 21 and breast cancer 22 . Increased TIM-3 expression has been found in tumor tissues in several malignancies, including diffuse large B cell lymphoma 23 and head and neck cancer 24 . Additionally, several studies have shown that TIM-3 expression is associated with T-cell dysfunction in the context of chronic viral infection and cancer 25,26 .…”

Section: Discussionmentioning

confidence: 99%

Association of TIM-3 checkpoint receptor expression on T cells with treatment-free remission in chronic myeloid leukemia

et al. 2023

View full text Add to dashboard Cite

Dysregulation of immune checkpoint receptors has been reported at diagnosis of chronic myeloid leukemia (CML), but their role in the maintenance of remission after tyrosine kinase inhibitor (TKI) cessation is unclear. We assessed PD-1, TIM-3, CTLA-4, LAG-3 and TIGIT expression on T-cell subsets, regulatory T cells (T-regs), and natural killer (NK) cells at the time of TKI cessation in 44 patients (22 who sustained treatment-free remission (TFR), 22 who experienced molecular relapse (MolR)). We confirmed our previous finding that absolute numbers of T-regs are increased in MolR patients compared to TFR. The immune checkpoint receptors PD-1, CTLA-4, LAG-3 and TIGIT on T or NK cells were not differentially expressed between the MolR and TFR groups. However, TIM-3 was consistently upregulated on bulk T-cells (CD3+), and T-cell subsets including, CD4+T-cells, CD8+T-cells, and T-regs, in patients who relapsed in comparison to those who maintained TFR after discontinuation. Furthermore, gene expression analysis from publicly available datasets showed increased TIM-3 expression on CML stem cells compared with normal hematopoietic stem cells. These findings suggest that among the targetable immune checkpoint molecules, TIM-3 blockade may potentially improve effector immune response in CML patients stopping TKI, whilst concomitantly targeting leukemic stem cells, and could be a promising therapeutic strategy for preventing relapse after cessation of TKI in CML patients.

show abstract

Section: Discussionmentioning

confidence: 99%

Association of TIM-3 checkpoint receptor expression on T cells with treatment-free remission in chronic myeloid leukemia

et al. 2023

View full text Add to dashboard Cite

show abstract

“…DLBCL is the most common type of Non-Hodgkin’s lymphoma(NHL) and is highly invasive and heterogeneous in clinical presentation and prognosis.The therapeutic effect of PD-1/PD-L1 inhibitors in DLBCL is not significant.Compared with reactive hyperplasia lymph nodes, PD1+CD8+T cells were often increased in DLBCL.These CD8+T cells are almost universally activated and functional in DLBCL, even in the presence of the expression of negative regulatory molecules such as PD-1 and TIM-3, but lack the main feature of depletion, which PD-1 inhibitors require in order to function ( 21 ).In addition, it has also been observed that PD-1 shows high expression on Treg, and anti-PD-1 antibodies may lead to increased activity of Treg, leading to suppression of immune response ( 22 ).These findings may explain the current failure of immune checkpoint therapy.Therefore, we urgently need to find new immune checkpoint inhibitors to improve the treatment status of DLBCL.…”

Section: Discussionmentioning

confidence: 99%

The immune checkpoint expression in the tumor immune microenvironment of DLBCL: Clinicopathologic features and prognosis

Pang

et al. 2022

Front. Oncol.

View full text Add to dashboard Cite

Background & aimsThe immune checkpoint recently provides a new strategy for the immunotherapy of malignant tumors. However, the role in the immune microenvironment of DLBCL is not completely clear.MethodsWe detected the expression of PD-1, LAG-3, TIM-3, and TIGIT on TILs and on tumor cells among 174 DLBCL patients by IHC.ResultsIn TILs, the positive rates of PD-1, LAG-3, TIM-3 and TIGIT were 79.3%, 78.8%, 62.7% and 69.5%, respectively.TIM-3 and TIGIT were expressed in 44.8% and 45.4% of tumor cells. The expression of TIM-3 in TILs was significantly correlated with the Ann-Arbor stage (P=0.039). There was a positive correlation Between PD-1 and LAG-3 or TIM-3 and TIGIT.In addition, LAG-3 expression in TILs was associated with inferior prognosis.Multivariate analysis showed that PS score and R-CHOP therapy were independent risk factors for OS and PFS in patients with DLBCL (P=0.000).ConclusionsThe expression level of TIM-3 is closely related to the Ann-Arbor stage, which may be expected to be a new index to evaluate the invasiveness of DLBCL. PD-1 was correlated with the expression of LAG-3, and the high expression of LAG-3 and LAG-3/PD-1 predicted the poor prognosis of DLBCL. Therefore, LAG-3 may become a new target of immunotherapy, or be used in combination with PD-1 inhibitors to improve the drug resistance of current patients with DLBCL.

show abstract

“…To understand the molecular mechanisms underlying relapsed DLBCL, Florian et al studied differences in the lipid and metabolic compositions of nontreated and R-CHOP-resistant tumors using a combination of in vivo DLBCL xenograft models and MSI (27). In another study, Anthony et al used imaging mass cytometry on 33 cases of DLBCL to characterise the tumor and immune cell architecture and correlate it to clinicopathological features, such as the cell of origin, gene mutations, and responsiveness to chemotherapy (163). Notably, the spatial metabolomic technology is performed only in the lymph nodes in DLBCL due to its relatively stable position within the tissue.…”

Section: Dlbclmentioning

confidence: 99%

When cancer drug resistance meets metabolomics (bulk, single-cell and/or spatial): Progress, potential, and perspective

Zhang

Bao

et al. 2023

Front. Oncol.

View full text Add to dashboard Cite

Resistance to drug treatment is a critical barrier in cancer therapy. There is an unmet need to explore cancer hallmarks that can be targeted to overcome this resistance for therapeutic gain. Over time, metabolic reprogramming has been recognised as one hallmark that can be used to prevent therapeutic resistance. With the advent of metabolomics, targeting metabolic alterations in cancer cells and host patients represents an emerging therapeutic strategy for overcoming cancer drug resistance. Driven by technological and methodological advances in mass spectrometry imaging, spatial metabolomics involves the profiling of all the metabolites (metabolomics) so that the spatial information is captured bona fide within the sample. Spatial metabolomics offers an opportunity to demonstrate the drug-resistant tumor profile with metabolic heterogeneity, and also poses a data-mining challenge to reveal meaningful insights from high-dimensional spatial information. In this review, we discuss the latest progress, with the focus on currently available bulk, single-cell and spatial metabolomics technologies and their successful applications in pre-clinical and translational studies on cancer drug resistance. We provide a summary of metabolic mechanisms underlying cancer drug resistance from different aspects; these include the Warburg effect, altered amino acid/lipid/drug metabolism, generation of drug-resistant cancer stem cells, and immunosuppressive metabolism. Furthermore, we propose solutions describing how to overcome cancer drug resistance; these include early detection during cancer initiation, monitoring of clinical drug response, novel anticancer drug and target metabolism, immunotherapy, and the emergence of spatial metabolomics. We conclude by describing the perspectives on how spatial omics approaches (integrating spatial metabolomics) could be further developed to improve the management of drug resistance in cancer patients.

show abstract

Single-cell spatial analysis of tumor immune architecture in diffuse large B-cell lymphoma

Cited by 26 publications

References 56 publications

Association of TIM-3 checkpoint receptor expression on T cells with treatment-free remission in chronic myeloid leukemia

Association of TIM-3 checkpoint receptor expression on T cells with treatment-free remission in chronic myeloid leukemia

The immune checkpoint expression in the tumor immune microenvironment of DLBCL: Clinicopathologic features and prognosis

When cancer drug resistance meets metabolomics (bulk, single-cell and/or spatial): Progress, potential, and perspective

Contact Info

Product

Resources

About