Targeting immune checkpoints in hematological malignancies

Salik, Basit; Smyth, Mark J.; Nakamura, Kyohei

doi:10.1186/s13045-020-00947-6

Cited by 98 publications

(85 citation statements)

References 186 publications

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“…4 e and Supplementary Figure 4 B). Immunotherapies have changed the methods of cancer treatment subversively, such as the application of checkpoint inhibitors targeting PD-1 and CTLA-4 [ 74 , 75 ]. But these strategies are not always efficacious, which is partly due to the difference of heterogeneity and/or ability of tumor-infiltrating T lymphocytes.…”

Section: Resultsmentioning

confidence: 99%

Single-cell map of diverse immune phenotypes in the acute myeloid leukemia microenvironment

et al. 2021

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Background Knowledge of immune cell phenotypes, function, and developmental trajectory in acute myeloid leukemia (AML) microenvironment is essential for understanding mechanisms of evading immune surveillance and immunotherapy response of targeting special microenvironment components. Methods Using a single-cell RNA sequencing (scRNA-seq) dataset, we analyzed the immune cell phenotypes, function, and developmental trajectory of bone marrow (BM) samples from 16 AML patients and 4 healthy donors, but not AML blasts. Results We observed a significant difference between normal and AML BM immune cells. Here, we defined the diversity of dendritic cells (DC) and macrophages in different AML patients. We also identified several unique immune cell types including T helper cell 17 (TH17)-like intermediate population, cytotoxic CD4+ T subset, T cell: erythrocyte complexes, activated regulatory T cells (Treg), and CD8+ memory-like subset. Emerging AML cells remodels the BM immune microenvironment powerfully, leads to immunosuppression by accumulating exhausted/dysfunctional immune effectors, expending immune-activated types, and promoting the formation of suppressive subsets. Conclusion Our results provide a comprehensive AML BM immune cell census, which can help to select pinpoint targeted drug and predict efficacy of immunotherapy.

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Section: Resultsmentioning

confidence: 99%

Single-cell map of diverse immune phenotypes in the acute myeloid leukemia microenvironment

et al. 2021

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“…A series of clinical studies showed that anti-PD-1/ PD-L1 antibodies had robust and durable anti-cancer activities across several solid and hematologic cancers, such as lung cancer [7][8][9], renal cell cancer [10], melanoma [11], hepatocellular carcinoma [12], as well as lymphoma [13][14][15]. Besides, synergistic anti-tumor responses have been observed in combination of anti-PD1/PD-L1 with PARP inhibition [16] or radiotherapy [17].…”

Section: Introductionmentioning

confidence: 99%

The construction, expression, and enhanced anti-tumor activity of YM101: a bispecific antibody simultaneously targeting TGF-β and PD-L1

Yi¹,

Zhang²,

Li³

et al. 2021

J Hematol Oncol

146

124

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Background Therapeutic antibodies targeting programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) axis induce potent and durable anti-tumor responses in multiple types of cancers. However, only a subset of patients benefits from anti-PD-1/PD-L1 therapies. As a negative regulator of anti-tumor immunity, TGF-β impairs the efficacy of anti-PD-1/PD-L1 and induces drug resistance. Developing a novel treatment strategy to simultaneously block PD-1/PD-L1 and TGF-β would be valuable to enhance the effect of anti-PD-1/PD-L1 and relieve drug resistance. Methods Based on the Check-BODY™ technology platform, we developed an anti-TGF-β/PD-L1 bispecific antibody YM101. The bioactivity of the anti-TGF-β moiety was determined by Smad-luciferase reporter assay, transwell assay, western blotting, CCK-8, and flow cytometry. The bioactivity of the anti-PD-L1 moiety was measured by T cell activation assays. EMT-6, CT26, and 3LL tumor models were used to investigate the anti-tumor activity of YM101 in vivo. RNA-seq, immunohistochemical staining, and flow cytometry were utilized to analyze the effect of YM101 on the tumor microenvironment. Results YM101 could bind to TGF-β and PD-L1 specifically. In vitro experiments showed that YM101 effectively counteracted the biological effects of TGF-β and PD-1/PD-L1 pathway, including activating Smad signaling, inducing epithelial-mesenchymal transition, and immunosuppression. Besides, in vivo experiments indicated the anti-tumor activity of YM101 was superior to anti-TGF-β and anti-PD-L1 monotherapies. Mechanistically, YM101 promoted the formation of ‘hot tumor’: increasing the numbers of tumor infiltrating lymphocytes and dendritic cells, elevating the ratio of M1/M2, and enhancing cytokine production in T cells. This normalized tumor immune microenvironment and enhanced anti-tumor immune response might contribute to the robust anti-tumor effect of YM101. Conclusion Our results demonstrated that YM101 could simultaneously block TGF-β and PD-L1 pathways and had a superior anti-tumor effect compared to the monotherapies.

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“…With the emergence of immune checkpoint blockade (ICB) therapy, immune checkpoint inhibitors have considerably transformed clinical decision-making in cancer oncology [ 38 – 40 ]. Subsequently, six key immune checkpoint inhibitors genes (PDCD1, CD274, PDCD1LG2, CTLA‐4, HAVCR2, and IDO1) [ 34 – 36 ] were correlated.…”

Section: Resultsmentioning

confidence: 99%

Immunological significance of prognostic alternative splicing signature in hepatocellular carcinoma

Deng

et al. 2021

Cancer Cell Int

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Background Hepatocellular carcinoma (HCC) ranks the sixth prevalent tumors with high mortality globally. Alternative splicing (AS) drives protein diversity, the imbalance of which might act an important factor in tumorigenesis. This study aimed to construct of AS-based prognostic signature and elucidate the role in tumor immune microenvironment (TIME) and immunotherapy in HCC. Methods Univariate Cox regression analysis was performed to determine the prognosis-related AS events and gene set enrichment analysis (GSEA) was employed for functional annotation, followed by the development of prognostic signatures using univariate Cox, LASSO and multivariate Cox regression. K-M survival analysis, proportional hazards model, and ROC curves were conducted to validate prognostic value. ESTIMATE R package, ssGSEA algorithm and CIBERSORT method and TIMER database exploration were performed to uncover the context of TIME in HCC. Quantitative real-time polymerase chain reaction was implemented to detect ZDHHC16 mRNA expression. Cytoscape software 3.8.0 were employed to visualize AS-splicing factors (SFs) regulatory networks. Results A total of 3294 AS events associated with survival of HCC patients were screened. Based on splicing subtypes, eight AS prognostic signature with robust prognostic predictive accuracy were constructed. Furthermore, quantitative prognostic nomogram was developed and exhibited robust validity in prognostic prediction. Besides, the consolidated signature was significantly correlated with TIME diversity and ICB-related genes. ZDHHC16 presented promising prospect as prognostic factor in HCC. Finally, the splicing regulatory network uncovered the potential functions of splicing factors (SFs). Conclusion Herein, exploration of AS patterns may provide novel and robust indicators (i.e., risk signature, prognostic nomogram, etc.,) for prognostic prediction of HCC. The AS-SF networks could open up new approach for investigation of potential regulatory mechanisms. And pivotal players of AS events in context of TIME and immunotherapy efficiency were revealed, contributing to clinical decision-making and personalized prognosis monitoring of HCC.

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Targeting immune checkpoints in hematological malignancies

Cited by 98 publications

References 186 publications

Single-cell map of diverse immune phenotypes in the acute myeloid leukemia microenvironment

Single-cell map of diverse immune phenotypes in the acute myeloid leukemia microenvironment

The construction, expression, and enhanced anti-tumor activity of YM101: a bispecific antibody simultaneously targeting TGF-β and PD-L1

Immunological significance of prognostic alternative splicing signature in hepatocellular carcinoma

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