scholarly journals Immune Checkpoint Inhibition in Classical Hodgkin Lymphoma: From Early Achievements towards New Perspectives

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Diego De Goycoechea ◽  
Gregoire Stalder ◽  
Filipe Martins ◽  
Michel A. Duchosal
Keyword(s):  
Hodgkin Lymphoma ◽  
Immune Checkpoint ◽  
Immune Escape ◽  
Response Rates ◽  
Genetic Alterations ◽  
Immune Checkpoints ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition ◽  
Classical Hodgkin Lymphoma ◽  
Immune Escape Mechanisms

Immune checkpoint inhibition (ICI) became one of the major breakthroughs in cancer treatment over the past decade and entered into therapy within standard oncohematology practice. ICI has demonstrated impressive response rates as salvage therapy in relapsed/refractory (R/R) classical Hodgkin lymphoma (cHL) and is now being tested as an adjunction to chemotherapy in the frontline settings. CHL exquisite sensitivity to PD-1/PD-L1 axis inhibition relies on a particular biological background. By contrast, non-Hodgkin lymphomas (NHL) have demonstrated heterogeneous response rates using ICI. These observations highlight discrepancies between various types of lymphomas in terms of genetic alterations, immune microenvironment interactions, and disease phenotype. This review aims to focus on cHL immune escape mechanisms, focusing on cHL biological sensitivity to PD-1 blockade. We will summarize the available data issued from clinical trials on ICI in cHL and its safety profile. Going beyond the current use of monoclonal antibodies (mAb) targeting immune checkpoints in clinical practice, we will offer an overview of new combinatory therapeutic perspectives where cHL immunotherapy may be considered.

scholarly journals A Novel Epitope Quality-Based Immune Escape Mechanism Reveals Patient’s Suitability for Immune Checkpoint Inhibition

2020 ◽  
Vol Volume 12 ◽  
pp. 7881-7890
Author(s):  
Michael Wessolly ◽  
Susann Stephan-Falkenau ◽  
Anna Streubel ◽  
Robert Werner ◽  
Sabrina Borchert ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Immune Escape ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition ◽  
Escape Mechanism ◽  
Immune Escape Mechanism

Immune Checkpoint Inhibitors in AML-A New Frontier

2020 ◽  
Vol 20 (7) ◽  
pp. 545-557
Author(s):  
Rohit Thummalapalli ◽  
Hanna A. Knaus ◽  
Ivana Gojo ◽  
Joshua F. Zeidner
Keyword(s):  
Immune Checkpoint ◽  
Checkpoint Inhibitors ◽  
Immune Dysfunction ◽  
Cytotoxic Chemotherapy ◽  
Immune Checkpoints ◽  
Clinical Activity ◽  
Cell Mediated Immunity ◽  
Hypomethylating Agents ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition

Despite recent therapeutic advancements, acute myeloid leukemia (AML) remains a challenging clinical entity with overall poor outcomes. Given the evident role of T cell-mediated immunity in response to allogeneic stem cell transplantation and donor lymphocyte infusions, strategies that enhance immune activation and mitigate immune dysfunction represent attractive therapeutic platforms to improve clinical outcomes in AML. Pre-clinical data suggest that immune dysfunction is a major contributor to AML progression and relapse. Increased expression of immune checkpoints such as programmed death 1 (PD-1) contributes to AML immune evasion and is associated with disease progression. Immune checkpoint inhibition is being explored in AML with early evidence of clinical activity, particularly in combination with cytotoxic chemotherapy and hypomethylating agents. In this review, we explore the scientific rationale behind the use of immune checkpoint inhibition either as single agents or in combination with hypomethylating agents or cytotoxic chemotherapy and provide a clinical update of both completed and ongoing trials in AML.

Delta-radiomics for prediction of pseudoprogression in malignant melanoma treated with immune checkpoint inhibition.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 9575-9575 ◽  
Author(s):  
Lucas Basler ◽  
Hubert Gabrys ◽  
Sabrina A. Hogan ◽  
Marta Bogowicz ◽  
Diem Vuong ◽  
...  
Keyword(s):  
Metastatic Melanoma ◽  
Immune Checkpoint ◽  
Prediction Models ◽  
Lung Metastases ◽  
Univariate Analysis ◽  
Response Rates ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition ◽  
Melanoma Patients

9575 Background: Distinguishing progressive disease (PD) from pseudoprogression (PP) in patients treated with immune-checkpoint inhibition (ICI) is challenging and usually requires confirmation follow-up imaging or invasive diagnostic techniques. This project aimed to identify predictive radiomic signatures for PP from CT imaging. Methods: The response to ICI of 105 metastatic melanoma patients with 645 metastases was retrospectively correlated with radiomic signatures (172 total features). All metastatic lesions were delineated at 3 time points: prior to ICI (t0), at 3 (t1) and 6 months (t2). Response was defined individually for each metastasis using RECIST 1.1, comparing baseline t0 to t2. Three prediction models for PP were built: CT radiomics at t0 and t1, as well as the relative difference between both t0 and t1 (delta-radiomics). Results: Median follow-up was 18 months and 2-year OS and PFS were 72% and 25%, respectively. Median OS: not reached, median PFS: 6 months. Response per lesion at t1: 13% complete remission (CR), 19% partial remission (PR), 52% stable disease (SD) and 16% PD. At t2: 16% CR, 31% PR, 38% SD and 15% PD. 106 progressive lesions were identified at t1, of which, 26 changed to SD, 1 to CR and 3 to PR at t2, resulting in 30 PPs (4.7%). Metastasis location significantly influenced response rates but was not associated with PP (p = 0.4). Lung metastases had significantly higher response rates than soft tissue (p < 0.001), liver (p < 0.001) and bone metastases (p = 0.008). Univariate analysis followed by removal of correlated features revealed no significant radiomic features associated with PP at t0. One independent feature was identified at t1 (AUC 0.74), while delta-radiomics was the best performing approach, identifying four independent features (AUC 0.72 to 0.81). A final multivariate delta radiomics logistic regression model was generated and internally validated, achieving an AUC of 0.81 (± 0.11, 10-fold cross-validation). Conclusions: Metastasis location significantly influenced response rates and CT-based delta-radiomics is a promising biomarker for early differentiation between pseudoprogression and true progression in metastatic melanoma patients treated with ICI.

scholarly journals Immune Checkpoints as Promising Targets for the Treatment of Idiopathic Pulmonary Fibrosis?

2019 ◽  
Vol 8 (10) ◽  
pp. 1547 ◽  
Author(s):  
JanWillem Duitman ◽  
Tom van den Ende ◽  
C. Arnold Spek
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Immune Checkpoint ◽  
Checkpoint Inhibitors ◽  
Immune Checkpoints ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition ◽  
General Role ◽  
Checkpoint Proteins ◽  
Immune Checkpoint Proteins

Idiopathic pulmonary fibrosis is a rare, progressive and fatal lung disease which affects approximately 5 million persons worldwide. Although pirfenidone and/or nintedanib treatment improves patients’ wellbeing, the prognosis of IPF remains poor with 5-year mortality rates still ranging from 70 to 80%. The promise of the anti-cancer agent nintedanib in IPF, in combination with the recent notion that IPF shares several pathogenic pathways with cancer, raised hope that immune checkpoint inhibitors, the novel revolutionary anticancer agents, could also be the eagerly awaited ground-breaking and unconventional novel treatment modality limiting IPF-related morbidity/mortality. In the current review, we analyse the available literature on immune checkpoint proteins in IPF to explore whether immune checkpoint inhibition may be as promising in IPF as it is in cancer. We conclude that despite several promising papers showing that inhibiting specific immune checkpoint proteins limits pulmonary fibrosis, overall the data seem to argue against a general role of immune checkpoint inhibition in IPF and suggest that only PD-1/PD-L1 inhibition may be beneficial.

scholarly journals DNA methylation-based prediction of response to immune checkpoint inhibition in metastatic melanoma

2021 ◽  
Vol 9 (7) ◽  
pp. e002226
Author(s):  
Katharina Filipski ◽  
Michael Scherer ◽  
Kim N. Zeiner ◽  
Andreas Bucher ◽  
Johannes Kleemann ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Metastatic Melanoma ◽  
Immune Checkpoint ◽  
Large Scale ◽  
Stage Iv ◽  
Immune Checkpoints ◽  
Term Therapy ◽  
Methylation Data ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition

BackgroundTherapies based on targeting immune checkpoints have revolutionized the treatment of metastatic melanoma in recent years. Still, biomarkers predicting long-term therapy responses are lacking.MethodsA novel approach of reference-free deconvolution of large-scale DNA methylation data enabled us to develop a machine learning classifier based on CpG sites, specific for latent methylation components (LMC), that allowed for patient allocation to prognostic clusters. DNA methylation data were processed using reference-free analyses (MeDeCom) and reference-based computational tumor deconvolution (MethylCIBERSORT, LUMP).ResultsWe provide evidence that DNA methylation signatures of tumor tissue from cutaneous metastases are predictive for therapy response to immune checkpoint inhibition in patients with stage IV metastatic melanoma.ConclusionsThese results demonstrate that LMC-based segregation of large-scale DNA methylation data is a promising tool for classifier development and treatment response estimation in cancer patients under targeted immunotherapy.

Short review of potential synergies of immune checkpoint inhibition and radiotherapy with a focus on Hodgkin lymphoma: radio-immunotherapy opens new doors

Immunotherapy ◽  
2017 ◽  
Vol 9 (5) ◽  
pp. 423-433 ◽  
Author(s):  
Christian Baues ◽  
Maike Trommer-Nestler ◽  
Karolina Jablonska ◽  
Paul J Bröckelmann ◽  
Max Schlaak ◽  
...  
Keyword(s):  
Hodgkin Lymphoma ◽  
Immune Checkpoint ◽  
Short Review ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition
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