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 ◽  
...  

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.

2021 ◽  
Vol 22 (6) ◽  
pp. 3228
Author(s):  
Alexander C. Chacon ◽  
Alexa D. Melucci ◽  
Shuyang S. Qin ◽  
Peter A. Prieto

Metastatic melanoma remains the deadliest form of skin cancer. Immune checkpoint inhibition (ICI) immunotherapy has defined a new age in melanoma treatment, but responses remain inconsistent and some patients develop treatment resistance. The myriad of newly developed small molecular (SM) inhibitors of specific effector targets now affords a plethora of opportunities to increase therapeutic responses, even in resistant melanoma. In this review, we will discuss the multitude of SM classes currently under investigation, current and prospective clinical combinations of ICI and SM therapies, and their potential for synergism in melanoma eradication based on established mechanisms of immunotherapy resistance.


2020 ◽  
Vol 9 (1) ◽  
pp. 1738814
Author(s):  
Wouter W. van Willigen ◽  
Martine Bloemendal ◽  
Marye J. Boers-Sonderen ◽  
Jan Willem B. de Groot ◽  
Rutger H.T. Koornstra ◽  
...  

2016 ◽  
Vol 136 (9) ◽  
pp. S244
Author(s):  
J.C. Hassel ◽  
M. Flossdorf ◽  
S. Hänzelmann ◽  
J. Winkler ◽  
L. Appel ◽  
...  

2020 ◽  
Vol 20 (7) ◽  
pp. 545-557
Author(s):  
Rohit Thummalapalli ◽  
Hanna A. Knaus ◽  
Ivana Gojo ◽  
Joshua F. Zeidner

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.


2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 9575-9575 ◽  
Author(s):  
Lucas Basler ◽  
Hubert Gabrys ◽  
Sabrina A. Hogan ◽  
Marta Bogowicz ◽  
Diem Vuong ◽  
...  

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.


JAMA Oncology ◽  
2018 ◽  
Vol 4 (1) ◽  
pp. 126 ◽  
Author(s):  
Andrew J. Sinnamon ◽  
Madalyn G. Neuwirth ◽  
Phyllis A. Gimotty ◽  
Tara C. Gangadhar ◽  
Ravi K. Amaravadi ◽  
...  

2019 ◽  
Vol 8 (10) ◽  
pp. 1547 ◽  
Author(s):  
JanWillem Duitman ◽  
Tom van den Ende ◽  
C. Arnold Spek

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.


Sign in / Sign up

Export Citation Format

Share Document