Predictive biomarkers for PD-1 and PD-L1 immune checkpoint blockade therapy

Immunotherapy ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 515-529 ◽  
Author(s):  
Yue Song ◽  
Zhaoming Li ◽  
Weili Xue ◽  
Mingzhi Zhang
2020 ◽  
Vol 8 (2) ◽  
pp. e000374 ◽  
Author(s):  
Zhihao Lu ◽  
Huan Chen ◽  
Shuang Li ◽  
Jifang Gong ◽  
Jian Li ◽  
...  

BackgroundDespite the great achievements made in immune-checkpoint-blockade (ICB) in cancer therapy, there are no effective predictive biomarkers in gastrointestinal (GI) cancer.MethodsThis study included 93 metastatic GI patients treated with ICBs. The first cohort comprising 73 GI cancer patients were randomly assigned into discovery (n=44) and validation (n=29) cohorts. Comprehensive genomic profiling was performed on all samples to determine tumor mutational burden (TMB) and copy-number alterations (CNAs). A subset of samples was collected for RNA immune oncology (IO) panel sequencing, microsatellite instability (MSI)/mismatch repair and program death ligand 1 (PD-L1) expression evaluation. In addition, 20 gastric cancer (GC) patients were recruited as the second validation cohort.ResultsIn the first cohort of 73 GI cancer patients, a lower burden of CNA was observed in patients with durable clinical benefit (DCB). In both the discovery (n=44) and validation (n=29) subsets, lower burden of CNA was associated with an improved clinical benefit and better overall survival (OS). Efficacy also correlated with a higher TMB. Of note, a combinatorial biomarker of TMB and CNA may better stratify DCB patients from ICB treatment, which was further confirmed in the second validation cohort of 20 GC patients. Finally, patients with lower burden of CNA revealed increased immune signatures in our cohort and The Cancer Genome Atlas data sets as well.ConclusionsOur results suggest that the burden of CNA may have superior predictive value compared with other signatures, including PD-L1, MSI and TMB. The joint biomarker of CNA burden and TMB may better stratify DCB patients, thereby providing a rational choice for GI patients treated with ICBs.


2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e20512-e20512
Author(s):  
Paul R. Walker ◽  
Nitika Sharma ◽  
Chipman Robert Geoffrey Stroud ◽  
Mahvish Muzaffar ◽  
Cynthia R. Cherry ◽  
...  

e20512 Background: Veristrat (Biodesix, Boulder, CO) is a blood based proteomic assay that is dominated by inflammatory proteins and is prognostic and predictive in metastatic NSCLC after treatment with platinum based chemotherapy (Gregorc et al, Lancet 2014). Smoldering inflammation in the tumor microenvironment regulates and escalates cancer invasion, angiogenesis and immune surveillance escape (Balkwill and Mantovani, Lancet 2001). There is preclinical evidence to suggest that the tumor microenvironment can be altered with immunomodulatory interventions (Martino et al, 2016). While immune checkpoint blockade has shown durable benefit in metastatic NSCLC, the response rates still hover around 20%. As a result, identification of predictive biomarkers are of critical importance. The predictive value of the Veristrat assay with respect to ICB is poorly defined. Methods: At our institution, 83 pts with metastatic lung cancer pts were treated with nivolumab between 6/2015 to 12/2016. The following clinicopathologic characteristics were abstracted from medical records: tumor histology, Veristrat status, no. of doses of nivolumab, irAEs and overall survival. Results: Of the 83 pts, 65 pts were found to have NSCLC. Veristrat status was available for 17/65 of these pts. Nine pts were identified to have “Veristrat good” and seven pts were “Veristrat poor”. Median number of nivolumab doses was 4. Median survival for all patients was 30 weeks. Median survival was 20 weeks for “Veristrat poor” and 26 weeks for “Veristrat good”(p = 0.68). Grade 3-4 irAEs were noted in 5/9 patients with “Veristrat good” and 5/7 patients with “Veristrat poor”. Conclusions: “Veristrat poor” pts treated with ICB have a lower median survival as compared to “Veristrat good” pts. Our study did not meet statistically significant end point due to limited sample size. Further studies are needed to identify poorly immunogenic tumors and develop novel treatment approaches to optimize outcomes. [Table: see text]


2019 ◽  
Vol 6 (3) ◽  
pp. 232-246 ◽  
Author(s):  
Hongxing Shen ◽  
Eddy Shih-Hsin Yang ◽  
Marty Conry ◽  
John Fiveash ◽  
Carlo Contreras ◽  
...  

2018 ◽  
Vol Volume 10 ◽  
pp. 4501-4507 ◽  
Author(s):  
Mengting Tong ◽  
Jing Wang ◽  
Wenting He ◽  
Yanling Wang ◽  
Hongming Pan ◽  
...  

2020 ◽  
Vol 9 (1) ◽  
pp. 286 ◽  
Author(s):  
Qingyang Xiao ◽  
André Nobre ◽  
Pilar Piñeiro ◽  
Miguel-Ángel Berciano-Guerrero ◽  
Emilio Alba ◽  
...  

Checkpoint inhibitor therapy constitutes a promising cancer treatment strategy that targets the immune checkpoints to re-activate silenced T cell cytotoxicity. In recent pivotal trials, immune checkpoint blockade (ICB) demonstrated durable responses and acceptable toxicity, resulting in the regulatory approval of 8 checkpoint inhibitors to date for 15 cancer indications. However, up to ~85% of patients present with innate or acquired resistance to ICB, limiting its clinical utility. Current response biomarker candidates, including DNA mutation and neoantigen load, immune profiles, as well as programmed death-ligand 1 (PD-L1) expression, are only weak predictors of ICB response. Thus, identification of novel, more predictive biomarkers that could identify patients who would benefit from ICB constitutes one of the most important areas of immunotherapy research. Aberrant DNA methylation (5mC) and hydroxymethylation (5hmC) were discovered in multiple cancers, and dynamic changes of the epigenomic landscape have been identified during T cell differentiation and activation. While their role in cancer immunosuppression remains to be elucidated, recent evidence suggests that 5mC and 5hmC may serve as prognostic and predictive biomarkers of ICB-sensitive cancers. In this review, we describe the role of epigenetic phenomena in tumor immunoediting and other immune evasion related processes, provide a comprehensive update of the current status of ICB-response biomarkers, and highlight promising epigenomic biomarker candidates.


2021 ◽  
Author(s):  
Dean Lee ◽  
Ross Fulton ◽  
Monika Manne ◽  
Liang Schweizer ◽  
Andreas Raue

AbstractThe identification of predictive biomarkers for patient treatment response is urgently needed to increase the probability of success of existing and novel experimental therapies. Single-cell profiling has provided novel biological insights into drug responses in the tumor microenvironment, but its potential for biomarker discovery has not been fully explored for therapeutic purposes. We describe a novel approach to discover predictive response biomarkers from single-cell data from a small patient cohort using the T cell receptor sequence intrinsic to each T cell to match clonotypes between pre- and post-treatment tumor samples. As a result, we have identified a predictive gene expression signature for immune checkpoint blockade and validated its predictive performance using data from three larger clinical studies. Our results demonstrated that applying clonotyping with single-cell genomic profiling is a promising novel approach for biomarker identification that does not require data collected from large patient cohorts. This could increase success rates, reduce clinical trial size, and significantly impact future clinical developments of immunomodulatory therapeutics.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Katrin Aslan ◽  
Verena Turco ◽  
Jens Blobner ◽  
Jana K. Sonner ◽  
Anna Rita Liuzzi ◽  
...  

Abstract Intrinsic malignant brain tumors, such as glioblastomas are frequently resistant to immune checkpoint blockade (ICB) with few hypermutated glioblastomas showing response. Modeling patient-individual resistance is challenging due to the lack of predictive biomarkers and limited accessibility of tissue for serial biopsies. Here, we investigate resistance mechanisms to anti-PD-1 and anti-CTLA-4 therapy in syngeneic hypermutated experimental gliomas and show a clear dichotomy and acquired immune heterogeneity in ICB-responder and non-responder tumors. We made use of this dichotomy to establish a radiomic signature predicting tumor regression after pseudoprogression induced by ICB therapy based on serial magnetic resonance imaging. We provide evidence that macrophage-driven ICB resistance is established by CD4 T cell suppression and Treg expansion in the tumor microenvironment via the PD-L1/PD-1/CD80 axis. These findings uncover an unexpected heterogeneity of response to ICB in strictly syngeneic tumors and provide a rationale for targeting PD-L1-expressing tumor-associated macrophages to overcome resistance to ICB.


2021 ◽  
Vol 11 ◽  
Author(s):  
Yanna Lei ◽  
Xiaoying Li ◽  
Qian Huang ◽  
Xiufeng Zheng ◽  
Ming Liu

Over the past decade, immune checkpoint blockade (ICB) therapy has revolutionized the outlook for oncology with significant and sustained improvement in the overall patient survival. Unlike traditional cancer therapies, which target the cancer cells directly, ICB acts on the immune system to enhance anti-tumoral immunity. However, the response rate is still far from satisfactory and most patients are refractory to such treatment. Unfortunately, the mechanisms underlying such heterogeneous responses between patients to ICB therapy remain unclear. In addition, escalating costs of cancer care and unnecessary immune-related adverse events also are pertinent considerations with applications of ICB. Given these issues, identifying explicit predictive biomarkers for patient selection is an urgent unmet need to increase the efficacy of ICB therapy. The markers can be classified as tumor related and non-tumor-related biomarkers. Although substantial efforts have been put into investigating various biomarkers, none of them has been found to be sufficient for effectively stratifying patients who may benefit from immunotherapy. The present write up is an attempt to review the various emerging clinically relevant biomarkers affecting the efficacy of immune checkpoint inhibitors, as well as the limitations associated with their clinical application.


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