PD-L1 expression as a predictive biomarker for immune checkpoint inhibitors: between a dream and a nightmare

Immunotherapy ◽  
2021 ◽  
Author(s):  
Joseph Zouein ◽  
Carole Kesrouani ◽  
Hampig Raphael Kourie
Keyword(s):  
Cell Surface ◽  
Tumor Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarker ◽  
Potential Biomarker ◽  
Companion Diagnostic ◽  
Score Reporting

PD-L1 is an important predictive biomarker for treatment by immune checkpoint inhibitors (ICIs). ICIs are now indicated for the treatment of various cancer depending on the level of expression of PD-L1 on tumor cells. PD-L1 testing is done using immunohistochemistry with five different assays approved as companion diagnostic for ICIs. However, these assays have different score reporting methods and do not accurately measure PD-L1 expression. Exosomal PD-L1 testing has recently emerged as an alternative for cell-surface PD-L1 testing however studies are still premature and more extensive knowledge about this new potential biomarker is needed.

IMMU-06. COMBINATORIAL IMMUNE CHECKPOINT INHIBITORS FOR TARGETED INTRATUMORAL DELIVERY IN GBM

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi93-vi93
Author(s):  
Stephanie Sanders ◽  
Denise Herpai ◽  
Waldemar Debinski
Keyword(s):  
T Cells ◽  
Tumor Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Cell Activity ◽  
Live Cells ◽  
Normal Brain ◽  
Cytotoxic Therapies ◽  
Checkpoint Receptors

Abstract Glioblastoma (GBM) is an immunologically cold tumor. Using single cell sequencing of CD45+ cells we confirmed that T cells are present within GBM samples. These T cells are positive for exhaustion markers such as LAG3 and TIGIT, as well as CTLA4 and PD1 checkpoint receptors. Modulating T cell activity through use of immune checkpoint inhibitors (ICIs) has shown efficacy in the treatment of a variety of solid tumors, and the combination of anti-CTLA4 and anti-PD1 ICIs has shown increased efficacy over use of a single therapeutic. Additionally, targeting ICIs to the tumor cells may increase efficacy of this treatment. We therefore constructed a combinatorial ICI redirected to GBM via interleukin 13 receptor alpha 2 (IL13RA2), a receptor over-expressed on the majority of GBM cells but not normal brain. The first component of the construct, labeled with a histidine tag, targets CTLA4 while the second component, tagged with a StrepII tag, targets PD1. The tags added to the constructs will allow for purification of a combinatorial heterodimer simultaneously targeting PD1, CTLA4 and IL13RA2. We purified individual components via fast protein liquid chromatography (FPLC) using a proteinG column followed by a HisTrap or StrepTrap column. We obtained a recombinant, targeted multivalent ICI at > 95% purity. We found that these constructs are able to bind their target receptors via ELISA in which the Kd values ranged from picomolar to low nanomolar range. Additionally, our constructs bind their target on live cells by flow cytometry. We next designed a heterodimeric construct which can combinatorially target CTLA4 and PD1 while also directing the ICI therapy to GBM. These constructs in conjunction with other immune stimulants like cytotoxic therapies are intended to facilitate the interaction between T cells and GBM tumor cells directly in a tumor microenvironment.

PD-L1 expression of high grade glial tumors at diagnosis and change of expression status at recurrence.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 2035-2035 ◽  
Author(s):  
Basak Oyan ◽  
Seyma Eren ◽  
Ozlem Sonmez ◽  
Ferda Ozkan ◽  
Kaan Yaltırak ◽  
...  
Keyword(s):  
Tumor Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
High Grade ◽  
Cross Sectional ◽  
Glial Tumors ◽  
The Impact ◽  
Expression Status ◽  
Over Time

2035 Background: PD-L1 expression status is the main predictive factor for response to immune checkpoint inhibitors. PD-L1 status may change over time with the impact of therapies. The aim of this study is to determine if PD-L1 expression status changes in recurrent gliomas after chemoradiotherapy. Methods: Thirty eight patients with recurrent high grade gliomas who had surgical excision at least two times were included in this retrospective cross-sectional study. Nine patients were excluded because of the lack of appropriate pathology slides for pathologic evaluation. PD-L1 expression of 29 patients was evaluated by an expert pathologist with immunohistochemical methods. PD-L1 positivity was defined as expression in ≥1% of tumor cells. Change in PD-L1 expression status was defined as an absolute 5% difference between two resections. Results: Of the 29 patients, 15 patients (51.7%) had PD-L1 expression in ≥1% of tumor cells and 7 patients (24.1%) had PD-L1 expression in ≥10% of tumor cells. Tumor PD-L1 expression (defined as expression in ≥1% of tumor cells) was positive in 15 (51.7%) of 29 patients at diagnosis and at the time of recurrence. The PD-L1 status did not change in 17 patients (58.6%). 8 patients had PD-L1 negative tumors both at diagnosis and at recurrence, while 9 patients had PD-L1 positive tumors both at diagnosis and at recurrence. In 6 patients (20.7%) a negative-to-positive switch and in 6 patients (20.7%) a positive to negative switch were seen. Tumor PD-L1 expression increased in 7 of 29 patients (24.1%) and decreased in 9 of 29 patients (31.1%). PD-L1 expression remained stable in 13 of 29 patients (34.4%). The change in PD-L1 status over time was not statistically significant. Conclusions: More than 50% of high grade glial tumors express PD-L1 at diagnosis, so these tumors are good candidates for immune checkpoint inhibitors. The expression status changes in more than 40% of high grade glial tumors at recurrence, so immune responsiveness of glial tumors can be modified by treatments like chemotherapy and radiotherapy.

scholarly journals Eosinophil Count as Predictive Biomarker of Immune-Related Adverse Events (irAEs) in Immune Checkpoint Inhibitors (ICIs) Therapies in Oncological Patients

Immuno ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 253-263
Author(s):  
Elisa Giommoni ◽  
Roberta Giorgione ◽  
Agnese Paderi ◽  
Elisa Pellegrini ◽  
Elisabetta Gambale ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Adverse Events ◽  
Immune Checkpoint ◽  
Eosinophil Count ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Objective Response ◽  
Predictive Biomarker ◽  
Response To Treatment ◽  
Analysis Model

Background: To date, no biomarkers are effective in predicting the risk of developing immune-related adverse events (irAEs) in patients treated with immune checkpoint inhibitors (ICIs). This study aims to evaluate the association between basal absolute eosinophil count (AEC) and irAEs during treatment with ICIs for solid tumors. Methods: We retrospectively evaluated 168 patients with metastatic melanoma (mM), renal cell carcinoma (mRCC), and non-small cell lung cancer (mNSCLC) receiving ICIs at our medical oncology unit. By combining baseline AEC with other clinical factors, we developed a mathematical model for predicting the risk of irAEs, which we validated in an external cohort of patients. Results: Median baseline AEC was 135/µL and patients were stratified into two groups accordingly; patients with high baseline AEC (>135/µL) were more likely to experience toxicity (p = 0.043) and have a better objective response rate (ORR) (p = 0.003). By constructing a covariance analysis model, it emerged that basal AEC correlated with the risk of irAEs (p < 0.01). Finally, we validated the proposed model in an independent cohort of 43 patients. Conclusions: Baseline AEC could be a predictive biomarker of ICI-related toxicity, as well as of response to treatment. The use of a mathematical model able to predict the risk of developing irAEs could be useful for clinicians for monitoring patients receiving ICIs.

scholarly journals Clinical Development of Immune Checkpoint Inhibitors

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Ayumu Ito ◽  
Shunsuke Kondo ◽  
Kohei Tada ◽  
Shigehisa Kitano
Keyword(s):  
Clinical Trials ◽  
T Cells ◽  
Metastatic Melanoma ◽  
Tumor Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Clinical Development ◽  
Phase Iii ◽  
Immune Checkpoint Molecules

Recent progress in cancer immunotherapy has been remarkable. Most striking are the clinical development and approval of immunomodulators, also known as immune checkpoint inhibitors. These monoclonal antibodies (mAb) are directed to immune checkpoint molecules, which are expressed on immune cells and mediate signals to attenuate excessive immune reactions. Although mAbs targeting tumor associated antigens, such as anti-CD20 mAb and anti-Her2 mAb, directly recognize tumor cells and induce cell death, immune checkpoint inhibitors restore and augment the antitumor immune activities of cytotoxic T cells by blocking immune checkpoint molecules on T cells or their ligands on antigen presenting and tumor cells. Based on preclinical data, many clinical trials have demonstrated the acceptable safety profiles and efficacies of immune checkpoint inhibitors in a variety of cancers. The first in class approved immune checkpoint inhibitor is ipilimumab, an anti-CTLA-4 (cytotoxic T lymphocyte antigen-4) mAb. Two pivotal phase III randomized controlled trials demonstrated a survival benefit in patients with metastatic melanoma. In 2011, the US Food and Drug Administration (FDA) approved ipilimumab for metastatic melanoma. Several clinical trials have since investigated new agents, alone and in combination, for various cancers. In this review, we discuss the current development status of and future challenges in utilizing immune checkpoint inhibitors.

scholarly journals LAG-3 expression in the inflammatory microenvironment of glioma

2021 ◽  
Vol 152 (3) ◽  
pp. 533-539
Author(s):  
Maximilian J. Mair ◽  
Barbara Kiesel ◽  
Katharina Feldmann ◽  
Georg Widhalm ◽  
Karin Dieckmann ◽  
...  
Keyword(s):  
Tumor Cells ◽  
Immune Checkpoint ◽  
Dna Methyltransferase ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Lymphocyte Activation ◽  
Diffuse Glioma ◽  
Who Grade ◽  
Inflammatory Microenvironment ◽  
Grade Ii

Abstract Purpose Immune modulatory therapies including immune checkpoint inhibitors have so far failed to result in clinically meaningful efficacy in glioma. We aimed to investigate lymphocyte activation gene 3 (LAG-3), an inhibitory receptor on immune cells and target of second-generation immune checkpoint inhibitors, in glioma. Methods 97 patients with diffuse glioma (68 with glioblastoma, 29 with WHO grade II-III glioma) were identified from the Neuro-Biobank of the Medical University of Vienna. LAG-3 expression in the inflammatory microenvironment was assessed by immunohistochemistry (monoclonal anti-LAG-3 antibody, clone 17B4) and correlated to CD3+ , CD8+ , CD20+ and PD-1+ tumor-infiltrating lymphocytes (TILs) and PD-L1 expression on tumor cells. Results LAG-3+ TILs could be observed in 10/97 (10.3%) IDH-wildtype samples and in none of the included IDH-mutant glioma samples (p = 0.057). Further, LAG-3+ TILs were only observed in WHO grade IV glioblastoma, while none of the investigated WHO grade II–III glioma presented with LAG-3+ TILs (p = 0.03). No association of O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation and presence of LAG-3+ TILs was observed (p = 0.726). LAG-3 expression was associated with the presence of CD3+ (p = 0.029), CD8+ (p = 0.001), PD-1+ (p < 0.001) TILs and PD-L1+ tumor cells (p = 0.021), respectively. No association of overall survival with LAG-3+ TIL infiltration was evident (median OS 9.9 vs. 14.2 months, p = 0.95). Conclusions LAG-3 is only rarely expressed on TILs in IDH-wildtype glioma and associated with active inflammatory milieu as defined by higher TIL density. Immune microenvironment diversity should be considered in the design of future immunotherapy trials in glioma.

scholarly journals Crosstalk Between the Tumor Microenvironment and Cancer Cells: A Promising Predictive Biomarker for Immune Checkpoint Inhibitors

2021 ◽  
Vol 9 ◽  
Author(s):  
Xiaoying Li ◽  
Yueyao Yang ◽  
Qian Huang ◽  
Yu Deng ◽  
Fukun Guo ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Cancer Cells ◽  
Immune Cells ◽  
Immune Checkpoint ◽  
Small Proportion ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarker ◽  
Cell Populations ◽  
Functional Interaction

Immune checkpoint inhibitors (ICIs) have changed the landscape of cancer treatment and are emerging as promising curative treatments in different type of cancers. However, only a small proportion of patients have benefited from ICIs and there is an urgent need to find robust biomarkers for individualized immunotherapy and to explore the causes of immunotherapy resistance. In this article, we review the roles of immune cells in the tumor microenvironment (TME) and discuss the effects of ICIs on these cell populations. We discuss the potential of the functional interaction between the TME and cancer cells as a predictive biomarker for ICIs. Furthermore, we outline the potential personalized strategies to improve the effectiveness of ICIs with precision.

scholarly journals Predictive Biomarkers of Immune Checkpoint Inhibitor Response in Breast Cancer: Looking beyond Tumoral PD-L1

Biomedicines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1863
Author(s):  
Nan Chen ◽  
Nicole Higashiyama ◽  
Valentina Hoyos
Keyword(s):  
Breast Cancer ◽  
Tumor Cells ◽  
Immune Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Large Scale ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Cytotoxic T Cells ◽  
Predictive Biomarkers

Immune checkpoint inhibitors utilize the immune system to kill cancer cells and are now widely applied across numerous malignancies. Pembrolizumab has two breast-specific indications in triple-negative disease. Currently, programmed death ligand-1 (PD-L1) expression on tumor and surrounding immune cells is the only validated predictive biomarker for immune checkpoint inhibitors (ICIs) in breast cancer; however, it can be imprecise. Additional biomarkers are needed to identify the patient population who will derive the most benefit from these therapies. The tumor immune microenvironment contains many biomarker candidates. In tumor cells, tumor mutational burden has emerged as a robust biomarker across malignancies in general, with higher burden cancers demonstrating improved response, but will need further refinement for less mutated cancers. Preliminary studies suggest that mutations in breast cancer gene 2 (BRCA-2) are associated with increased immune infiltration and response to ICI therapy. Other genomic alterations are also being investigated as potential predictive biomarkers. In immune cells, increased quantity of tumor-infiltrating lymphocytes and CD8+ cytotoxic T cells have correlated with response to immunotherapy treatment. The role of other immune cell phenotypes is being investigated. Peripherally, many liquid-based biomarker strategies such as PD-L1 expression on circulating tumor cells and peripheral immune cell quantification are being studied; however, these strategies require further standardization and refinement prior to large-scale testing. Ultimately, multiple biomarkers utilized together may be needed to best identify the appropriate patients for these treatments.

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