scholarly journals FDA-Approved and Emerging Next Generation Predictive Biomarkers for Immune Checkpoint Inhibitors in Cancer Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Ye Wang ◽  
Zhuang Tong ◽  
Wenhua Zhang ◽  
Weizhen Zhang ◽  
Anton Buzdin ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Predictive Performance ◽  
Gene Signature ◽  
Contributing Factors ◽  
Extrinsic Factors

A patient’s response to immune checkpoint inhibitors (ICIs) is a complex quantitative trait, and determined by multiple intrinsic and extrinsic factors. Three currently FDA-approved predictive biomarkers (progra1mmed cell death ligand-1 (PD-L1); microsatellite instability (MSI); tumor mutational burden (TMB)) are routinely used for patient selection for ICI response in clinical practice. Although clinical utility of these biomarkers has been demonstrated in ample clinical trials, many variables involved in using these biomarkers have poised serious challenges in daily practice. Furthermore, the predicted responders by these three biomarkers only have a small percentage of overlap, suggesting that each biomarker captures different contributing factors to ICI response. Optimized use of currently FDA-approved biomarkers and development of a new generation of predictive biomarkers are urgently needed. In this review, we will first discuss three widely used FDA-approved predictive biomarkers and their optimal use. Secondly, we will review four novel gene signature biomarkers: T-cell inflamed gene expression profile (GEP), T-cell dysfunction and exclusion gene signature (TIDE), melanocytic plasticity signature (MPS) and B-cell focused gene signature. The GEP and TIDE have shown better predictive performance than PD-L1, and PD-L1 or TMB, respectively. The MPS is superior to PD-L1, TMB, and TIDE. The B-cell focused gene signature represents a previously unexplored predictive biomarker to ICI response. Thirdly, we will highlight two combined predictive biomarkers: TMB+GEP and MPS+TIDE. These integrated biomarkers showed improved predictive outcomes compared to a single predictor. Finally, we will present a potential nucleic acid biomarker signature, allowing DNA and RNA biomarkers to be analyzed in one assay. This comprehensive signature could represent a future direction of developing robust predictive biomarkers, particularly for the cold tumors, for ICI response.

scholarly journals Current Clinical Applications and Future Perspectives of Immune Checkpoint Inhibitors in Non-Hodgkin Lymphoma

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
John Apostolidis ◽  
Ayman Sayyed ◽  
Mohammed Darweesh ◽  
Panayotis Kaloyannidis ◽  
Hani Al Hashmi
Keyword(s):  
Clinical Trials ◽  
T Cells ◽  
Cell Death ◽  
T Cell ◽  
Programmed Cell Death ◽  
B Cell ◽  
Cancer Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors

Cancer cells escape immune recognition by exploiting the programmed cell-death protein 1 (PD-1)/programmed cell-death 1 ligand 1 (PD-L1) immune checkpoint axis. Immune checkpoint inhibitors that target PD-1/PD-L1 unleash the properties of effector T cells that are licensed to kill cancer cells. Immune checkpoint blockade has dramatically changed the treatment landscape of many cancers. Following the cancer paradigm, preliminary results of clinical trials in lymphoma have demonstrated that immune checkpoint inhibitors induce remarkable responses in specific subtypes, most notably classical Hodgkin lymphoma and primary mediastinal B-cell lymphoma, while in other subtypes, the results vary considerably, from promising to disappointing. Lymphomas that respond to immune checkpoint inhibitors tend to exhibit tumor cells that reside in a T-cell-rich immune microenvironment and display constitutive transcriptional upregulation of genes that facilitate innate immune resistance, such as structural variations of the PD-L1 locus, collectively referred to as T-cell-inflamed lymphomas, while those lacking such characteristics are referred to as noninflamed lymphomas. This distinction is not necessarily a sine qua non of response to immune checkpoint inhibitors, but rather a framework to move the field forward with a more rational approach. In this article, we provide insights on our current understanding of the biological mechanisms of immune checkpoint evasion in specific subtypes of B-cell and T-cell non-Hodgkin lymphomas and summarize the clinical experience of using inhibitors that target immune checkpoints in these subtypes. We also discuss the phenomenon of hyperprogression in T-cell lymphomas, related to the use of such inhibitors when T cells themselves are the target cells, and consider future approaches to refine clinical trials with immune checkpoint inhibitors in non-Hodgkin lymphomas.

scholarly journals How to Best Exploit Immunotherapeutics in Advanced Gastric Cancer: Between Biomarkers and Novel Cell-Based Approaches

2021 ◽  
Vol 10 (7) ◽  
pp. 1412
Author(s):  
Michele Ghidini ◽  
Angelica Petrillo ◽  
Andrea Botticelli ◽  
Dario Trapani ◽  
Alessandro Parisi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Advanced Gastric Cancer ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitor ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Clinical Implementation ◽  
T Cell Therapy ◽  
Dismal Prognosis

Despite extensive research efforts, advanced gastric cancer still has a dismal prognosis with conventional treatment options. Immune checkpoint inhibitors have revolutionized the treatment landscape for many solid tumors. Amongst gastric cancer subtypes, tumors with microsatellite instability and Epstein Barr Virus positive tumors provide the strongest rationale for responding to immunotherapy. Various predictive biomarkers such as mismatch repair status, programmed death ligand 1 expression, tumor mutational burden, assessment of tumor infiltrating lymphocytes and circulating biomarkers have been evaluated. However, results have been inconsistent due to different methodologies and thresholds used. Clinical implementation therefore remains a challenge. The role of immune checkpoint inhibitors in gastric cancer is emerging with data from monotherapy in the heavily pre-treated population already available and studies in earlier disease settings with different combinatorial approaches in progress. Immune checkpoint inhibitor combinations with chemotherapy (CT), anti-angiogenics, tyrosine kinase inhibitors, anti-Her2 directed therapy, poly (ADP-ribose) polymerase inhibitors or dual checkpoint inhibitor strategies are being explored. Moreover, novel strategies including vaccines and CAR T cell therapy are also being trialed. Here we provide an update on predictive biomarkers for response to immunotherapy with an overview of their strengths and limitations. We discuss clinical trials that have been reported and trials in progress whilst providing an account of future steps needed to improve outcome in this lethal disease.

scholarly journals Rethinking immune checkpoint blockade: ‘Beyond the T cell’

2021 ◽  
Vol 9 (1) ◽  
pp. e001460 ◽  
Author(s):  
Xiuting Liu ◽  
Graham D Hogg ◽  
David G DeNardo
Keyword(s):  
Immune System ◽  
T Cell ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Antitumor Immunity ◽  
Checkpoint Inhibitors ◽  
Clinical Success ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade

The clinical success of immune checkpoint inhibitors has highlighted the central role of the immune system in cancer control. Immune checkpoint inhibitors can reinvigorate anti-cancer immunity and are now the standard of care in a number of malignancies. However, research on immune checkpoint blockade has largely been framed with the central dogma that checkpoint therapies intrinsically target the T cell, triggering the tumoricidal potential of the adaptive immune system. Although T cells undoubtedly remain a critical piece of the story, mounting evidence, reviewed herein, indicates that much of the efficacy of checkpoint therapies may be attributable to the innate immune system. Emerging research suggests that T cell-directed checkpoint antibodies such as anti-programmed cell death protein-1 (PD-1) or programmed death-ligand-1 (PD-L1) can impact innate immunity by both direct and indirect pathways, which may ultimately shape clinical efficacy. However, the mechanisms and impacts of these activities have yet to be fully elucidated, and checkpoint therapies have potentially beneficial and detrimental effects on innate antitumor immunity. Further research into the role of innate subsets during checkpoint blockade may be critical for developing combination therapies to help overcome checkpoint resistance. The potential of checkpoint therapies to amplify innate antitumor immunity represents a promising new field that can be translated into innovative immunotherapies for patients fighting refractory malignancies.

scholarly journals New drug developments in metastatic gastric cancer

2018 ◽  
Vol 11 ◽  
pp. 175628481880807 ◽  
Author(s):  
Aaron C. Tan ◽  
David L. Chan ◽  
Wasek Faisal ◽  
Nick Pavlakis
Keyword(s):  
Gastric Cancer ◽  
Clinical Trials ◽  
Targeted Therapies ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Treatment Options ◽  
Predictive Biomarkers ◽  
Metastatic Gastric Cancer ◽  
New Era

Metastatic gastric cancer is associated with a poor prognosis and novel treatment options are desperately needed. The development of targeted therapies heralded a new era for the management of metastatic gastric cancer, however results from clinical trials of numerous targeted agents have been mixed. The advent of immune checkpoint inhibitors has yielded similar promise and results from early trials are encouraging. This review provides an overview of the systemic treatment options evaluated in metastatic gastric cancer, with a focus on recent evidence from clinical trials for targeted therapies and immune checkpoint inhibitors. The failure to identify appropriate predictive biomarkers has hampered the success of many targeted therapies in gastric cancer, and a deeper understanding of specific molecular subtypes and genomic alterations may allow for more precision in the application of novel therapies. Identifying appropriate biomarkers for patient selection is essential for future clinical trials, for the most effective use of novel agents and in combination approaches to account for growing complexity of treatment options.

scholarly journals Development and validation of blood-based predictive biomarkers for response to PD-(L)-1 checkpoint inhibitors: evidence of a universal systemic core of 3D immunogenetic profiling across multiple oncological indications.

2021 ◽  
Author(s):  
Ewan Hunter ◽  
Mehrnoush Dizfouli ◽  
Christina Koutsothanasi ◽  
Adam Wilson ◽  
Francisco Coroado Santos ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Checkpoint Inhibition ◽  
Brain Lymphoma ◽  
3D Genome ◽  
Clinical Assay ◽  
Genomic Approach ◽  
Development And Validation

Unprecedented advantages in cancer treatment with immune checkpoint inhibitors (ICI) remain limited to a subset of patients. Systemic analyses of the regulatory 3D genome architecture linked to individual epigenetics and immunogenetic controls associated with tumour immune evasion mechanisms and immune checkpoint pathways reveals a highly prevalent patient molecular profiles predictive of response to PD-(L)1 immune checkpoint inhibitors. A clinical blood test based on the set of 8 3D genomic biomarkers has been developed and validated on several independent cancer patient cohorts to predict response to PD-(L)1 immune checkpoint inhibition. The predictive 8 biomarker set is derived from prospective observational clinical trials, representing 229 treatments with Pembrolizumab, Atezolizumab, Durvalumab, in diverse indications: melanoma, non-small cell lung, urethral, hepatocellular, bladder, prostate cancer, head and neck, vulvar, colon, breast, bone, brain, lymphoma, larynx cancer, and cervix cancers. The 3D genomic 8 biomarker panel for response to immune checkpoint therapy achieved high accuracy up to 85%, sensitivity of 93% and specificity of 82%. This study demonstrates that a 3D genomic approach could be used to develop a predictive clinical assay for response to PD-(L)1 checkpoint inhibition in cancer patients.

scholarly journals Risk Signature Related to Immunotherapy Reaction of Hepatocellular Carcinoma Based on the Immune-Related Genes Associated With CD8+ T Cell Infiltration

2021 ◽  
Vol 8 ◽  
Author(s):  
Yiping Zou ◽  
Zhihong Chen ◽  
Hongwei Han ◽  
Shiye Ruan ◽  
Liang Jin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cell ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Response Rate ◽  
Risk Group ◽  
Checkpoint Inhibitors ◽  
Cell Infiltration ◽  
T Cell Infiltration ◽  
Immune Related Genes

Background: Hepatocellular carcinoma (HCC) is the most common histological type of liver cancer, with an unsatisfactory long-term survival rate. Despite immune checkpoint inhibitors for HCC have got glories in recent clinical trials, the relatively low response rate is still a thorny problem. Therefore, there is an urgent need to screen biomarkers of HCC to predict the prognosis and efficacy of immunotherapy.Methods: Gene expression profiles of HCC were retrieved from TCGA, GEO, and ICGC databases while the immune-related genes (IRGs) were retrieved from the ImmPort database. CIBERSORT and WGCNA algorithms were combined to identify the gene module most related to CD8+ T cells in the GEO cohort. Subsequently, the genes in hub modules were subjected to univariate, LASSO, and multivariate Cox regression analyses in the TCGA cohort to develop a risk signature. Afterward, the accuracy of the risk signature was validated by the ICGC cohort, and its relationships with CD8+ T cell infiltration and PDL1 expression were explored.Results: Nine IRGs were finally incorporated into a risk signature. Patients in the high-risk group had a poorer prognosis than those in the low-risk group. Confirmed by TCGA and ICGC cohorts, the risk signature possessed a relatively high accuracy. Additionally, the risk signature was demonstrated as an independent prognostic factor and closely related to the CD8+ T cell infiltration and PDL1 expression.Conclusion: A risk signature was constructed to predict the prognosis of HCC patients and detect patients who may have a higher positive response rate to immune checkpoint inhibitors.

Circulating T-Cell Biomarkers to Predict Response to Immune Checkpoint Inhibitors

2018 ◽  
Vol 227 (4) ◽  
pp. e56
Author(s):  
Takayoshi Yamauchi ◽  
Toshifumi Hoki ◽  
Hongbin Chen ◽  
Saby George ◽  
Grace Dy ◽  
...  
Keyword(s):  
T Cell ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors
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