scholarly journals Peripheral Cytokine Levels as Predictive Biomarkers of Benefit from Immune Checkpoint Inhibitors in Cancer Therapy

2020 ◽  
Author(s):  
Shoujian Ji ◽  
Huan Chen ◽  
Keyan Yang ◽  
Guanxiong Zhang ◽  
Beibei Mao ◽  
...  
Keyword(s):  
Cancer Therapy ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Cytokine Levels

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 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 Mechanism and potential predictive biomarkers of immune checkpoint inhibitors in NSCLC

2020 ◽  
Vol 127 ◽  
pp. 109996 ◽  
Author(s):  
Jialin Qu ◽  
Man Jiang ◽  
Li Wang ◽  
Deze Zhao ◽  
Kang Qin ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers

scholarly journals 120P Predictive biomarkers for hyper progression in response to immune checkpoint inhibitors therapy: Analysis of somatic alterations by NGS

2020 ◽  
Vol 31 ◽  
pp. S288
Author(s):  
I.R.R. Gonzalez Espinoza ◽  
N. Cortés Escobar ◽  
R. Ibarra Fernández ◽  
J.C. Garibay Díaz ◽  
S. Sánchez Sosa ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Somatic Alterations

scholarly journals Biomarkers for Predicting Response to Immunotherapy with Immune Checkpoint Inhibitors in Cancer Patients

2019 ◽  
Vol 65 (10) ◽  
pp. 1228-1238 ◽  
Author(s):  
Michael J Duffy ◽  
John Crown
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Future Research ◽  
Specific Gene ◽  
Tumor Type ◽  
Clinical Use ◽  
Durable Response ◽  
Cancer Types

Abstract BACKGROUND Immunotherapy, especially the use of immune checkpoint inhibitors, has revolutionized the management of several different cancer types in recent years. However, for most types of cancer, only a minority of patients experience a durable response. Furthermore, administration of immunotherapy can result in serious adverse reactions. Thus, for the most efficient and effective use of immunotherapy, accurate predictive biomarkers that have undergone analytical and clinical validation are necessary. CONTENT Among the most widely investigated predictive biomarkers for immunotherapy are programmed death-ligand 1 (PD-L1), microsatellite instability/defective mismatch repair (MSI/dMMR), and tumor mutational burden (TMB). MSI/dMMR is approved for clinical use irrespective of the tumor type, whereas PD-L1 is approved only for use in certain cancer types (e.g., for predicting response to first-line pembrolizumab monotherapy in non-small cell lung cancer). Although not yet approved for clinical use, TMB has been shown to predict response to several different forms of immunotherapy and across multiple cancer types. Less widely investigated predictive biomarkers for immunotherapy include tumor-infiltrating CD8+ lymphocytes and specific gene signatures. Despite being widely investigated, assays for MSI/dMMR, PD-L1, and TMB lack standardization and are still evolving. An urgent focus of future research should be the optimization and standardization of method for determining these biomarkers. SUMMARY Biomarkers for predicting response to immunotherapy are paving the way for personalized treatment for patients with diverse cancer types. However, standardization of the available biomarker assays is an urgent requirement.

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