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Updated: Jan 20, 2026

Exosomal miRNA Analysis in Non-small Cell Lung Cancer NSCLC Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool
Published on: May 27, 2016
Plasma Biomarkers and Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer: New Tools for Better Patient
Adrien Costantini1,2, Paul Takam Kamga2, Coraline Dumenil1,2
1Department of Respiratory Diseases and Thoracic Oncology, APHP-Hôpital Ambroise Paré, 92100 Boulogne-Billancourt, France.
Abstract:
Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape for patients with non-small cell lung cancer (NSCLC). Although some patients can experience important response rates and improved survival, many others do not benefit from ICIs developing hyper-progressive disease or immune-related adverse events. This underlines the need to select biomarkers for ICIs use in order to better select patients. There is currently no universally validated robust biomarker for daily use of ICIs. Programmed death-ligand 1 (PD-L1) or tumor mutational burden (TMB) are sometimes used but still have several limitations. Plasma biomarkers are a promising approach in ICI treatment. This review will describe the development of novel plasma biomarkers such as soluble proteins, circulating tumor DNA (ctDNA), blood TMB, and blood microbiome in NSCLC patients treated with ICIs and their potential use in predicting response and toxicity.
Insights
Novel plasma biomarkers show promise for predicting response and toxicity in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). This could improve patient selection and treatment outcomes for NSCLC.
Area of Science:
- Oncology
- Immunotherapy
- Biomarker Discovery
Background:
- Immune checkpoint inhibitors (ICIs) have revolutionized non-small cell lung cancer (NSCLC) treatment, but patient response varies significantly.
- Many NSCLC patients do not benefit from ICIs, experiencing hyper-progressive disease or immune-related adverse events.
- Current biomarkers like PD-L1 and tumor mutational burden (TMB) have limitations for predicting ICI efficacy.
Purpose of the Study:
- To review the development and potential of novel plasma biomarkers for predicting response and toxicity in NSCLC patients undergoing ICI therapy.
- To highlight the limitations of existing biomarkers and the promise of blood-based markers.
- To discuss emerging plasma biomarkers including soluble proteins, ctDNA, blood TMB, and blood microbiome.
Main Methods:
- Literature review of studies on plasma biomarkers in NSCLC patients treated with ICIs.
- Analysis of the development and validation of novel plasma biomarkers.
- Discussion of the predictive and prognostic value of these biomarkers.
Main Results:
- Existing biomarkers (PD-L1, TMB) have limitations in predicting ICI response in NSCLC.
- Plasma biomarkers, including soluble proteins, ctDNA, blood TMB, and blood microbiome, are emerging as promising tools.
- These novel biomarkers may offer improved prediction of response and toxicity for ICI therapy in NSCLC.
Conclusions:
- There is a critical need for robust biomarkers to guide ICI treatment selection in NSCLC.
- Plasma-derived biomarkers represent a promising, less invasive approach for predicting ICI efficacy and toxicity.
- Further research and validation are essential to integrate these novel plasma biomarkers into clinical practice for NSCLC management.
Related Concept Videos
08:49Exosomal miRNA Analysis in Non-small Cell Lung Cancer (NSCLC) Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool
04:21Exosome Isolation: A Technique to Separate Exosomes from the Plasma of Non-small Cell Lung Cancer Patients
08:25Detection of Cell-Free DNA in Blood Plasma Samples of Cancer Patients
10:29Semi-automatic PD-L1 Characterization and Enumeration of Circulating Tumor Cells from Non-small Cell Lung Cancer Patients by Immunofluorescence
07:43Using 22C3 Anti-PD-L1 Antibody Concentrate on Biopsy and Cytology Samples from Non-small Cell Lung Cancer Patients
05:17Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing

