Programmed Death-Ligand 1 and Programmed Death-Ligand 2 mRNAs Measured Using Closed-System Quantitative Real-Time
Aileen I Fernandez1, Niki Gavrielatou1, Leena McCann2
1Department of Pathology, Yale University School of Medicine, New Haven, Connecticut.
Introduction:
Immune checkpoint inhibitors (ICIs) have become standard of care in lung cancer management, but only a relatively small percentage of patients treated respond. Current predictive biomarkers, including immunohistochemical detection of programmed death-ligand 1 (PD-L1), are insufficient for determining who will respond or, more importantly in the adjuvant setting, who will not respond to ICI therapy. Here, we investigate an alternative method of assessment of PD-L1 to predict nonresponse.
Methods:
This study uses a research use only quantitative real-time reverse transcription polymerase chain reaction assay on the GeneXpert system, to test for the association between four target immune genes, CD274 (PD-L1), PDCD1LG2 (programmed death-ligand 2 [PD-L2]), CD8A, and IRF1, and response to ICI therapy. Tissues were collected from 122 patients with advanced NSCLC before ICI therapy in a retrospective cohort, macrodissected, and analyzed using the GeneXpert.
Results:
Both high PD-L1 and PD-L2 mRNA expression levels were associated with improved long-term benefit at 24 months (p = 0.047 for both PD-L1 and PD-L2) and overall survival (PD-L1, p = 0.048; PD-L2, p = 0.049). Both PD-L1 and PD-L2 mRNA levels were higher in patients with KRAS mutations. Most importantly, low PD-L1 mRNA level had a high negative predictive value of 0.92 for absence of long-term benefit.
Conclusions:
With further validation of this assay in low-stage patients, an assessment of PD-L1 mRNA rather than protein, could be a method to determine which low-stage patients that should not be treated with ICIs in the adjuvant setting. This approach may also be a useful objective method for selecting patients for treatment in the advanced setting.
Insights
Assessing programmed death-ligand 1 (PD-L1) mRNA levels, rather than protein, can predict nonresponse to immune checkpoint inhibitors (ICIs) in lung cancer. This mRNA assessment offers a valuable tool for selecting patients unlikely to benefit from ICI therapy.
Area of Science:
- Oncology
- Immunology
- Molecular Biology
Background:
- Immune checkpoint inhibitors (ICIs) are standard lung cancer treatment, but response rates are limited.
- Current biomarkers like PD-L1 protein are insufficient for predicting ICI response, especially in the adjuvant setting.
- There is a need for improved methods to identify patients who will not respond to ICIs.
Purpose of the Study:
- To investigate programmed death-ligand 1 (PD-L1) mRNA expression as a predictive biomarker for ICI nonresponse in lung cancer.
- To evaluate the association between PD-L1, PD-L2, CD8A, and IRF1 mRNA levels and response to ICI therapy.
- To determine the utility of PD-L1 mRNA assessment for patient selection in advanced and adjuvant settings.
Main Methods:
- A quantitative real-time reverse transcription polymerase chain reaction (RT-PCR) assay was used.
- The study analyzed mRNA expression of CD274 (PD-L1), PDCD1LG2 (PD-L2), CD8A, and IRF1.
- Tissues from 122 advanced non-small cell lung cancer (NSCLC) patients were analyzed retrospectively before ICI therapy.
Main Results:
- High PD-L1 and PD-L2 mRNA expression correlated with improved 24-month benefit and overall survival (p=0.047-0.049).
- PD-L1 and PD-L2 mRNA levels were elevated in patients with KRAS mutations.
- Low PD-L1 mRNA expression demonstrated a high negative predictive value (0.92) for lack of long-term benefit.
Conclusions:
- PD-L1 mRNA assessment could identify lung cancer patients unlikely to benefit from adjuvant ICI therapy.
- This mRNA-based approach may serve as an objective method for selecting patients for ICI treatment.
- Further validation in low-stage patients is warranted to confirm its clinical utility.
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