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Updated: Jun 24, 2025
Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
Published on: September 8, 2023
High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in
Myrto K Moutafi1, Katherine M Bates1, Thazin Nwe Aung2,3
1Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, USA.
Background:
Despite the impressive outcomes with immune checkpoint inhibitor (ICI) in non-small cell lung cancer (NSCLC), only a minority of the patients show long-term benefits from ICI. In this study, we used retrospective cohorts of ICI treated patients with NSCLC to discover and validate spatially resolved protein markers associated with resistance to programmed cell death protein-1 (PD-1) axis inhibition.
Methods:
Pretreatment samples from 56 patients with NSCLC treated with ICI were collected and analyzed in a tissue microarray (TMA) format in including four different tumor regions per patient using the GeoMx platform for spatially informed transcriptomics. 34 patients had assessable tissue with tumor compartment in all 4 TMA spots, 22 with leukocyte compartment and 12 with CD68 compartment. The patients' tissue that was not assessable in fourfold redundancy in each compartment was designated as the validation cohort; cytokeratin (CK) (N=22), leukocytes CD45 (N=31), macrophages, CD68 (N=43). The human whole transcriptome, represented by~18,000 individual genes assessed by oligonucleotide-tagged in situ hybridization, was sequenced on the NovaSeq platform to quantify the RNAs present in each region of interest.
Results:
54,000 gene variables were generated per case, from them 25,740 were analyzed after removing targets with expression lower than a prespecified frequency. Cox proportional-hazards model analysis was performed for overall and progression-free survival (OS, PFS, respectively). After identifying genes significantly associated with limited survival benefit (HR>1)/progression per spot per patient, we used the intersection of them across the four TMA spots per patient. This resulted in a list of 12 genes in the tumor-cell compartment (RPL13A, GNL3, FAM83A, CYBA, ACSL4, SLC25A6, EPAS1, RPL5, APOL1, HSPD1, RPS4Y1, ADI1). RPL13A, GNL3 in tumor-cell compartment were also significantly associated with OS and PFS, respectively, in the validation cohort (CK: HR, 2.48; p=0.02 and HR, 5.33; p=0.04). In CD45 compartment, secreted frizzled-related protein 2, was associated with OS in the discovery cohort but not in the validation cohort. Similarly, in the CD68 compartment ARHGAP and PNN interacting serine and arginine rich protein were significantly associated with PFS and OS, respectively, in the majority but not all four spots per patient.
Conclusion:
This work highlights RPL13A and GNL3 as potential indicative biomarkers of resistance to PD-1 axis blockade that might help to improve precision immunotherapy strategies for lung cancer.
Insights
This study identified RPL13A and GNL3 as potential biomarkers for resistance to programmed cell death protein-1 (PD-1) axis inhibition in non-small cell lung cancer (NSCLC). These findings may improve precision immunotherapy strategies for lung cancer patients.
Area of Science:
- Oncology
- Immunotherapy
- Genomics
- Biomarker Discovery
Background:
- Immune checkpoint inhibitors (ICIs) show impressive outcomes in non-small cell lung cancer (NSCLC), but only a minority of patients benefit long-term.
- Identifying mechanisms of resistance to programmed cell death protein-1 (PD-1) axis inhibition is crucial for improving treatment efficacy.
- Spatially resolved molecular markers may provide insights into treatment resistance.
Purpose of the Study:
- To discover and validate spatially resolved protein markers associated with resistance to PD-1 axis inhibition in NSCLC.
- To identify potential biomarkers that can predict patient response to ICI therapy.
- To enhance precision immunotherapy strategies for lung cancer.
Main Methods:
- Retrospective analysis of pretreatment tissue samples from 56 NSCLC patients treated with ICI.
- Spatially informed transcriptomics using the GeoMx platform on tissue microarrays (TMAs) covering tumor and immune cell compartments.
- Whole transcriptome sequencing (~18,000 genes) to quantify RNA expression in specific regions of interest.
Main Results:
- Analysis identified 12 genes in the tumor-cell compartment associated with limited survival benefit.
- RPL13A and GNL3 in the tumor-cell compartment were significantly associated with overall survival (OS) and progression-free survival (PFS) respectively in the validation cohort.
- Other potential markers were identified in leukocyte (CD45) and macrophage (CD68) compartments, though with varying validation results.
Conclusions:
- RPL13A and GNL3 are highlighted as potential predictive biomarkers for resistance to PD-1 axis blockade in NSCLC.
- These biomarkers could aid in the development of more precise immunotherapy strategies.
- Further validation is warranted to integrate these findings into clinical practice for lung cancer treatment.
