High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC)
- PMID: 38857914
- PMCID: PMC11168162
- DOI: 10.1136/jitc-2024-009039
High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC)
Abstract
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.
Keywords: biomarker; immune checkpoint inhibitor; lung cancer.
© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
Conflict of interest statement
Competing interests: DLR has served as an advisor for AstraZeneca, Agendia, Amgen, BMS, Cell Signaling Technology, Cepheid, Danaher, Daiichi Sankyo, Genoptix/Novartis, GSK, Konica Minolta, Merck, NanoString, PAIGE.AI, Roche, and Sanofi. Amgen, Cepheid, NavigateBP, NextCure, and Konica Minolta fund or have funded research in DLR’s laboratory. KAS has served as a Consultant or advisor: AbbVie Inc.; Agenus Inc.; AstraZeneca; Bristol Myers Squibb; CDR-Life Inc.; Clinica Alemana de Santiago; EMD Serono Inc.; F.Hoffmann-La Roche; Genmab A/S; Indaptus Therapeutics; Janssen Pharmaceuticals, Inc.; Merck Sharpe & Dohme; Moderna, Inc.; Molecular Templates, Inc.; OnCusp Therapeutics; Parthenon/Incendia Therapeutics; Repertoire Therapeutics; Sanofi; Sensei Biotherapeutics; Shattuck Labs, Inc.; and Takeda Pharmaceutical Company Limited.
Figures
![Figure 1](https://cdn.statically.io/img/www.ncbi.nlm.nih.gov/pmc/articles/instance/11168162/bin/jitc-2024-009039f01.gif)
![Figure 2](https://cdn.statically.io/img/www.ncbi.nlm.nih.gov/pmc/articles/instance/11168162/bin/jitc-2024-009039f02.gif)
![Figure 3](https://cdn.statically.io/img/www.ncbi.nlm.nih.gov/pmc/articles/instance/11168162/bin/jitc-2024-009039f03.gif)
Similar articles
-
MiRNAs and Microbiota in Non-Small Cell Lung Cancer (NSCLC): Implications in Pathogenesis and Potential Role in Predicting Response to ICI Treatment.Int J Mol Sci. 2024 Jun 18;25(12):6685. doi: 10.3390/ijms25126685. Int J Mol Sci. 2024. PMID: 38928392 Free PMC article. Review.
-
Association of Machine Learning-Based Assessment of Tumor-Infiltrating Lymphocytes on Standard Histologic Images With Outcomes of Immunotherapy in Patients With NSCLC.JAMA Oncol. 2023 Jan 1;9(1):51-60. doi: 10.1001/jamaoncol.2022.4933. JAMA Oncol. 2023. PMID: 36394839 Free PMC article.
-
Spatially resolved proteomic profiling identifies tumor cell CD44 as a biomarker associated with sensitivity to PD-1 axis blockade in advanced non-small-cell lung cancer.J Immunother Cancer. 2022 Aug;10(8):e004757. doi: 10.1136/jitc-2022-004757. J Immunother Cancer. 2022. PMID: 36002182 Free PMC article.
-
Discovery of Biomarkers of Resistance to Immune Checkpoint Blockade in NSCLC Using High-Plex Digital Spatial Profiling.J Thorac Oncol. 2022 Aug;17(8):991-1001. doi: 10.1016/j.jtho.2022.04.009. Epub 2022 Apr 28. J Thorac Oncol. 2022. PMID: 35490853 Free PMC article.
-
Biomarkers Associated with Beneficial PD-1 Checkpoint Blockade in Non-Small Cell Lung Cancer (NSCLC) Identified Using High-Plex Digital Spatial Profiling.Clin Cancer Res. 2020 Aug 15;26(16):4360-4368. doi: 10.1158/1078-0432.CCR-20-0175. Epub 2020 Apr 6. Clin Cancer Res. 2020. PMID: 32253229 Free PMC article.
References
-
- O’Brien M, Paz-Ares L, Marreaud S, et al. . Pembrolizumab versus placebo as adjuvant therapy for completely Resected stage IB–IIIA non-small-cell lung cancer (PEARLS/KEYNOTE-091): an interim analysis of a randomised, triple-blind, phase 3 trial. Lancet Oncol 2022;23:1274–86. 10.1016/S1470-2045(22)00518-6 - DOI - PubMed
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Medical
Research Materials
Miscellaneous