Abstract 466: Differential expression of circRNAs allows discrimination of NSCLC from cancer-free lung specimens using the nCounter platform
Authors: Pedraz-Valdunciel Carlos , Molina-Vila Miguel Ángel , Giannoukakos Stavros , Potie Nicolas , Roman-Llado Ruth , Bracht Jill , Filipska Martyna , Ito Masaoki , Gimenez-Capitán Ana , Aguado-Esteban Cristina , Warren Sarah , Huang Chung-Ying , Bivona Trever , Rosell Rafael 
Published: July 2021

Abstract
Introduction: Lung cancer mortality ranks as the highest of the cancer-related deaths. Studies on tumor profiling at the genomic, transcriptomic and proteomic level has soared in the last decade improving overall survival of these patients by shaping the current targeted therapies; however, further investigation of novel biomarkers for an early diagnosis still remains imperative.circRNAs are a class of tissue-specific stable structures that control mammalian transcription. Their aberrant expression plays an important role in carcinogenesis and tumor progression which profiles them as valuable biomarkers; Conversely, its potential has not been fully explored in lung cancer due to several limitations of current circRNA quantification methods that prevent their clinical implementation.The nCounter technology allows for quantitative and qualitative assessment of up to 800 targets providing an accurate and factual perspective of expression levels. To our knowledge, thru this study we stand as the first on assessing circRNA differential expression with this platform for lung cancer detection both in FFPE specimens and cell lines providing preliminary evidence of their differential expression in lung cancer.
Methods: Cells were cultured under standard conditions until harvested. RNA was isolated by using Allprep DNA/RNA/miRNA universal kit (Qiagen). FFPE lung tissue samples (n=28; 18 NSCLC,10 non-cancer) were retrospectively collected and micro-dissected. RNA was isolated with High Pure FFPET RNA isolation kit (Roche) and quantified by Qubit (Thermo Fisher).Overnight hybridization and posterior nCounter FLEX processing were performed following NanoString protocol for nCounter Elements. Expression analysis was carried out based on a tailored panel of 85 circRNAs related to the biology of the disease.
Results: FFPE lung tissues revealed a cluster of differentially expressed circRNAs that allow distinction of lung cancer versus control. circFOXP1, circEPB41L2 and circBNC2 ranked as the most downregulated circRNAs, whereas circCHD9, circAASDH, circRUNX1 and circCHST15 led the catalog of most upregulated in cancer specimens. circRNA expression of A549, H2228, H3122, PC9, H1666, and HOP-62 cells was compared to the CCL-171 fibroblast cell line. circEPB41L2 and circFOXP1 were also confirmed distinctly downregulated in cancer cell lines.
Conclusion: This study presents for the first time the use of the differential expression of circRNAs in FFPE tissues for lung cancer discrimination using the nCounter platform. While more samples are currently being collected to increase the statistical power of the study, these results pave the way for the developing of future circRNA-based nCounter tests for lung cancer diagnosis. Further experiments using epithelial cells as control will be carried out and results will be pertinently updated at the time of the meeting.
Citation Format: Carlos Pedraz-Valdunciel, Miguel Ángel Molina-Vila, Stavros Giannoukakos, Nicolas Potie, Ruth Roman-Llado, Jill Bracht, Martyna Filipska, Masaoki Ito, Ana Gimenez-Capitán, Cristina Aguado-Esteban, Sarah Warren, Chung-Ying Huang, Trever Bivona, Rafael Rosell. Differential expression of circRNAs allows discrimination of NSCLC from cancer-free lung specimens using the nCounter platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 466.