Abstract 1424: Prospective validation of a mRNA signature in plasma for the diagnosis of early stage lung cancer
Authors: Capitán Ana María Giménez , Rubisntein Pablo , Aguilar-Hernández Andrés , González-cao María , Moya Irene , Viteri Santiago , Cabrera Carlos , Ramón y Cajal Santiago , Loor Karina , Culebras Mario , Sansano Irene , Rubisntein Federico , Valarezo Joselyn , Mayo-de las-Casas Clara , Pedraz Carlos , Beechem Joseph , Warren Sarah , Rosell Rafael , Molina-Vila Miguel Ángel 
Published: June 2022

Abstract
Background: Non-small cell lung cancer (NSCLC) is usually diagnosed at stages IIIB-IV, with a median overall survival that does not exceed two years. In contrast, patients diagnosed at early and locally advanced stages (I-IIIA) can undergo surgery and have a significantly better prognosis. Imaging technologies often detect lung nodules of unknown significance that pose a diagnostic challenge. In a proof-of-concept study, based on a 76-patient cohort, we developed a preliminary mRNA expression signature in plasma that discriminated healthy individuals from early-stage NSCLC patients with AUC=0.98. Here, we aimed to expand the training cohort, to refine the diagnostic signature and to prospectively validate the final signature in the clinical setting.
Methods: Two hundred and thirty individuals with pulmonary nodules suspicious of lung cancer have been enrolled in the training cohort. All of them underwent bronchoscopy, fine needle aspiration, percutaneous or surgical biopsy to confirm the diagnosis. Circulating-free RNA (cfRNA) has been isolated from plasma using an automatic extraction method (Qiasymphony, Qiagen). Purified cfRNA has been quantified using Qubit®, retrotranscribed and pre-amplified with 14 cycles using the Low RNA Input Amplification kit (NanoString Technologies). Gene expression analysis has been performed on the nCounter platform using the PanCancer IO360࣪ panel (NanoString Technologies), which can detect 770 transcripts related to tumor biology, micro-environment and the immune system.
Results: One hundred twenty-six patients have been analyzed so far; plasma samples have been successfully analyzed by nCounter in all cases. Ongoing analysis reveal differential patterns of gene expression in early-stage NSCLC patients versus non-cancer individuals. Using a bioinformatics recursive feature elimination algorithm, we have selected a diagnostic signature with an area under the ROC curve of 0.89. The signature scores derived from the algorithm are significantly different between the non-cancer and NSCLC cases. Final results of the training and validation cohort will be presented at the meeting
Conclusions: Plasma RNA expression signatures can be a useful tool to guide clinical decision in patients with pulmonary nodules suspicious of malignancy, orienting towards surgery or observation.
Citation Format: Ana María Giménez Capitán, Pablo Rubisntein, Andrés Aguilar-Hernández, María González-cao, Irene Moya, Santiago Viteri, Carlos Cabrera, Santiago Ramón y Cajal, Karina Loor, Mario Culebras, Irene Sansano, Federico Rubisntein, Joselyn Valarezo, Clara Mayo-de las-Casas, Carlos Pedraz, Joseph Beechem, Sarah Warren, Rafael Rosell, Miguel Ángel Molina-Vila. Prospective validation of a mRNA signature in plasma for the diagnosis of early stage lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1424.