Abstract 5920: Nanomechanical signatures: a breakthrough in personalized diagnosis and treatment optimization for lung cancer
Authors: Jordi Alcaraz, Elba Marin, Hector Sanz-Fraile, Marina Querol, Paula Gausa, Kate Neal, Marselina Arshakyan, Marc Rico-Pastó, Marc Boada, David Sanchez, Daniel Martinez, Reinier Oropesa Nunez, Gitika Srivastava, Ahmed Jizawi, Carolina Ortiz-Velez, Tobias Appenzeller, Sara Nizzero, Marko Loparic, Marija Plodinec, Noemi Reguart
Journal: Cancer Research (2025)

Abstract Background: Non-small cell lung cancer (NSCLC) is the most common lung cancer subtype and the leading cause of cancer-related deaths worldwide. Advances in treatment have focused on personalized approaches that use targeted therapies and immunotherapies based on protein, DNA, or RNA biomarkers. Assessing molecular biomarkers typically takes 1-2 weeks with challenges such as tissue exhaustion and poor response prediction. Atomic Force Microscopy (AFM) allows for point-of care evaluation of nanomechanical signatures (NS) in hours, offering a fast and accurate method for diagnosis and treatment personalization. Methods: We used the AFM-based Automated and Reliable Tissue Diagnostics (ARTIDIS) platform to evaluate the diagnostic and prognostic capabilities of NS. Fresh tumor and paired uninvolved pulmonary tissue samples were collected from 70 early-stage NSCLC patients who underwent curative surgical procedures at the Hospital Clinic of Barcelona. Measurements were blinded, and samples were preserved in formalin for further histopathological and molecular analyses. Results: In this proof-of-concept study, ARTIDIS NS successfully distinguished malignant tumors from uninvolved pulmonary tissue with 88% sensitivity, 86% specificity, and 87% accuracy (n=52). The NS also accurately identified histological subtypes, including adenocarcinoma (ADC, 100% sensitivity) and squamous cell carcinoma (SCC, 83% specificity). ARTIDIS NS identified aggressive features predictive of early recurrence in non-involved samples (82% sensitivity, 72% specificity). Out of 70 patients, 17 had recurrences (median time: 7.7 months), leading to 12 deaths, 10 due to cancer. Remarkably, ARTIDIS NS accurately predicted tumor progression within 10 months post-surgery, achieving 100% sensitivity and 93% specificity in identifying patients at risk of recurrence after curative treatment. Conclusions: The findings suggest that ARTIDIS NS is a rapid and reliable tool for predicting recurrence and assessing outcomes in NSCLC while preserving tissues for downstream assessment. The ARTIDIS platform not only demonstrated significant accuracy in differentiating malignant tissues, but also showed exceptional precision in predicting early recurrence and progression, effectively identifying high-risk patients. Furthermore, NS identified early recurrence indicators through nanomechanical changes in uninvolved samples, offering insights beyond traditional pathology. A 200-patient extension specifically in neoadjuvant treatment is planned to enhance NSCLC management and improve patient outcomes. Citation Format: Jordi Alcaraz, Elba Marin, Hector Sanz-Fraile, Marina Querol, Paula Gausa, Kate Neal, Marselina Arshakyan, Marc Rico-Pastó, Marc Boada, David Sanchez, Daniel Martinez, Reinier Oropesa Nunez, Gitika Srivastava, Ahmed Jizawi, Carolina Ortiz-Velez, Tobias Appenzeller, Sara Nizzero, Marko Loparic, Marija Plodinec, Noemi Reguart. Nanomechanical signatures: a breakthrough in personalized diagnosis and treatment optimization for lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5920.