TY - JOUR
T1 - Proposal of real-world solutions for the implementation of predictive biomarker testing in patients with operable non-small cell lung cancer
AU - Hofman, Paul
AU - Christopoulos, Petros
AU - D'Haene, Nicky
AU - Gosney, John
AU - Normanno, Nicola
AU - Schuuring, Ed
AU - Tsao, Ming-Sound
AU - Quinn, Christine
AU - Russell, Jayne
AU - Keating, Katherine E
AU - López-Ríos, Fernando
N1 - Copyright © 2025. Published by Elsevier B.V.
PY - 2025/3
Y1 - 2025/3
N2 - The implementation of biomarker testing for targeted therapies and immune checkpoint inhibitors is a cornerstone in the management of metastatic and locally advanced non-small cell lung cancer (NSCLC), playing a pivotal role in guiding treatment decisions and patient care. The emergence of precision medicine in the realm of operable NSCLC has been marked by the recent approvals of osimertinib, atezolizumab, nivolumab, pembrolizumab and alectinib for early-stage disease, signifying a shift towards more tailored therapeutic strategies. Concurrently, the landscape of this disease is rapidly evolving, with several further pending approvals and numerous clinical trials in progress. To harness the benefits of these innovative neo-adjuvant and adjuvant therapies, the integration of predictive biomarker testing into standard clinical protocols is imperative for patients with operable NSCLC. A multidisciplinary international consortium has identified three primary obstacles impeding the effective testing of patients with operable NSCLC. These challenges encompass the limited number of test requests by physicians, the inadequacy of tissue samples for comprehensive testing, and the prevalence of cost-reduction measures leading to suboptimal testing practices. This review delineates the aforementioned challenges and proposed solutions, and strategic recommendations aimed at enhancing the testing process. By addressing these issues, we strive to optimize patient outcomes in operable NSCLC, ensuring that individuals receive the most appropriate and effective care based on their unique disease profile.
AB - The implementation of biomarker testing for targeted therapies and immune checkpoint inhibitors is a cornerstone in the management of metastatic and locally advanced non-small cell lung cancer (NSCLC), playing a pivotal role in guiding treatment decisions and patient care. The emergence of precision medicine in the realm of operable NSCLC has been marked by the recent approvals of osimertinib, atezolizumab, nivolumab, pembrolizumab and alectinib for early-stage disease, signifying a shift towards more tailored therapeutic strategies. Concurrently, the landscape of this disease is rapidly evolving, with several further pending approvals and numerous clinical trials in progress. To harness the benefits of these innovative neo-adjuvant and adjuvant therapies, the integration of predictive biomarker testing into standard clinical protocols is imperative for patients with operable NSCLC. A multidisciplinary international consortium has identified three primary obstacles impeding the effective testing of patients with operable NSCLC. These challenges encompass the limited number of test requests by physicians, the inadequacy of tissue samples for comprehensive testing, and the prevalence of cost-reduction measures leading to suboptimal testing practices. This review delineates the aforementioned challenges and proposed solutions, and strategic recommendations aimed at enhancing the testing process. By addressing these issues, we strive to optimize patient outcomes in operable NSCLC, ensuring that individuals receive the most appropriate and effective care based on their unique disease profile.
KW - Humans
KW - Carcinoma, Non-Small-Cell Lung/drug therapy
KW - Lung Neoplasms/drug therapy
KW - Biomarkers, Tumor
KW - Precision Medicine/methods
KW - Molecular Targeted Therapy
KW - Immune Checkpoint Inhibitors/therapeutic use
U2 - 10.1016/j.lungcan.2025.108107
DO - 10.1016/j.lungcan.2025.108107
M3 - Review article
C2 - 39904223
SN - 0169-5002
VL - 201
JO - Lung Cancer
JF - Lung Cancer
M1 - 108107
ER -