Multi-Institutional Prospective Validation of Prognostic mRNA Signatures in Early Stage Squamous Lung Cancer (Alliance).

Introduction: Surgical resection is curative for some patients with early lung squamous cell carcinoma. Staging and clinical factors do not adequately predict recurrence risk. We sought to validate the discriminative performance of proposed prognostic gene expression signatures at a level of rigor sufficient to support clinical use.
Methods: The two-stage validation used independent core laboratories, objective quality control standards, locked test parameters, and large multi-institutional specimen and data sets. The first stage validation confirmed a signature's ability to stratify patient survival. The second-stage validation determined which signature(s) optimally improved risk discrimination when added to baseline clinical predictors. Participants were prospectively enrolled in institutional (cohort I) or cooperative group (cohort II) biospecimen and data collection protocols. All cases underwent a central review of clinical, pathologic, and biospecimen parameters using objective criteria to determine final inclusion (cohort I: n = 249; cohort II: n = 234). Primary selection required that a signature significantly predict a 3-year survival after surgical resection in cohort I. Signatures meeting this criterion were further tested in cohort II, comparing risk prediction using baseline risk factors alone versus in combination with the signature.
Results: Male sex, advanced age, and higher stage were associated with shorter survival in cohort I and established a baseline clinical model. Of the three signatures validated in cohort I, one signature was validated in cohort II and statistically significantly enhanced the prognosis relative to the baseline model (C-index difference 0.122; p < 0.05).
Conclusions: These results represent the first rigorous validation of a test appropriate to direct adjuvant treatment or clinical trials for patients with lung squamous cell carcinoma.
(Copyright © 2020. Published by Elsevier Inc.)