Non-invasive radiogenomic assessment of growth-associated protein 43 in lung adenocarcinoma brain metastases.
TL;DR
GAP43 is an adverse prognostic biomarker in LUAD brain metastases and a CE-T1WI radiogenomic model accurately predicts GAP43 expression, facilitating individualized short-term survival stratification.
Abstract
Background
To evaluate the prognostic role of growth-associated protein 43 (GAP43) in lung adenocarcinoma (LUAD) brain metastases and develop a non-invasive radiogenomic model combining MRI radiomics with transcriptomics for GAP43 prediction and survival estimation.
Methods
This retrospective study included 308 patients with surgically resected LUAD brain metastases (2012-2021). Fifty-six patients with paired RNA sequencing and contrast-enhanced T1-weighted MRI (CE-T1WI) were used to build the radiomics model predicting GAP43 expression. An additional independent cohort of 252 patients was included for exploratory prognostic evaluation of the imaging-derived radiomics score (RS). Radiomic features (n = 1,130) were extracted using PyRadiomics and underwent sequential feature selection, including inter-observer reproducibility assessment using intraclass correlation coefficients (ICCs), univariate t-tests, correlation-based redundancy filtering, and least absolute shrinkage and selection operator (LASSO)-based feature selection. An optimized support vector machine (SVM) model was subsequently developed to predict GAP43 expression and generate the RS. Survival was analyzed via Kaplan-Meier and Cox regression.
Results
A total of 56 patients were enrolled in the radiogenomics cohort. GAP43 was significantly independently associated with poorer overall survival (OS; P = 0.026). High GAP43 expression correlated positively with activated mast cells (R = 0.53), eosinophils (R = 0.34). The radiogenomic model showed favorable performance for predicting GAP43 expression in repeated nested cross-validation, with an AUC of 0.825 (95% CI, 0.791-0.858). In an independent prognostic cohort of 252 patients, a higher imaging-derived radiomics score (RS) was independently associated with poorer OS (P < 0.001). The RS-based nomogram showed acceptable prognostic performance, with time-dependent AUCs of 0.661, 0.666, and 0.631 for 3-, 6-, and 12-month OS, respectively.
Conclusions
GAP43 is an adverse prognostic biomarker in LUAD brain metastases. A CE-T1WI radiogenomic model accurately predicts GAP43 expression, facilitating individualized short-term survival stratification.