Molecular diagnosis & therapy · 2026
Development of Diagnostic Models and Biomarker Identification for Type 1 Leptomeningeal Metastasis in Lung Adenocarcinoma Using Olink: Exploratory Cohort Study with Internal Temporal Validation.
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Ding Peng, Chen Qiuchi, Li Yun, Kui Yulan, Wang Zhi, Zhou Hongxia, Kuang Bohua, Chen Lingjuan, Zhang Xing, Ge Minghui, Han Tiantian, Zhang Ruiguang, Tong Fan, Dong Xiaorong
Аннотация
BACKGROUND: To enable early identification of type 1 leptomeningeal metastasis (LM) risk and to identify plasma- and cerebrospinal fluid (CSF)-based biomarkers in lung adenocarcinoma (LUAD).
METHODS: Blood and CSF samples were prospectively obtained from patients with advanced LUAD with or without LM. A total of 174 samples were analyzed using the Olink® Target-96 platform. Two predictive models were established via logistic regression and subjected to internal temporal validation.
RESULTS: In total, 88 blood samples and 86 CSF samples were obtained. Seven representative plasma proteins were consistently selected, forming a plasma protein diagnostic model with the area under the curve (AUC, p-training set) of 0.918, a sensitivity of 100%, and a specificity of 73.0%; the AUC in the p-test set was 0.765. A total of 12 representative CSF proteins were selected to establish a CSF protein diagnostic model with an AUC (c-training set) of 0.984, a sensitivity of 96.7%, and a specificity of 96.7%; the AUC in the c-test set was 0.944. In CSF samples, 65 differentially expressed proteins were identified between the LM and nLM groups, and enrichment analysis indicated predominant clustering within inflammatory and immune activation pathways. In addition, tumor necrosis factor receptor superfamily member 9 (TNFRSF9) alone yielded an AUC of 0.960 for discriminating the LM group from the nLM_nBM (brain metastasis) group.
CONCLUSIONS: A diagnostic model for type 1 LUAD-LM was developed with high accuracy and potential clinical applicability. Moreover, CSF-specific biomarkers have been identified, offering potential candidate targets for the management of LUAD-LM.
METHODS: Blood and CSF samples were prospectively obtained from patients with advanced LUAD with or without LM. A total of 174 samples were analyzed using the Olink® Target-96 platform. Two predictive models were established via logistic regression and subjected to internal temporal validation.
RESULTS: In total, 88 blood samples and 86 CSF samples were obtained. Seven representative plasma proteins were consistently selected, forming a plasma protein diagnostic model with the area under the curve (AUC, p-training set) of 0.918, a sensitivity of 100%, and a specificity of 73.0%; the AUC in the p-test set was 0.765. A total of 12 representative CSF proteins were selected to establish a CSF protein diagnostic model with an AUC (c-training set) of 0.984, a sensitivity of 96.7%, and a specificity of 96.7%; the AUC in the c-test set was 0.944. In CSF samples, 65 differentially expressed proteins were identified between the LM and nLM groups, and enrichment analysis indicated predominant clustering within inflammatory and immune activation pathways. In addition, tumor necrosis factor receptor superfamily member 9 (TNFRSF9) alone yielded an AUC of 0.960 for discriminating the LM group from the nLM_nBM (brain metastasis) group.
CONCLUSIONS: A diagnostic model for type 1 LUAD-LM was developed with high accuracy and potential clinical applicability. Moreover, CSF-specific biomarkers have been identified, offering potential candidate targets for the management of LUAD-LM.