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Updated: Jul 23, 2026
A Murine Ommaya Xenograft Model to Study Direct-Targeted Therapy of Leptomeningeal Disease
Published on: January 29, 2021
Intrathecal pemetrexed for leptomeningeal metastasis from lung adenocarcinoma: a clinical efficacy and multiplex
Zhi Wang1,2, Peng Ding1,2, Hongxia Zhou1,2
1Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Background:
Leptomeningeal metastasis (LM) is an advanced complication of lung cancer with a poor prognosis. It remains unknown whether intrathecal pemetrexed (IP) can improve the outcomes of patients with LM from lung adenocarcinoma (LUAD). This study explored the efficacy of intrathecal pemetrexed (IP) and proteomic biomarkers in LM from LUAD.
Patients And Methods:
We conducted a retrospective survival analysis of 157 confirmed LM patients (54 IP vs 103 non-IP). To balance the baseline, propensity score matching (PSM) was implemented. We investigated clinical baseline characteristics and treatment factors to identify those influencing the outcomes of LM patients. Plasma and cerebrospinal fluid (CSF) samples underwent proteomic profiling using Olink Immuno-Oncology panels to identify IP response biomarkers and build a prediction model.
Results:
After PSM, 82 patients were included in two matched cohort (41 IP vs 41 non-IP). IP treatment (HR = 0.427, P = .022) and ECOG performance status (HR = 2.737, P = .005) were independent predictors of overall survival (OS). Stratified analysis showed IP significantly improved OS in patients with poor performance status (ECOG 3-4: IP vs non-IP, 11.2 vs 2.5 months, P = .0029). Proteomics revealed low plasma MCP-2 (AUC = 0.873) and high CSF ARG1 (AUC = 0.875) levels distinguished IP responders from nonresponders.
Conclusions:
IP therapy improves OS in LUAD patients with LM, particularly offering significant benefit as salvage treatment for those with ECOG 3-4. Proteomic analysis suggests plasma MCP-2 and CSF ARG1 are promising predictive biomarkers for IP response. The small sample size in biomarker analysis may limit these findings, necessitating validation through multicenter studies.
