ArticleActa neuropathologica communications2024
An immune scoring system predicts prognosis and immune characteristics in lung adenocarcinoma brain metastases by RNA sequencing.
Article in Acta neuropathologica communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Multi-cell death gene signature predicts lung adenocarcinoma prognosis and reveals FURIN regulates ferroptosis via NRF2-xCT-GPX4 axis.Respiratory research · 2026Article
- Profiling the tumor immunological status in Japanese solid cancers using the tumor immune status scoring algorithm.Scientific reports · 2026Article
- Prognostic role of CDCA3 in lung adenocarcinoma with immune infiltration.Scientific reports · 2026Article
- Crosstalk in the brain tumor microenvironment: mechanisms, therapeutic strategies, and clinical advances.Military Medical Research · 2026Review
- Immune Checkpoint Inhibition in Patients with Brain Metastases from Non-Small-Cell Lung Cancer: Emerging Mechanisms and Personalized Clinical Strategies.International journal of molecular sciences · 2025Review
- Identification and characterization of tertiary lymphoid structures in brain metastases.Acta neuropathologica communications · 2025Article
- Pre-treatment endocrine-nutritional signatures predict clinical benefit from PD-1/PD-L1 blockade in hematologic malignancies.Frontiers in nutrition · 2025Review
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Abstract
backgroundPrevious studies have reported that the tumor immune microenvironment (TIME) was associated with the prognosis of lung cancer patients and the efficacy of immunotherapy. However, given the significant challenges in obtaining specimens of brain metastases (BrMs), few studies explored the correlation between the TIME and the prognosis in patients with BrMs from lung adenocarcinoma (LUAD).
methodsTranscript profiling of archival formalin-fixed and paraffin-embedded specimens of BrMs from 70 LUAD patients with surgically resected BrMs was carried out using RNA sequencing. An immune scoring system, the green-yellow module score (GYMS), was developed to predict prognosis and immune characteristics in both BrMs and primary LUAD using Weighted Correlation Network analysis (WGCNA) and GSVA analysis. We comprehensively evaluated the immunological role of GYMS based on gene expression profile of LUAD BrMs by systematically correlating GYMS with immunological characteristics and immunotherapy responsiveness in the BrMs. Immunohistochemistry was applied for validation.
resultsWe found that the high-GYMS group had better clinical prognosis and inflamed immune landscape including high infiltrations of various immune cells, increased immunomodulatory expression, and enriched immune-related pathways by using RNA-seq and immunohistochemical analysis. Low-GYMS group presented a lacked immune infiltration characteristic. Besides, the high-GYMS group had lower TIDE score and higher T-cell inflamed score than low-GYMS group. The GYMS has been validated in independent BrMs cohorts and primary NSCLC cohort treated with anti-PD-1/PD-L1, showing strong reproducibility and stability in both primary LUAD and BrMs. In addition, we construct a GYMS-related risk signature for patients with LUAD BrMs to predict prognosis.
conclusionsWe identified two immune-related subtypes which used to estimate prognosis and immune characteristics and developed a reliable GYMS-related risk signature in LUAD BrMs. These results will enhance the understanding of the immune microenvironment in LUAD BrMs and lay the theoretical foundation for the development of personalized therapies for LUAD patients with BrMs.
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