ArticleFrontiers in immunology2024
Heterogeneity in peripheral blood immune lymphocyte subsets predicts the response of immunotherapy or chemoradiotherapy in advanced lung cancer: an analysis across different pathological types, treatment modalities and age.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Revisiting the Abscopal Effect in the Era of Immuno-Radiotherapy: Mechanisms, Challenges, and Clinical Perspectives.Biomolecules · 2026Review
- Baseline low-level viremia in HBV-related hepatocellular carcinoma: prognostic significance, risk stratification, and clinical implications.Frontiers in immunology · 2026Article
- LY-H as a potential screening biomarker for lymphocyte activation in peripheral blood.Frontiers in immunology · 2026Article
- Mendelian randomization analysis unveils causal associations between immune cells, metabolites, and lung cancer risk.Discover oncology · 2025Article
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Abstract
Background: The shaping of the tumor immune microenvironment does not only rely on tumor-infiltrating lymphocytes but on the recruitment of lymphocytes in peripheral blood. Monitoring peripheral blood lymphocyte subsets level (PBLSL) can predict treatment response and prognosis with immune checkpoint inhibitors. This study investigated the heterogeneity of PBLSL in response to chemoradiotherapy (CRT) or combined with immunotherapy (CRIT) in advanced lung cancer patients. Methods: 77 patients with advanced lung cancer receiving CRT or CRIT were divided into treatment-responsive and non-responsive groups based on efficacy. The study analyzed short-term efficacy and progression-free survival (PFS) according to baseline PBLSL and explored the impact under different stratifications, including treatment modality, pathology type, and age. Results: In all patients, higher levels of B cells, higher CD4+/CD8+ T cell ratios, and lower CD8+ T cell levels were associated with better short-term outcomes (P = 0.0035, P = 0.044, P = 0.022). Subgroup analysis revealed that in the CRT group, higher B cell levels correlated with improved efficacy (P = 0.011) and superior PFS (P = 0.048, HR = 0.3886, 95% CI = 0.1696 to 0.8902). In the CRIT group, higher CD4+ T cell levels, lower CD8+ T cell levels, and higher CD4+/CD8+ T cell ratios were linked to better efficacy (P = 0.038, P = 0.047, P = 0.017). For adenocarcinoma patients, higher CD4+/CD8+ T cell ratios and lower CD8+ T cell levels predicted better efficacy (P = 0.0155, P = 0.0119). B cell levels were significant in squamous cell carcinoma (P = 0.0291), while no PBLSL was predictive for small cell lung cancer. Among patients under 65, higher B cell levels were linked to improved efficacy and prolonged PFS (P = 0.0036, P = 0.0332, HR = 0.4111, 95% CI = 0.1973 to 0.8563). For patients over 65, differences in CD4+ T cell levels and CD4+/CD8+ T cell ratios were significant (P = 0.0433, P = 0.0338). Conclusion: PBLSL predicted efficacy and prognosis in various patient stratifications, suggesting PBLSL is a reliable predictor for CRT and CRIT in advanced lung cancer. Detecting different cellular subpopulations helps identify patients with significant treatment responses across different stratifications.
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