ArticleBiomedicines2022
Identification of sSIGLEC5 and sLAG3 as New Relapse Predictors in Lung Cancer.
Article in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 7 citations in OpenAlex.
- Identification of a circulating immunological signature as a liquid biopsy approach for the diagnosis of endometriosis.Scientific reports · 2026Article
- Integrative Multi-omics Analysis and Mendelian Randomization Reveal Potential Therapeutic Targets and their Stratification in Lung Squamous Cell Carcinoma.Current medicinal chemistry · 2026Article
- A blood-based liquid biopsy analyzing soluble immune checkpoints and cytokines identifies distinct neuroendocrine tumors.Journal of experimental & clinical cancer research : CR · 2025Article
- Soluble immune checkpoints: implications for cancer prognosis and response to immune checkpoint therapy and conventional therapies.Journal of experimental & clinical cancer research : CR · 2024Review
- Soluble lymphocyte activation gene-3 (sLAG3) and CD4/CD8 ratio dynamics as predictive biomarkers in patients undergoing immune checkpoint blockade for solid malignancies.British journal of cancer · 2024Article
- Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins.Frontiers in immunology · 2023Article
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Authors and funding
9 authors at 2 institutions in 1 country.
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Abstract
Lung cancer (LC) continues to be the leading cause of cancer-related deaths in both men and women worldwide. After complete tumour resection, around half of the patients suffer from disease relapse, emphasising the critical need for robust relapse predictors in this disease. In search of such biomarkers, 83 patients with non-microcytic lung cancer and 67 healthy volunteers were studied. Pre-operative levels of sSIGLEC5 along with other soluble immune-checkpoints were measured and correlated with their clinical outcome. Soluble SIGLEC5 (sSIGLEC5) levels were higher in plasma from patients with LC compared with healthy volunteers. Looking into those patients who suffered relapse, sSIGLEC5 and sLAG3 were found to be strong relapse predictors. Following a binary logistic regression model, a sSIGLEC5 + sLAG3 score was established for disease relapse prediction (area under the curve 0.8803, 95% confidence intervals 0.7955−0.9652, cut-off > 2.782) in these patients. Based on score cut-off, a Kaplan−Meier analysis showed that patients with high sSIGLEC5 + sLAG3 score had significantly shorter relapse-free survival (p ≤ 0.0001) than those with low sSIGLEC5 + sLAG3 score.Our study suggests that pre-operative sSIGLEC5 + sLAG3 score is a robust relapse predictor in LC patients.
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