Search Continues for New Biomarkers in NSCLC
Researchers are searching for new biomarkers to improve treatment selection for non-small cell lung cancer (NSCLC) patients. Recent studies have explored various potential biomarkers, including PD-L1, tumor mutational burden, and genomic alterations, to better predict responses to immunotherapy.
Non-small cell lung cancer (NSCLC) treatment selection is being refined through research on new biomarkers. Established predictors like PD-L1 and tumor mutational burden have limitations. Other potential biomarkers, such as genomic alterations and markers of metabolic pathway dysregulation, have shown promise. Patient characteristics like tobacco exposure, sex, and body mass index may also provide clues about therapeutic efficacy. The use of AI and machine learning is being explored to integrate data and generate prognostic predictions. Researchers continue to work towards finding improved predictive biomarkers to optimize treatment plans for NSCLC patients.
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