Lung cancer (LC) remains one of the key factors contributing to cancer-related deaths globally, necessitating precise and personalized therapeutic approaches. The clinical management of LC has been markedly advanced with the identification and incorporation of biomarkers, facilitating more accurate and individualized treatment strategies. Biomarkers are essential for directing targeted therapeutic approaches, selecting immunotherapy, and predicting prognosis. The usage of genetic-based biomarkers, including the identification of driver mutations, has incredibly generated genotype-directed therapy and constructed altering LC treatment from cytotoxic chemotherapy into targeted and individualized therapy. They have become essential tools for managing LC, enabling focused treatments, and bettering patient outcomes. Despite the considerable promise of biomarker-driven precision medicine, substantial challenges remain to be addressed. These challenges include the genetic heterogeneity of LC, the variability in the sensitivity and specificity of biomarker assays, and the complexity of incorporating biomarker data into clinical decision-making. However, many biomarkers lack the necessary sensitivity and specificity for early-stage LC detection, and the emergence of these biomarkers remains poorly understood. Thus, in this study, in order to fully exploit the capabilities of these advancements, continuous research efforts should prioritize addressing the constraints of existing methods, creating reliable techniques that involve several biomarkers, and guaranteeing the widespread availability of advanced diagnostic tools.
Abdullah et al. (Wed,) studied this question.