Unveiling the potential of proteomic and genetic signatures for precision therapeutics in lung cancer management

精密医学 个性化医疗 生物标志物发现 组学 蛋白质组学 生物标志物 肺癌 医学 生物信息学 临床试验 基因组学 计算生物学 生物 病理 基因组 基因 生物化学
作者
Shriyansh Srivastava,Nandani Jayaswal,Sachin Kumar,Pramod Kumar Sharma,Tapan Behl,Asaad Khalid,Syam Mohan,Asim Najmi,Khalid Zoghebi,Hassan A. Alhazmi
出处
期刊:Cellular Signalling [Elsevier BV]
卷期号:113: 110932-110932 被引量:19
标识
DOI:10.1016/j.cellsig.2023.110932
摘要

Lung cancer's enduring global significance necessitates ongoing advancements in diagnostics and therapeutics. Recent spotlight on proteomic and genetic biomarker research offers a promising avenue for understanding lung cancer biology and guiding treatments. This review elucidates genetic and proteomic lung cancer biomarker progress and their treatment implications. Technological strides in mass spectrometry-based proteomics and next-generation sequencing enable pinpointing of genetic abnormalities and abnormal protein expressions, furnishing vital data for precise diagnosis, patient classification, and customized treatments. Biomarker-driven personalized medicine yields substantial treatment improvements, elevating survival rates and minimizing adverse effects. Integrating omics data (genomics, proteomics, etc.) enhances understanding of lung cancer's intricate biological milieu, identifying novel treatment targets and biomarkers, fostering precision medicine. Liquid biopsies, non-invasive tools for real-time treatment monitoring and early resistance detection, gain popularity, promising enhanced management and personalized therapy. Despite advancements, biomarker repeatability and validation challenges persist, necessitating interdisciplinary efforts and large-scale clinical trials. Integrating artificial intelligence and machine learning aids analyzing vast omics datasets and predicting treatment responses. Single-cell omics reveal cellular connections and intratumoral heterogeneity, valuable for combination treatments. Biomarkers enable accurate diagnosis, tailored medicines, and treatment response tracking, significantly impacting personalized lung cancer care. This approach spurs patient-centered trials, empowering active patient engagement. Lung cancer proteomic and genetic biomarkers illuminate disease biology and treatment prospects. Progressing towards individualized efficient therapies is imminent, alleviating lung cancer's burden through ongoing research, omics integration, and technological strides.
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