Advancing Lung Cancer Treatment Through Multi-Omics Integration and Personalized Immunotherapy
Md Shamsuddin Sultan Khan 1*, Anton Yuryev 2, John Catanzaro 3
Journal of Precision Biosciences 1(1) 1-6 https://doi.org/10.25163/biosciences.112090DB112921119
Submitted: 29 October 2019 Revised: 29 October 2019 Published: 02 November 2019
Abstract
Background: Lung cancer remains a major challenge in oncology due to its complex pathogenesis and heterogeneous presentation. Traditional diagnostic and therapeutic methods often fail to address the disease's biological variations. Recent advancements in Next-Generation Sequencing (NGS) technologies, including Whole Exome Sequencing (WES), Whole Genome Sequencing (WGS), RNA sequencing (RNAseq), and proteomics, have enhanced our understanding of cancer biology. Neo7logix, LLC utilizes these technologies to develop a precision-based approach to cancer treatment. Methods: We integrated WES, RNAseq, and urine proteomics data from a lung cancer patient using Neo7logix, LLC’s platform. WES identified 264 mutated genes linked to Cancer Hallmarks pathways. RNAseq analysis provided gene expression profiles, highlighting significant expression regulators and enriched pathways. Urine proteomics detected 1,772 proteins, contributing to neoantigen selection. Peptides with high binding affinity to the patient’s HLA types were identified for vaccine development. Drug recommendations were based on the personalized cancer model. Results: The integration of multi-omics data revealed complex molecular alterations and identified potential neoantigens for personalized vaccine development. Drug recommendations included Endostatin, EGFR inhibitors, and Enoblituzumab, tailored to the patient’s tumor profile. Conclusion: This study demonstrates that integrating advanced sequencing technologies and personalized treatment strategies can significantly enhance lung cancer therapy. Validation in clinical settings is essential to confirm the effectiveness of these personalized approaches in improving patient outcomes.
Keywords: Lung cancer, Next-Generation Sequencing (NGS), Personalized immunotherapy, Neoantigens, Proteomics
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