The Application of Long-Read Sequencing to Cancer.

Simple Summary: Cancer is a complex disease caused by a slew of genetic mutations discovered through advances in sequencing technologies such as next-generation sequencing. While this technology has been useful, it can only retrieve genomic information through short reads or sequences, which is a limitation. A new sequencing technology known as third-generation sequencing overcomes this limitation by using much longer reads. This is a game changer for cancer research, diagnosis and treatment. Third-generation sequencing enables the decipherment of complex genomic rearrangements, resulting in a better understanding of how cancer develops, as well as the examination of the entire transcriptome, revealing isoforms that could be used in diagnostics or treatment. Third-generation sequencing enhances cancer genome assembly, detects epigenetic changes, and can provide a comprehensive picture of a patient's specific cancer aberrations. This has the potential to lead to more effective treatments with fewer adverse effects. This review provides a rigorous scientific analysis of the advantages and limitations of third-generation sequencing, emphasizing its potential for the future of cancer research and personalized medicine. Although this is still a developing technology, it has enormous potential for research and clinical applications, ultimately leading to improved cancer diagnosis and treatment. Cancer is a multifaceted disease arising from numerous genomic aberrations that have been identified as a result of advancements in sequencing technologies. While next-generation sequencing (NGS), which uses short reads, has transformed cancer research and diagnostics, it is limited by read length. Third-generation sequencing (TGS), led by the Pacific Biosciences and Oxford Nanopore Technologies platforms, employs long-read sequences, which have marked a paradigm shift in cancer research. Cancer genomes often harbour complex events, and TGS, with its ability to span large genomic regions, has facilitated their characterisation, providing a better understanding of how complex rearrangements affect cancer initiation and progression. TGS has also characterised the entire transcriptome of various cancers, revealing cancer-associated isoforms that could serve as biomarkers or therapeutic targets. Furthermore, TGS has advanced cancer research by improving genome assemblies, detecting complex variants, and providing a more complete picture of transcriptomes and epigenomes. This review focuses on TGS and its growing role in cancer research. We investigate its advantages and limitations, providing a rigorous scientific analysis of its use in detecting previously hidden aberrations missed by NGS. This promising technology holds immense potential for both research and clinical applications, with far-reaching implications for cancer diagnosis and treatment. [ABSTRACT FROM AUTHOR]

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