title: Next generation sequencing in cancer: opportunities and challenges for precision cancer medicine.
abstract: Over the past decade, testing the genes of patients and their specific cancer types has become standardized practice in medical oncology since somatic mutations, changes in gene expression and epigenetic modifications are all hallmarks of cancer. However, while cancer genetic assessment has been limited to single biomarkers to guide the use of therapies, improvements in nucleic acid sequencing technologies and implementation of different genome analysis tools have enabled clinicians to detect these genomic alterations and identify functional and disease-associated genomic variants. Next-generation sequencing (NGS) technologies have provided clues about therapeutic targets and genomic markers for novel clinical applications when standard therapy has failed. While Sanger sequencing, an accurate and sensitive approach, allows for the identification of potential novel variants, it is however limited by the single amplicon being interrogated. Similarly, quantitative and qualitative profiling of gene expression changes also represents a challenge for the cancer field. Both RT-PCR and microarrays are efficient approaches, but are limited to the genes present on the array or being assayed. This leaves vast swaths of the transcriptome, including non-coding RNAs and other features, unexplored. With the advent of the ability to collect and analyze genomic sequence data in a timely fashion and at an ever-decreasing cost, many of these limitations have been overcome and are being incorporated into cancer research and diagnostics giving patients and clinicians new hope for targeted and personalized treatment. Below we highlight the various applications of next-generation sequencing in precision cancer medicine.
authors.affiliation: a Department of Cancer Biology , Sidney Kimmel Medical College , Philadelphia , PA , USA ;
authors.forename: Carmela
authors.initials: C
authors.lastname: Paolillo
authors.affiliation: b Computational Medicine Center , Thomas Jefferson University , Philadelphia , PA , USA.
authors.forename: Eric
authors.initials: E
authors.lastname: Londin
authors.affiliation: a Department of Cancer Biology , Sidney Kimmel Medical College , Philadelphia , PA , USA ;
authors.forename: Paolo
authors.initials: P
authors.lastname: Fortina
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D004273:DNA, Neoplasm / Q000235:genetics / Q000378:metabolism; D015894:Genome, Human; D055106:Genome-Wide Association Study; D023281:Genomics / Q000295:instrumentation / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing / Q000191:economics / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D025202:Molecular Diagnostic Techniques / Q000191:economics / Q000295:instrumentation / Q000379:methods*; D009363:Neoplasm Proteins / Q000235:genetics / Q000378:metabolism; D009369:Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D009360:Neoplastic Cells, Circulating / Q000378:metabolism / Q000473:pathology; D020411:Oligonucleotide Array Sequence Analysis; D057285:Precision Medicine / Q000191:economics / Q000295:instrumentation / Q000379:methods*; D017422:Sequence Analysis, DNA; D059467:Transcriptome
chemical_list: D014408:Biomarkers, Tumor; D004273:DNA, Neoplasm; D009363:Neoplasm Proteins
keywords: Cancer genomics; circulating cancer cells; formalin-fixed paraffin-embedded; precision oncology