Development of Personalized Tumor Biomarkers Using Massively Parallel Sequencing

Abstract

Clinical management of human cancer is dependent on the accurate monitoring of residual and recurrent tumors. The evaluation of patient-specific translocations in leukemias and lymphomas has revolutionized diagnostics for these diseases. We have developed a method, called personalized analysis of rearranged ends (PARE), which can identify translocations in solid tumors. Analysis of four colorectal and two breast cancers with massively parallel sequencing revealed an average of nine rearranged sequences (range, 4 to 15) per tumor. Polymerase chain reaction with primers spanning the breakpoints was able to detect mutant DNA molecules present at levels lower than 0.001% and readily identified mutated circulating DNA in patient plasma samples. This approach provides an exquisitely sensitive and broadly applicable approach for the development of personalized biomarkers to enhance the clinical management of cancer patients.

Cancer stem cell definitions and terminology: the devil is in the details

“…Interestingly, non-malignant clones bearing the genetic hallmarks of malignant clones have been reported to be commonly present at detectable levels in normal individuals [99][100][101][102] . Whole-genome sequencing now offers an approach to discriminate different subclones and their clonal relationships and mode of evolution with unprecedented power, particularly if this methodology can be made usefully applicable to blood or other body fluids 103 . Thus, as sequencing costs decrease, it seems likely that such approaches will aid the use of MRD assessments to predict the likelihood of relapse.…”

Direct mutation analysis by high-throughput sequencing: From germline to low-abundant, somatic variants

“…The mate-pair approach produces a considerably higher mapping coverage of the genome from the same number of reads and provides a cost-effective approach for identifying large structural variants genome-wide. Recently two groups used this approach to identify rearrangements in tumor samples[74, 75]. …”

“…High-throughput sequencing is also being used as a tool to monitor disease progression through the identification of cancer-specific rearrangements[74, 75]. After discovering these rearrangements through whole-genome sequencing, simple PCR assays were designed to target the rearrangement signatures in circulating tumor cells in plasma (CTCs) and thereby track disease progression and response to treatments.…”

“…After discovering these rearrangements through whole-genome sequencing, simple PCR assays were designed to target the rearrangement signatures in circulating tumor cells in plasma (CTCs) and thereby track disease progression and response to treatments. A mate-paired sequencing approach was used in one of these studies, with a cost of only $2000 per patient[74]. The ability to track the disease in real-time and monitor the effectiveness of different treatments represents a potentially invaluable tool for clinicians that could reduce both the cost and treatment time associated with ineffective chemotherapy drugs.…”

Review of massively parallel DNA sequencing technologies

“…• Multi-gene diagnostic panels (Morgan et al 2010) • Achieving a molecular diagnosis for rare genetic diseases (Lupski et al 2010;Ng et al 2010a, b;Worthey et al 2011;Vissers et al 2010) • Tissue matching and HLA-typing (Bentley et al 2009;Gabriel et al 2009;Lind et al 2010) • Non-invasive prenatal diagnosis (Chiu et al 2008;Fan et al 2008;Lo et al 2010) • Quantifying the burden of disease from solid tumours (Leary et al 2010;McBride et al 2010) and • Cancer genome profiling leading to stratified treatment regimens Diamandis et al 2010;Stratton et al 2009) RNA sequencing (RNA-seq) and chromatin immunoprecipitation (ChIP) sequencing can also be used to study gene expression and for detection of somatic mutations, gene fusions, and other non-mutational events, an understanding of which can have an impact on management of diseases such as cancer (Cowin et al 2010;Robison 2010). However, numerous barriers to clinical translation still exist, including: validation of the technology; standardisation of the analysis pipeline; integration of information from the numerous databases of genomic variation; building a robust evidence base to allow clinical interpretation of novel variants; developing a service delivery infrastructure that can capitalise upon the high-throughput advantages of new sequencing technologies; providing an appropriately skilled health care workforce to deal with genomic medicine; and addressing the numerous ethical, legal and social implications of sequencing, storing and accessing whole genomes.…”