Unique molecular identifiers / molecular barcodes 

Detection of cancer-associated somatic mutations is challenging when cancer-derived DNA is in low abundance, such as in impure tissue specimens or in circulating free-DNA. Next-generation sequencing is particularly prone to technical artefacts that can limit the accuracy for calling low-allele-frequency mutations. State-of-the-art methods to improve detection of low-frequency mutations often employ unique molecular identifiers (UMIs) for error suppression; however, these methods are highly inefficient as they depend on redundant sequencing to assemble consensus sequences. We developed a novel strategy to enhance the efficiency of UMI-based error suppression by retaining single reads (singletons) that can participate in consensus assembly. This ‘Singleton Correction’ methodology outperformed other duplex UMI strategies in efficiency, leading to greater sensitivity with high specificity. Singleton Correction can also be incorporated into existing UMI-based error suppression workflows to boost mutation detection accuracy, thus improving the cost-effectiveness and clinical impact of sequencing.

We developed ConsensusCruncher, a tool that suppresses errors in next-generation sequencing data by using Unique Molecular Identifiers (UMIs). We amalgamate reads derived from the same DNA template, indicated by a common UMI, into a consensus sequence using Singleton Correction (https://github.com/pughlab/ConsensusCruncher).

High efficiency error suppression for accurate detection of low-frequency variants
Ting Ting Wang, Sagi Abelson, Jinfeng Zou, Tiantian Li, Zhen Zhao, John E Dick, Liran I Shlush, Trevor J Pugh, Scott V Bratman
Nucleic Acids Research, gkz474, https://doi.org/10.1093/nar/gkz474 PMID 31127310

Targeted sequencing

Targeted sequencing can allow the interrogation of multiple loci with high sensitivity achieved through error correction to suppress background noises. We use hybrid capture to focus on a subset of the genome, which can range from a few genes or mutation loci to a larger proportion of the genome, such as the exome. We design custom targeted sequencing panels that are gene-specific or patient-specific using mutations identified from a patient’s tumour sample. While targeted sequencing can enable the assessment of a larger number of loci, current off-the-shelf panels can only detect mutations with an allele fraction greater than 1%. By reducing the background error rates of sequencing using molecular barcoding, we can detect mutations at allele fractions below 0.1%. 

Liquid Biopsy Sequencing (LB-Seq)

Our laboratory and computational methods for generation and analysis of DNA sequence from circulating tumour DNA.

More details here.
 

cfMeDIP-seq

Cell-free Methylated DNA Immunoprecipitation and high-throughput sequencing, or cfMeDIP-seq, is an improved way to detect and analyze tumour DNA from blood samples. This method is based on analyzing patterns in how the DNA is modified – more specifically, methylated – rather than the common approach of analyzing variations in the DNA sequence itself. It presents an alternative to current liquid biopsies that often lack the accuracy and sensitivity required for clinical use. This type of blood test analyzes the rare traces of tumour DNA that are circulating in the blood, but distinguishing tumour DNA from healthy DNA is both difficult and expensive. The advantages of cfMeDIP-seq over liquid biopsies are numerous:

  1. cfMeDIP-seq examines the methylation patterns across the entire genome, unlike the traditional liquid biopsies which often examine specific areas of a tumour’s genome and look for predefined markers of disease. This could allow cfMeDIP-seq to detect cancers that may not have common or well-defined mutations, such as certain brain cancers, and in some cases determine the disease’s aggressiveness.
  2. cfMeDIP-seq has also the potential to differentiate between cancer types, something that was not possible with traditional liquid biopsies. This opens the opportunity to detect cancer and its tissue of origin from a blood sample in its early stages, before the disease is detectable by a CT or MRI scan.
  3. cfMeDIP-seq could offer earlier tumour detection, more accurate cancer staging, less-invasive monitoring of the disease, and a better understanding of how a patient’s cancer evolves throughout treatment since methylation patterns in circulating DNA can be very informative.