Cancer research and sequencing

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We’re really excited about this novel RNA isoform discovery that’s enabled by this platform

Daniel Kim, University of California, Santa Cruz, USA

  • Icon displaying a graphic of cancerous cells
    Discover novel cancer biomarkers and identify known signatures with the most comprehensive genomics platform
  • Icon displaying a graphic of any length nanopore reads
    Detect SVs, SNVs, and CNVs at the haplotype level and resolve full-length RNA isoforms with any-length reads
  • Icon displaying a graphic of epigenetic base modification detection
    Simultaneously detect epigenetic base modifications by directly sequencing native DNA/RNA
Intro

Reveal more cancer biology with ultra-rich nanopore sequencing data

The genetic underpinnings of cancer are diverse and many types of genomic aberration — from single nucleotide variants (SNVs) to structural variants (SVs), copy number variants (CNVs), fusion transcripts, and epigenetic modifications (e.g. DNA/RNA methylation) — can cause, contribute to, or indicate disease. As a result, researchers traditionally relied on multiple techniques to identify and analyse different facets of cancer. Now, with nanopore technology, researchers can generate sequencing reads of any length, including ultra-long reads (>4 Mb achieved) that can span complex genomic regions. This, combined with integrated base modification detection and real-time results, means that nanopore sequencing delivers a streamlined and rapid solution for complete characterisation of cancer and tumour samples.

Technology comparison

Oxford Nanopore sequencing

Legacy short-read sequencing

Any read length (20 bp to >4 Mb)

Short read length (<300 bp)

  • Assembly contiguity is reduced and complex computational analyses are required to infer results
  • Complex genomic regions such as SVs and repeat elements typically cannot be sequenced in single reads (e.g. transposons, gene duplications, and prophage sequences)
  • Transcript analysis is limited to gene-level expression data
  • Important genetic information is missed

Direct sequencing of native DNA/RNA

Amplification required

  • Eliminate amplification- and GC-bias, along with read length limitations, and access genomic regions that are difficult to amplify
  • Detect epigenetic modifications, such as methylation, as standard — no additional, time-consuming sample prep required
  • Create cost-effective, amplification-free, targeted panels with adaptive sampling to detect SVs, repeats, SNVs, and methylation in a single assay
  • Amplification is often required and can introduce bias
  • Base modifications are removed, necessitating additional sample prep, sequencing runs, and expense
  • Uniformity of coverage is reduced, resulting in assembly gaps

Real-time data streaming

Fixed run time with bulk data delivery

  • Analyse data as it is generated for immediate access to actionable results
  • Stop sequencing when sufficient data is obtained — wash and reuse flow cell
  • Combine real-time data streaming with intuitive, real-time EPI2ME data analysis workflows for deeper insights
  • Time to result is increased
  • Workflow errors cannot be identified until it is too late
  • Additional complexities of handling large volumes of bulk data

Accessible and affordable sequencing

Constrained to centralised labs

  • Sequence on demand with flexible end-to-end workflows that suit your throughput needs
  • Sequence at sample source, even in the most extreme or remote environments, with the portable MinION device — minimise potential sample degradation caused by storage and shipping
  • Scale up with modular GridION and PromethION devices — suitable for high-output, high-throughput sequencing to generate ultra-rich data
  • Perform cost-effective targeted analyses with single-use Flongle Flow Cells
  • Sequence as and when needed using low-cost, independently addressable flow cells — no sample batching needed
  • Use sample barcodes to multiplex samples on a single flow cell
  • Bulky, expensive devices that require substantial site infrastructure — use is restricted to well-resourced, centralised locations, limiting global accessibility
  • High sample batching is required for optimal efficiency, delaying time to results

Streamlined, automatable workflows

Laborious workflows

  • Lengthy sample prep is required
  • Long sequencing run times
  • Workflow efficiency is reduced, and time to result is increased