London Calling 2020: Human translational research breakout: Thidathip Wongsurawat – GLIoma Molecular Marker Enrichment & long-Read Sequencing (GLIMMERS)
Thidathip introduced how glioma is a type of brain tumour that grows from glial cells. It has a high mortality rate and can occur at any age, although it is most common in 45-65-year olds. In 2016, for the first time, the WHO incorporated genotype along with phenotype into the classification of gliomas. The major genetic markers for glioma diagnosis are mutations in the isocitrate dehydrogenase genes, IDH1 and IDH2.
The current standards for glioma treatment include surgical resection, radiation and/or chemotherapy. Temozolomide (TMZ) is one of the FDA-approved chemotherapy agents, but not all patients respond to this drug. In 2005, a study by Monika Hegi et al. showed that this is because only those patients with a methylated MGMT promoter benefit from TMZ. In 2017, the European Association of Neuro-oncology (EANO) recommend that MGMT promoter methylation status was important to test for prior to treatment decision-making. ‘Zooming in’ to the MGMT promoter site, Thidathip explained how it is 841 nt in length, containing 98 CpG sites. There are currently many tests available for analysing its methylation status, however these assays test different CpGs. Therefore, current analysis methods are limited: there is no consensus regarding the CpG sites tested, and current short-read sequencing-based methods involve PCR (associated with PCR bias) and bisulfite treatment, a method which damages the DNA; plus there is a high capital cost, and a 2-week typical turnaround time.
Thidathip explained how we need to move beyond the limitations of the existing assays, and she described how they aimed to investigate the use of nanopore sequencing technology to assess glioma markers. Why choose nanopore sequencing? As it can sequence native DNA, you can simultaneously assess both MGMT methylation and IDH1 and IDH2 mutations. Furthermore, the 841 nucleotide MGMT promoter region can be obtained in single long reads. She stated that it should be possible to make a simple, fast, and cheap assessment.
Explaining how a typical MinION whole-genome sequencing run on a single flow cell would generate ~10 Gb and therefore 3.3x depth of coverage of the ~3 Gb human genome, which is insufficient for accurate detection, Thidathip described how they have been investigating nanopore Cas9-targeted sequencing (nCATS). This can produce up to 3,000x depth of coverage of the target regions. Their experimental approach started with the design of guide RNAs (designed using the CHOPCHOP tool), targeting MGMT (2,216 bp), IDH1 (1,953 bp), and IDH2 (1,293 bp). Next, nCATS was tested on high quality gDNA, then, as results were promising, in four glioma cell lines, and thirdly, four patient tumour samples. Samples were also shipped to different certified labs to test methylation and mutation status, for comparison with nCATS results.
Their results revealed how, for the two high-quality gDNA standards, all 3 targets could be enriched to >100x depth of coverage. MGMT methylation was successfully identified using nCATS; in the sample known to contain >95% methylated CpGs, all of the 98 CpGs at the MGMT promoter were methylated. In contrast, results from pyrosequencing at a CLIA-certified lab investigated the methylation status of only a small number of CpG sites in the promoter, producing a less comprehensive result.
She also demonstrated how their method could enrich for the three targets in all four glioma cell lines tested. Furthermore, by simultaneously extracting DNA and RNA from the same sample at the same time, they could also investigate MGMT expression levels (using qPCR) alongside the methylation analysis. Thidathip stated that the methylation signals they obtained correlated well with the conventional lab results for these cell lines (r=0.73 to 0.94), and the methylation patterns were in line with expectations: the two cell lines with low MGMT methylation also showed high MGMT expression at the RNA level, and vice versa.
Next Thidathip described their experiments performed on patient tumour samples. The challenges of working with tissue samples include: their heterogeneity, blood contamination, high fat content, homogenisation difficulties, and tissue size. She explained how she opted for homogenising the fresh-frozen tissue by mashing the sample by hand. Of the four fresh-frozen samples, two were grade 4 secondary glioblastomas, and two were grade 2 astrocytoma samples. They were selected based on the knowledge that, according to conventional results, they had IDH mutations (determined by Sanger sequencing), and their MGMT methylation status was known (determined by MassARRAY). Thidathip performed nCATS to blindly assess their methylation and mutation status.
Thidathip showed how they could simultaneously assess methylation and mutation profiles in the tumour samples. The IDH mutation statuses agreed with Sanger sequencing and short-read sequencing variant calling results that had been obtained for these samples, and the MGMT methylation status correlated well with that determined using MassARRAY data (r=0.64 to 0.80) and pyrosequencing data. She displayed in more detail how the nCATS method could genotype both pathogenic and non-pathogenic SNVs in MGMT, IDH1, and IDH2, in tumour samples and saliva samples from the same patient, the results of which accorded with variant calling data obtained with short-read sequencing on the same samples.
To conclude, Thidathip stated how they have demonstrated the feasibility of using nCATS as a tool to assess glioma molecular markers. This method is simple, as all targets can be investigated in the same sample, and fast, requiring only 2 days. Current limitations of the method include that it requires a high amount of DNA (3.5-5 µg), and this needs to be intact. In future she plans to add more targets to the workflow, and try the Flongle device for sequencing. She would also like to use this approach for different populations, for which she says that she is open to collaboration.
Original Source -Nanopore website: https://community.nanoporetech.com/posts/lc20-blog-human-translati