Rapid-CNS2: Rapid comprehensive adaptive nanopore-sequencing of CNS tumors, a proof of concept study

Background: The 2021 WHO classification of central nervous system tumors includes multiple molecular markers and patterns that are recommended for routine diagnostic use in addition to histology. Sequencing infrastructures for complete molecular profiling require considerable investment, while batching samples for sequencing and methylation profiling can delay turnaround time. We introduce RAPID-CNS2, a nanopore adaptive sequencing pipeline that enables comprehensive mutational, methylation and copy number profiling of CNS tumours with a single, cost-effective sequencing assay. It can be run for single samples and offers highly flexible target selection that can be personalized per case with no additional library preparation. Methods: Utilizing ReadFish, a toolkit enabling targeted nanopore sequencing without the need for library enrichment, we sequenced DNA from 22 diffuse glioma samples on a MinION device. Target regions comprised our Heidelberg brain tumor NGS panel and pre-selected CpG sites for methylation classification using an adapted random forest classifier. Pathognomonic alterations, copy number profiles, and methylation classes were called using a custom bioinformatics pipeline. The resulting data were compared to their corresponding standard NGS panel sequencing and EPIC methylation array results. Results: Complete concordance with the EPIC array was found for copy number profiles. The vast majority (94%) of pathognomonic mutations were congruent with standard NGS panel-seq data. MGMT promoter status was correctly identified in all samples. Methylation families from the random forest classifier were detected with 96% congruence. Among the alterations decisive for rendering a WHO 2021 classification-compatible integrated diagnosis, 97% of the alterations were consistent over the entire cohort (completely congruent in 19/22 cases and sufficient for unequivocal diagnosis in all 22 samples). Conclusions: RAPID-CNS2 provides a swift and highly flexible alternative to conventional NGS and array-based methods for SNV/InDel analysis, detection of copy number alterations, target gene methylation analysis (e.g. MGMT) and methylation-based classification. The turnaround time of ~5 days for this proof-of-concept study can be further shortened to < 24h by optimizing target sizes and enabling real-time computational analysis. Expected advances in nanopore sequencing and analysis hardware make the prospect of integrative molecular diagnosis in an intra-operative setting a feasible prospect in future. This low-capital approach would be cost-efficient for low throughput settings or in locations with less sophisticated laboratory infrastructure, and invaluable in cases requiring immediate diagnoses.

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PATH-48. RAPID-CNS2: RAPID COMPREHENSIVE ADAPTIVE NANOPORE-SEQUENCING OF CNS TUMORS, A PROOF OF CONCEPT STUDY

Neuro-Oncology ◽

10.1093/neuonc/noab196.500 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi126-vi126

Author(s):

Areeba Patel ◽

Helin Dogan ◽

Alexander Payne ◽

Philipp Sievers ◽

Natalie Schoebe ◽

...

Keyword(s):

Copy Number ◽

Target Selection ◽

Turnaround Time ◽

Diffuse Glioma ◽

Nanopore Sequencing ◽

Bioinformatics Pipeline ◽

Entire Cohort ◽

Integrated Diagnosis ◽

Cost Efficient ◽

Epic Array

Abstract BACKGROUND The WHO classification 2021 includes multiple molecular markers for routine diagnostics in addition to histology. Sequencing setup for complete molecular profiling requires considerable investment, while batching samples for sequencing and methylation profiling can delay turnaround time. We introduce RAPID-CNS2, a nanopore adaptive sequencing pipeline that enables comprehensive mutational, methylation and copy number profiling of CNS tumours with a single third generation sequencing assay. It can be run for single samples and offers highly flexible target selection requiring no additional library preparation. METHODS Utilising ReadFish, a toolkit enabling targeted nanopore sequencing, we sequenced DNA from 22 diffuse glioma patient samples on a MinION device. Target regions comprised our Heidelberg brain tumour NGS panel and pre-selected CpG sites for methylation classification by an adapted random forest classifier. Pathognomonic alterations, copy number profiles, and methylation classes were called using a custom bioinformatics pipeline. Results were compared to their corresponding NGS panel-seq and EPIC array outputs. RESULTS Complete concordance with the EPIC array was found for copy number profiles from RAPID-CNS2. 94% pathognomonic mutations were congruent with NGS panel-seq. MGMT promoter status was correctly identified in all samples. Methylation families were detected with 96% congruence. Among the alterations decisive for rendering a classification-compatible integrated diagnosis, 97% of the alterations were consistent over the entire cohort (completely congruent in 19/22 cases and sufficient for unequivocal diagnosis in all). CONCLUSIONS RAPID-CNS2 provides a swift and highly flexible alternative to conventional NGS and array- based methods for SNV/Indel analysis, detection of copy number alterations and methylation classification. The turnaround time of ~4 days can be further shortened to < 12h by altering target sizes. It offers a low-capital approach that would be cost-efficient for low throughput settings and invaluable in cases requiring immediate diagnoses.

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P07.04 Rapid-CNS2: Rapid comprehensive adaptive nanopore-sequencing of CNS tumors, a proof of concept study

Neuro-Oncology ◽

10.1093/neuonc/noab180.087 ◽

2021 ◽

Vol 23 (Supplement_2) ◽

pp. ii25-ii26

Author(s):

H Dogan ◽

A Patel ◽

C Herold-Mende ◽

S Pfister ◽

W Wick ◽

...

Keyword(s):

Copy Number ◽

Target Selection ◽

Turnaround Time ◽

Diffuse Glioma ◽

Nanopore Sequencing ◽

Bioinformatics Pipeline ◽

Entire Cohort ◽

Integrated Diagnosis ◽

Cost Efficient ◽

Epic Array

Abstract BACKGROUND The WHO classification 2021 includes multiple molecular markers for routine diagnostics in addition to histology. Sequencing setup for complete molecular profiling requires considerable investment, while batching samples for sequencing and methylation profiling can delay turnaround time. We introduce RAPID-CNS2, a nanopore adaptive sequencing pipeline that enables comprehensive mutational, methylation and copy number profiling of CNS tumours with a single third generation sequencing assay. It can be run for single samples and offers highly flexible target selection requiring no additional library preparation. MATERIAL AND METHODS Utilising ReadFish, a toolkit enabling targeted nanopore sequencing, we sequenced DNA from 22 diffuse glioma patient samples on a MinION device. Target regions comprised our Heidelberg brain tumour NGS panel and pre-selected CpG sites for methylation classification by an adapted random forest classifier. Pathognomonic alterations, copy number profiles, and methylation classes were called using a custom bioinformatics pipeline. Results were compared to their corresponding NGS panel-seq and EPIC array outputs. RESULTS Complete concordance with the EPIC array was found for copy number profiles from RAPID-CNS2. 94% pathognomonic mutations were congruent with NGS panel-seq. MGMT promoter status was correctly identified in all samples. Methylation families were detected with 96% congruence. Among the alterations decisive for rendering a classification-compatible integrated diagnosis, 97% of the alterations were consistent over the entire cohort (completely congruent in 19/22 cases and sufficient for unequivocal diagnosis in all). CONCLUSION RAPID-CNS2 provides a swift and highly flexible alternative to conventional NGS and array-based methods for SNV/Indel analysis, detection of copy number alterations and methylation classification. The turnaround time of ~4 days can be further shortened to <12h by altering target sizes. It offers a low-capital approach that would be cost-efficient for low throughput settings and invaluable in cases requiring immediate diagnoses.

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PATH-17. INTRAGENIC COPY NUMBER BREAKPOINT ANALYSIS OF METHYLATION DATA FROM CNS TUMOURS IDENTIFIES NOVEL SUBGROUP-SPECIFIC CANDIDATE FUSION GENE ENRICHMENTS

Neuro-Oncology ◽

10.1093/neuonc/noaa222.652 ◽

2020 ◽

Vol 22 (Supplement_3) ◽

pp. iii427-iii428

Author(s):

Alan Mackay ◽

Yura Grabovska ◽

Matthew Clarke ◽

Diana Carvalho ◽

Sara Temelso ◽

...

Keyword(s):

Copy Number ◽

Fusion Gene ◽

High Grade Glioma ◽

Structural Variations ◽

Methylation Array ◽

Kinase Gene ◽

Integrated Diagnosis ◽

Cns Tumours ◽

Breakpoint Analysis ◽

Balanced Translocations

Abstract Methylation array-based molecular profiling has redefined the classification of brain tumours and now forms an important part of their integrated diagnosis, providing both subgroup assignment and genome wide DNA copy number profiles. These latter data can be used to identify intragenic breakpoints which are frequently associated with structural variations resulting in therapeutically targetable oncogenic fusion genes. To systematically assess the landscape of these alterations, we combined publicly available methylation datasets resulting in a total of 5660 CNS tumours, around half paediatric, and including >1000 high grade glioma and DIPG. These were analysed by standard methodology (MNP, conumee), and intragenic breakpoint enrichment was compared within methylation subgroups, superfamilies, and tumours with no high-scoring classification. Benchmarking included sequence-verified cases such as infant hemispheric gliomas (IHG) with ALK(15%) and ROS1(7%) fusions, and pathognomic alterations associated with specific entities such as RELA-EPN, MYB-LGG and HGNET-MN1. We identified previously unreported enrichments of well-recognised fusion targets such as NTRK2in GBM_MID and NTRK3in DMG_K27 (both 5%), METin A_IDH / A_IDH_HG (3–5%), and FGFR1/3in GBM_G34 (8–9%). Novel recurrent kinase gene candidates to be verified and explored further include IGF1Rin 2–12% cases spanning glioma subgroups, and TIE1in poorly classified tumours. This latter ‘NOS’ group were also enriched in various transcription factor targets of breakpoints, including TCF4and PLAGL2. Despite limitations due to sample quality, resolution or balanced translocations, breakpoint analysis of methylation copy number profiles provides simple screening for structural rearrangements which may directly influence targeted therapy in paediatric CNS tumours.

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The Application of Nanopore Sequencing Technology to the Study of Dinoflagellates: A Proof of Concept Study for Rapid Sequence-Based Discrimination of Potentially Harmful Algae

Frontiers in Microbiology ◽

10.3389/fmicb.2020.00844 ◽

2020 ◽

Vol 11 ◽

Cited By ~ 1

Author(s):

Robert G. Hatfield ◽

Frederico M. Batista ◽

Timothy P. Bean ◽

Vera G. Fonseca ◽

Andres Santos ◽

...

Keyword(s):

Harmful Algae ◽

Nanopore Sequencing ◽

Proof Of Concept ◽

Sequencing Technology ◽

Concept Study ◽

Rapid Sequence

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Validation of DNA Methylation to Predict Outcome in Acute Myeloid Leukemia by Use of xMELP

Clinical Chemistry ◽

10.1373/clinchem.2014.229781 ◽

2015 ◽

Vol 61 (1) ◽

pp. 249-258 ◽

Cited By ~ 8

Author(s):

Gerald B W Wertheim ◽

Catherine Smith ◽

Marlise Luskin ◽

Alison Rager ◽

Maria E Figueroa ◽

...

Keyword(s):

Dna Methylation ◽

Acute Myeloid Leukemia ◽

Random Forest ◽

Myeloid Leukemia ◽

Clinical Laboratory ◽

Methylation Status ◽

Turnaround Time ◽

Random Forest Classifier ◽

Multiple Loci ◽

Acute Myeloid

Abstract BACKGROUND Epigenetic dysregulation involving alterations in DNA methylation is a hallmark of various types of cancer, including acute myeloid leukemia (AML). Although specific cancer types and clinical aggressiveness of tumors can be determined by DNA methylation status, the assessment of DNA methylation at multiple loci is not routinely performed in the clinical laboratory. METHODS We recently described a novel microsphere-based assay for multiplex evaluation of DNA methylation. In the current study, we validated and used an improved assay [termed expedited microsphere HpaII small fragment Enrichment by Ligation-mediated PCR (xMELP)] that can be performed with appropriate clinical turnaround time. RESULTS Using the xMELP assay in conjunction with a new 17-locus random forest classifier that has been trained using 344 AML samples, we were able to segregate an independent cohort of 70 primary AML patients into methylation-determined subgroups with significantly distinct mortality risk (P = 0.009). We also evaluated precision, QC parameters, and preanalytic variables of the xMELP assay and determined the sensitivity of the random forest classifier score to failure at 1 or more loci. CONCLUSIONS Our results demonstrate that xMELP performance is suitable for implementation in the clinical laboratory and predicts AML outcome in an independent patient cohort.

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