The ICR639 CPG NGS validation series: A resource to assess analytical sensitivity of cancer predisposition gene testing

A machine learning approach based on ACMG/AMP guidelines for genomic variant classification and prioritization

Genomic variant interpretation is a critical step of the diagnostic procedure, often supported by the application of tools that may predict the damaging impact of each variant or provide a guidelines-based classification. We propose the application of Machine Learning methodologies, in particular Penalized Logistic Regression, to support variant classification and prioritization. Our approach combines ACMG/AMP guidelines for germline variant interpretation as well as variant annotation features and provides a probabilistic score of pathogenicity, thus supporting the prioritization and classification of variants that would be interpreted as uncertain by the ACMG/AMP guidelines. We compared different approaches in terms of variant prioritization and classification on different datasets, showing that our data-driven approach is able to solve more variant of uncertain significance (VUS) cases in comparison with guidelines-based approaches and in silico prediction tools.

Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study

Assessing the reproducibility, accuracy and utility of massively parallel DNA sequencing platforms remains an ongoing challenge. Here the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Study benchmarks the performance of a set of sequencing instruments (HiSeq/NovaSeq/paired-end 2 × 250-bp chemistry, Ion S5/Proton, PacBio circular consensus sequencing (CCS), Oxford Nanopore Technologies PromethION/MinION, BGISEQ-500/MGISEQ-2000 and GS111) on human and bacterial reference DNA samples. Among short-read instruments, HiSeq 4000 and X10 provided the most consistent, highest genome coverage, while BGI/MGISEQ provided the lowest sequencing error rates. The long-read instrument PacBio CCS had the highest reference-based mapping rate and lowest non-mapping rate. The two long-read platforms PacBio CCS and PromethION/MinION showed the best sequence mapping in repeat-rich areas and across homopolymers. NovaSeq 6000 using 2 × 250-bp read chemistry was the most robust instrument for capturing known insertion/deletion events. This study serves as a benchmark for current genomics technologies, as well as a resource to inform experimental design and next-generation sequencing variant calling.

Assessment of structural chromosomal instability phenotypes as biomarkers of carboplatin response in triple negative breast cancer: the TNT trial

BACKGROUND

In the TNT trial of triple negative breast cancer (NCT00532727), germline BRCA1/2 mutations were present in 28% of carboplatin responders. We assessed quantitative measures of structural chromosomal instability (CIN) to identify a wider patient subgroup within TNT with preferential benefit from carboplatin over docetaxel.

PATIENTS AND METHODS

Copy number aberrations (CNAs) were established from 135 formalin-fixed paraffin-embedded primary carcinomas using Illumina OmniExpress SNP-arrays. Seven published [allelic imbalanced CNA (AiCNA); allelic balanced CNA (AbCNA); copy number neutral loss of heterozygosity (CnLOH); number of telomeric allelic imbalances (NtAI); BRCA1-like status; percentage of genome altered (PGA); homologous recombination deficiency (HRD) scores] and two novel [Shannon diversity index (SI); high-level amplifications (HLAMP)] CIN-measurements were derived. HLAMP was defined based on the presence of at least one of the top 5% amplified cytobands located on 1q, 8q and 10p. Continuous CIN-measurements were divided into tertiles. All nine CIN-measurements were used to analyse objective response rate (ORR) and progression-free survival (PFS).

RESULTS

Patients with tumours without HLAMP had a numerically higher ORR and significantly longer PFS in the carboplatin (C) than in the docetaxel (D) arm [56% (C) versus 29% (D), PHLAMP,quiet = 0.085; PFS 6.1 months (C) versus 4.1 months (D), Pinteraction/HLAMP = 0.047]. In the carboplatin arm, patients with tumours showing intermediate telomeric NtAI and AiCNA had higher ORR [54% (C) versus 20% (D), PNtAI,intermediate = 0.03; 62% (C) versus 33% (D), PAiCNA,intermediate = 0.076]. Patients with high AiCNA and PGA had shorter PFS in the carboplatin arm [3.4 months (high) versus 5.7 months (low/intermediate); and 3.8 months (high) versus 5.6 months (low/intermediate), respectively; Pinteraction/AiCNA = 0.027, Padj.interaction/AiCNA = 0.125 and Pinteraction/PGA = 0.053, Padj.interaction/PGA = 0.176], whilst no difference was observed in the docetaxel arm.

CONCLUSIONS

Patients with tumours lacking HLAMP and demonstrating intermediate CIN-measurements formed a subgroup benefitting from carboplatin relative to docetaxel treatment within the TNT trial. This suggests a complex and paradoxical relationship between the extent of genomic instability in primary tumours and treatment response in the metastatic setting.

The ICR639 CPG NGS validation series: A resource to assess analytical sensitivity of cancer predisposition gene testing

The analytical sensitivity of a next generation sequencing (NGS) test reflects the ability of the test to detect real sequence variation. The evaluation of analytical sensitivity relies on the availability of gold-standard, validated, benchmarking datasets. For NGS analysis the availability of suitable datasets has been limited. Most laboratories undertake small scale evaluations using in-house data, and/or rely on in silico generated datasets to evaluate the performance of NGS variant detection pipelines. Cancer predisposition genes (CPGs), such as BRCA1 and BRCA2, are amongst the most widely tested genes in clinical practice today. Hundreds of providers across the world are now offering CPG testing using NGS methods. Validating and comparing the analytical sensitivity of CPG tests has proved difficult, due to the absence of comprehensive, orthogonally validated, benchmarking datasets of CPG pathogenic variants. To address this we present the ICR639 CPG NGS validation series. This dataset comprises data from 639 individuals. Each individual has sequencing data generated using the TruSight Cancer Panel (TSCP), a targeted NGS assay for the analysis of CPGs, together with orthogonally generated data showing the presence of at least one CPG pathogenic variant per individual. The set consists of 645 pathogenic variants in total. There is strong representation of the most challenging types of variants to detect, with 339 indels, including 16 complex indels and 24 with length greater than five base pairs and 74 exon copy number variations (CNVs) including 23 single exon CNVs. The series includes pathogenic variants in 31 CPGs, including 502 pathogenic variants in BRCA1 or BRCA2, making this an important comprehensive validation dataset for providers of BRCA1 and BRCA2 NGS testing. We have deposited the TSCP FASTQ files of the ICR639 series in the European Genome-phenome Archive (EGA) under accession number EGAD00001004134.