Dataset Information

Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing.

ABSTRACT: As more clinically relevant cancer genes are identified, comprehensive diagnostic approaches are needed to match patients to therapies, raising the challenge of optimization and analytical validation of assays that interrogate millions of bases of cancer genomes altered by multiple mechanisms. Here we describe a test based on massively parallel DNA sequencing to characterize base substitutions, short insertions and deletions (indels), copy number alterations and selected fusions across 287 cancer-related genes from routine formalin-fixed and paraffin-embedded (FFPE) clinical specimens. We implemented a practical validation strategy with reference samples of pooled cell lines that model key determinants of accuracy, including mutant allele frequency, indel length and amplitude of copy change. Test sensitivity achieved was 95-99% across alteration types, with high specificity (positive predictive value >99%). We confirmed accuracy using 249 FFPE cancer specimens characterized by established assays. Application of the test to 2,221 clinical cases revealed clinically actionable alterations in 76% of tumors, three times the number of actionable alterations detected by current diagnostic tests.

SUBMITTER: Frampton GM

PROVIDER: S-EPMC5710001 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing.

Frampton Garrett M GM Fichtenholtz Alex A Otto Geoff A GA Wang Kai K Downing Sean R SR He Jie J Schnall-Levin Michael M White Jared J Sanford Eric M EM An Peter P Sun James J Juhn Frank F Brennan Kristina K Iwanik Kiel K Maillet Ashley A Buell Jamie J White Emily E Zhao Mandy M Balasubramanian Sohail S Terzic Selmira S Richards Tina T Banning Vera V Garcia Lazaro L Mahoney Kristen K Zwirko Zac Z Donahue Amy A Beltran Himisha H Mosquera Juan Miguel JM Rubin Mark A MA Dogan Snjezana S Hedvat Cyrus V CV Berger Michael F MF Pusztai Lajos L Lechner Matthias M Boshoff Chris C Jarosz Mirna M Vietz Christine C Parker Alex A Miller Vincent A VA Ross Jeffrey S JS Curran John J Cronin Maureen T MT Stephens Philip J PJ Lipson Doron D Yelensky Roman R

Nature biotechnology 20131020 11

As more clinically relevant cancer genes are identified, comprehensive diagnostic approaches are needed to match patients to therapies, raising the challenge of optimization and analytical validation of assays that interrogate millions of bases of cancer genomes altered by multiple mechanisms. Here we describe a test based on massively parallel DNA sequencing to characterize base substitutions, short insertions and deletions (indels), copy number alterations and selected fusions across 287 cance ...[more]

PMID: 24142049

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Project description:BackgroundVariation of microorganism communities in the rumen of cattle (Bos taurus) is of great interest because of possible links to economically or environmentally important traits, such as feed conversion efficiency or methane emission levels. The resolution of studies investigating this variation may be improved by utilizing untargeted massively parallel sequencing (MPS), that is, sequencing without targeted amplification of genes. The objective of this study was to develop a method which used MPS to generate "rumen metagenome profiles", and to investigate if these profiles were repeatable among samples taken from the same cow. Given faecal samples are much easier to obtain than rumen fluid samples; we also investigated whether rumen metagenome profiles were predictive of faecal metagenome profiles.ResultsRather than focusing on individual organisms within the rumen, our method used MPS data to generate quantitative rumen micro-biome profiles, regardless of taxonomic classifications. The method requires a previously assembled reference metagenome. A number of such reference metagenomes were considered, including two rumen derived metagenomes, a human faecal microflora metagenome and a reference metagenome made up of publically available prokaryote sequences. Sequence reads from each test sample were aligned to these references. The "rumen metagenome profile" was generated from the number of the reads that aligned to each contig in the database. We used this method to test the hypothesis that rumen fluid microbial community profiles vary more between cows than within multiple samples from the same cow. Rumen fluid samples were taken from three cows, at three locations within the rumen. DNA from the samples was sequenced on the Illumina GAIIx. When the reads were aligned to a rumen metagenome reference, the rumen metagenome profiles were repeatable (P?<?0.00001) by cow regardless of location of sampling rumen fluid. The repeatability was estimated at 9%, albeit with a high standard error, reflecting the small number of animals in the study. Finally, we compared rumen microbial profiles to faecal microbial profiles. Our hypothesis, that there would be a stronger correlation between faeces and rumen fluid from the same cow than between faeces and rumen fluid from different cows, was not supported by our data (with much greater significance of rumen versus faeces effect than animal effect in mixed linear model).ConclusionsWe have presented a simple and high throughput method of metagenome profiling to assess the similarity of whole metagenomes, and illustrated its use on two novel datasets. This method utilises widely used freeware. The method should be useful in the exploration and comparison of metagenomes.

Dataset Information

Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing.

Publications

Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing.

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