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Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine | Nature Medicine
Description:
Whole-exome sequencing (WES) has emerged as a transformative technology for biological discovery, but technical difficulties have so far prevented its widespread clinical use. Here, Eliezer Van Allen and colleagues are able to perform production-scale WES on small amounts of clinically acquired formalin-fixed, paraffin-embedded tumor tissues. Using a newly created WES clinical interpretation algorithm, they apply the complete clinical WES framework prospectively to patients and demonstrate how it can be used to directly affect patient care. Translating whole-exome sequencing (WES) for prospective clinical use may have an impact on the care of patients with cancer; however, multiple innovations are necessary for clinical implementation. These include rapid and robust WES of DNA derived from formalin-fixed, paraffin-embedded tumor tissue, analytical output similar to data from frozen samples and clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival formalin-fixed, paraffin-embedded tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a
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nature portfolio permissions reprints privacy policy advertising nature 486 nature 455 nature social media open platform autophagy-related molecular features jak-mutant myeloproliferative neoplasms dana-farber leadership council dana-farber cancer institute paraffin-embedded tumor tissue formaldehyde fixed-paraffin embedded fresh-frozen tissue specimens paraffin-embedded tumor samples precision cancer medicine integrative high-throughput sequencing report generation toolkit springerlink instant access permissions breast cancer subtypes copy-number alterations policy knowledge-based approach pilot study genomics-driven oncology generation sequence data nih u24ca143845 grant analytical output similar facilitating data deposition frozen tumor tissue privacy hypertension-related genes lung cancer biopsies prostate cancer foundation ret gene fusions crkl gene encoding generation sequencing data clinically important genes high-throughput detection data analysis pipelines systems biology approach wes data generally dna-mutation inventory enhance cancer treatment cancer reveal classes broad genomics platform clinical cancer settings
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headline:Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine
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Cancer genomics
Predictive markers
Biomedicine
general
Cancer Research
Metabolic Diseases
Infectious Diseases
Molecular Medicine
Neurosciences
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headline:Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine
description:Whole-exome sequencing (WES) has emerged as a transformative technology for biological discovery, but technical difficulties have so far prevented its widespread clinical use. Here, Eliezer Van Allen and colleagues are able to perform production-scale WES on small amounts of clinically acquired formalin-fixed, paraffin-embedded tumor tissues. Using a newly created WES clinical interpretation algorithm, they apply the complete clinical WES framework prospectively to patients and demonstrate how it can be used to directly affect patient care. Translating whole-exome sequencing (WES) for prospective clinical use may have an impact on the care of patients with cancer; however, multiple innovations are necessary for clinical implementation. These include rapid and robust WES of DNA derived from formalin-fixed, paraffin-embedded tumor tissue, analytical output similar to data from frozen samples and clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival formalin-fixed, paraffin-embedded tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a 'long tail' of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15 out of 16 patients. In one patient, previously undetected findings guided clinical trial enrollment, leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine.
datePublished:2014-05-18T00:00:00Z
dateModified:2014-05-18T00:00:00Z
pageStart:682
pageEnd:688
sameAs:https://doi.org/10.1038/nm.3559
keywords:
Cancer genomics
Predictive markers
Biomedicine
general
Cancer Research
Metabolic Diseases
Infectious Diseases
Molecular Medicine
Neurosciences
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name:Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.,
name:Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,
name:Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.,
name:Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.,
name:Children's Hospital Boston, Boston, USA
name:Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.,
name:Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.,
name:Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.,
name:Department of Pathology, Brigham and Women's Hospital, Boston, USA
name:Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.,
name:Department of Pathology, Brigham and Women's Hospital, Boston, USA
name:Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.,
name:Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.,
name:Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,
name:Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,
name:Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,
name:Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts, USA.,
name:Cancer Center, Massachusetts General Hospital, Boston, Massachusetts, USA.,
name:Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.,
name:Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,
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- Explore the financials of https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=search&term=Nikhil%20Wagle
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- How much does https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=search&term=Jennifer%20Fostel bring in each month?
- Financial intake of https://scholar.google.co.uk/scholar?as_q=&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_sauthors=%22Jennifer%20Fostel%22&as_publication=&as_ylo=&as_yhi=&as_allsubj=all&hl=en
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- https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=search&term=Laura%20MacConaill's revenue stream
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