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      Integration of whole-exome and anchored PCR-based next generation sequencing significantly increases detection of actionable alterations in precision oncology

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          Highlights

          • NGS-based clinical studies have reported detection of clinically relevant alterations in ∼30% of patients.

          • To increase the detection of potential targets, we integrated whole-exome sequencing with a multiplex PCR-based NGS assay for fusion detection.

          • The targeted transcriptome sequencing was performed using a very low RNA input from archival cancer tissues.

          • With this integrated approach, we demonstrate a significant increase in detection of targetable genomic alterations in cancer patients.

          Abstract

          Background

          Frequency of clinically relevant mutations in solid tumors by targeted and whole-exome sequencing is ∼30%. Transcriptome analysis complements detection of actionable gene fusions in advanced cancer patients. Goal of this study was to determine the added value of anchored multiplex PCR (AMP)-based next-generation sequencing (NGS) assay to identify further potential drug targets, when coupled with whole-exome sequencing (WES).

          Methods

          Selected series of fifty-six samples from 55 patients enrolled in our precision medicine study were interrogated by WES and AMP-based NGS. RNA-seq was performed in 19 cases. Clinically relevant and actionable alterations detected by three methods were integrated and analyzed.

          Results

          AMP-based NGS detected 48 fusions in 31 samples (55.4%); 31.25% (15/48) were classified as targetable based on published literature. WES revealed 29 samples (51.8%) harbored targetable alterations. TMB-high and MSI-high status were observed in 12.7% and 1.8% of cases. RNA-seq from 19 samples identified 8 targetable fusions (42.1%), also captured by AMP-based NGS. When number of actionable fusions detected by AMP-based NGS were added to WES targetable alterations, 66.1% of samples had potential drug targets. When both WES and RNA-seq were analyzed, 57.8% of samples had targetable alterations.

          Conclusions

          This study highlights importance of an integrative genomic approach for precision oncology, including use of different NGS platforms with complementary features. Integrating RNA data (whole transcriptome or AMP-based NGS) significantly enhances detection of potential targets in cancer patients. In absence of fresh frozen tissue, AMP-based NGS is a robust method to detect actionable fusions using low-input RNA from archival tissue.

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          Most cited references59

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              Efficacy of Larotrectinib in TRK Fusion–Positive Cancers in Adults and Children

              Fusions involving one of three tropomyosin receptor kinases (TRK) occur in diverse cancers in children and adults. We evaluated the efficacy and safety of larotrectinib, a highly selective TRK inhibitor, in adults and children who had tumors with these fusions.
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                Author and article information

                Contributors
                Journal
                Transl Oncol
                Transl Oncol
                Translational Oncology
                Neoplasia Press
                1936-5233
                12 November 2020
                January 2021
                12 November 2020
                : 14
                : 1
                : 100944
                Affiliations
                [a ]Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, United States
                [b ]Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine and NewYork Presbyterian, New York, NY, United States
                [c ]Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, United States
                [d ]Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, United States
                [e ]Department of Medicine, Weill Cornell Medicine, New York, NY, United States
                Author notes
                [* ]Corresponding author. jmm9018@ 123456med.cornell.edu
                [±]

                Current address (R. Rao): Montefiore Medical Center, 111 East 210th Street, Bronx NY 10467.

                [§]

                Current address (H. Beltran): Dana Farber Cancer Institute, 450 Brookline Avenue, Boston MA 02215.

                [1]

                These authors contributed equally to this work.

                [2]

                These authors share senior authorship.

                Article
                S1936-5233(20)30436-8 100944
                10.1016/j.tranon.2020.100944
                7674614
                33190043
                fd225688-7376-41ee-a808-8fc2e2a3b3bb
                © 2020 The Authors. Published by Elsevier Inc.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 28 June 2020
                : 17 October 2020
                : 22 October 2020
                Categories
                Original article

                anchored multiplex pcr-based next-generation sequencing,whole-exome sequencing,rna sequencing,novel fusion,oncogenic

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