Evidence map›Paper›PMID 30728399›Full record

ArticleScientific reports2019

Comparison of TCGA and GENIE genomic datasets for the detection of clinically actionable alterations in breast cancer.

Pushpinder Kaur, Tania B Porras, Alexander Ring, John D Carpten, Julie E Lang

Open access · goldAbstract readComparative Study
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.6field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 29 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Pushpinder KaurDepartment of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, United States.
Tania B PorrasDepartment of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, United States.
Alexander RingDepartment of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, United States.
John D CarptenUniversity of Southern California, Norris Comprehensive Cancer Center, Los Angeles, CA, 90033, United States.
Julie E LangDepartment of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, United States. julie.lang@med.usc.edu.
University of Southern California · USUSC Norris Comprehensive Cancer Center · US

Funding

USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fumito Ito · 1985 to 2026
$181.4M
NCI NIH HHS P30 CA014089
6 · The paper itself

Abstract

Whole exome sequencing (WES), targeted gene panel sequencing and single nucleotide polymorphism (SNP) arrays are increasingly used for the identification of actionable alterations that are critical to cancer care. Here, we compared The Cancer Genome Atlas (TCGA) and the Genomics Evidence Neoplasia Information Exchange (GENIE) breast cancer genomic datasets (array and next generation sequencing (NGS) data) in detecting genomic alterations in clinically relevant genes. We performed an in silico analysis to determine the concordance in the frequencies of actionable mutations and copy number alterations/aberrations (CNAs) in the two most common breast cancer histologies, invasive lobular and invasive ductal carcinoma. We found that targeted sequencing identified a larger number of mutational hotspots and clinically significant amplifications that would have been missed by WES and SNP arrays in many actionable genes such as PIK3CA, EGFR, AKT3, FGFR1, ERBB2, ERBB3 and ESR1. The striking differences between the number of mutational hotspots and CNAs generated from these platforms highlight a number of factors that should be considered in the interpretation of array and NGS-based genomic data for precision medicine. Targeted panel sequencing was preferable to WES to define the full spectrum of somatic mutations present in a tumor.

Indexed as

Breast NeoplasmsComputer SimulationDatabases, GeneticDNA Copy Number VariationsExomeFemaleGenomicsHigh-Throughput Nucleotide SequencingHumansMutationPrecision Medicine

Identifiers

PMID30728399
PMCPMC6365517
OpenAlexW2912329425

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.