Evidence map›Paper›PMID 22585170›Full record

ArticleCancer discovery2012

High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing.

Nikhil Wagle, Michael F Berger, Matthew J Davis, Brendan Blumenstiel, Matthew Defelice, Panisa Pochanard, Matthew Ducar, Paul Van Hummelen, Laura E Macconaill, William C Hahn and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Cancer discovery, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 314 papers.

0numbers the graph read from it
0cells of the map it votes in
314citing papers in PubMed
15.8field-weighted citation impact, top 1% 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

314 citing papers in PubMed, 537 citations in OpenAlex.

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  6. PD-1 Blockade in Advanced Adrenocortical Carcinoma.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2020
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  7. Phase II Study of Avelumab in Patients With Mismatch Repair Deficient and Mismatch Repair Proficient Recurrent/Persistent Endometrial Cancer.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2019
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  11. Cancer discovery · 2018
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254 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 3 institutions in 1 country.

Nikhil WagleDepartment of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.
Michael F Berger
Matthew J Davis
Brendan Blumenstiel
Matthew Defelice
Panisa Pochanard
Matthew Ducar
Paul Van Hummelen
Laura E Macconaill
William C Hahn
Matthew Meyerson
Stacey B Gabriel
Levi A Garraway
Broad Institute · USHarvard University · USDana-Farber Cancer Institute · US

Funding

Large Scale Sequencing and Analysis of GenomesU54HG003067 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GABRIEL, STACEY, LANDER, ERIC S · 2004 to 2015
$568.6M
Physician Scientist Training in Cancer ResearchT32CA009172 · NCI · DANA-FARBER CANCER INSTITUTE · PI Jennifer R Brown, James A. DeCaprio · 1985 to 2026
$17.1M
Genome Characterization Center (GCC)U24CA143867 · NCI · BROAD INSTITUTE, INC. · PI GABRIEL, STACEY, MEYERSON, MATTHEW L. · 2009 to 2016
$17.0M
Therapeutic Opportunities for Pediatric AstrocytomaP01CA142536 · NCI · DANA-FARBER CANCER INST · PI LIGON, KEITH LLOYD · 2011 to 2015
$7.9M
Defining Melanoma Therapeutic Avenues by Integrative Functional GenomicsDP2OD002750 · OD · DANA-FARBER CANCER INST · PI GARRAWAY, LEVI ALEXANDER · 2007 to 2007
$2.6M
High-Throughput Tumor Genomic Profiling by Massively Parallel SequencingR33CA155554 · NCI · DANA-FARBER CANCER INST · PI GARRAWAY, LEVI A., MACCONAILL, LAURA E · 2011 to 2013
$717k
High-throughput oncogene mutation detection in human cancerR33CA126674 · NCI · DANA-FARBER CANCER INST · PI GARRAWAY, LEVI A. · 2010 to 2011
$608k
NCI NIH HHS P01 CA142536NCI NIH HHS R33 CA126674NCI NIH HHS R33CA126674NCI NIH HHS R33 CA155554NCI NIH HHS T32 CA009172NCI NIH HHS U24 CA143867NCI NIH HHS U24CA143867NHGRI NIH HHS U54 HG003067NIH HHS DP2 OD002750NIH HHS DP2OD002750
6 · The paper itself

Abstract

unlabelledKnowledge of "actionable" somatic genomic alterations present in each tumor (e.g., point mutations, small insertions/deletions, and copy-number alterations that direct therapeutic options) should facilitate individualized approaches to cancer treatment. However, clinical implementation of systematic genomic profiling has rarely been achieved beyond limited numbers of oncogene point mutations. To address this challenge, we utilized a targeted, massively parallel sequencing approach to detect tumor genomic alterations in formalin-fixed, paraffin-embedded (FFPE) tumor samples. Nearly 400-fold mean sequence coverage was achieved, and single-nucleotide sequence variants, small insertions/deletions, and chromosomal copynumber alterations were detected simultaneously with high accuracy compared with other methods in clinical use. Putatively actionable genomic alterations, including those that predict sensitivity or resistance to established and experimental therapies, were detected in each tumor sample tested. Thus, targeted deep sequencing of clinical tumor material may enable mutation-driven clinical trials and, ultimately, "personalized" cancer treatment. SIGNIFICANCE: Despite the rapid proliferation of targeted therapeutic agents, systematic methods to profile clinically relevant tumor genomic alterations remain underdeveloped. We describe a sequencingbased approach to identifying genomic alterations in FFPE tumor samples. These studies affirm the feasibility and clinical utility of targeted sequencing in the oncology arena and provide a foundation for genomics-based stratification of cancer patients.

Indexed as

Cell Line, TumorDNA Mutational AnalysisGene DosageHigh-Throughput Nucleotide SequencingHumansNeoplasms

Identifiers

PMID22585170
PMCPMC3353152
OpenAlexW2130940380

What OpenQuestion holds

Textmetadata
LicenceTDM
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.