Evidence map›Paper›PMID 34855780›Full record

ArticlePloS one2021

A scalable high-throughput targeted next-generation sequencing assay for comprehensive genomic profiling of solid tumors.

Jeffrey M Conroy, Sarabjot Pabla, Sean T Glenn, R J Seager, Erik Van Roey, Shuang Gao, Blake Burgher, Jonathan Andreas, Vincent Giamo, Melissa Mallon and 7 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

32 citing papers in PubMed, 55 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

17 authors at 2 institutions in 1 country.

Jeffrey M ConroyResearch and Development, OmniSeq Inc., Buffalo, New York, United States of America.ORCID 0000-0003-1764-9706
Sarabjot PablaBioinformatics, OmniSeq Inc., Buffalo, New York, United States of America.
Sean T GlennResearch and Development, OmniSeq Inc., Buffalo, New York, United States of America.
R J SeagerBioinformatics, OmniSeq Inc., Buffalo, New York, United States of America.
Erik Van RoeyBioinformatics, OmniSeq Inc., Buffalo, New York, United States of America.
Shuang GaoBioinformatics, OmniSeq Inc., Buffalo, New York, United States of America.
Blake BurgherResearch and Development, OmniSeq Inc., Buffalo, New York, United States of America.
Jonathan AndreasResearch and Development, OmniSeq Inc., Buffalo, New York, United States of America.
Vincent GiamoResearch and Development, OmniSeq Inc., Buffalo, New York, United States of America.
Melissa MallonResearch and Development, OmniSeq Inc., Buffalo, New York, United States of America.
Yong Hee LeeClinical Evidence Development, OmniSeq Inc., Buffalo, New York, United States of America.
Paul DePietroClinical Evidence Development, OmniSeq Inc., Buffalo, New York, United States of America.
Mary NeslineClinical Evidence Development, OmniSeq Inc., Buffalo, New York, United States of America.
Yirong WangInformation Technology, OmniSeq Inc., Buffalo, New York, United States of America.
Felicia L LenzoResearch and Development, OmniSeq Inc., Buffalo, New York, United States of America.
Roger KleinMedical Affairs, OmniSeq Inc., Buffalo, New York, United States of America.ORCID 0000-0002-7155-6642
Shengle ZhangLaboratory Operations, OmniSeq Inc., Buffalo, New York, United States of America.
Roswell Park Comprehensive Cancer Center · USInfor (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Timely and accurate identification of molecular alterations in solid tumors is essential for proper management of patients with advanced cancers. This has created a need for rapid, scalable comprehensive genomic profiling (CGP) systems that detect an increasing number of therapeutically-relevant variant types and molecular signatures. In this study, we assessed the analytical performance of the TruSight Oncology 500 High-Throughput assay for detection of somatic alterations from formalin-fixed paraffin-embedded tissue specimens. In parallel, we developed supporting software and automated sample preparation systems designed to process up to 70 clinical samples in a single NovaSeq 6000TM sequencing run with a turnaround time of <7 days from specimen receipt to report. The results demonstrate that the scalable assay accurately and reproducibly detects small variants, copy number alterations, microsatellite instability (MSI) and tumor mutational burden (TMB) from 40ng DNA, and multiple gene fusions, including known and unknown partners and splice variants from 20ng RNA. 717 tumor samples and reference materials with previously known alterations in 96 cancer-related genes were sequenced to evaluate assay performance. All variant classes were reliably detected at consistent and reportable variant allele percentages with >99% overall accuracy and precision. Our results demonstrate that the high-throughput CGP assay is a reliable method for accurate detection of molecular alterations in support of precision therapeutics in oncology. The supporting systems and scalable workflow allow for efficient interpretation and prompt reporting of hundreds of patient cancer genomes per week with excellent analytical performance.

Indexed as

Genetic VariationMicrosatellite InstabilityBiomarkers, TumorDNA Copy Number VariationsHigh-Throughput Nucleotide SequencingHumansMutationNeoplasmsReproducibility of ResultsSensitivity and SpecificitySequence Analysis, RNAWorkflowBiomarkers, Tumor

Identifiers

PMID34855780
PMCPMC8639101
OpenAlexW3217510643

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.