Evidence map›Paper›PMID 36675685›Full record

ArticleJournal of personalized medicine2022

Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies.

P Sean Walsh, Yangyang Hao, Jie Ding, Jianghan Qu, Jonathan Wilde, Ruochen Jiang, Richard T Kloos, Jing Huang, Giulia C Kennedy

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. The Molecular Heterogeneity of NRAS Variants in Thyroid Nodules.Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery · 2026
    Article
  3. Article
  4. Article
  5. Article
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

9 authors.

P Sean WalshVeracyte, Inc., 600 Shoreline Court, South San Francisco, CA 94080, USA.
Yangyang HaoVeracyte, Inc., 600 Shoreline Court, South San Francisco, CA 94080, USA.
Jie DingVeracyte, Inc., 600 Shoreline Court, South San Francisco, CA 94080, USA.
Jianghan QuVeracyte, Inc., 600 Shoreline Court, South San Francisco, CA 94080, USA.
Jonathan WildeVeracyte, Inc., 600 Shoreline Court, South San Francisco, CA 94080, USA.
Ruochen JiangVeracyte, Inc., 600 Shoreline Court, South San Francisco, CA 94080, USA.
Richard T KloosVeracyte, Inc., 600 Shoreline Court, South San Francisco, CA 94080, USA.ORCID 0000-0003-4183-7387
Jing HuangVeracyte, Inc., 600 Shoreline Court, South San Francisco, CA 94080, USA.
Giulia C KennedyVeracyte, Inc., 600 Shoreline Court, South San Francisco, CA 94080, USA.

Funding

Veracyte (United States) N/A
6 · The paper itself

Abstract

Despite its wide-ranging benefits, whole-transcriptome or RNA exome profiling is challenging to implement in a clinical diagnostic setting. The Unified Assay is a comprehensive workflow wherein exome-enriched RNA-sequencing (RNA-Seq) assays are performed on clinical samples and analyzed by a series of advanced machine learning-based classifiers. Gene expression signatures and rare and/or novel genomic events, including fusions, mitochondrial variants, and loss of heterozygosity were assessed using RNA-Seq data generated from 120,313 clinical samples across three clinical indications (thyroid cancer, lung cancer, and interstitial lung disease). Since its implementation, the data derived from the Unified Assay have allowed significantly more patients to avoid unnecessary diagnostic surgery and have played an important role in guiding follow-up decisions regarding treatment. Collectively, data from the Unified Assay show the utility of RNA-Seq and RNA expression signatures in the clinical laboratory, and their importance to the future of precision medicine.

Indexed as

diagnosticsinterstitial lung diseaselung cancerprecision medicineRNA sequencingsmall biopsythyroid cancer

Identifiers

PMID36675685
PMCPMC9866839

What OpenQuestion holds

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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.