Evidence map›Paper›PMID 34074327›Full record

ArticleGenome medicine2021

Detection of cryptogenic malignancies from metagenomic whole genome sequencing of body fluids.

Wei Gu, Eric Talevich, Elaine Hsu, Zhongxia Qi, Anatoly Urisman, Scot Federman, Allan Gopez, Shaun Arevalo, Marc Gottschall, Linda Liao and 15 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Recurrent Pulmonary Infection Caused byRespirology case reports · 2025
    Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

25 authors.

Wei GuDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA. weigu@stanford.edu.ORCID 0000-0002-2480-6645
Eric TalevichDNANexus, Mountain View, CA, 94040, USA.
Elaine HsuDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA.
Zhongxia QiDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA.
Anatoly UrismanDepartment of Pathology, University of California San Francisco, San Francisco, CA, 94107, USA.
Scot FedermanDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA.
Allan GopezDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA.
Shaun ArevaloDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA.
Marc GottschallDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA.
Linda LiaoStanford Health Care, Stanford University, Stanford, CA, 94305, USA.
Jack TungDepartment of Pathology, Stanford University, Stanford, CA, 94305, USA.
Lei ChenStanford Health Care, Stanford University, Stanford, CA, 94305, USA.
Harumi LimStanford Health Care, Stanford University, Stanford, CA, 94305, USA.
Chandler HoStanford Health Care, Stanford University, Stanford, CA, 94305, USA.
Maya KasowskiDepartment of Pathology, Stanford University, Stanford, CA, 94305, USA.
Jean OakDepartment of Pathology, Stanford University, Stanford, CA, 94305, USA.
Brittany J HolmesDepartment of Pathology, Stanford University, Stanford, CA, 94305, USA.
Iwei YehDepartment of Pathology, University of California San Francisco, San Francisco, CA, 94107, USA.
Jingwei YuDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA.
Linlin WangDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA.
Steve MillerDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA.
Joseph L DeRisiDepartment of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, 94107, USA.
Sonam PrakashDepartment of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA.
Jeff Simko *Department of Pathology, University of California San Francisco, San Francisco, CA, 94107, USA.
Charles Y Chiu *Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, 94107, USA. charles.chiu@ucsf.edu.

Funding

Pan-Genomic Approaches for Comprehensive Blood Screening of Novel or Emerging Infectious AgentsR01HL105704 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHIU, CHARLES YEN · 2011 to 2020
$5.9M
Noninvasive Risk Stratification of Prostate Cancer Using Cell-Free Nucleic AcidsK08CA230156 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GU, WEI · 2018 to 2022
$1.4M
Identification of diagnostic and prognostic host biomarkers of Zika virus infection by transcriptome profilingR21AI129455 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHIU, CHARLES YEN · 2017 to 2018
$436k
NCI NIH HHS K08 CA230156NHLBI NIH HHS R01 HL105704NIAID NIH HHS R21 AI129455
6 · The paper itself

Abstract

backgroundMetagenomic next-generation sequencing (mNGS) of body fluids is an emerging approach to identify occult pathogens in undiagnosed patients. We hypothesized that metagenomic testing can be simultaneously used to detect malignant neoplasms in addition to infectious pathogens.

methodsFrom two independent studies (n = 205), we used human data generated from a metagenomic sequencing pipeline to simultaneously screen for malignancies by copy number variation (CNV) detection. In the first case-control study, we analyzed body fluid samples (n = 124) from patients with a clinical diagnosis of either malignancy (positive cases, n = 65) or infection (negative controls, n = 59). In a second verification cohort, we analyzed a series of consecutive cases (n = 81) sent to cytology for malignancy workup that included malignant positives (n = 32), negatives (n = 18), or cases with an unclear gold standard (n = 31).

resultsThe overall CNV test sensitivity across all studies was 87% (55 of 63) in patients with malignancies confirmed by conventional cytology and/or flow cytometry testing and 68% (23 of 34) in patients who were ultimately diagnosed with cancer but negative by conventional testing. Specificity was 100% (95% CI 95-100%) with no false positives detected in 77 negative controls. In one example, a patient hospitalized with an unknown pulmonary illness had non-diagnostic lung biopsies, while CNVs implicating a malignancy were detectable from bronchoalveolar fluid.

conclusionsMetagenomic sequencing of body fluids can be used to identify undetected malignant neoplasms through copy number variation detection. This study illustrates the potential clinical utility of a single metagenomic test to uncover the cause of undiagnosed acute illnesses due to cancer or infection using the same specimen.

Indexed as

Body FluidsMetagenomeCase-Control StudiesComputational BiologyCytogenetic AnalysisDisease ManagementDisease SusceptibilityFlow CytometryHistocytochemistryHumansIn Situ Hybridization, FluorescenceLiquid BiopsyMetagenomicsNeoplasmsReproducibility of ResultsSensitivity and Specificity

Identifiers

PMID34074327
PMCPMC8167833

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.