Evidence map›Paper›PMID 31837432›Full record

ArticleThe Journal of molecular diagnostics : JMD2020

Therapeutic Monitoring of Circulating DNA Mutations in Metastatic Cancer with Personalized Digital PCR.

Christina M Wood-Bouwens, Derrick Haslem, Bryce Moulton, Alison F Almeda, Hojoon Lee, Gregory M Heestand, Lincoln D Nadauld, Hanlee P Ji

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of molecular diagnostics : JMD, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.9field-weighted citation impact, top 30% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. Review
  3. The Impact of Liquid Biopsy in Advanced Ovarian Cancer Care.Diagnostics (Basel, Switzerland) · 2024
    Article
  4. Review
  5. Article
  6. Review
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  8. Article
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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

8 authors at 3 institutions in 1 country.

Christina M Wood-BouwensDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California.
Derrick HaslemPrecision Genomics, Intermountain Healthcare, St. George, Utah.
Bryce MoultonPrecision Genomics, Intermountain Healthcare, St. George, Utah.
Alison F AlmedaDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California.
Hojoon LeeDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California.
Gregory M HeestandDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California.
Lincoln D NadauldPrecision Genomics, Intermountain Healthcare, St. George, Utah. Electronic address: lincoln.nadauld@imail.org.
Hanlee P JiDivision of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California; Stanford Genome Technology Center, Stanford University, Palo Alto, California. Electronic address: genomics_ji@stanford.edu.
Stanford University · USIntermountain Healthcare · USStanford Medicine · US

Funding

WHOLE YEAST GENOME TRANSCRIPTIONAL AND FUNCTIONAL GENE MAPS--A FEASIBILITY STUDYP01HG000205 · NHGRI · STANFORD UNIVERSITY · PI HOWE, ROGER THOMAS, JI, HANLEE P · 1990 to 2016
$120.9M
Statistical Models for Genome Sequencing and AssociationR01HG006137 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI JI, HANLEE P, ZHANG, NANCY R · 2011 to 2022
$4.3M
An Integrated Approach to the Validation of Novel Gastric Cancer OncogenesK08CA166512 · NCI · STANFORD UNIVERSITY · PI NADAULD, LINCOLN D. · 2012 to 2016
$689k
NCI NIH HHS K08 CA166512NHGRI NIH HHS P01 HG000205NHGRI NIH HHS R01 HG006137
6 · The paper itself

Abstract

As a high-performance solution for longitudinal monitoring of patients being treated for metastatic cancer, a single-color digital PCR (dPCR) assay that detects and quantifies specific cancer mutations present in circulating tumor DNA (ctDNA) was developed. This customizable assay has a high sensitivity of detection. One can detect a mutation allelic fraction of 0.1%, equivalent to three mutation-bearing DNA molecules among 3000 genome equivalents. The objective of this study was to validate the use of personalized dPCR mutation assays to monitor patients with metastatic cancer. The dPCR results were compared with serum biomarkers indicating disease progression or response. Patients had metastatic colorectal, biliary, breast, lung, and melanoma cancers. Mutations occurred in essential cancer drivers such as BRAF, KRAS, and PIK3CA. Patients were monitored over multiple cycles of treatment for up to a year. All patients had detectable ctDNA mutations. The results correlated with serum markers of metastatic cancer burden, including carcinoembryonic antigen, CA-19-9, and CA-15-3, and qualitatively corresponding to imaging studies. Corresponding trends were observed among these patients receiving active treatment with chemotherapy or targeted agents. For example, in one patient under active treatment, increasing quantities of ctDNA molecules were detected over time, indicating recurrence of tumor. This study demonstrates that personalized dPCR enables longitudinal monitoring of patients with metastatic cancer and may be a useful indicator for treatment response.

Indexed as

Biomarkers, TumorCell-Free Nucleic AcidsCirculating Tumor DNAMutationPrecision MedicineAllelesClass I Phosphatidylinositol 3-KinasesDNA Mutational AnalysisFemaleHumansLiquid BiopsyMaleNeoplasm MetastasisNeoplasm StagingReal-Time Polymerase Chain ReactionTomography, X-Ray ComputedBiomarkers, TumorCell-Free Nucleic AcidsCirculating Tumor DNAClass I Phosphatidylinositol 3-KinasesPIK3CA protein, human

Identifiers

PMID31837432
PMCPMC7031679
OpenAlexW2995327911

What OpenQuestion holds

Textmetadata
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.