Evidence map›Paper›PMID 31767951›Full record

ArticleScientific reports2019

PIC&RUN: An integrated assay for the detection and retrieval of single viable circulating tumor cells.

Mohamed Kamal, Shahin Saremi, Remi Klotz, Oihana Iriondo, Yonatan Amzaleg, Yvonne Chairez, Varsha Tulpule, Julie E Lang, Irene Kang, Min Yu

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Technologies for Viable Circulating Tumor Cell Isolation.International journal of molecular sciences · 2022
    Review
  7. Article
  8. Review
  9. Review
  10. Review
  11. N-Acetyl-L-cysteine PromotesMolecular cancer research : MCR · 2021
    Article
  12. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Mohamed KamalDepartment of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, 90033, USA.
Shahin SaremiDepartment of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, 90033, USA.
Remi KlotzDepartment of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, 90033, USA.
Oihana IriondoDepartment of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, 90033, USA.
Yonatan AmzalegDepartment of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, 90033, USA.
Yvonne ChairezDepartment of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, 90033, USA.
Varsha TulpuleUSC Norris Comprehensive Cancer Center, Keck School of Medicine of the University of Southern California, Los Angeles, California, 90033, USA.
Julie E LangUSC Norris Comprehensive Cancer Center, Keck School of Medicine of the University of Southern California, Los Angeles, California, 90033, USA.
Irene KangUSC Norris Comprehensive Cancer Center, Keck School of Medicine of the University of Southern California, Los Angeles, California, 90033, USA.
Min YuDepartment of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, 90033, USA. minyu@med.usc.edu.

Funding

USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fumito Ito · 1985 to 2026
$181.4M
DOCTORAL AND POST-DOCTORAL TRAINING IN CRANIOFACIAL BIOLOGYT90DE021982 · NIDCR · UNIVERSITY OF SOUTHERN CALIFORNIA · PI PAINE, MICHAEL LANSDELL · 2011 to 2025
$6.2M
Developing Individualized Medicine Targeting Metastatic Breast Cancer Stem CellsDP2CA206653 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI YU, MIN · 2015 to 2019
$2.6M
NCI NIH HHS DP2 CA206653NCI NIH HHS P30 CA014089NIDCR NIH HHS T90 DE021982
6 · The paper itself

Abstract

Circulating tumor cells (CTCs) shed from solid tumors can serve as a minimally invasive liquid biopsy for monitoring disease progression. Because CTCs are rare and heterogeneous, their biological properties need to be investigated at the single cell level, which requires efficient ways to isolate and analyze live single CTCs. Current methods for CTC isolation and identification are either performed on fixed and stained cells or need multiple procedures to isolate pure live CTCs. Here, we used the AccuCyte-RareCyte system to develop a Protocol for Integrated Capture and Retrieval of Ultra-pure single live CTCs using Negative and positive selection (PIC&RUN). The positive selection module of PIC&RUN identifies CTCs based on detection of cancer surface markers and exclusion of immune markers. Combined with a two-step cell picking protocol to retrieve ultrapure single CTCs, the positive selection module is compatible for downstream single cell transcriptomic analysis. The negative selection module of PIC&RUN identifies CTCs based on a live cell dye and the absence of immune markers, allowing retrieval of viable CTCs that are suitable for ex vivo culture. This new assay combines the CTC capture and retrieval in one integrated platform, providing a valuable tool for downstream live CTC analyses.

Indexed as

AdultAgedBiomarkers, TumorBreast NeoplasmsCase-Control StudiesCell CountCell SeparationFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedNeoplastic Cells, CirculatingSingle-Cell AnalysisTumor Cells, CulturedBiomarkers, Tumor

Identifiers

PMID31767951
PMCPMC6877641

What OpenQuestion holds

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Registered trials

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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.