Evidence map›Paper›PMID 32372001›Full record

ArticleScientific reports2020

Characterization of a novel automated microfiltration device for the efficient isolation and analysis of circulating tumor cells from clinical blood samples.

Juan F Yee-de León, Brenda Soto-García, Diana Aráiz-Hernández, Jesús Rolando Delgado-Balderas, Miguel Esparza, Carlos Aguilar-Avelar, J D Wong-Campos, Franco Chacón, José Y López-Hernández, A Mauricio González-Treviño and 8 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. 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
0.7field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Membranes for the life sciences and their future roles in medicine.Chinese journal of chemical engineering · 2022
    Review
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

18 authors at 4 institutions in 2 countries.

Juan F Yee-de León *Delee Corp., Mountain View, CA, 94041, USA.
Brenda Soto-García *Delee Corp., Mountain View, CA, 94041, USA.
Diana Aráiz-Hernández *Delee Corp., Mountain View, CA, 94041, USA.
Jesús Rolando Delgado-Balderas *Delee Corp., Mountain View, CA, 94041, USA.
Miguel EsparzaDelee Corp., Mountain View, CA, 94041, USA.
Carlos Aguilar-AvelarDelee Corp., Mountain View, CA, 94041, USA.
J D Wong-CamposDelee Corp., Mountain View, CA, 94041, USA.
Franco ChacónDelee Corp., Mountain View, CA, 94041, USA.
José Y López-HernándezDelee Corp., Mountain View, CA, 94041, USA.
A Mauricio González-TreviñoDelee Corp., Mountain View, CA, 94041, USA.
José R Yee-de LeónDelee Corp., Mountain View, CA, 94041, USA.
Jorge L Zamora-MendozaDelee Corp., Mountain View, CA, 94041, USA.
Mario M AlvarezCentro de Biotecnología-FEMSA, Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Monterrey, 64849, Mexico.
Grissel Trujillo-de SantiagoCentro de Biotecnología-FEMSA, Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Monterrey, 64849, Mexico.
Lauro S Gómez-GuerraServicio de Urología, Hospital Universitario "Dr. José Eleuterio González", Universidad Autónoma de Nuevo León, Monterrey, 64460, Mexico.
Celia N Sánchez-DomínguezDepartamento de Bioquímica y Medicina Molecular, Facultad de Medicina, Universidad Autónoma de Nuevo León, Monterrey, 64460, Mexico.
Liza P Velarde-CalvilloDelee Corp., Mountain View, CA, 94041, USA. liza@delee.bio.
Alejandro Abarca-BlancoDelee Corp., Mountain View, CA, 94041, USA. alejandro@delee.bio.
Tecnológico de Monterrey · MXUniversidad Autónoma de Nuevo León · MXHarvard University · USHospital Universitario Dr José Eleuterio Gonzalez · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The detection and analysis of circulating tumor cells (CTCs) may enable a broad range of cancer-related applications, including the identification of acquired drug resistance during treatments. However, the non-scalable fabrication, prolonged sample processing times, and the lack of automation, associated with most of the technologies developed to isolate these rare cells, have impeded their transition into the clinical practice. This work describes a novel membrane-based microfiltration device comprised of a fully automated sample processing unit and a machine-vision-enabled imaging system that allows the efficient isolation and rapid analysis of CTCs from blood. The device performance was characterized using four prostate cancer cell lines, including PC-3, VCaP, DU-145, and LNCaP, obtaining high assay reproducibility and capture efficiencies greater than 93% after processing 7.5 mL blood samples spiked with 100 cancer cells. Cancer cells remained viable after filtration due to the minimal shear stress exerted over cells during the procedure, while the identification of cancer cells by immunostaining was not affected by the number of non-specific events captured on the membrane. We were also able to identify the androgen receptor (AR) point mutation T878A from 7.5 mL blood samples spiked with 50 LNCaP cells using RT-PCR and Sanger sequencing. Finally, CTCs were detected in 8 out of 8 samples from patients diagnosed with metastatic prostate cancer (mean ± SEM = 21 ± 2.957 CTCs/mL, median = 21 CTCs/mL), demonstrating the potential clinical utility of this device.

Indexed as

Neoplastic Cells, CirculatingAdultAgedAged, 80 and overBiomarkers, TumorBiomedical EngineeringCell Line, TumorCell SeparationFiltrationHumansMaleMiddle AgedMutationNeoplasm MetastasisPattern Recognition, AutomatedPolymethyl MethacrylateAR protein, humanBiomarkers, TumorPolymethyl MethacrylateReceptors, Androgen

Identifiers

PMID32372001
PMCPMC7200708
OpenAlexW2994913043

What OpenQuestion holds

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LicenceCC BY
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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.