Evidence map›Paper›PMID 28371753›Full record

ArticleBiosensors & bioelectronics2017

A microfluidic platform for drug screening in a 3D cancer microenvironment.

Hardik J Pandya, Karan Dhingra, Devbalaji Prabhakar, Vineethkrishna Chandrasekar, Siva Kumar Natarajan, Anish S Vasan, Ashish Kulkarni, Hadi Shafiee

Abstract read
In one paragraph

Article in Biosensors & bioelectronics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

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  7. Microphysiological systems as models for immunologically 'cold' tumors.Frontiers in cell and developmental biology · 2024
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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.

Hardik J PandyaDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital - Harvard Medical School, Boston, MA 02115, USA.
Karan DhingraDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital - Harvard Medical School, Boston, MA 02115, USA.
Devbalaji PrabhakarDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital - Harvard Medical School, Boston, MA 02115, USA.
Vineethkrishna ChandrasekarDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital - Harvard Medical School, Boston, MA 02115, USA.
Siva Kumar NatarajanDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital - Harvard Medical School, Boston, MA 02115, USA.
Anish S VasanDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital - Harvard Medical School, Boston, MA 02115, USA.
Ashish KulkarniDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital - Harvard Medical School, Boston, MA 02115, USA. Electronic address: akulkarni@bwh.harvard.edu.
Hadi ShafieeDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital - Harvard Medical School, Boston, MA 02115, USA; Department of Medicine, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA. Electronic address: hshafiee@bwh.harvard.edu.

Funding

Sensitive and quantitative point-of-care viral load testing on paperR01AI118502 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI SHAFIEE, HADI · 2016 to 2020
$2.2M
NIAID NIH HHS R01 AI118502
6 · The paper itself

Abstract

Development of resistance to chemotherapy treatments is a major challenge in the battle against cancer. Although a vast repertoire of chemotherapeutics is currently available for treating cancer, a technique for rapidly identifying the right drug based on the chemo-resistivity of the cancer cells is not available and it currently takes weeks to months to evaluate the response of cancer patients to a drug. A sensitive, low-cost diagnostic assay capable of rapidly evaluating the effect of a series of drugs on cancer cells can significantly change the paradigm in cancer treatment management. Integration of microfluidics and electrical sensing modality in a 3D tumour microenvironment may provide a powerful platform to tackle this issue. Here, we report a 3D microfluidic platform that could be potentially used for a real-time deterministic analysis of the success rate of a chemotherapeutic drug in less than 12h. The platform (66mm×50mm; L×W) is integrated with the microsensors (interdigitated gold electrodes with width and spacing 10µm) that can measure the change in the electrical response of cancer cells seeded in a 3D extra cellular matrix when a chemotherapeutic drug is flown next to the matrix. B16-F10 mouse melanoma, 4T1 mouse breast cancer, and DU 145 human prostate cancer cells were used as clinical models. The change in impedance magnitude on flowing chemotherapeutics drugs measured at 12h for drug-susceptible and drug tolerant breast cancer cells compared to control were 50,552±144 Ω and 28,786±233 Ω, respectively, while that of drug-susceptible melanoma cells were 40,197±222 Ω and 4069±79 Ω, respectively. In case of prostate cancer the impedance change between susceptible and resistant cells were 8971±1515 Ω and 3281±429 Ω, respectively, which demonstrated that the microfluidic platform was capable of delineating drug susceptible cells, drug tolerant, and drug resistant cells in less than 12h.

Indexed as

AnimalsBiosensing TechniquesBreast NeoplasmsCell Culture TechniquesDrug Evaluation, PreclinicalDrug Resistance, NeoplasmFemaleHumansMaleMiceMicrofluidicsProstatic NeoplasmsTumor MicroenvironmentCancer microenvironmentChemotherapyDrug screeningElectrical sensingMicrofluidics

Identifiers

PMID28371753
PMCPMC5499155

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.