Evidence map›Paper›PMID 30484294›Full record

ArticleJournal of biomedical optics2018

Combining fluorescence-based image segmentation and automated microfluidics for ultrafast cell-by-cell assessment of biomarkers for HER2-type breast carcinoma.

Daniel Migliozzi, Huu T Nguyen, Martin A M Gijs

Open access · goldAbstract read
In one paragraph

Article in Journal of biomedical optics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-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

8 citing papers in PubMed, 10 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Daniel MigliozziÉcole Polytechnique Fédérale de Lausanne, Laboratory of Microsystems, Lausanne, Switzerland.
Huu T NguyenÉcole Polytechnique Fédérale de Lausanne, Laboratory of Microsystems, Lausanne, Switzerland.
Martin A M GijsÉcole Polytechnique Fédérale de Lausanne, Laboratory of Microsystems, Lausanne, Switzerland.
École Polytechnique Fédérale de Lausanne · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunohistochemistry (IHC) is one of the main clinical techniques for biomarker assessment on tissue biopsies. It consists in chromogenic labeling with specific antibodies, followed by optical imaging, and it is used for diagnosis and therapeutic targeting. A well-known drawback of IHC is its limited robustness, which often precludes quantitative biomarker assessment. We combine microfluidic immunostaining, fluorescence imaging, and image-based cell segmentation to create an ultrafast procedure for accurate biomarker assessment via IHC. The experimental protocol is very simple and based on fast delivery of reagents in a microfluidic chamber created by clamping a half-chamber patterned in a silicon chip on top of a tumor tissue section. Also, the imaging procedure simply requires a standard fluorescence microscope, already widely used in clinical practice. The image processing is based on local-contrast enhancement and thresholding of the obtained fluorescence image, with subsequent Voronoi segmentation. To assess the experimental and analytical procedure on robust biological controls, we apply our method to well-characterized cell lines, which guarantee higher reproducibility than whole-tissue samples and therefore enable to disentangle the technical variability from the biological variability. To increase the potential translationality, we address the detection and quantification of the human epidermal growth factor receptor 2 (HER2) protein, which is a biomarker for HER2-type breast carcinoma diagnosis and therapy. We report both ultrafast immunofluorescence staining (5 min per sample) of two breast cancer biomarkers and ultrafast cell segmentation (1 min per sample = processing of thousands of cells). This provides a quantitative, cell-based immunofluorescent signal, with which we propose a potential diagnostic criterion to separate HER2-positive and HER2-negative breast cancer cells at high sensitivity and specificity.

Indexed as

Biomarkers, TumorBreast NeoplasmsErb-b2 Receptor Tyrosine KinasesFemaleFluorescent Antibody TechniqueHumansImage Processing, Computer-AssistedMicrofluidicsReproducibility of ResultsBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine Kinasesbiomarker quantificationbreast cancerimage segmentationimmunofluorescencemicrofluidic chip

Identifiers

PMID30484294
PMCPMC6987647
OpenAlexW2902716812

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.