Evidence map›Paper›PMID 31864316›Full record

ArticleBMC cancer2019

Non-destructive, label free identification of cell cycle phase in cancer cells by multispectral microscopy of autofluorescence.

Jared M Campbell, Abbas Habibalahi, Saabah Mahbub, Martin Gosnell, Ayad G Anwer, Sharon Paton, Stan Gronthos, Ewa Goldys

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 7% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 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

8 authors at 3 institutions in 2 countries.

Jared M CampbellDepartment of Physics and Astronomy, Macquarie University, North Ryde, New South Wales, 2109, Australia. j.campbell@unsw.edu.au.ORCID http://orcid.org/0000-0003-0163-4251
Abbas HabibalahiDepartment of Physics and Astronomy, Macquarie University, North Ryde, New South Wales, 2109, Australia.
Saabah MahbubDepartment of Physics and Astronomy, Macquarie University, North Ryde, New South Wales, 2109, Australia.
Martin GosnellDepartment of Physics and Astronomy, Macquarie University, North Ryde, New South Wales, 2109, Australia.
Ayad G AnwerDepartment of Physics and Astronomy, Macquarie University, North Ryde, New South Wales, 2109, Australia.
Sharon PatonMesenchymal Stem Cell Laboratory, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, 5000, Australia.
Stan GronthosMesenchymal Stem Cell Laboratory, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, 5000, Australia.
Ewa GoldysDepartment of Physics and Astronomy, Macquarie University, North Ryde, New South Wales, 2109, Australia.
UNSW Sydney · AUSouth Australian Health and Medical Research Institute · AUQuantitative BioSciences · US

Funding

Australian Research Council CE140100003Australian Research Council DP170101863
6 · The paper itself

Abstract

backgroundCell cycle analysis is important for cancer research. However, available methodologies have drawbacks including limited categorisation and reliance on fixation, staining or transformation. Multispectral analysis of endogenous cell autofluorescence has been shown to be sensitive to changes in cell status and could be applied to the discrimination of cell cycle without these steps.

methodsCells from the MIA-PaCa-2, PANC-1, and HeLa cell lines were plated on gridded dishes and imaged using a multispectral fluorescence microscope. They were then stained for proliferating cell nuclear antigen (PCNA) and DNA intensity as a reference standard for their cell cycle position (G1, S, G2, M). The multispectral data was split into training and testing datasets and models were generated to discriminate between G1, S, and G2 + M phase cells. A standard decision tree classification approach was taken, and a two-step system was generated for each line.

resultsAcross cancer cell lines accuracy ranged from 68.3% (MIA-PaCa-2) to 73.3% (HeLa) for distinguishing G1 from S and G2 + M, and 69.0% (MIA-PaCa-2) to 78.0% (PANC1) for distinguishing S from G2 + M. Unmixing the multispectral data showed that the autofluorophores NADH, FAD, and PPIX had significant differences between phases. Similarly, the redox ratio and the ratio of protein bound to free NADH were significantly affected.

conclusionsThese results demonstrate that multispectral microscopy could be used for the non-destructive, label free discrimination of cell cycle phase in cancer cells. They provide novel information on the mechanisms of cell-cycle progression and control, and have practical implications for oncology research.

Indexed as

Cell CycleCell Line, TumorHeLa CellsHumansImage Processing, Computer-AssistedMicroscopy, FluorescenceNeoplasmsOptical ImagingProliferating Cell Nuclear AntigenProliferating Cell Nuclear AntigenCancerCell cycleCell phaseHyperspectralMultispectralNeoplasia

Identifiers

PMID31864316
PMCPMC6925881
OpenAlexW2995269319

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.