Evidence map›Paper›PMID 30279418›Full record

ArticleScientific reports2018

Clinical value of bioelectrical properties of cancerous tissue in advanced epithelial ovarian cancer patients.

Paula Cunnea, Tommy Gorgy, Konstantinos Petkos, Sally A N Gowers, Haonan Lu, Cristina Morera, Wen Wu, Phillip Lawton, Katherine Nixon, Chi Leng Leong and 8 more

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
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.

Paula CunneaDepartment of Surgery and Cancer, Imperial College, London, UK.ORCID http://orcid.org/0000-0002-3699-4911
Tommy GorgyDepartment of Surgery and Cancer, Imperial College, London, UK.
Konstantinos PetkosDepartment of Bioengineering, Imperial College, London, UK.
Sally A N GowersDepartment of Bioengineering, Imperial College, London, UK.
Haonan LuDepartment of Surgery and Cancer, Imperial College, London, UK.ORCID http://orcid.org/0000-0002-2472-7488
Cristina MoreraDepartment of Surgery and Cancer, Imperial College, London, UK.
Wen WuDepartment of Bioengineering, Imperial College, London, UK.
Phillip LawtonDepartment of Surgery and Cancer, Imperial College, London, UK.
Katherine NixonDepartment of Surgery and Cancer, Imperial College, London, UK.
Chi Leng LeongDepartment of Bioengineering, Imperial College, London, UK.
Flavia SorbiDepartment of Surgery and Cancer, Imperial College, London, UK.ORCID http://orcid.org/0000-0001-7277-6420
Lavinia DomeniciDepartment of Surgery and Cancer, Imperial College, London, UK.
Andrew PatersonDepartment of Surgery and Cancer, Imperial College, London, UK.
Ed CurryDepartment of Surgery and Cancer, Imperial College, London, UK.
Hani GabraDepartment of Surgery and Cancer, Imperial College, London, UK.
Martyn G BoutelleDepartment of Bioengineering, Imperial College, London, UK.
Emmanuel M DrakakisDepartment of Bioengineering, Imperial College, London, UK.
Christina FotopoulouDepartment of Surgery and Cancer, Imperial College, London, UK. c.fotopoulou@imperial.ac.uk.

Funding

Medical Research Council MC_PC_14100
6 · The paper itself

Abstract

Currently, there are no valid pre-operatively established biomarkers or algorithms that can accurately predict surgical and clinical outcome for patients with advanced epithelial ovarian cancer (EOC). In this study, we suggest that profiling of tumour parameters such as bioelectrical-potential and metabolites, detectable by electronic sensors, could facilitate the future development of devices to better monitor disease and predict surgical and treatment outcomes. Biopotential was recorded, using a potentiometric measurement system, in ex vivo paired non-cancerous and cancerous omental tissues from advanced stage EOC (n = 36), and lysates collected for metabolite measurement by microdialysis. Consistently different biopotential values were detected in cancerous tissue versus non-cancerous tissue across all cases (p < 0.001). High tumour biopotential levels correlated with advanced tumour stage (p = 0.048) and tumour load, and negatively correlated with stroma. Within our EOC cohort and specifically the high-grade serous subtype, low biopotential levels associated with poorer progression-free survival (p = 0.0179, p = 0.0143 respectively). Changes in biopotential levels significantly correlated with common apoptosis related pathways. Lactate and glucose levels measured in paired tissues showed significantly higher lactate/glucose ratio in tissues with low biopotential (p < 0.01, n = 12). Our study proposes the feasibility of biopotential and metabolite monitoring as a biomarker modality profiling EOC to predict surgical and clinical outcomes.

Indexed as

Electric ImpedanceAdultAgedAged, 80 and overBiomarkers, TumorBiosensing TechniquesCarcinoma, Ovarian EpithelialCytoreduction Surgical ProceduresDisease ProgressionElectrodesFemaleHumansKaplan-Meier EstimateMicrodialysisMicrofluidicsMiddle AgedBiomarkers, Tumor

Identifiers

PMID30279418
PMCPMC6168525

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.