Evidence map›Paper›PMID 24478986›Full record

ArticleFrontiers in oncology2014

Gene expression analysis in ovarian cancer - faults and hints from DNA microarray study.

Katarzyna Marta Lisowska, Magdalena Olbryt, Volha Dudaladava, Jolanta Pamuła-Piłat, Katarzyna Kujawa, Ewa Grzybowska, Michał Jarząb, Sebastian Student, Iwona Krystyna Rzepecka, Barbara Jarząb and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 4 pooled it
7.6field-weighted citation impact, top 3% 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

70 citing papers in PubMed, 4 syntheses or guidelines pooled it, 93 citations in OpenAlex.

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10 more citing papers are in PubMed but not listed here.

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

11 authors at 3 institutions in 2 countries.

Katarzyna Marta LisowskaCenter for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Magdalena OlbrytCenter for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Volha DudaladavaDepartment of Medical Biology and Genetics, Grodno State Medical University , Grodno , Belarus.
Jolanta Pamuła-PiłatCenter for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Katarzyna KujawaCenter for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Ewa GrzybowskaCenter for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Michał JarząbCenter for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Sebastian StudentFaculty of Automated Control, Electronics and Computer Science, Silesian University of Technology , Gliwice , Poland.
Iwona Krystyna RzepeckaDepartment of Pathology, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Warsaw , Poland.
Barbara JarząbDepartment of Nuclear Medicine and Oncological Endocrinology, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Jolanta KupryjańczykDepartment of Pathology, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Warsaw , Poland.
The Maria Sklodowska-Curie National Research Institute of Oncology · PLGrodno State Medical University · BYSilesian University of Technology · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The introduction of microarray techniques to cancer research brought great expectations for finding biomarkers that would improve patients' treatment; however, the results of such studies are poorly reproducible and critical analyses of these methods are rare. In this study, we examined global gene expression in 97 ovarian cancer samples. Also, validation of results by quantitative RT-PCR was performed on 30 additional ovarian cancer samples. We carried out a number of systematic analyses in relation to several defined clinicopathological features. The main goal of our study was to delineate the molecular background of ovarian cancer chemoresistance and find biomarkers suitable for prediction of patients' prognosis. We found that histological tumor type was the major source of variability in genes expression, except for serous and undifferentiated tumors that showed nearly identical profiles. Analysis of clinical endpoints [tumor response to chemotherapy, overall survival, disease-free survival (DFS)] brought results that were not confirmed by validation either on the same group or on the independent group of patients. CLASP1 was the only gene that was found to be important for DFS in the independent group, whereas in the preceding experiments it showed associations with other clinical endpoints and with BRCA1 gene mutation; thus, it may be worthy of further testing. Our results confirm that histological tumor type may be a strong confounding factor and we conclude that gene expression studies of ovarian carcinomas should be performed on histologically homogeneous groups. Among the reasons of poor reproducibility of statistical results may be the fact that despite relatively large patients' group, in some analyses one has to compare small and unequal classes of samples. In addition, arbitrarily performed division of samples into classes compared may not always reflect their true biological diversity. And finally, we think that clinical endpoints of the tumor probably depend on subtle changes in many and, possibly, alternative molecular pathways, and such changes may be difficult to demonstrate.

Indexed as

CLASP1epithelial ovarian cancergene expression profilinggenomic medicinemolecular markersoligonucleotide microarrayssurvival timetumor histology

Identifiers

PMID24478986
PMCPMC3904181
OpenAlexW2078344435

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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.