Evidence map›Paper›PMID 22235027›Full record

ArticleCarcinogenesis2012

Evaluation of microRNA expression profiles and their associations with risk alleles in lymphoblastoid cell lines of familial ovarian cancer.

Jie Shen, Dan Wang, Steven R Gregory, Leonard Medico, Qiang Hu, Li Yan, Kunle Odunsi, Shashikant B Lele, Christine B Ambrosone, Song Liu and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in Carcinogenesis, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

9 citing papers in PubMed, 18 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

11 authors at 2 institutions in 2 countries.

Jie ShenDepartment of Cancer Prevention and Controls, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, USA.
Dan Wang
Steven R Gregory
Leonard Medico
Qiang Hu
Li Yan
Kunle Odunsi
Shashikant B Lele
Christine B Ambrosone
Song Liu
Hua Zhao
Cancers et Préventions · FRRoswell Park Comprehensive Cancer Center · US

Funding

Two-Spirit Films in Indigenous Cancer HealthP30CA016056 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI MARK G FRATTINI · 1985 to 2026
$116.6M
MIcroRNA: A Novel Genetic Modifier for Breast Cancer PredispositionR01CA136483 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI ZHAO, HUA · 2009 to 2012
$2.2M
NCI NIH HHS 5R01CA136483NCI NIH HHS P30 CA016056NCI NIH HHS R01 CA136483
6 · The paper itself

Abstract

Interindividual variations of microRNA expression are likely to influence the expression of microRNA target genes and, therefore, contribute to phenotypic differences in humans, including cancer susceptibility. Whether microRNA expression variation has any role in ovarian cancer development is still unknown. Here, we evaluated microRNA expression profiles in lymphoblastoid cell lines from 74 women with familial ovarian cancer and 47 unrelated controls matched on gender and race. We found that the cases and unrelated controls can be clustered using 95 differentially expressed microRNAs with 91% accuracy. To assess the potential implications of microRNAs in ovarian cancer, we investigated the associations between microRNA expression and seven ovarian cancer risk variants discovered from genome-wide association studies (GWAS), namely, rs3814113 on 9p22.2, rs2072590 on 2q31, rs2665390 on 3q25, rs10088218, rs1516982, rs10098821 on 8q24.21 and rs2363956 on 19p13. We observed 130 significant associations at a permutation level of 0.01. Compared with other risk variants, rs3814113 and rs2072590 had the greatest number of significant associations (68 and 37, respectively). Interestingly, 14 microRNAs that were associated with ovarian cancer risk alleles belong to five microRNA clusters. The most notable cluster is the tumorigenic miR-17-92 cluster with five microRNAs, all of which are significantly associated with rs3814113. Using pathway analysis, several key biological pathways were significantly overrepresented, such as cellular response to stress (P = 2.87 × 10(-06)), etc. Further characterization of significant associations between microRNAs and risk alleles could facilitate the understanding of the functions of these GWAS discovered risk alleles in the genetic etiology of ovarian cancer.

Indexed as

Gene Expression ProfilingCell Line, TumorFemaleGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyHumansMicroRNAsOligonucleotide Array Sequence AnalysisOvarian NeoplasmsPhenotypePolymorphism, Single NucleotideRisk FactorsMicroRNAs

Identifiers

PMID22235027
PMCPMC3291866
OpenAlexW2168719052

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.