Evidence map›Paper›PMID 27472710›Full record

ArticleMedicine2016

Integrative exploration of genomic profiles for triple negative breast cancer identifies potential drug targets.

Xiaosheng Wang, Chittibabu Guda

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

18 citing papers in PubMed, 30 citations in OpenAlex.

  1. Trial
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  12. Journal of oncology · 2019
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Xiaosheng WangSchool of Basic Medicine and Clinic Pharmacy, China Pharmaceutical University, Nanjing, China Department of Genetics, Cell Biology and Anatomy Bioinformatics and Systems Biology Core Department of Biochemistry and Molecular Biology Fred and Pamela Buffet Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska, USA.
Chittibabu Guda
China Pharmaceutical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTriple negative breast cancer (TNBC) is high-risk due to its rapid drug resistance and recurrence, metastasis, and lack of targeted therapy. So far, no molecularly targeted therapeutic agents have been clinically approved for TNBC. It is imperative that we discover new targets for TNBC therapy.

objectivesA large volume of cancer genomics data are emerging and advancing breast cancer research. We may integrate different types of TNBC genomic data to discover molecular targets for TNBC therapy. DATA SOURCES: We used publicly available TNBC tumor tissue genomic data in the Cancer Genome Atlas database in this study.

methodsWe integratively explored genomic profiles (gene expression, copy number, methylation, microRNA [miRNA], and gene mutation) in TNBC and identified hyperactivated genes that have higher expression, more copy numbers, lower methylation level, or are targets of miRNAs with lower expression in TNBC than in normal samples. We ranked the hyperactivated genes into different levels based on all the genomic evidence and performed functional analyses of the sets of genes identified. More importantly, we proposed potential molecular targets for TNBC therapy based on the hyperactivated genes.

resultsSome of the genes we identified such as FGFR2, MAPK13, TP53, SRC family, MUC family, and BCL2 family have been suggested to be potential targets for TNBC treatment. Others such as CSF1R, EPHB3, TRIB1, and LAD1 could be promising new targets for TNBC treatment. By utilizing this integrative analysis of genomic profiles for TNBC, we hypothesized that some of the targeted treatment strategies for TNBC currently in development are more likely to be promising, such as poly (ADP-ribose) polymerase inhibitors, while the others are more likely to be discouraging, such as angiogenesis inhibitors. LIMITATIONS: The findings in this study need to be experimentally validated in the future.

conclusionThis is a systematic study that combined 5 different types of genomic data to molecularly characterize TNBC and identify potential targets for TNBC therapy. The integrative analysis of genomic profiles for TNBC could assist in identifying potential new therapeutic targets and predicting the effectiveness of a targeted treatment strategy for TNBC therapy.

Indexed as

Gene Expression ProfilingDNA Copy Number VariationsDNA MethylationFemaleGene Expression Regulation, NeoplasticHumansMicroRNAsMolecular Targeted Therapysrc-Family KinasesTranscriptional ActivationTriple Negative Breast NeoplasmsMicroRNAssrc-Family Kinases

Identifiers

PMID27472710
PMCPMC5265847
OpenAlexW2511241192

What OpenQuestion holds

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LicenceCC BY
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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.