Evidence map›Paper›PMID 26801900›Full record

ArticleJournal of translational medicine2016

Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations.

Massimiliano Cocca, Davide Bedognetti, Martina La Bianca, Paolo Gasparini, Giorgia Girotto

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2016. 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
1.3field-weighted citation impact, top 18% 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

4 citing papers in PubMed, 11 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

5 authors at 3 institutions in 2 countries.

Massimiliano CoccaDepartment of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy. massimiliano.cocca@burlo.trieste.it.
Davide BedognettiTumor Biology, Immunology, and Therapy Section, Division of Translational Medicine, Sidra Medical and Research Center, Doha, Qatar. dbedognetti@sidra.org.
Martina La BiancaIRCCS Burlo Garofolo, Trieste, Italy. martina.labianca@burlo.trieste.it.
Paolo GaspariniDepartment of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy. pgasparini@sidra.org.
Giorgia GirottoDepartment of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy. giorgia.girotto@burlo.trieste.it.
University of Trieste · ITIRCCS Materno Infantile Burlo Garofolo · ITSidra Medical and Research Center · QA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer is the most common cancer in women characterized by a high variable clinical outcome among individuals treated with equivalent regimens and novel targeted therapies. In this study, we performed a population based approach intersecting high-throughput genotype data from Friuli Venezia Giulia (FVG) isolated populations with publically available pharmacogenomics information to estimate the frequency of genotypes correlated with responsiveness to breast cancer treatment thus improving the clinical management of this disease in an efficient and cost effective way.

methodsA list of 80 variants reported to be related to the efficacy or toxicity of breast cancer drugs was obtained from PharmGKB database. Fourty-one were present in FVG, 1000G European (EUR) and ExAC (Non Finnish European) databases. Their frequency was extracted using PLINK software and the differences tested by Fisher's exact test.

resultsStatistical analyses revealed that 13 out of the 41 (32 %) variants were significantly different in frequency in our sample as compared to the EUR/ExAC cohorts. For nine variants the available level of evidence (LOE) included polymorphisms related to cyclophosphamide, tamoxifen, doxorubicin, fluorpyrimidine and paclitaxel. In particular, for trastuzumab two variants were detected: (1) rs1801274-G within FCGR2A and associated with decreased efficacy (LOE 2B); (2) rs1136201-G located within ERBB2 and associated with increased toxicity (LOE 3). Both these two variants were underrepresented in the FVG population compared to EUR/ExAC population thus suggesting a high therapeutic index of this drug in our population. Moreover, as regards fluoropyrimidines, the frequency of two polymorphisms within the DPYD gene associated with drug toxicity (e.g., rs2297595-C allele and rs3918290-T allele, LOE 2A and 1, respectively) was extremely low in FVG population thus suggesting that a larger number of FVG patients could benefit from full dosage of fluoropyrimidine therapy.

conclusionsAll these findings increase the overall knowledge on the prevalence of specific variants related with breast cancer treatment responsiveness in FVG population and highlight the importance of assessing gene polymorphisms related with cancer medications in isolated communities.

Indexed as

Genetic Predisposition to DiseasePolymorphism, GeneticPrecision MedicineBreast NeoplasmsFemaleGene FrequencyGenotypeGeographyHumansItalyPharmacogeneticsRisk Factors

Identifiers

PMID26801900
PMCPMC4722680
OpenAlexW2269773818

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.