Evidence map›Paper›PMID 25573079›Full record

ReviewCellular oncology (Dordrecht, Netherlands)2015

Germline oncopharmacogenetics, a promising field in cancer therapy.

Chiara Pesenti, Milena Gusella, Silvia M Sirchia, Monica Miozzo

Abstract readReview
In one paragraph

Review in Cellular oncology (Dordrecht, Netherlands), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Personalized cancer medicine: next steps in the genomic era.Cellular oncology (Dordrecht, Netherlands) · 2015
    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

4 authors.

Chiara PesentiDivision of Pathology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Milena Gusella
Silvia M Sirchia
Monica Miozzo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pharmacogenetics (PGx) is the study of the relationship between inter-individual genetic variation and drug responses. Germline variants of genes involved in drug metabolism, drug transport, and drug targets can affect individual response to medications. Cancer therapies are characterized by an intrinsically high toxicity; therefore, the application of pharmacogenetics to cancer patients is a particularly promising method for avoiding the use of inefficacious drugs and preventing the associated adverse effects. However, despite continuing efforts in this field, very few labels include information about germline genetic variants associated with drug responses. DPYD, TPMT, UGT1A1, G6PD, CYP2D6, and HLA are the sole loci for which the European Medicines Agency (EMA) and the US Food and Drug Administration (FDA) report specific information. This review highlights the germline PGx variants that have been approved to date for anticancer treatments, and also provides some insights about other germline variants with potential clinical applications. The continuous and rapid evolution of next-generation sequencing applications, together with the development of computational methods, should help to refine the implementation of personalized medicine. One day, clinicians may be able to prescribe the best treatment and the correct drug dosage based on each patient's genotype. This approach would improve treatment efficacy, reduce toxicity, and predict non-responders, thereby decreasing chemotherapy-associated morbidity and improving health benefits.

Indexed as

Genetic VariationHumansNeoplasmsPharmacogenetics

Identifiers

PMID25573079
PMCPMC13004258

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.