Evidence map›Paper›PMID 28031929›Full record

ReviewFuture science OA2015

Pharmacogenetics of cancer therapy: breakthroughs from beyond?

Da-Yong Lu, Ting-Ren Lu, Bin Xu, Jian Ding

Abstract readReview
In one paragraph

Review in Future science OA, 2015. 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
–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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. The application of clinical genetics · 2021
    Article
  4. Review
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.

Da-Yong LuSchool of Life Sciences, Shanghai University, Shanghai 200444, PR China; School of Life Sciences, Shanghai University, Shanghai 200444, PR China.
Ting-Ren LuSchool of Life Sciences, Shanghai University, Shanghai 200444, PR China; School of Life Sciences, Shanghai University, Shanghai 200444, PR China.
Bin XuShanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, PR China; Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, PR China.
Jian DingShanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, PR China; Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

'Pharmacogenetics or Pharmacogenomics' (PG) is one of the most practiced cancer therapeutic strategies, tailored for individualized patients. Despite its popularity and rapid advancements in the field, many obstacles for cancer therapy PG still need to be overcome. By borrowing scientific systems from other disciplines such as cancer diagnosis, and therapeutic information from the diversity of tumor origins, categories and stages, cancer therapy PG may hopefully be improved. Furthermore, to quickly acquire genetic and pathologic information and seek therapeutic interventions, possible breakthroughs may come from beyond - changing the cancer therapeutic landscapes. The next generations of PG protocols and hospital routines for searching deadly cancer pathogenic pathways versus drug-targeting predictions are of great clinical significance for the future. Yet, progress of cancer therapy PG is entering into a bottleneck stage owing to simple model of relevant techniques and routines. Promoting or even innovating present PG modular is very necessary. This perspective highlights this issue by introducing new initiatives and ideas.

Indexed as

antineoplastic drugscancer stem cellscost–effectiveness studydrug targetsdrug toxicityneoplasm metastasispersonalized cancer therapypharmacogenetics

Identifiers

PMID28031929
PMCPMC5137899

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.