Evidence map›Paper›PMID 27702751›Full record

ReviewEndocrine-related cancer2016

Patient-derived tumour xenografts for breast cancer drug discovery.

John W Cassidy, Ankita S Batra, Wendy Greenwood, Alejandra Bruna

Open access · hybridAbstract readReview
In one paragraph

Review in Endocrine-related cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 19% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. 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 at 2 institutions in 2 countries.

John W CassidyBreast Cancer Functional GenomicsCRUK Cambridge Research Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, UK john.cassidy@cruk.cam.ac.uk alejandra.bruna@cruk.cam.ac.uk.
Ankita S BatraBreast Cancer Functional GenomicsCRUK Cambridge Research Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, UK.
Wendy GreenwoodBreast Cancer Functional GenomicsCRUK Cambridge Research Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, UK.
Alejandra BrunaDepartment of OncologyUniversity of Cambridge, Cambridge, UK john.cassidy@cruk.cam.ac.uk alejandra.bruna@cruk.cam.ac.uk.
Breast Cancer Research Foundation · USUniversity of Cambridge · GB

Funding

Cancer Research UK 16942Cancer Research UK 18832Cancer Research UK 9675Cancer Research UK RG84936Medical Research Council G0300648
6 · The paper itself

Abstract

Despite remarkable advances in our understanding of the drivers of human malignancies, new targeted therapies often fail to show sufficient efficacy in clinical trials. Indeed, the cost of bringing a new agent to market has risen substantially in the last several decades, in part fuelled by extensive reliance on preclinical models that fail to accurately reflect tumour heterogeneity. To halt unsustainable rates of attrition in the drug discovery process, we must develop a new generation of preclinical models capable of reflecting the heterogeneity of varying degrees of complexity found in human cancers. Patient-derived tumour xenograft (PDTX) models prevail as arguably the most powerful in this regard because they capture cancer's heterogeneous nature. Herein, we review current breast cancer models and their use in the drug discovery process, before discussing best practices for developing a highly annotated cohort of PDTX models. We describe the importance of extensive multidimensional molecular and functional characterisation of models and combination drug-drug screens to identify complex biomarkers of drug resistance and response. We reflect on our own experiences and propose the use of a cost-effective intermediate pharmacogenomic platform (the PDTX-PDTC platform) for breast cancer drug and biomarker discovery. We discuss the limitations and unanswered questions of PDTX models; yet, still strongly envision that their use in basic and translational research will dramatically change our understanding of breast cancer biology and how to more effectively treat it.

Indexed as

Xenograft Model Antitumor AssaysAnimalsAntineoplastic AgentsBreast NeoplasmsDrug DiscoveryFemaleHumansMammary Neoplasms, ExperimentalNeoplasm TransplantationPrecision MedicineAntineoplastic Agentsbiomarker discoverybreast cancerdrug discoveryhigh-throughput screeningpatient-derived tumour xenograftspharmacogenomicstargeted therapies

Identifiers

PMID27702751
PMCPMC5118939
OpenAlexW2528037923

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.