ReviewDer Pathologe2017
[Establishment of a living biobank : Improved guidance of precision cancer care with in vitro and in vivo cancer models].
Review in Der Pathologe, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Advances in organoid imaging and automated morphometric analysis: from optical microscopy to computational approaches.Frontiers in cell and developmental biology · 2026Review
- Three-Dimensional Culture System: A New Frontier in Cancer Research, Drug Discovery, and Stem Cell-Based Therapy.Biology · 2025Review
- Clinical trial design: Past, present, and future in the context of big data and precision medicine.Cancer · 2020Review
- Patient-derived cell line, xenograft and organoid models in lung cancer therapy.Translational lung cancer research · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrecision oncology is a clinical approach aimed towards tailoring treatment strategies for patients based on the genetic profile of each patient's cancer. The integration of a living biobank, consisting of patient-derived tumor organoids and PDXs, with next generation sequencing approaches and high-throughput drug screening help to guide clinical decision-making and clinical trial development.
methodsTumor organoids derived from fresh tumor samples were used for in vitro and in vivo high-throughput drug testing.
resultsOver a period of two years we established 56 in vitro tumor organoids and 19 in vivo xenografts from 18 different solid tumor types. Tumor morphology and molecular profiles show good concordance between the in vitro and in vivo models compared to their native tumor. High-throughput drug screening (up to 160 drugs) has been tested on eight tumor organoid lines. Seven of them underwent an additional combination drug screen. We nominated several targeted small molecules and novel combinations that have been validated in corresponding xenograft models.
conclusionThis precision medicine approach outlines the integration of genomic data with drug screening from personalized preclinical cancer models to guide precision cancer care. It also fuels next generation research and has been implemented for clinical trial development.
Indexed as
Identifiers
28956107What OpenQuestion holds
Registered trials
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.