Evidence map›Paper›PMID 27933214›Full record

ReviewESMO open2016

Integrating next-generation sequencing into clinical oncology: strategies, promises and pitfalls.

Peter Horak, Stefan Fröhling, Hanno Glimm

Abstract readReview
In one paragraph

Review in ESMO open, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
97citing papers in PubMed, 1 pooled it
–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

97 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Genetic landscape of cancer: mechanisms, key genes, and therapeutic implications.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Precision oncology: transforming cancer care through personalized medicine.Medical oncology (Northwood, London, England) · 2025
    Review
  12. Article
  13. Review
  14. Review
  15. iSeq: an integrated tool to fetch public sequencing data.Bioinformatics (Oxford, England) · 2024
    Article
  16. Review
  17. Review
  18. Article
  19. Genomic characterization of peritoneal lavage cytology-positive gastric cancer.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2024
    Article
  20. Article

37 more citing papers are in PubMed but not listed here.

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

3 authors.

Peter HorakDepartment of Translational Oncology , National Center for Tumor Diseases Heidelberg, German Cancer Research Center (DKFZ) , Heidelberg , Germany.
Stefan FröhlingDepartment of Translational Oncology , National Center for Tumor Diseases Heidelberg, German Cancer Research Center (DKFZ) , Heidelberg , Germany.
Hanno GlimmDepartment of Translational Oncology , National Center for Tumor Diseases Heidelberg, German Cancer Research Center (DKFZ) , Heidelberg , Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We live in an era of genomic medicine. The past five years brought about many significant achievements in the field of cancer genetics, driven by rapidly evolving technologies and plummeting costs of next-generation sequencing (NGS). The official completion of the Cancer Genome Project in 2014 led many to envision the clinical implementation of cancer genomic data as the next logical step in cancer therapy. Stemming from this vision, the term 'precision oncology' was coined to illustrate the novelty of this individualised approach. The basic assumption of precision oncology is that molecular markers detected by NGS will predict response to targeted therapies independently from tumour histology. However, along with a ubiquitous availability of NGS, the complexity and heterogeneity at the individual patient level had to be acknowledged. Not only does the latter present challenges to clinical decision-making based on sequencing data, it is also an obstacle to the rational design of clinical trials. Novel tissue-agnostic trial designs were quickly developed to overcome these challenges. Results from some of these trials have recently demonstrated the feasibility and efficacy of this approach. On the other hand, there is an increasing amount of whole-exome and whole-genome NGS data which allows us to assess ever smaller differences between individual patients with cancer. In this review, we highlight different tumour sequencing strategies currently used for precision oncology, describe their individual strengths and weaknesses, and emphasise their feasibility in different clinical settings. Further, we evaluate the possibility of NGS implementation in current and future clinical trials, and point to the significance of NGS for translational research.

Indexed as

Clinical Trial DesignNext-Generation SequencingPersonalized MedicinePrecision OncologyWhole-exome Sequencing

Identifiers

PMID27933214
PMCPMC5133384

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.