Evidence map›Paper›PMID 31165154›Full record

ReviewJournal of the National Cancer Institute2019

The Pros and Cons of Incorporating Transcriptomics in the Age of Precision Oncology.

Victor T G Lin, Eddy S Yang

Abstract readReview
In one paragraph

Review in Journal of the National Cancer Institute, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Current status of ctDNA in precision oncology for hepatocellular carcinoma.Journal of experimental & clinical cancer research : CR · 2021
    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

2 authors.

Victor T G Lin
Eddy S Yang

Funding

Research Training Program in Basic and Translational OncologyT32CA183926 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI BHATIA, RAVI · 2014 to 2018
$1.0M
NCI NIH HHS T32 CA183926
6 · The paper itself

Abstract

The treatment of cancer continues to evolve toward personalized therapies based on individual patient and tumor characteristics. Our successes and failures in adopting a precision-oncology approach have demonstrated the utmost importance in identifying the proper predictive biomarkers of response. Until recently, most biomarkers were identified using immunohistochemistry for protein expression or single-gene analysis to identify targetable alterations. With the rapid propagation of next-generation sequencing to evaluate tumor tissue and "liquid biopsies," identification of genomic biomarkers is now standard, particularly in non-small cell lung cancer, for which there is now an extensive catalog of biomarker-directed therapies with more anticipated to come. Despite these great strides, it has also become apparent that using genomic biomarkers alone will be insufficient, as it has been consistently shown that at least one-half of patients who undergo tumor genomic profiling have no actionable alteration. This is perhaps to be expected given the remarkable breadth of nongenetic factors that contribute to tumor initiation and progression. Some have proposed that the next logical step is to use transcriptome profiling to define new biomarkers of response to targeted agents. Recently, results from the WINTHER trial were published, specifically investigating the use of transcriptomics to improve match rates over genomic next-generation sequencing alone. In this review, we discuss the complexities of precision-oncology efforts and appraise the available evidence supporting the incorporation of transcriptomic data into the precision-oncology framework in the historical context of the development of biomarkers for directing cancer therapy.

Indexed as

Gene Expression ProfilingMedical OncologyPrecision MedicineTranscriptomeBiomarkers, TumorDisease ManagementHumansLiquid BiopsyMolecular Diagnostic TechniquesMolecular Targeted TherapyNeoplasmsBiomarkers, Tumor

Identifiers

PMID31165154
PMCPMC6792065

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.