Evidence map›Paper›PMID 27099341›Full record

ReviewMolecular & cellular proteomics : MCP2016

Omics Profiling in Precision Oncology.

Kun-Hsing Yu, Michael Snyder

Abstract readReview
In one paragraph

Review in Molecular & cellular proteomics : MCP, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing 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

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

  1. Pooled it
  2. Review
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  4. Neuropilin-1: A Multifaceted Target for Cancer Therapy.Current oncology (Toronto, Ont.) · 2025
    Review
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  11. Diabetes management in the era of artificial intelligence.Archives of medical sciences. Atherosclerotic diseases · 2024
    Article
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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.

Kun-Hsing YuFrom the ‡Department of Genetics, Stanford University School of Medicine, Stanford, California; §Biomedical Informatics Program, Stanford University School of Medicine, Stanford, California.
Michael SnyderFrom the ‡Department of Genetics, Stanford University School of Medicine, Stanford, California; mpsnyder@stanford.edu.

Funding

Proteome Characterization Center: A Genoproteomics Pipeline for Cance ResearchU24CA160036 · NCI · JOHNS HOPKINS UNIVERSITY · PI CHAN, DANIEL WANYUI, ZHANG, HUI · 2011 to 2016
$10.7M
Integrative Omics as a Discovery Tool for Pulmonary HypertensionR01HL122887 · NHLBI · STANFORD UNIVERSITY · PI NICOLLS, MARK ROBERT, RABINOVITCH, MARLENE · 2015 to 2018
$4.1M
Robust, Generalizable, and Fair Machine Learning Models for BiomedicineR35GM142879 · NIGMS · HARVARD MEDICAL SCHOOL · PI YU, KUN-HSING · 2021 to 2025
$2.4M
Howard Hughes Medical InstituteNCI NIH HHS U24 CA160036NHLBI NIH HHS R01 HL122887NIGMS NIH HHS R35 GM142879
6 · The paper itself

Abstract

Cancer causes significant morbidity and mortality worldwide, and is the area most targeted in precision medicine. Recent development of high-throughput methods enables detailed omics analysis of the molecular mechanisms underpinning tumor biology. These studies have identified clinically actionable mutations, gene and protein expression patterns associated with prognosis, and provided further insights into the molecular mechanisms indicative of cancer biology and new therapeutics strategies such as immunotherapy. In this review, we summarize the techniques used for tumor omics analysis, recapitulate the key findings in cancer omics studies, and point to areas requiring further research on precision oncology.

Indexed as

MutationComputational BiologyGenomicsHumansMetabolomicsNeoplasmsPrecision MedicinePrognosisProteomics

Identifiers

PMID27099341
PMCPMC4974334

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.