Evidence map›Paper›PMID 27668290›Full record

ArticleTrends in cancer2016

Emerging role of mTOR in the response to cancer therapeutics.

Erika Ilagan, Brendan D Manning

Abstract read
In one paragraph

Article in Trends in cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers.

0numbers the graph read from it
0cells of the map it votes in
83citing 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

83 citing papers in PubMed.

  1. Article
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  14. Growth Signaling Networks Orchestrate Cancer Metabolic Networks.Cold Spring Harbor perspectives in medicine · 2024
    Review
  15. Article
  16. Defining theThyroid : official journal of the American Thyroid Association · 2024
    Article
  17. Article
  18. Article
  19. Review
  20. Article

23 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

2 authors.

Erika IlaganDepartment of Genetics and Complex Diseases, Harvard T.H. Chan School of Public Health, Boston, MA.
Brendan D ManningDepartment of Genetics and Complex Diseases, Harvard T.H. Chan School of Public Health, Boston, MA.

Funding

Tuberous Sclerosis-Pathway and PathogenesisP01CA120964 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI David J. Kwiatkowski · 2007 to 2026
$35.9M
Decoding and Targeting the PI3K-mTOR Signaling Network in CancerR35CA197459 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI BRENDAN D. MANNING · 2015 to 2026
$10.8M
Interdisciplinary Training in Genes and the EnvironmentT32ES016645 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LEE, CHIH-HAO · 2008 to 2018
$4.0M
Regulatory mechanisms and role of the PI3K-TSC-mTOR signaling network in tumorsR01CA122617 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI MANNING, BRENDAN D. · 2006 to 2015
$2.7M
NCI NIH HHS P01 CA120964NCI NIH HHS R01 CA122617NCI NIH HHS R35 CA197459NIEHS NIH HHS T32 ES016645
6 · The paper itself

Abstract

The movement toward precision medicine with targeted therapeutics for cancer treatment has been hindered by both innate and acquired resistance. Understanding the molecular wiring and plasticity of oncogenic signaling networks is essential to the development of therapeutic strategies to avoid or overcome resistance. The mechanistic target of rapamycin (mTOR) complex 1 (mTORC1) represents a highly integrated signaling node that is dysregulated in the majority of human cancers. Several studies have revealed that sustained mTORC1 inhibition is essential to avoid resistance to targeted therapeutics against the driving oncogenic pathway in a given cancer. Here we discuss the role of mTORC1 in dictating the response of tumors to targeted therapeutics and review recent examples from lung cancer, breast cancer, and melanoma.

Identifiers

PMID27668290
PMCPMC5033243

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Registered trials

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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.