Evidence map›Paper›PMID 25392689›Full record

ArticleCancer informatics2014

Inferring the Effects of Honokiol on the Notch Signaling Pathway in SW480 Colon Cancer Cells.

Michelle L Wynn, Nikita Consul, Sofia D Merajver, Santiago Schnell

Abstract read
In one paragraph

Article in Cancer informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Honokiol Suppression of Human Epidermal Growth Factor Receptor 2 (HER2)-Positive Gastric Cancer Cell Biological Activity and Its Mechanism.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
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

4 authors.

Michelle L WynnDepartment of Internal Medicine, Division of Hematology and Oncology and Comprehensive Cancer Center, University of Michigan, Medical School, Ann Arbor, MI, USA. ; Department of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, USA. ; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA. ; Brehm Center for Diabetes Research, University of Michigan Medical School, Ann Arbor, MI, USA.
Nikita ConsulColumbia University College of Physicians and Surgeons, New York, NY, USA.
Sofia D MerajverDepartment of Internal Medicine, Division of Hematology and Oncology and Comprehensive Cancer Center, University of Michigan, Medical School, Ann Arbor, MI, USA.
Santiago SchnellDepartment of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI, USA. ; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA. ; Brehm Center for Diabetes Research, University of Michigan Medical School, Ann Arbor, MI, USA.

Funding

Proteogenomics of Cancer Training ProgramT32CA140044 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI RAO, ARVIND, SARTOR, MAUREEN AGNES · 2010 to 2024
$3.9M
Interfacing computation and engineering with digestive and metabolic physiologyR25DK088752 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MACDOUGALD, ORMOND A · 2010 to 2020
$1.1M
NCI NIH HHS T32 CA140044NIDDK NIH HHS R25 DK088752
6 · The paper itself

Abstract

In a tumor cell, the development of acquired therapeutic resistance and the ability to survive in extracellular environments that differ from the primary site are the result of molecular adaptations in potentially highly plastic molecular networks. The accurate prediction of intracellular networks in a tumor remains a difficult problem in cancer informatics. In order to make truly rational patient-driven therapeutic decisions, it will be critical to develop methodologies that can accurately infer the molecular circuitry in the cells of a specific tumor. Despite enormous heterogeneity, cellular networks elicit deterministic digital-like responses. We discuss the use and limitations of methodologies that model molecular networks in cancer cells as a digital circuit. We also develop a network model of Notch signaling in colon cancer using a novel reverse engineering logic-based method and published western blot data to elucidate the interactions likely present in the circuits of the SW480 colon cancer cell line. Within this framework, we make predictions related to the role that honokiol may be playing as an anti-cancer drug.

Indexed as

honokiollogic networksNotchreverse engineeringsignaling pathways

Identifiers

PMID25392689
PMCPMC4218690

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.