Evidence map›Paper›PMID 28678827›Full record

ReviewPloS one2017

Identifying novel genes and biological processes relevant to the development of cancer therapy-induced mucositis: An informative gene network analysis.

Cielito C Reyes-Gibby, Stephanie C Melkonian, Jian Wang, Robert K Yu, Samuel A Shelburne, Charles Lu, Gary Brandon Gunn, Mark S Chambers, Ehab Y Hanna, Sai-Ching J Yeung and 1 more

Open access · goldAbstract readReview
In one paragraph

Review in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% of its field
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Prediction of mucositis risk secondary to cancer therapy: a systematic review of current evidence and call to action.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2020
    Pooled it
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  15. Leveraging human genetic and adverse outcome pathway (AOP) data to inform susceptibility in human health risk assessment.Mammalian genome : official journal of the International Mammalian Genome Society · 2018
    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

11 authors at 1 institution in 1 country.

Cielito C Reyes-GibbyDepartment of Emergency Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Stephanie C MelkonianDepartment of Emergency Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Jian WangDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Robert K YuDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Samuel A ShelburneDepartment of Infectious Diseases, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Charles LuDepartment of Thoracic Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Gary Brandon GunnDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Mark S ChambersDepartment of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Ehab Y HannaDepartment of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Sai-Ching J YeungDepartment of Emergency Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Sanjay SheteDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
The University of Texas MD Anderson Cancer Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Molecular Epidemiology of Neuropathic Pain in Head and Neck CancerR01DE022891 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI REYES-GIBBY, CIELITO C, SHETE, SANJAY · 2012 to 2016
$3.0M
Innovative Multidisciplinary Education: The Statistical Genetics of AddictionR25DA026120 · NIDA · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI CHANG, SHINE, SHETE, SANJAY · 2010 to 2014
$1.5M
Method to analyze X-chromosomal genetic dataR03CA192197 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI WANG, JIAN · 2015 to 2016
$160k
NCI NIH HHS P30 CA016672NCI NIH HHS R03 CA192197NIDA NIH HHS R25 DA026120NIDCR NIH HHS R01 DE022891
6 · The paper itself

Abstract

Mucositis is a complex, dose-limiting toxicity of chemotherapy or radiotherapy that leads to painful mouth ulcers, difficulty eating or swallowing, gastrointestinal distress, and reduced quality of life for patients with cancer. Mucositis is most common for those undergoing high-dose chemotherapy and hematopoietic stem cell transplantation and for those being treated for malignancies of the head and neck. Treatment and management of mucositis remain challenging. It is expected that multiple genes are involved in the formation, severity, and persistence of mucositis. We used Ingenuity Pathway Analysis (IPA), a novel network-based approach that integrates complex intracellular and intercellular interactions involved in diseases, to systematically explore the molecular complexity of mucositis. As a first step, we searched the literature to identify genes that harbor or are close to the genetic variants significantly associated with mucositis. Our literature review identified 27 candidate genes, of which ERCC1, XRCC1, and MTHFR were the most frequently studied for mucositis. On the basis of this 27-gene list, we used IPA to generate gene networks for mucositis. The most biologically significant novel molecules identified through IPA analyses included TP53, CTNNB1, MYC, RB1, P38 MAPK, and EP300. Additionally, uracil degradation II (reductive) and thymine degradation pathways (p = 1.06-08) were most significant. Finally, utilizing 66 SNPs within the 8 most connected IPA-derived candidate molecules, we conducted a genetic association study for oral mucositis in the head and neck cancer patients who were treated using chemotherapy and/or radiation therapy (186 head and neck cancer patients with oral mucositis vs. 699 head and neck cancer patients without oral mucositis). The top ranked gene identified through this association analysis was RB1 (rs2227311, p-value = 0.034, odds ratio = 0.67). In conclusion, gene network analysis identified novel molecules and biological processes, including pathways related to inflammation and oxidative stress, that are relevant to mucositis development, thus providing the basis for future studies to improve the management and treatment of mucositis in patients with cancer.

Indexed as

Gene Regulatory NetworksGenetic Predisposition to DiseaseAntineoplastic AgentsHead and Neck NeoplasmsHumansMucositisAntineoplastic Agents

Identifiers

PMID28678827
PMCPMC5498049
OpenAlexW2725431702

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.