Evidence map›Paper›PMID 28117883›Full record

ReviewCancer2017

Identifying and targeting cancer stem cells in the treatment of gastric cancer.

Tanios Bekaii-Saab, Bassel El-Rayes

Open access · hybridAbstract readReview
In one paragraph

Review in Cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
6.1field-weighted citation impact, top 2% 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

67 citing papers in PubMed, 119 citations in OpenAlex.

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  19. Article
  20. Stem Cell Biomarkers and Tumorigenesis in Gastric Cancer.Journal of personalized medicine · 2022
    Review

7 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 at 1 institution in 1 country.

Tanios Bekaii-SaabGastrointestinal Cancer Program, Mayo Clinic Cancer Center, Phoenix, Arizona.
Bassel El-RayesDepartment of Hematology and Medical Oncology, Emory School of Medicine, Atlanta, Georgia.
Mayo Clinic Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current treatment regimens for gastric cancer are not adequate. Cancer stem cells (CSCs) may be a key driving factor for growth and metastasis of this tumor type. In contrast to the conventional clonal evolution hypothesis, CSCs can initiate tumor formation, self-renew, and differentiate into tumor-propagating cells. Because gastric cancer can originate from CSCs, it is necessary to review current targets of signaling pathways for CSCs in gastric cancer that are being studied in clinical trials. These pathways are known to regulate the self-renewal and differentiation process in gastric CSCs. A better understanding of the clinical results of trials that target gastric CSCs will lead to better outcomes for patients with gastric cancer. Cancer 2017;123:1303-1312. © 2017 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Indexed as

Molecular Targeted TherapyAnimalsAntineoplastic AgentsBiomarkers, TumorClinical Trials as TopicDisease ManagementDrug DiscoveryHumansNeoplastic Stem CellsPractice Guidelines as TopicRisk FactorsSignal TransductionStomach NeoplasmsTreatment OutcomeAntineoplastic AgentsBiomarkers, Tumorcancer stem cellsclinical trialsgastric cancernapabucasintargeted therapyvismodeqib

Identifiers

PMID28117883
PMCPMC5412889
OpenAlexW2580141764

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.