Evidence map›Paper›PMID 32266133›Full record

ArticleFrontiers in oncology2020

Promoter-Level Transcriptome Identifies Stemness Associated With Relatively High Proliferation in Pancreatic Cancer Cells.

Ru Chen, Aiko Sugiyama, Naoyuki Kataoka, Masahiro Sugimoto, Shoko Yokoyama, Akihisa Fukuda, Shigeo Takaishi, Hiroshi Seno

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 58% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

8 authors at 3 institutions in 1 country.

Ru ChenDepartment of Gastroenterology and Hepatology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Aiko SugiyamaDepartment of Gastroenterology and Hepatology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Naoyuki KataokaLaboratory of Cell Regulation, Department of Applied Animal Sciences, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan.
Masahiro SugimotoResearch and Development Center for Minimally Invasive Therapies Health Promotion and Preemptive Medicine, Tokyo Medical University, Tokyo, Japan.
Shoko YokoyamaDSK Project, Medical Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Akihisa FukudaDepartment of Gastroenterology and Hepatology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Shigeo TakaishiDSK Project, Medical Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Hiroshi SenoDepartment of Gastroenterology and Hepatology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Kyoto University · JPThe University of Tokyo · JPTokyo Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Both pancreatic intraepithelial neoplasia (PanIN), a frequent precursor of pancreatic cancer, and intraductal papillary mucinous neoplasm (IPMN), a less common precursor, undergo several phases of molecular conversions and finally develop into highly malignant solid tumors with negative effects on the quality of life. We approached this long-standing issue by examining the following PanIN/IPMN cell lines derived from mouse models of pancreatic cancer: Ptf1a-Cre; Kras

Indexed as

cap analysis of gene expressionintraductal papillary mucinous neoplasmmolecular profilingpancreatic intraepithelial neoplasiatranscriptome

Identifiers

PMID32266133
PMCPMC7099289
OpenAlexW3011420820

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.