Evidence map›Paper›PMID 30559933›Full record

ArticleOncotarget2018

Establishment of a novel cell line from a rare human duodenal poorly differentiated neuroendocrine carcinoma.

Kazuyoshi Yanagihara, Takanori Kubo, Keichiro Mihara, Takeshi Kuwata, Atsushi Ochiai, Toshio Seyama, Hiroshi Yokozaki

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

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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

7 authors at 5 institutions in 1 country.

Kazuyoshi YanagiharaDivision of Biomarker Discovery, Exploratory Oncology and Clinical Trial Center, National Cancer Center, Chiba, Japan.
Takanori KuboDepartment of Life Sciences, Yasuda Women's University Faculty of Pharmacy, Hiroshima, Japan.
Keichiro MiharaDepartment of Hematology/Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan.
Takeshi KuwataDepartment of Pathology and Clinical Laboratories, National Cancer Center Hospital East, Chiba, Japan.
Atsushi OchiaiDivision of Biomarker Discovery, Exploratory Oncology and Clinical Trial Center, National Cancer Center, Chiba, Japan.
Toshio SeyamaDepartment of Life Sciences, Yasuda Women's University Faculty of Pharmacy, Hiroshima, Japan.
Hiroshi YokozakiDivision of Pathology, Department of Pathology, Kobe University Graduate School of Medicine, Kobe, Japan.
Kobe University · JPYasuda Women's University · JPChiba Cancer Center · JPHiroshima University · JPNational Cancer Center Hospital East · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Poorly differentiated neuroendocrine carcinoma of the duodenum (D-NEC) is a rare cancer with poor prognosis. However, a D-NEC cell line has not yet been established to study the disease. We established a cell line, TCC-NECT-2, from the ascites tumor of a 59-year-old male Japanese patient with D-NEC. TCC-NECT-2 was positive for neuroendocrine markers, chromogranin A (CGA), cluster of differentiation 56 (CD56/NCAM), synaptophysin (SYN/p38), and neuron specific enolase (NSE). Cells exhibited retinoblastoma (RB) protein loss. Orthotopic implantation of TCC-NECT-2 cells into nu/nu mice resulted in tumor formation (incidence = 83.3%) with neuroendocrine characteristics, metastasis, and weight loss. BRAF

Indexed as

BRAFV600E mutationduodenal neuroendocrine carcinomaestablished cell lineorthotopic animal modelrare human cancer

Identifiers

PMID30559933
PMCPMC6284856
OpenAlexW2901289186

What OpenQuestion holds

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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.