Evidence map›Paper›PMID 33094831›Full record

ArticleHistology and histopathology2021

Identifying specific Notch1 target proteins in lung carcinoma cells.

Wael Abdo Hassan, Takaaki Ito

Abstract read
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In one paragraph

Article in Histology and histopathology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 53% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
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 2 institutions in 2 countries.

Wael Abdo HassanDepartment of Pathology, Faculty of Medicine, Suez Canal University, Ismailia, Egypt.
Takaaki ItoDepartment of Pathology and Experimental Medicine, Kumamoto University, Graduate School of Medical Sciences, Kumamoto, Japan.
Kumamoto University · JPSuez Canal University · EG

Funding

Ministry of Education, Culture, Sports, Science and Technology of Japan 23220010
6 · The paper itself

Abstract

backgroundThe Notch signaling pathway has different roles in many human neoplasms, being either tumor-promoting or anti-proliferative. In addition, Notch signaling in carcinogenesis can be tissue dependent. The aim of the current study is to elucidate the relation between Notch1 protein expression in lung cancer cells and the following Notch related proteins: Hes1, c-Myc, Jagged1 and Jagged2.

methodsNotch1 and its related proteins were detected in human lung cancer cell lines and in 54 surgically resected different lung carcinoma tissues. Then, we used small interfering RNA (siRNA) technology, to down-regulate the expression of Notch1 in H69AR and SBC3 small cell lung carcinoma (SCLC) cells. Also, we transfected venus Notch1 intracellular domain (v.NICD) plasmid into human SCLC lines; H69.

resultsThe expression of Hes1, c-Myc and Jagged2 is affected by Notch1 in SCLC.

conclusionThere is a strong association between the expression of Notch1 protein and the expression of Hes1, c-Myc and Jagged2 proteins, which could aid in better understanding tumorigenesis in SCLC.

Indexed as

Gene Expression Regulation, NeoplasticA549 CellsCell Line, TumorHumansJagged-1 ProteinJagged-2 ProteinLung NeoplasmsProto-Oncogene Proteins c-mycReceptor, Notch1Receptors, NotchRNA, Small InterferingSignal TransductionSmall Cell Lung CarcinomaTranscription Factor HES-1HES1 protein, humanJAG1 protein, humanJAG2 protein, humanJagged-1 ProteinJagged-2 ProteinMYC protein, humanNOTCH1 protein, humanProto-Oncogene Proteins c-mycReceptor, Notch1Receptors, NotchRNA, Small InterferingTranscription Factor HES-1

Identifiers

PMID33094831
OpenAlexW3094229204

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.