Evidence map›Paper›PMID 29079795›Full record

ArticleScientific reports2017

Comprehensive single-cell transcriptome analysis reveals heterogeneity in endometrioid adenocarcinoma tissues.

Shinichi Hashimoto, Yuta Tabuchi, Hideaki Yurino, Yoshihiko Hirohashi, Shungo Deshimaru, Takuya Asano, Tasuku Mariya, Kenshiro Oshima, Yuzuru Takamura, Yoshiaki Ukita and 13 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

10 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
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  4. Article
  5. Follicle-Stimulating Hormone Induces Lipid DropletsFrontiers in endocrinology · 2021
    Article
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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

23 authors at 8 institutions in 1 country.

Shinichi HashimotoDepartment of Integrative Medicine for Longevity, Graduate School of Medical Sciences, Kanazawa University, Ishikawa, 920-8641, Japan. hashimoto@med.kanazawa-u.ac.jp.
Yuta TabuchiDepartment of Pathology, School of Medicine, Sapporo Medical University, Hokkaido, 060-0061, Japan.
Hideaki YurinoDepartment of Integrative Medicine for Longevity, Graduate School of Medical Sciences, Kanazawa University, Ishikawa, 920-8641, Japan.
Yoshihiko HirohashiCREST, Japan Science and Technology Agency, Tokyo, 102-0076, Japan.
Shungo DeshimaruDepartment of Molecular Preventive Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan.
Takuya AsanoDepartment of Pathology, School of Medicine, Sapporo Medical University, Hokkaido, 060-0061, Japan.
Tasuku MariyaDepartment of Pathology, School of Medicine, Sapporo Medical University, Hokkaido, 060-0061, Japan.
Kenshiro OshimaDepartment of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, 277-8561, Japan.
Yuzuru TakamuraDepartment of Bioscience and Biotechnology, Japan Advanced Institute of Science and Technology, Ishikawa, 923-1292, Japan.
Yoshiaki UkitaFaculty of Engineering, Graduate Faculty of Interdisciplinary Research, University of Yamanashi, Yamanashi, 400-8511, Japan.
Akio AmetaniDepartment of Molecular Preventive Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan.
Naoto KondoRIKEN Center for Life Science Technologies, Kanagawa, 230-0045, Japan.
Norikazu MonmaLaboratory of DNA Data Analysis, National Institute of Genetics, Shizuoka, 411-8540, Japan.
Tadayuki TakedaRIKEN Center for Life Science Technologies, Kanagawa, 230-0045, Japan.
Sadahiko MisuLaboratory of DNA Data Analysis, National Institute of Genetics, Shizuoka, 411-8540, Japan.
Toshitugu OkayamaLaboratory of DNA Data Analysis, National Institute of Genetics, Shizuoka, 411-8540, Japan.
Kazuho IkeoLaboratory of DNA Data Analysis, National Institute of Genetics, Shizuoka, 411-8540, Japan.
Tsuyoshi SaitoDepartment of Obsterics and Gynecology, School of Medicine, Sapporo Medical University, Hokkaido, 060-0061, Japan.
Shuich KanekoDepartment of Disease Control and Homeostasis, Faculty of Medicine, Kanazawa University, Ishikawa, 920-8641, Japan.
Yutaka SuzukiDepartment of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, 277-8561, Japan.
Masahira HattoriDepartment of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, 277-8561, Japan.
Kouji MatsushimaDepartment of Molecular Preventive Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan.
Toshihiko TorigoeCREST, Japan Science and Technology Agency, Tokyo, 102-0076, Japan.
Sapporo Medical University · JPThe University of Tokyo · JPNational Institute of Genetics · JPKanazawa University · JPJapan Advanced Institute of Science and Technology · JPJapan Science and Technology Agency · JPUniversity of Yamanashi · JPWaseda University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single cell transcriptome analysis of a cancer tissue can provide objective assessment of subtype population or the activation of each of various microenvironment component cells. In this study, we applied our newly developed technique of single cell analysis to the myometrial infiltration side (M-side) and the endometrial side (E-side) of a human endometrioid adenocarcinoma with squamous differentiation tissues. We also analyzed spherogenic cultures derived from the same tissue to identify putative regulators of stemness in vivo. Cancer cells in the E-side were highly malignant compared with those in the M-side. Many cells on the E-side were positive for spheroid-specific tumorigenesis-related markers including SOX2. In addition, there were higher numbers of epithelial-to-mesenchymal transition (EMT) cells in the E-side compared with the M-side. This study identified a site containing cells with high malignant potential such as EMT and cancer stem-like cells in cancer tissues. Finally, we demonstrate that established endometrioid adenocarcinoma subtype classifiers were variably expressed across individual cells within a tumor. Thus, such intratumoral heterogeneity may be related to prognostic implications.

Indexed as

Gene Expression ProfilingSingle-Cell AnalysisAdenocarcinomaAdultChemokinesEndometrial NeoplasmsFemaleHumansMiddle AgedNeoplasm StagingPrognosisSpheroids, CellularChemokines

Identifiers

PMID29079795
PMCPMC5660171
OpenAlexW2766220228

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.