Evidence map›Paper›PMID 39715959›Full record

ArticleDiscover oncology2024

Nuclear receptor profiling for subtype classification and as prognostic markers in 33 cancer types.

Kazuya Nakamichi, Hironori Suzuki, Yusuke Yamamoto, Kentaro Semba, Jun Nakayama

Abstract read
In one paragraph

Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Kazuya NakamichiDepartment of Life Science and Medical Bioscience, School of Advanced Science and Engineering, Waseda University, Tokyo, Japan.ORCID http://orcid.org/0009-0002-9794-590X
Hironori SuzukiLaboratory of Integrative Oncology, National Cancer Center Research Institute, Tokyo, Japan.ORCID http://orcid.org/0009-0001-6291-4217
Yusuke YamamotoLaboratory of Integrative Oncology, National Cancer Center Research Institute, Tokyo, Japan.ORCID http://orcid.org/0000-0002-5262-8479
Kentaro SembaDepartment of Life Science and Medical Bioscience, School of Advanced Science and Engineering, Waseda University, Tokyo, Japan.ORCID http://orcid.org/0000-0001-7507-8214
Jun NakayamaLaboratory of Integrative Oncology, National Cancer Center Research Institute, Tokyo, Japan. jun.nakayama@oici.jp.ORCID http://orcid.org/0000-0001-8844-4295

Funding

Japan Society for the Promotion of Science 18K16269Japan Society for the Promotion of Science 21H02721
6 · The paper itself

Abstract

Nuclear receptors, a group of 48 transcription factors that regulate a multitude of processes within our body, have long been employed as diagnostic markers or therapeutic targets in breast cancer, prostate cancer, and acute promyelocytic leukemia. Unfortunately, no comprehensive investigation has been conducted on their significance in other cancer types. The current study aimed to explore novel diagnostic markers by classifying nuclear receptors according to their expression patterns based on transcriptome data from The Cancer Genome Atlas on 10,071 tumor samples across 33 cancer types and investigating their association with genetic mutations, histological types, and prognosis. Our analysis showed that 21 cancers, including breast cancer, can be classified into distinct clusters based on their nuclear receptor expression profiles. Moreover, significant differences in overall survival were observed in 9 of the 21 cancer types. Overall, the results of this study indicate that previously overlooked nuclear receptors, such as NR0B1 in lung adenocarcinoma, may prove beneficial in the diagnosis of several cancers.

Indexed as

ClassificationHierarchical clusteringNuclear receptorPan-cancer analysisTCGA

Identifiers

PMID39715959
PMCPMC11666854

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.