Evidence map›Paper›PMID 26073078›Full record

ArticleOncogene2016

High-resolution profiling of histone h3 lysine 36 trimethylation in metastatic renal cell carcinoma.

T H Ho, I Y Park, H Zhao, P Tong, M D Champion, H Yan, F A Monzon, A Hoang, P Tamboli, A S Parker and 11 more

Open access · hybridAbstract read
In one paragraph

Article in Oncogene, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
4.8field-weighted citation impact, top 4% 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

62 citing papers in PubMed, 84 citations in OpenAlex.

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  12. Investigating the Role ofInternational journal of molecular sciences · 2023
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2 more citing papers are in PubMed but not listed here.

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

21 authors at 8 institutions in 2 countries.

T H HoDivision of Hematology and Medical Oncology, Mayo Clinic, Scottsdale, AZ, USA.
I Y ParkCenter for Translational Cancer Research, Institute of Biosciences and Technology, Texas A&M Health Science Center, Houston, TX, USA.
H ZhaoDepartment of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
P TongDepartment of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
M D ChampionCenter for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
H YanCenter for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
F A MonzonDepartment of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA.
A HoangDepartment of Genitourinary Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
P TamboliDepartment of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
A S ParkerDepartment of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA.
R W JosephDivision of Hematology and Medical Oncology, Mayo Clinic, Jacksonville, FL, USA.
W QiaoDivision of Quantitative Sciences, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
K DykemaCenter for Cancer Genomics and Computational Biology, Van Andel Institute, Grand Rapids, MI, USA.
N M TannirDepartment of Genitourinary Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
E P CastleDepartment of Urology, Mayo Clinic, Scottsdale, AZ, USA.
R Nunez-NaterasDepartment of Urology, Mayo Clinic, Scottsdale, AZ, USA.
B T TehCenter for Cancer Genomics and Computational Biology, Van Andel Institute, Grand Rapids, MI, USA.
J WangDepartment of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
C L WalkerCenter for Translational Cancer Research, Institute of Biosciences and Technology, Texas A&M Health Science Center, Houston, TX, USA.
M-C HungDepartment of Molecular and Cellular Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
E JonaschDepartment of Genitourinary Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
The University of Texas MD Anderson Cancer Center · USMayo Clinic in Arizona · USTexas A&M Health Science Center · USVan Andel Institute · USBaylor College of Medicine · USMayo Clinic · USMayo Clinic in Florida · USWinnMed · US

Funding

Women's Cancer ProgramP30CA015083 · NCI · MAYO CLINIC ROCHESTER · PI Felicity Enders · 1985 to 2026
$151.3M
Paul Calabresi Program in Clinical/Translational Research at Mayo ClinicK12CA090628 · NCI · MAYO CLINIC ROCHESTER · PI WEROHA, SARAVUT · 2001 to 2025
$19.7M
Tumor Suppressor Localization and Function at the PeroxisomeR01CA143811 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI WALKER, CHERYL L. · 2010 to 2018
$2.9M
Design and Validation of a Biomarker-enhanced System to Predict RCC ProgressionR01CA134466 · NCI · MAYO CLINIC JACKSONVILLE · PI PARKER, ALEXANDER S · 2010 to 2014
$1.7M
NCI NIH HHS K12 CA090628NCI NIH HHS K12 CA90628NCI NIH HHS P30 CA015083NCI NIH HHS R01 CA134466NCI NIH HHS R01 CA143811
6 · The paper itself

Abstract

Mutations in SETD2, a histone H3 lysine trimethyltransferase, have been identified in clear cell renal cell carcinoma (ccRCC); however it is unclear if loss of SETD2 function alters the genomic distribution of histone 3 lysine 36 trimethylation (H3K36me3) in ccRCC. Furthermore, published epigenomic profiles are not specific to H3K36me3 or metastatic tumors. To determine if progressive SETD2 and H3K36me3 dysregulation occurs in metastatic tumors, H3K36me3, SETD2 copy number (CN) or SETD2 mRNA abundance was assessed in two independent cohorts: metastatic ccRCC (n=71) and the Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma data set (n=413). Although SETD2 CN loss occurs with high frequency (>90%), H3K36me3 is not significantly impacted by monoallelic loss of SETD2. H3K36me3-positive nuclei were reduced an average of ~20% in primary ccRCC (90% positive nuclei in uninvolved vs 70% positive nuclei in ccRCC) and reduced by ~60% in metastases (90% positive in uninvolved kidney vs 30% positive in metastases) (P<0.001). To define a kidney-specific H3K36me3 profile, we generated genome-wide H3K36me3 profiles from four cytoreductive nephrectomies and SETD2 isogenic renal cell carcinoma (RCC) cell lines using chromatin immunoprecipitation coupled with high-throughput DNA sequencing and RNA sequencing. SETD2 loss of methyltransferase activity leads to regional alterations of H3K36me3 associated with aberrant RNA splicing in a SETD2 mutant RCC and SETD2 knockout cell line. These data suggest that during progression of ccRCC, a decline in H3K36me3 is observed in distant metastases, and regional H3K36me3 alterations influence alternative splicing in ccRCC.

Indexed as

Neoplasm MetastasisCarcinoma, Renal CellChromatin ImmunoprecipitationCohort StudiesHistonesHumansKidney NeoplasmsLysineMethylationHistonesLysine

Identifiers

PMID26073078
PMCPMC4679725
OpenAlexW1524165063

What OpenQuestion 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 OpenQuestion graph.