Evidence map›Paper›PMID 36417526›Full record

ArticleScience advances2022

Widespread hypertranscription in aggressive human cancers.

Matthew Zatzman, Fabio Fuligni, Ryan Ripsman, Tannu Suwal, Federico Comitani, Lisa-Monique Edward, Rob Denroche, Gun Ho Jang, Faiyaz Notta, Steven Gallinger and 6 more

Abstract read
In one paragraph

Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

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  17. Combined HDAC and eIF4A inhibition: A novel epigenetic therapy for pancreatic ductal adenocarcinoma.Drug resistance updates : reviews and commentaries in antimicrobial and anticancer chemotherapy · 2026
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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

16 authors.

Matthew ZatzmanDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0001-5235-4116
Fabio FuligniProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.
Ryan RipsmanProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.ORCID 0000-0003-1763-2357
Tannu SuwalDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0002-9434-9064
Federico ComitaniProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.ORCID 0000-0003-3226-1179
Lisa-Monique EdwardProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.
Rob DenrochePanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.ORCID 0000-0003-2197-7083
Gun Ho JangPanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
Faiyaz NottaPanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
Steven GallingerPanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
Saravana P SelvanathanDepartments of Oncology and Pediatrics, Georgetown University, Washington, DC 20057, USA.ORCID 0000-0002-6990-5188
Jeffrey A ToretskyDepartments of Oncology and Pediatrics, Georgetown University, Washington, DC 20057, USA.ORCID 0000-0003-3619-2879
Matthew D HellmannDepartment of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Uri TaboriProgram in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.
Annie HuangDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
Adam ShlienDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0002-0368-5370

Funding

Large Scale Sequencing and Analysis of GenomesU54HG003067 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GABRIEL, STACEY, LANDER, ERIC S · 2004 to 2015
$568.6M
X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Dissection of EWS-FLI1 oncogenic mechanisms and small molecule targetingR01CA233619 · NCI · GEORGETOWN UNIVERSITY · PI TORETSKY, JEFFREY A · 2020 to 2025
$1.9M
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA233619NHGRI NIH HHS U54 HG003067
6 · The paper itself

Abstract

Cancers are often defined by the dysregulation of specific transcriptional programs; however, the importance of global transcriptional changes is less understood. Hypertranscription is the genome-wide increase in RNA output. Hypertranscription's prevalence, underlying drivers, and prognostic significance are undefined in primary human cancer. This is due, in part, to limitations of expression profiling methods, which assume equal RNA output between samples. Here, we developed a computational method to directly measure hypertranscription in 7494 human tumors, spanning 31 cancer types. Hypertranscription is ubiquitous across cancer, especially in aggressive disease. It defines patient subgroups with worse survival, even within well-established subtypes. Our data suggest that loss of transcriptional suppression underpins the hypertranscriptional phenotype. Single-cell analysis reveals hypertranscriptional clones, which dominate transcript production regardless of their size. Last, patients with hypertranscribed mutations have improved response to immune checkpoint therapy. Our results provide fundamental insights into gene dysregulation across human cancers and may prove useful in identifying patients who would benefit from novel therapies.

Indexed as

NeoplasmsHumansPrognosisRNARNA

Identifiers

PMID36417526
PMCPMC9683723

What OpenQuestion holds

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LicenceCC BY-NC
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.