Evidence map›Paper›PMID 29712909›Full record

ArticleNature communications2018

Widespread intronic polyadenylation diversifies immune cell transcriptomes.

Irtisha Singh, Shih-Han Lee, Adam S Sperling, Mehmet K Samur, Yu-Tzu Tai, Mariateresa Fulciniti, Nikhil C Munshi, Christine Mayr, Christina S Leslie

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers.

0numbers the graph read from it
0cells of the map it votes in
105citing papers in PubMed
6.7field-weighted citation impact, top 2% 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

105 citing papers in PubMed, 154 citations in OpenAlex.

  1. Review
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  5. Intronic polyadenylation-derived long noncoding RNA modulates nucleolar integrity and function.Proceedings of the National Academy of Sciences of the United States of America · 2026
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45 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

9 authors at 2 institutions in 1 country.

Irtisha SinghComputational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Shih-Han LeeCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Adam S SperlingLebow Institute of Myeloma Therapeutics and Jerome Lipper Multiple Myeloma Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.
Mehmet K SamurLebow Institute of Myeloma Therapeutics and Jerome Lipper Multiple Myeloma Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.
Yu-Tzu TaiLebow Institute of Myeloma Therapeutics and Jerome Lipper Multiple Myeloma Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.
Mariateresa FulcinitiLebow Institute of Myeloma Therapeutics and Jerome Lipper Multiple Myeloma Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.
Nikhil C MunshiLebow Institute of Myeloma Therapeutics and Jerome Lipper Multiple Myeloma Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.
Christine MayrCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. mayrc@mskcc.org.ORCID http://orcid.org/0000-0002-7084-7608
Christina S LeslieComputational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. cleslie@cbio.mskcc.org.
Dana-Farber Cancer Institute · USMemorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
Targeting Genomic Instability and Evolution in MyelomaP01CA155258 · NCI · DANA-FARBER CANCER INST · PI Nikhil C. Munshi · 2011 to 2026
$32.5M
3'UTR-mediated protein-protein interactions determine protein functionsDP1GM123454 · NIGMS · SLOAN-KETTERING INST CAN RESEARCH · PI MAYR, CHRISTINE · 2016 to 2020
$6.1M
Dissecting the role of alternative 3'UTRs in cancer with 3'-seqU01CA164190 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI LESLIE, CHRISTINA S, MAYR, CHRISTINE · 2012 to 2015
$2.3M
NCI NIH HHS P01 CA155258NCI NIH HHS P30 CA008748NCI NIH HHS U01 CA164190NIGMS NIH HHS DP1 GM123454
6 · The paper itself

Abstract

Alternative cleavage and polyadenylation (ApA) is known to alter untranslated region (3'UTR) length but can also recognize intronic polyadenylation (IpA) signals to generate transcripts that lose part or all of the coding region. We analyzed 46 3'-seq and RNA-seq profiles from normal human tissues, primary immune cells, and multiple myeloma (MM) samples and created an atlas of 4927 high-confidence IpA events represented in these cell types. IpA isoforms are widely expressed in immune cells, differentially used during B-cell development or in different cellular environments, and can generate truncated proteins lacking C-terminal functional domains. This can mimic ectodomain shedding through loss of transmembrane domains or alter the binding specificity of proteins with DNA-binding or protein-protein interaction domains. MM cells display a striking loss of IpA isoforms expressed in plasma cells, associated with shorter progression-free survival and impacting key genes in MM biology and response to lenalidomide.

Indexed as

IntronsPolyadenylationTranscriptome3' Untranslated RegionsAngiogenesis InhibitorsCase-Control StudiesGene ExpressionGene LibraryGene OntologyHeavy Chain DiseaseHumansImmunoglobulin mu-ChainsLenalidomideMultiple MyelomaPlasma CellsPrimary Cell Culture3' Untranslated RegionsAngiogenesis InhibitorsIGHM protein, humanImmunoglobulin mu-ChainsLenalidomide

Identifiers

PMID29712909
PMCPMC5928244
OpenAlexW2951986696

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.