Evidence map›Paper›PMID 29888341›Full record

ArticleJCO precision oncology2017

Comprehensive Analysis of the Unfolded Protein Response in Breast Cancer Subtypes.

Dadi Jiang, Brandon Turner, Jie Song, Ruijiang Li, Maximilian Diehn, Quynh-Thu Le, Purvesh Khatri, Albert C Koong

Abstract read
In one paragraph

Article in JCO precision oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

11 citing papers in PubMed, 18 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Dadi JiangStanford University School of Medicine, Stanford, CA.
Brandon TurnerStanford University School of Medicine, Stanford, CA.
Jie SongStanford University School of Medicine, Stanford, CA.
Ruijiang LiStanford University School of Medicine, Stanford, CA.
Maximilian DiehnStanford University School of Medicine, Stanford, CA.
Quynh-Thu LeStanford University School of Medicine, Stanford, CA.
Purvesh KhatriStanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA.
Albert C KoongStanford University School of Medicine, Stanford, CA.
Stanford University · US

Funding

Using a tonsil organoid system to probe conditions for the induction of protective antibody and T cell responses to influenza.U19AI057229 · NIAID · STANFORD UNIVERSITY · PI Mark Morris Davis · 2003 to 2026
$88.5M
Bioinformatics Approach to Influenza A/H1N1 Vaccine Immune ProfilingU01AI089859 · NIAID · MAYO CLINIC ROCHESTER · PI POLAND, GREGORY A. · 2010 to 2015
$33.8M
Translational Incubator CoreU19AI109662 · NIAID · STANFORD UNIVERSITY · PI GLENN, JEFFREY S · 2014 to 2019
$28.6M
TUMOR HYPOXIA--MOLECULAR STUDIES &CLINICAL EXPLOITATIONP01CA067166 · NCI · STANFORD UNIVERSITY · PI DENKO, NICHOLAS C. · 1996 to 2017
$25.5M
Targeting Galectin-1 with radiation in lung cancerR01CA161585 · NCI · STANFORD UNIVERSITY · PI KOONG, ALBERT, LE, QUYNH-THU XUAN · 2012 to 2016
$1.6M
NCI NIH HHS P01 CA067166NCI NIH HHS R01 CA161585NIAID NIH HHS U01 AI089859NIAID NIH HHS U19 AI057229NIAID NIH HHS U19 AI109662
6 · The paper itself

Abstract

purposeTriple-negative breast cancers (TNBCs) are associated with a worse prognosis and patients with TNBC have fewer therapeutic options than patients with non-TNBC. Recently, the IRE1α-XBP1 branch of the unfolded protein response (UPR) was implicated in TNBC prognosis on the basis of a relatively small patient population, suggesting the diagnostic and therapeutic value of this pathway in TNBCs. In addition, the IRE1α-XBP1 and hypoxia-induced factor 1 α (HIF1α) pathways have been identified as interacting partners in TNBC, suggesting a novel mechanism of regulation. To comprehensively evaluate and validate these findings, we investigated the relative activities and relevance to patient survival of the UPR and HIF1α pathways in different breast cancer subtypes in large populations of patients. MATERIALS AND

methodsWe performed a comprehensive analysis of gene expression and survival data from large cohorts of patients with breast cancer. The patients were stratified based on the average expression of the UPR or HIF1α gene signatures.

resultsWe identified a strong positive association between the XBP1 gene signature and estrogen receptor-positive status or the HIF1α gene signature, as well as the predictive value of the XBP1 gene signature for survival of patients who are estrogen receptor negative, or have TNBC or HER2

conclusionThese findings clarify the relevance of the UPR pathways in different breast cancer subtypes and underscore the potential therapeutic importance of the IRE1α-XBP1 branch in breast cancer treatment.

Identifiers

PMID29888341
PMCPMC5992919
OpenAlexW2738794631

What OpenQuestion holds

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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.