Evidence map›Paper›PMID 30596229›Full record

ArticleChemical research in toxicology2019

Targeted Profiling of Heat Shock Proteome in Radioresistant Breast Cancer Cells.

Weili Miao, Ming Fan, Ming Huang, Jian Jian Li, Yinsheng Wang

Abstract read
In one paragraph

Article in Chemical research in toxicology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

9 citing papers in PubMed, 19 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

5 authors at 2 institutions in 1 country.

Weili Miao
Ming Fan
Ming Huang
Jian Jian Li
University of California, Riverside · USUniversity of California, Davis · US

Funding

Research Training in Environmental ToxicologyT32ES018827 · NIEHS · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI Yinsheng Wang · 2010 to 2026
$5.3M
Quantitative Adductomics Approaches for Assessing the Occurrence and Repair of DNA AdductsR01CA210072 · NCI · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI WANG, YINSHENG · 2017 to 2021
$1.8M
NCI NIH HHS R01 CA210072NIEHS NIH HHS T32 ES018827
6 · The paper itself

Abstract

Breast cancer is the most commonly diagnosed cancer and the second leading cause of cancer death in women. Radioresistance remains one of the most critical barriers in radiation therapy for breast cancer. In this study, we employed a parallel-reaction monitoring (PRM)-based targeted proteomic method to examine the reprogramming of the heat shock proteome during the development of radioresistance in breast cancer. In particular, we investigated the differential expression of heat shock proteins (HSPs) in two pairs of matched parental/radioresistant breast cancer cell lines. We were able to quantify 43 and 42 HSPs in the MCF-7 and MDA-MB-231 pairs of cell lines, respectively. By analyzing the commonly altered proteins, we found that several members of the HSP70 and HSP40 subfamilies of HSPs exhibited substantially altered expression upon development of radioresistance. Moreover, the expression of HSPB8 is markedly elevated in the radioresistant lines relative to the parental MCF-7 and MDA-MB-231 cells. Together, our PRM-based targeted proteomics method revealed the reprogramming of the heat shock proteome during the development of radioresistance in breast cancer cells and offered potential targets for sensitizing breast cancer cells toward radiation therapy.

Indexed as

Radiation, IonizingBreast NeoplasmsCell Line, TumorChromatography, High Pressure LiquidFemaleHeat-Shock ProteinsHumansProteomeRadiation ToleranceTandem Mass SpectrometryHeat-Shock ProteinsProteome

Identifiers

PMID30596229
PMCPMC6469359
OpenAlexW2908196813

What OpenQuestion holds

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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.