Evidence map›Paper›PMID 30231942›Full record

ArticleCancer communications (London, England)2018

Transcriptomic but not genomic variability confers phenotype of breast cancer stem cells.

Mengying Tong, Ziqian Deng, Mengying Yang, Chang Xu, Xiaolong Zhang, Qingzheng Zhang, Yuwei Liao, Xiaodi Deng, Dekang Lv, Xuehong Zhang and 7 more

Abstract read
In one paragraph

Article in Cancer communications (London, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Review
  3. Omics Technologies Improving Breast Cancer Research and Diagnostics.International journal of molecular sciences · 2023
    Review
  4. A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer.International journal of molecular sciences · 2023
    Review
  5. Article
  6. Review
  7. Article
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  11. Review
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  15. Article
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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

17 authors.

Mengying TongCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Ziqian DengCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Mengying YangCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Chang XuCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Xiaolong ZhangCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Qingzheng ZhangCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Yuwei LiaoCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Xiaodi DengCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Dekang LvCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Xuehong ZhangCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Yu ZhangCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Peiying LiCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Luyao SongCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Bicheng WangState Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, P. R. China.
Aisha Al-DherasiCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China.
Zhiguang LiCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China. zhiguangli2013@126.com.
Quentin LiuCenter of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, P. R. China. liuq9@mail.sysu.edu.cn.

Funding

Innovative Research Team in University of Liaoning LT2017001International Scientific and Technological Cooperation of Dalian 2015F11GH095National Natural Science Foundation of China 81573025National Natural Science Foundation of China 81602200National Natural Science Foundation of China 81672784National Natural Science Foundation of China (CN) 81472637National Natural Science Foundation of China (CN) 81630005Program for Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China IRT_17R15The program for climbing Scholars of Liaoning, Dalian High-level Talent Innovation Program 2016RD12
6 · The paper itself

Abstract

backgroundBreast cancer stem cells (BCSCs) are considered responsible for cancer relapse and drug resistance. Understanding the identity of BCSCs may open new avenues in breast cancer therapy. Although several discoveries have been made on BCSC characterization, the factors critical to the origination of BCSCs are largely unclear. This study aimed to determine whether genomic mutations contribute to the acquisition of cancer stem-like phenotype and to investigate the genetic and transcriptional features of BCSCs.

methodsWe detected potential BCSC phenotype-associated mutation hotspot regions by using whole-genome sequencing on parental cancer cells and derived serial-generation spheres in increasing order of BCSC frequency, and then performed target deep DNA sequencing at bulk-cell and single-cell levels. To identify the transcriptional program associated with BCSCs, bulk-cell and single-cell RNA sequencing was performed.

resultsBy using whole-genome sequencing of bulk cells, potential BCSC phenotype-associated mutation hotspot regions were detected. Validation by target deep DNA sequencing, at both bulk-cell and single-cell levels, revealed no genetic changes specifically associated with BCSC phenotype. Moreover, single-cell RNA sequencing showed profound transcriptomic variability in cancer cells at the single-cell level that predicted BCSC features. Notably, this transcriptomic variability was enriched during the transcription of 74 genes, revealed as BCSC markers. Breast cancer patients with a high risk of relapse exhibited higher expression levels of these BCSC markers than those with a low risk of relapse, thereby highlighting the clinical significance of predicting breast cancer prognosis with these BCSC markers.

conclusionsTranscriptomic variability, not genetic mutations, distinguishes BCSCs from non-BCSCs. The identified 74 BCSC markers have the potential of becoming novel targets for breast cancer therapy.

Indexed as

Breast NeoplasmsFemaleHumansNeoplastic Stem CellsPhenotypeTranscriptomeBreast cancerCancer stem cellGenomicsSequencingTranscriptomics

Identifiers

PMID30231942
PMCPMC6146522

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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.