Evidence map›Paper›PMID 30575323›Full record

ArticleCancer medicine2019

A gene expression signature-based nomogram model in prediction of breast cancer bone metastases.

Chenglong Zhao, Yan Lou, Yao Wang, Dongsheng Wang, Liang Tang, Xin Gao, Kun Zhang, Wei Xu, Tielong Liu, Jianru Xiao

Abstract read
In one paragraph

Article in Cancer medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

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  8. Long non-coding RNAs in retinal neovascularization: current research and future directions.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2023
    Review
  9. Article
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  12. Advancing therapy for neuroblastoma.Nature reviews. Clinical oncology · 2022
    Review
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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

10 authors.

Chenglong ZhaoSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, China.ORCID 0000-0003-3779-9752
Yan LouSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Yao WangSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Dongsheng WangSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Liang TangSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Xin GaoSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Kun ZhangSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Wei XuSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Tielong LiuSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Jianru XiaoSpine Tumor Center, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, China.ORCID 0000-0002-7472-9916

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is prone to form bone metastases and subsequent skeletal-related events (SREs) dramatically decrease patients' quality of life and survival. Prediction and early management of bone lesions are valuable; however, proper prognostic models are inadequate. In the current study, we reviewed a total of 572 breast cancer patients in three microarray data sets including 191 bone metastases and 381 metastases-free. Gene set enrichment analysis (GSEA) indicated less aggressive and low-grade features of patients with bone metastases compared with metastases-free ones, while luminal subtypes are more prone to form bone metastases. Five bone metastases-related genes (KRT23, REEP1, SPIB, ALDH3B2, and GLDC) were identified and subjected to construct a gene expression signature-based nomogram (GESBN) model. The model performed well in both training and testing sets for evaluation of breast cancer bone metastases (BCBM). Clinically, the model may help in prediction of early bone metastases, prevention and management of SREs, and even help to prolong survivals for patients with BCBM. The five-gene GESBN model showed some implications as molecular diagnostic markers and therapeutic targets. Furthermore, our study also provided a way for analysis of tumor organ-specific metastases. To the best of our knowledge, this is the first published model focused on tumor organ-specific metastases.

Indexed as

Gene Expression Regulation, NeoplasticModels, GeneticAldehyde OxidoreductasesBone NeoplasmsBreast NeoplasmsDNA-Binding ProteinsFemaleGlycine Dehydrogenase (Decarboxylating)HumansKeratins, Type IMembrane Transport ProteinsNomogramsTranscription FactorsTranscriptomeAldehyde OxidoreductasesDNA-Binding ProteinsGlycine Dehydrogenase (Decarboxylating)Keratins, Type IKRT23 protein, humanMembrane Transport ProteinsREEP1 protein, humanSPIB protein, humanTranscription Factorsbone metastasesbreast cancerGSEAnomogramprognosis

Identifiers

PMID30575323
PMCPMC6346244

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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.