Evidence map›Paper›PMID 33413400›Full record

ArticleJournal of translational medicine2021

Transcriptomic analysis identifies organ-specific metastasis genes and pathways across different primary sites.

Lin Zhang, Ming Fan, Francesco Napolitano, Xin Gao, Ying Xu, Lihua Li

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
6.9field-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

24 citing papers in PubMed, 37 citations in OpenAlex.

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  15. Metastatic organotropism: a brief overview.Frontiers in oncology · 2024
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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

6 authors at 3 institutions in 3 countries.

Lin ZhangInstitute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, 310000, China.
Ming FanInstitute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, 310000, China.
Francesco NapolitanoComputer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
Xin GaoComputer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
Ying XuCancer Systems Biology Center, The China-Japan Union Hospital, Jilin University, Changchun, 130033, China.
Lihua LiInstitute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, 310000, China. lilh@hdu.edu.cn.ORCID 0000-0003-0435-6453
Hangzhou Dianzi University · CNKing Abdullah University of Science and Technology · SAUniversity of Georgia · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetastasis is the most devastating stage of cancer progression and often shows a preference for specific organs.

methodsTo reveal the mechanisms underlying organ-specific metastasis, we systematically analyzed gene expression profiles for three common metastasis sites across all available primary origins. A rank-based method was used to detect differentially expressed genes between metastatic tumor tissues and corresponding control tissues. For each metastasis site, the common differentially expressed genes across all primary origins were identified as organ-specific metastasis genes.

resultsPathways enriched by these genes reveal an interplay between the molecular characteristics of the cancer cells and those of the target organ. Specifically, the neuroactive ligand-receptor interaction pathway and HIF-1 signaling pathway were found to have prominent roles in adapting to the target organ environment in brain and liver metastases, respectively. Finally, the identified organ-specific metastasis genes and pathways were validated using a primary breast tumor dataset. Survival and cluster analysis showed that organ-specific metastasis genes and pathways tended to be expressed uniquely by a subgroup of patients having metastasis to the target organ, and were associated with the clinical outcome.

conclusionsElucidating the genes and pathways underlying organ-specific metastasis may help to identify drug targets and develop treatment strategies to benefit patients.

Indexed as

Breast NeoplasmsLiver NeoplasmsBreastGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNeoplasm MetastasisTranscriptomeGene expression profilesOrgan-specific metastasisPathway analysis

Identifiers

PMID33413400
PMCPMC7791985
OpenAlexW3119108208

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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.