Evidence map›Paper›PMID 32457844›Full record

ReviewFrontiers in oncology2020

Extracellular Vesicles in Renal Cell Carcinoma: Multifaceted Roles and Potential Applications Identified by Experimental and Computational Methods.

Zhiyuan Qin, Qingwen Xu, Haihong Hu, Lushan Yu, Su Zeng

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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  19. Extracellular vesicles in urological malignancies.Biochimica et biophysica acta. Reviews on cancer · 2021
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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.

Zhiyuan QinCollege of Pharmaceutical Sciences, Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang University, Hangzhou, China.
Qingwen XuCollege of Pharmaceutical Sciences, Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang University, Hangzhou, China.
Haihong HuCollege of Pharmaceutical Sciences, Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang University, Hangzhou, China.
Lushan YuCollege of Pharmaceutical Sciences, Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang University, Hangzhou, China.
Su ZengCollege of Pharmaceutical Sciences, Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Renal cell carcinoma (RCC) is the most common type of kidney cancer. Increasingly evidences indicate that extracellular vesicles (EVs) orchestrate multiple processes in tumorigenesis, metastasis, immune evasion, and drug response of RCC. EVs are lipid membrane-bound vesicles in nanometer size and secreted by almost all cell types into the extracellular milieu. A myriad of bioactive molecules such as RNA, DNA, protein, and lipid are able to be delivered via EVs for the intercellular communication. Hence, the abundant content of EVs is appealing reservoir for biomarker identification through computational analysis and experimental validation. EVs with excellent biocompatibility and biodistribution are natural platforms that can be engineered to offer achievable drug delivery strategies for RCC therapies. Moreover, the multifaceted roles of EVs in RCC progression also provide substantial targets and facilitate EVs-based drug discovery, which will be accelerated by using artificial intelligence approaches. In this review, we summarized the vital roles of EVs in occurrence, metastasis, immune evasion, and drug resistance of RCC. Furthermore, we also recapitulated and prospected the EVs-based potential applications in RCC, including biomarker identification, drug vehicle development as well as drug target discovery.

Indexed as

artificial intelligencebiomarkersdrug targetsdrug vehiclesexosomesextracellular vesiclesmachine learningrenal cell carcinoma

Identifiers

PMID32457844
PMCPMC7221139

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.