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| Content Provider | frontiers |
|---|---|
| Author | Qin, Zhiyuan Xu, Qingwen Hu, Haihong Yu, Lushan Zeng, Su |
| 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. |
| ISSN | 2234943X |
| DOI | 10.3389/fonc.2020.00724 |
| Volume Number | 10 |
| Journal | Frontiers in Oncology |
| Language | English |
| Publisher Date | 2020-05-07 |
| Access Restriction | Open |
| Subject Keyword | Machine learning Renal cell carcinoma Drug vehicles Artificial intelligence Biomarkers Drug Targets Exosomes Extracellular vesicles (EVs) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Cancer Research Oncology |
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