journal article·2017-11-28Open access

The Exosome Total Isolation Chip

Fei Liu, Ophir Vermesh, Vigneshwaran Mani, Tianjia J. Ge, Steven J. Madsen, Andrew Sabour, En-Chi Hsu, Gayatri Gowrishankar, Masamitsu Kanada, Jesse V. Jokerst, Raymond G. Sierra, Edwin Chang, Kenneth Lau, Kaushik Sridhar, Abel Bermudez, Sharon J. Pitteri, Tanya Stoyanova, Robert Sinclair, Viswam S. Nair, Sanjiv S. Gambhir, Utkan Demirci

ACS Nano· Volume 11· Issue 11

Abstract

Circulating tumor-derived extracellular vesicles (EVs) have emerged as a promising source for identifying cancer biomarkers for early cancer detection. However, the clinical utility of EVs has thus far been limited by the fact that most EV isolation methods are tedious, nonstandardized, and require bulky instrumentation such as ultracentrifugation (UC). Here, we report a size-based EV isolation tool called ExoTIC (exosome total isolation chip), which is simple, easy-to-use, modular, and facilitates high-yield and high-purity EV isolation from biofluids. ExoTIC achieves an EV yield ∼4-1000-fold higher than that with UC, and EV-derived protein and microRNA levels are well-correlated between the two methods. Moreover, we demonstrate that ExoTIC is a modular platform that can sort a heterogeneous population of cancer cell line EVs based on size. Further, we utilize ExoTIC to isolate EVs from cancer patient clinical samples, including plasma, urine, and lavage, demonstrating the device's broad applicability to cancers and other diseases. Finally, the ability of ExoTIC to efficiently isolate EVs from small sample volumes opens up avenues for preclinical studies in small animal tumor models and for point-of-care EV-based clinical testing from fingerprick quantities (10-100 μL) of blood.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Extracellular vesicles in disease · RNA Interference and Gene Delivery · MicroRNA in disease regulation

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Ophthalmology & Optometry, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, Zhejiang 325035, China

Wenzhou Institute of Biomaterials and Engineering, Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China

Department of Pharmacology & Toxicology, and Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, Michigan 48824, United States

Department of NanoEngineering, University of California, San Diego, La Jolla, California 92093, United States

Stanford PULSE Institute, SLAC National Accelerator Lab, Menlo Park, California 94025, United States

Hard X-ray Department, LCLS, SLAC National Accelerator Lab, Menlo Park, California 94025, United States

Funding

National Cancer Institute · National Heart, Lung, and Blood Institute · U.S. Department of Defense · Canary Foundation

References (53)

Show source-provided references
1. 10.1016/0005-2736(81)90512-510.1016/0005-2736(81)90512-5 ↗
2. 10.1083/jcb.101.3.94210.1083/jcb.101.3.942 ↗
3. 10.1016/j.nano.2011.04.00310.1016/j.nano.2011.04.003 ↗
4. 10.1146/annurev-cellbio-101512-12232610.1146/annurev-cellbio-101512-122326 ↗
5. 10.1083/jcb.20121113810.1083/jcb.201211138 ↗
6. 10.1056/NEJMcibr150310010.1056/NEJMcibr1503100 ↗
7. 10.1016/j.tibtech.2017.03.00410.1016/j.tibtech.2017.03.004 ↗
8. 10.1038/nm.299410.1038/nm.2994 ↗
9. 10.4161/cc.2780410.4161/cc.27804 ↗
10. 10.1038/ncb221010.1038/ncb2210 ↗
11. 10.1038/nbt0416-35910.1038/nbt0416-359 ↗
12. 10.1038/nrclinonc.2017.1410.1038/nrclinonc.2017.14 ↗
13. 10.1002/0471143030.cb0322s3010.1002/0471143030.cb0322s30 ↗
14. 10.1016/j.jim.2014.06.00710.1016/j.jim.2014.06.007 ↗
15. 10.1016/j.chroma.2014.10.02610.1016/j.chroma.2014.10.026 ↗
16. 10.1152/ajprenal.00434.200610.1152/ajprenal.00434.2006 ↗
17. 10.1038/ncomms799910.1038/ncomms7999 ↗
18. 10.1002/pmic.20130028210.1002/pmic.201300282 ↗
19. 10.1016/j.ymeth.2015.02.01910.1016/j.ymeth.2015.02.019 ↗
20. 10.1007/978-1-61779-068-3_1510.1007/978-1-61779-068-3_15 ↗
21. 10.1039/c2lc41006k10.1039/c2lc41006k ↗
22. 10.1039/C4LC00662C10.1039/C4LC00662C ↗
23. 10.1021/nn506538f10.1021/nn506538f ↗
24. 10.1039/c3lc41343h10.1039/c3lc41343h ↗
25. 10.1021/acsnano.6b0613110.1021/acsnano.6b06131 ↗
26. 10.1038/nnano.2016.13410.1038/nnano.2016.134 ↗
27. 10.3402/jev.v3.2691310.3402/jev.v3.26913 ↗
28. 10.1038/s41551-016-002110.1038/s41551-016-0021 ↗
29. 10.3402/jev.v4.2706610.3402/jev.v4.27066 ↗
30. 10.7150/thno.1813310.7150/thno.18133 ↗
31. 10.1038/ncb180010.1038/ncb1800 ↗
32. 10.1593/neo.12201010.1593/neo.122010 ↗
33. 10.1186/1477-7819-12-210.1186/1477-7819-12-2 ↗
34. 10.1186/1476-4598-13-25610.1186/1476-4598-13-256 ↗
35. 10.3892/ijo.2016.345310.3892/ijo.2016.3453 ↗
36. 10.1097/MIB.000000000000054710.1097/MIB.0000000000000547 ↗
37. 10.1097/MIB.000000000000088310.1097/MIB.0000000000000883 ↗
38. 10.3390/jcm412195710.3390/jcm4121957 ↗
39. 10.1038/nbt138510.1038/nbt1385 ↗
40. 10.1186/s13000-015-0366-110.1186/s13000-015-0366-1 ↗
41. 10.1016/j.lungcan.2015.11.01310.1016/j.lungcan.2015.11.013 ↗
42. 10.1111/jcmm.1288910.1111/jcmm.12889 ↗
43. 10.18632/oncotarget.848210.18632/oncotarget.8482 ↗
44. 10.1016/j.nano.2016.12.00910.1016/j.nano.2016.12.009 ↗
45. 10.1182/blood-2010-06-29046010.1182/blood-2010-06-290460 ↗
46. 10.1248/bpb.b12-0060710.1248/bpb.b12-00607 ↗
47. 10.3402/jev.v4.2752210.3402/jev.v4.27522 ↗
48. 10.1038/srep2251910.1038/srep22519 ↗
49. 10.1007/s11060-015-1972-110.1007/s11060-015-1972-1 ↗
50. 10.3402/jev.v2i0.2038910.3402/jev.v2i0.20389 ↗
51. 10.1248/bpb.34.1310.1248/bpb.34.13 ↗
52. 10.1039/C5LC00240K10.1039/C5LC00240K ↗
53. 10.1038/srep4622410.1038/srep46224 ↗