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Principal Investigator
Yong Zeng
Awardee Organization

University Of Kansas Lawrence
United States

Fiscal Year
2016
Activity Code
R21
Project End Date

Integrated Microfluidic Exosome Profiling for Early Detection of Cancer

Detection of asymptomatic early-stage disease is critical for effective treatment of most cancer types. For instance, when detected at Stage I, the 5-year survival rate for ovarian cancer patients is greater than 90%, versus 20% for advanced-stage disease. However, currently most cancers are diagnosed at late stages, which underscore the pressing need of novel biomarkers, strategies and technologies. Probing circulating exosomes is emerging as a new paradigm for non-invasive cancer diagnosis and monitoring of treatment response, because of growing evidences of their biological functions and clinical implications in tumorigenesis and progression. Tumor-derived exosomes accumulate in human blood and are enriched in a selective repertoire of biomolecules, including signaling proteins, enzymes, tumor antigens, miRNAs, and mRNAs. The constitutive release and exosome enrichment of certain tumor markers present distinctive opportunities for early cancer diagnosis. Despite the potential for cancer diagnosis, biology and clinical value of exosomes remain largely unknown, due to the challenges in efficient isolation, molecular classification and comprehensive characterization of exosomes. Here we propose to tackle this major roadblock by developing an innovative microfluidic technology that enables selective isolation, subpopulation classification by surface protein topography, and in situ multiplexed barcode protein profiling of exosomes, all streamlined in a "sample-in-answer-out" system. The project consists of two specific aims: 1) Develop an integrated Microfluidic Exosome Profiling Assay (MEPA) for molecular analysis of circulating exosomes in microliter volumes of plasma; and 2) Characterize and validate MEPA for potential use in early detection of cancer using ovarian cancer as the disease model. This research, if successful, will yield a transformative technology that can substantially improve the analytical performance for molecular characterization of tumor-derived exosomes while overcoming the constraints of exosome loss/damage during isolation, analysis throughput, and sample consumption in conventional protocols. Thus the technology should offer an unprecedented ability to accelerate the exosome research, opening new opportunities to probing the biology of a tumor noninvasively and to developing novel reliable biomarkers for screening and early detection of cancer.

Publications

  • Zhang P, Zhou X, Zeng Y. Multiplexed immunophenotyping of circulating exosomes on nano-engineered ExoProfile chip towards early diagnosis of cancer. Chemical science. 2019 Apr 22;10(21):5495-5504. doi: 10.1039/c9sc00961b. eCollection 2019 Jun 7. PMID: 31293733
  • Bucur O, Almasan A, Zubarev R, Friedman M, Nicolson GL, Sumazin P, Leabu M, Nikolajczyk BS, Avram D, Kunej T, Calin GA, Godwin AK, Adami HO, Zaphiropoulos PG, Richardson DR, Schmitt-Ulms G, Westerblad H, Keniry M, Grau GE, Carbonetto S, Stan RV, Popa-Wagner A, Takhar K, Baron BW, Galardy PJ, Yang F, Data D, Fadare O, Yeo KJ, Gabreanu GR, Andrei S, Soare GR, Nelson MA, Liehn EA. An updated h-index measures both the primary and total scientific output of a researcher. Discoveries (Craiova, Romania). 2015 Jul-Sep;3. (3). Epub 2015 Sep 30. PMID: 26504901
  • Wang Y, Southard KM, Zeng Y. Digital PCR using micropatterned superporous absorbent array chips. The Analyst. 2016 Jun 21;141(12):3821-31. Epub 2016 Mar 24. PMID: 27010726
  • Zhang P, He M, Zeng Y. Ultrasensitive microfluidic analysis of circulating exosomes using a nanostructured graphene oxide/polydopamine coating. Lab on a chip. 2016 Aug 2;16(16):3033-42. PMID: 27045543
  • Li K, Rodosthenous RS, Kashanchi F, Gingeras T, Gould SJ, Kuo LS, Kurre P, Lee H, Leonard JN, Liu H, Lombo TB, Momma S, Nolan JP, Ochocinska MJ, Pegtel DM, Sadovsky Y, Sánchez-Madrid F, Valdes KM, Vickers KC, Weaver AM, Witwer KW, Zeng Y, Das S, Raffai RL, Howcroft TK. Advances, challenges, and opportunities in extracellular RNA biology: insights from the NIH exRNA Strategic Workshop. JCI insight. 2018 Apr 5;3. (7). doi: 10.1172/jci.insight.98942. eCollection 2018 Apr 5. PMID: 29618663
  • Yang Y, Zeng Y. Microfluidic communicating vessel chip for expedited and automated immunomagnetic assays. Lab on a chip. 2018 Dec 4;18(24):3830-3839. PMID: 30394473
  • He M, Zeng Y. Microfluidic Exosome Analysis toward Liquid Biopsy for Cancer. Journal of laboratory automation. 2016 Aug;21(4):599-608. Epub 2016 May 23. PMID: 27215792
  • Zhang P, Crow J, Lella D, Zhou X, Samuel G, Godwin AK, Zeng Y. Ultrasensitive quantification of tumor mRNAs in extracellular vesicles with an integrated microfluidic digital analysis chip. Lab on a chip. 2018 Dec 4;18(24):3790-3801. PMID: 30474100
  • Cao H, Zhou X, Zeng Y. Microfluidic Exponential Rolling Circle Amplification for Sensitive microRNA Detection Directly from Biological Samples. Sensors and actuators. B, Chemical. 2019 Jan 15;279:447-457. Epub 2018 Oct 4. PMID: 30533973
  • Zhang P, Samuel G, Crow J, Godwin AK, Zeng Y. Molecular assessment of circulating exosomes toward liquid biopsy diagnosis of Ewing sarcoma family of tumors. Translational research : the journal of laboratory and clinical medicine. 2018 Nov;201:136-153. Epub 2018 Jun 23. PMID: 30031766
  • Zhao Z, Yang Y, Zeng Y, He M. A microfluidic ExoSearch chip for multiplexed exosome detection towards blood-based ovarian cancer diagnosis. Lab on a chip. 2016 Feb 7;16(3):489-96. PMID: 26645590
  • Alturkmani HJ, Pessetto ZY, Godwin AK. Beyond standard therapy: drugs under investigation for the treatment of gastrointestinal stromal tumor. Expert opinion on investigational drugs. 2015;24(8):1045-58. Epub 2015 Jun 22. PMID: 26098203
  • Zhang P, Zhou X, He M, Shang Y, Tetlow AL, Godwin AK, Zeng Y. Ultrasensitive detection of circulating exosomes with a 3D-nanopatterned microfluidic chip. Nature biomedical engineering. 2019 Jun;3(6):438-451. Epub 2019 Feb 25. PMID: 31123323