| Literature DB >> 32795414 |
Ayuko Hoshino1, Han Sang Kim2, Linda Bojmar3, Kofi Ennu Gyan4, Michele Cioffi5, Jonathan Hernandez6, Constantinos P Zambirinis7, Gonçalo Rodrigues8, Henrik Molina9, Søren Heissel9, Milica Tesic Mark9, Loïc Steiner10, Alberto Benito-Martin5, Serena Lucotti5, Angela Di Giannatale11, Katharine Offer5, Miho Nakajima5, Caitlin Williams5, Laura Nogués12, Fanny A Pelissier Vatter5, Ayako Hashimoto13, Alexander E Davies14, Daniela Freitas15, Candia M Kenific5, Yonathan Ararso5, Weston Buehring5, Pernille Lauritzen5, Yusuke Ogitani5, Kei Sugiura16, Naoko Takahashi17, Maša Alečković18, Kayleen A Bailey5, Joshua S Jolissant7, Huajuan Wang5, Ashton Harris5, L Miles Schaeffer5, Guillermo García-Santos19, Zoe Posner5, Vinod P Balachandran20, Yasmin Khakoo21, G Praveen Raju22, Avigdor Scherz23, Irit Sagi24, Ruth Scherz-Shouval25, Yosef Yarden24, Moshe Oren26, Mahathi Malladi21, Mary Petriccione21, Kevin C De Braganca21, Maria Donzelli21, Cheryl Fischer21, Stephanie Vitolano21, Geraldine P Wright21, Lee Ganshaw21, Mariel Marrano21, Amina Ahmed21, Joe DeStefano21, Enrico Danzer27, Michael H A Roehrl28, Norman J Lacayo29, Theresa C Vincent30, Martin R Weiser31, Mary S Brady32, Paul A Meyers21, Leonard H Wexler21, Srikanth R Ambati21, Alexander J Chou21, Emily K Slotkin21, Shakeel Modak21, Stephen S Roberts21, Ellen M Basu21, Daniel Diolaiti33, Benjamin A Krantz34, Fatima Cardoso35, Amber L Simpson36, Michael Berger28, Charles M Rudin37, Diane M Simeone33, Maneesh Jain38, Cyrus M Ghajar39, Surinder K Batra38, Ben Z Stanger40, Jack Bui41, Kristy A Brown42, Vinagolu K Rajasekhar43, John H Healey43, Maria de Sousa8, Kim Kramer21, Sujit Sheth44, Jeanine Baisch45, Virginia Pascual45, Todd E Heaton27, Michael P La Quaglia27, David J Pisapia46, Robert Schwartz47, Haiying Zhang5, Yuan Liu48, Arti Shukla49, Laurence Blavier50, Yves A DeClerck50, Mark LaBarge51, Mina J Bissell52, Thomas C Caffrey38, Paul M Grandgenett38, Michael A Hollingsworth38, Jacqueline Bromberg53, Bruno Costa-Silva54, Hector Peinado55, Yibin Kang18, Benjamin A Garcia56, Eileen M O'Reilly37, David Kelsen37, Tanya M Trippett21, David R Jones48, Irina R Matei5, William R Jarnagin57, David Lyden58.
Abstract
There is an unmet clinical need for improved tissue and liquid biopsy tools for cancer detection. We investigated the proteomic profile of extracellular vesicles and particles (EVPs) in 426 human samples from tissue explants (TEs), plasma, and other bodily fluids. Among traditional exosome markers, CD9, HSPA8, ALIX, and HSP90AB1 represent pan-EVP markers, while ACTB, MSN, and RAP1B are novel pan-EVP markers. To confirm that EVPs are ideal diagnostic tools, we analyzed proteomes of TE- (n = 151) and plasma-derived (n = 120) EVPs. Comparison of TE EVPs identified proteins (e.g., VCAN, TNC, and THBS2) that distinguish tumors from normal tissues with 90% sensitivity/94% specificity. Machine-learning classification of plasma-derived EVP cargo, including immunoglobulins, revealed 95% sensitivity/90% specificity in detecting cancer. Finally, we defined a panel of tumor-type-specific EVP proteins in TEs and plasma, which can classify tumors of unknown primary origin. Thus, EVP proteins can serve as reliable biomarkers for cancer detection and determining cancer type.Entities:
Keywords: biomarkers; cancer; cancer of unknown primary origin; damage-associated molecular patterns; early cancer detection; exomeres; exosomes; extracellular vesicles and particles; liquid biopsy; proteomics
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Year: 2020 PMID： 32795414 PMCID： PMC7522766 DOI： 10.1016/j.cell.2020.07.009
Source DB: PubMed Journal: Cell ISSN： 0092-8674 Impact factor: 66.850