A proteomic signature of ovarian cancer tumor fluid identified by highthroughput and verified by targeted proteomics

被引:31
|
作者
Poersch, Aline [1 ,2 ,3 ]
Grassi, Mariana Lopes [1 ,3 ]
de Carvalho, Vinicius Pereira [1 ,4 ]
Lanfredi, Guilherme Pauperio [1 ]
Palma, Camila de Souza [1 ,3 ]
Greene, Lewis Joel [3 ,5 ]
de Sousa, Christiani Bisinoto [2 ]
Angotti Carrara, Helio Humberto [2 ]
Candido dos Reis, Francisco Jose [2 ]
Faca, Vitor Marcel [1 ,3 ]
机构
[1] Univ Sao Paulo, FMRP, Dept Biochem & Immunol, Av Bandeirantes 3900, BR-14040900 Ribeirao Preto, SP, Brazil
[2] Univ Sao Paulo, FMRP, Dept Gynecol & Obstet, Av Bandeirantes 3900, BR-14040900 Ribeirao Preto, SP, Brazil
[3] Hemotherapy Ctr Ribeirao Preto, Ctr Cell Based Therapy, Rua Tenente Catao Roxo 2501, BR-14051140 Ribeirao Preto, SP, Brazil
[4] Barao de Maua Univ, Sch Med, Rua Ramos de Azevedo 423, BR-14090180 Ribeirao Preto, SP, Brazil
[5] Univ Sao Paulo, FMRP, Dept Cell & Mol Biol & Pathogen Bioagents, Av Bandeirantes 3900, BR-14040900 Ribeirao Preto, SP, Brazil
基金
巴西圣保罗研究基金会;
关键词
Ovarian cancer; Biomarkers; Tumor fluid; Highthroughput proteomics; Multiple reactions monitoring (MRM); APOLIPOPROTEIN-E; CELL-PROLIFERATION; STATISTICAL-MODEL; PLASMA PROTEOME; EXPRESSION; SERUM; MARKERS; PROTEINS; DATABASE; CD44;
D O I
10.1016/j.jprot.2016.05.005
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Tumor fluid samples have emerged as a rich source for the identification of ovarian cancer in the context of proteomics studies. To uncover differences among benign and malignant ovarian samples, we performed a quantitative proteomic study consisting of albumin immunodepletion, isotope labeling with acrylamide and in-depth proteomic profiling by LC-MS/MS in a pool of 10 samples of each histological type. 1135 proteins were identified, corresponding to 505 gene products. 223 proteins presented associated quantification and the comparative analysis of histological types revealed 75 differentially abundant proteins. Based on this, we developed a panel for targeted proteomic analysis using the multiple reaction monitoring (MRM) method for validation of 51 proteins in individual samples of high-grade serous ovarian tumor fluids (malignant) and benign serous cystadenoma tumor fluids. This analysis showed concordant results in terms of average amounts of proteins, and APOE, SERPINF2, SERPING1, ADAM17, CD44 and OVGP1 were statistically significant between benign and malignant group. The results observed in the MRM for APOE were confirmed by western blotting, where APOE was more abundant in malignant samples. This molecular signature can contribute to improve tumor stratification and shall be investigated in combination with current biomarkers in larger cohorts to improve ovarian cancer diagnosis. Biological significance: Despite advances in cancer research, ovarian cancer has a high mortality and remains a major challenge due to a number of particularities of the disease, especially late diagnosis caused by vague clinical symptoms, the cellular and molecular heterogeneity of tumors, and the lack of effective treatment. Thus, efforts are directed to better understand this neoplasia, its origin, development and, particularly the identification and validation of biomarkers for early detection of the disease in asymptomatic stage. In the present work, we confirmed by MRM method in individual ovarian tumor fluid samples the regulation of 27 proteins out of 33 identified in a highthroughput study. We speculate that the presence and/or differential abundance observed in tumor fluid is a cooperation primarily of high rates of secretion of such tumor proteins to extra tumor environment that will at the end accumulate in plasma, and also the accumulation of acute-phase proteins throughout the entire body. On top of that, consideration of physiological influences in the interpretation of expression observed, including age, menopause status, route-of-elimination kinetics and metabolism of the tumor marker, coexisting disease, hormonal imbalances, life-style influences (smoking, alcoholism, obesity), among others, are mandatory to enable the selection of good protein tumor marker candidates for extensive validation. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:226 / 236
页数:11
相关论文
共 50 条
  • [1] Profile of ovarian cancer tumor fluid using high-throughput and targeted proteomic analysis
    Poersch, Aline
    Grassi, Mariana L.
    Palma, Camila S.
    Carvalho, Vinicius P.
    Lanfredi, Guilherme P.
    Carrara, Helio H. A.
    Candido dos Reis, Francisco J.
    Faca, Vitor M.
    [J]. MOLECULAR CANCER THERAPEUTICS, 2018, 17 (01)
  • [2] Targeted proteomic assays for quantitation of proteins identified by proteogenomic analysis of ovarian cancer
    Ehwang Song
    Yuqian Gao
    Chaochao Wu
    Tujin Shi
    Song Nie
    Thomas L. Fillmore
    Athena A. Schepmoes
    Marina A. Gritsenko
    Wei-Jun Qian
    Richard D. Smith
    Karin D. Rodland
    Tao Liu
    [J]. Scientific Data, 4
  • [3] Potential tumor biomarkers identified in ovarian cyst fluid by quantitative proteomic analysis, iTRAQ
    Kristjansdottir, Bjorg
    Levan, Kristina
    Partheen, Karolina
    Carlsohn, Elisabet
    Sundfeldt, Karin
    [J]. CLINICAL PROTEOMICS, 2013, 10
  • [4] Potential tumor biomarkers identified in ovarian cyst fluid by quantitative proteomic analysis, iTRAQ
    Björg Kristjansdottir
    Kristina Levan
    Karolina Partheen
    Elisabet Carlsohn
    Karin Sundfeldt
    [J]. Clinical Proteomics, 2013, 10
  • [5] Data Descriptor: Targeted proteomic assays for quantitation of proteins identified by proteogenomic analysis of ovarian cancer
    Song, Ehwang
    Gao, Yuqian
    Wu, Chaochao
    Shi, Tujin
    Nie, Song
    Fillmore, Thomas L.
    Schepmoes, Athena A.
    Gritsenko, Marina A.
    Qian, Wei-Jun
    Smith, Richard D.
    Rodland, Karin D.
    Liu, Tao
    [J]. SCIENTIFIC DATA, 2017, 4
  • [6] Cancer stem cell gene signature identified from ovarian tumor side populations
    Ozbun, L.
    Vathipadiekal, V.
    Radonovich, M. E.
    Pise-Masion, C.
    Saxena, D.
    Hauschka, P. V.
    Mok, S. C.
    Birrer, M. J.
    [J]. GYNECOLOGIC ONCOLOGY, 2008, 108 (03) : S24 - S24
  • [7] Comprehensive Analysis of Tumor Microenvironment Identified Prognostic Immune-Related Gene Signature in Ovarian Cancer
    Li, Na
    Li, Biao
    Zhan, Xianquan
    [J]. FRONTIERS IN GENETICS, 2021, 12
  • [8] Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer
    Carolina Moretto Carnielli
    Carolina Carneiro Soares Macedo
    Tatiane De Rossi
    Daniela Campos Granato
    César Rivera
    Romênia Ramos Domingues
    Bianca Alves Pauletti
    Sami Yokoo
    Henry Heberle
    Ariane Fidelis Busso-Lopes
    Nilva Karla Cervigne
    Iris Sawazaki-Calone
    Gabriela Vaz Meirelles
    Fábio Albuquerque Marchi
    Guilherme Pimentel Telles
    Rosane Minghim
    Ana Carolina Prado Ribeiro
    Thaís Bianca Brandão
    Gilberto de Castro
    Wilfredo Alejandro González-Arriagada
    Alexandre Gomes
    Fabio Penteado
    Alan Roger Santos-Silva
    Márcio Ajudarte Lopes
    Priscila Campioni Rodrigues
    Elias Sundquist
    Tuula Salo
    Sabrina Daniela da Silva
    Moulay A. Alaoui-Jamali
    Edgard Graner
    Jay W. Fox
    Ricardo Della Coletta
    Adriana Franco Paes Leme
    [J]. Nature Communications, 9
  • [9] Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer
    Carnielli, Carolina Moretto
    Soares Macedo, Carolina Carneiro
    De Rossi, Tatiane
    Granato, Daniela Campos
    Rivera, Cesar
    Domingues, Romenia Ramos
    Pauletti, Bianca Alves
    Yokoo, Sami
    Heberle, Henry
    Busso-Lopes, Ariane Fidelis
    Cervigne, Nilva Karla
    Sawazaki-Calone, Iris
    Meirelles, Gabriela Vaz
    Marchi, Fabio Albuquerque
    Telles, Guilherme Pimentel
    Minghim, Rosane
    Prado Ribeiro, Ana Carolina
    Brandao, Thais Bianca
    Castro, Gilberto de, Jr.
    Alejandro Gonzalez-Arriagada, Wilfredo
    Gomes, Alexandre
    Penteado, Fabio
    Santos-Silva, Alan Roger
    Lopes, Marcio Ajudarte
    Rodrigues, Priscila Campioni
    Sundquist, Elias
    Salo, Tuula
    da Silva, Sabrina Daniela
    Alaoui-Jamali, Moulay A.
    Graner, Edgard
    Fox, Jay W.
    Della Coletta, Ricardo
    Paes Leme, Adriana Franco
    [J]. NATURE COMMUNICATIONS, 2018, 9
  • [10] Validation of biomarkers for ovarian cancer identified through proteomic profiling.
    Sokoll, LJ
    Zhang, Z
    Fung, ET
    Mohr, P
    Chan, DW
    [J]. CLINICAL CHEMISTRY, 2003, 49 (06) : A101 - A101