Reproducibility and Crossplatform Validation of Reverse-Phase Protein Array Data

被引:6
作者
Byron, Adam [1 ]
机构
[1] Univ Edinburgh, Inst Genet & Mol Med, Canc Res UK Edinburgh Ctr, Edinburgh, Midlothian, Scotland
来源
REVERSE PHASE PROTEIN ARRAYS: FROM TECHNICAL AND ANALYTICAL FUNDAMENTALS TO APPLICATIONS | 2019年 / 1188卷
关键词
Biomarkers; Bioinformatics; Data evaluation; Data integration; Data normalization; Data validation; Protein microarray; Proteomics; Reproducibility; Reverse-phase protein array; CANCER-CELL LINES; PATHWAY-ACTIVATION; MICROARRAYS; PROTEOMICS; NORMALIZATION; TECHNOLOGIES; PERSPECTIVE; METASTASIS; INHIBITORS; PREDICTION;
D O I
10.1007/978-981-32-9755-5_10
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Reverse-phase protein array (RPPA) technology is a high-throughput antibody- and microarray-based approach for the rapid profiling of levels of proteins and protein posttranslational modifications in biological specimens. The technology consumes small amounts of samples, can sensitively detect low-abundance proteins and posttranslational modifications, enables measurements of multiple signaling pathways in parallel, has the capacity to analyze large sample numbers, and offers robust interexperimental reproducibility. These features of RPPA experiments have motivated and enabled the use of RPPA technology in various biomedical, translational, and clinical applications, including the delineation of molecular mechanisms of disease, profiling of druggable signaling pathway activation, and search for new prognostic markers. Owing to the complexity of many of these applications, such as developing multiplex protein assays for diagnostic laboratories or integrating posttranslational modification-level data using large-scale proteogenomic approaches, robust and well-validated data are essential. There are many distinct components of an RPPA workflow, and numerous possible technical setups and analysis parameter options exist. The differences between RPPA platform setups around the world offer opportunities to assess and minimize interplatform variation. Crossplatform validation may also aid in the evaluation of robust, platform-independent protein markers of disease and response to therapy.
引用
收藏
页码:181 / 201
页数:21
相关论文
共 101 条
  • [1] Realizing the Promise of Reverse Phase Protein Arrays for Clinical, Translational, and Basic Research: A Workshop Report
    Akbani, Rehan
    Becker, Karl-Friedrich
    Carragher, Neil
    Goldstein, Ted
    de Koning, Leanne
    Korf, Ulrike
    Liotta, Lance
    Mills, Gordon B.
    Nishizuka, Satoshi S.
    Pawlak, Michael
    Petricoin, Emanuel F.
    Pollard, Harvey B.
    Serrels, Bryan
    Zhu, Jingchun
    [J]. MOLECULAR & CELLULAR PROTEOMICS, 2014, 13 (07) : 1625 - 1643
  • [2] A pan-cancer proteomic perspective on The Cancer Genome Atlas
    Akbani, Rehan
    Ng, Patrick Kwok Shing
    Werner, Henrica M. J.
    Shahmoradgoli, Maria
    Zhang, Fan
    Ju, Zhenlin
    Liu, Wenbin
    Yang, Ji-Yeon
    Yoshihara, Kosuke
    Li, Jun
    Ling, Shiyun
    Seviour, Elena G.
    Ram, Prahlad T.
    Minna, John D.
    Diao, Lixia
    Tong, Pan
    Heymach, John V.
    Hill, Steven M.
    Dondelinger, Frank
    Stadler, Nicolas
    Byers, Lauren A.
    Meric-Bernstam, Funda
    Weinstein, John N.
    Broom, Bradley M.
    Verhaak, Roeland G. W.
    Liang, Han
    Mukherjee, Sach
    Lu, Yiling
    Mills, Gordon B.
    [J]. NATURE COMMUNICATIONS, 2014, 5
  • [3] Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach
    Ali, Mehreen
    Khan, Suleiman A.
    Wennerberg, Krister
    Aittokallio, Tero
    [J]. BIOINFORMATICS, 2018, 34 (08) : 1353 - 1362
  • [4] Improved reproducibility of reverse-phase protein microarrays using array microenvironment normalization
    Anderson, Troy
    Wulfkuhle, Julia
    Liotta, Lance
    Winslow, Raimond L.
    Petricoin, Emanuel, III
    [J]. PROTEOMICS, 2009, 9 (24) : 5562 - 5566
  • [5] Preclinical evaluation and reverse phase protein Array-based profiling of PI3K and MEK inhibitors in endometrial carcinoma in vitro
    Aslan, Ozlem
    Cremona, Mattia
    Morgan, Clare
    Cheung, Lydia W.
    Mills, Gordon B.
    Hennessy, Bryan T.
    [J]. BMC CANCER, 2018, 18
  • [6] Austin J, 2011, METHODS MOL BIOL, V785, P379, DOI 10.1007/978-1-61779-286-1_25
  • [7] Baldelli E, 2017, METHODS MOL BIOL, V1606, P149, DOI 10.1007/978-1-4939-6990-6_11
  • [8] Functional Proteomics of Breast Cancer Metabolism Identifies GLUL as Responder during Hypoxic Adaptation
    Bernhardt, Stephan
    Toensing, Christian
    Mitra, Devina
    Erdem, Nese
    Mueller-Decker, Karin
    Korf, Ulrike
    Kreutz, Clemens
    Timmer, Jens
    Wiemann, Stefan
    [J]. JOURNAL OF PROTEOME RESEARCH, 2019, 18 (03) : 1352 - 1362
  • [9] Proteomic profiling of breast cancer metabolism identifies SHMT2 and ASCT2 as prognostic factors
    Bernhardt, Stephan
    Bayerlova, Michaela
    Vetter, Martina
    Wachter, Astrid
    Mitra, Devina
    Hanf, Volker
    Lantzsch, Tilmann
    Uleer, Christoph
    Peschel, Susanne
    John, Jutta
    Buchmann, Joerg
    Weigert, Edith
    Buerrig, Karl-Friedrich
    Thomssen, Christoph
    Korf, Ulrike
    Beissbarth, Tim
    Wiemann, Stefan
    Kantelhardt, Eva Johanna
    [J]. BREAST CANCER RESEARCH, 2017, 19
  • [10] Boellner Stefanie, 2015, Microarrays (Basel), V4, P98, DOI 10.3390/microarrays4020098