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Wang XY, Xu YM, Lau ATY. Proteogenomics in Cancer: Then and Now. J Proteome Res 2023; 22:3103-3122. [PMID: 37725793 DOI: 10.1021/acs.jproteome.3c00196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/21/2023]
Abstract
For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.
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Affiliation(s)
- Xiu-Yun Wang
- Laboratory of Cancer Biology and Epigenetics, Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, Guangdong 515041, People's Republic of China
| | - Yan-Ming Xu
- Laboratory of Cancer Biology and Epigenetics, Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, Guangdong 515041, People's Republic of China
| | - Andy T Y Lau
- Laboratory of Cancer Biology and Epigenetics, Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, Guangdong 515041, People's Republic of China
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Lin TT, Zhang T, Kitata RB, Liu T, Smith RD, Qian WJ, Shi T. Mass spectrometry-based targeted proteomics for analysis of protein mutations. MASS SPECTROMETRY REVIEWS 2023; 42:796-821. [PMID: 34719806 PMCID: PMC9054944 DOI: 10.1002/mas.21741] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 09/28/2021] [Accepted: 10/07/2021] [Indexed: 05/03/2023]
Abstract
Cancers are caused by accumulated DNA mutations. This recognition of the central role of mutations in cancer and recent advances in next-generation sequencing, has initiated the massive screening of clinical samples and the identification of 1000s of cancer-associated gene mutations. However, proteomic analysis of the expressed mutation products lags far behind genomic (transcriptomic) analysis. With comprehensive global proteomics analysis, only a small percentage of single nucleotide variants detected by DNA and RNA sequencing have been observed as single amino acid variants due to current technical limitations. Proteomic analysis of mutations is important with the potential to advance cancer biomarker development and the discovery of new therapeutic targets for more effective disease treatment. Targeted proteomics using selected reaction monitoring (also known as multiple reaction monitoring) and parallel reaction monitoring, has emerged as a powerful tool with significant advantages over global proteomics for analysis of protein mutations in terms of detection sensitivity, quantitation accuracy and overall practicality (e.g., reliable identification and the scale of quantification). Herein we review recent advances in the targeted proteomics technology for enhancing detection sensitivity and multiplexing capability and highlight its broad biomedical applications for analysis of protein mutations in human bodily fluids, tissues, and cell lines. Furthermore, we review recent applications of top-down proteomics for analysis of protein mutations. Unlike the commonly used bottom-up proteomics which requires digestion of proteins into peptides, top-down proteomics directly analyzes intact proteins for more precise characterization of mutation isoforms. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale targeted detection and quantification of important protein mutations are discussed.
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Affiliation(s)
- Tai-Tu Lin
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Tong Zhang
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Reta B. Kitata
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Richard D. Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Tujin Shi
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
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Betancourt LH, Gil J, Sanchez A, Doma V, Kuras M, Murillo JR, Velasquez E, Çakır U, Kim Y, Sugihara Y, Parada IP, Szeitz B, Appelqvist R, Wieslander E, Welinder C, de Almeida NP, Woldmar N, Marko‐Varga M, Eriksson J, Pawłowski K, Baldetorp B, Ingvar C, Olsson H, Lundgren L, Lindberg H, Oskolas H, Lee B, Berge E, Sjögren M, Eriksson C, Kim D, Kwon HJ, Knudsen B, Rezeli M, Malm J, Hong R, Horvath P, Szász AM, Tímár J, Kárpáti S, Horvatovich P, Miliotis T, Nishimura T, Kato H, Steinfelder E, Oppermann M, Miller K, Florindi F, Zhou Q, Domont GB, Pizzatti L, Nogueira FCS, Szadai L, Németh IB, Ekedahl H, Fenyö D, Marko‐Varga G. The Human Melanoma Proteome Atlas-Complementing the melanoma transcriptome. Clin Transl Med 2021; 11:e451. [PMID: 34323402 PMCID: PMC8299047 DOI: 10.1002/ctm2.451] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 05/17/2021] [Accepted: 05/20/2021] [Indexed: 12/12/2022] Open
Abstract
The MM500 meta-study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass-spectrometry-based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well-annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein-coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.
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Pasic MD. The current status and future prospects of precision medicine. Clin Chem Lab Med 2020; 58:1423-1425. [PMID: 31940283 DOI: 10.1515/cclm-2019-0772] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Accepted: 11/13/2019] [Indexed: 12/14/2022]
Abstract
Over the last 5 years I have been coordinating a graduate course on genomic technologies and their applications in medicine. The course is offered to graduate students in the Department of Laboratory Medicine and Pathobiology at the University of Toronto. In attending the diverse lectures, I came to better understand the burgeoning field of "personalized" or "precision" medicine (PM) and its current status and future prospects. Below, I provide my personal views on this topic.
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Affiliation(s)
- Maria D Pasic
- Department of Laboratory Medicine, St. Joseph's Health Centre, Unity Health Toronto, 30 The Queensway, Toronto, ON M6R 1B5, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
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Ang MY, Low TY, Lee PY, Wan Mohamad Nazarie WF, Guryev V, Jamal R. Proteogenomics: From next-generation sequencing (NGS) and mass spectrometry-based proteomics to precision medicine. Clin Chim Acta 2019; 498:38-46. [DOI: 10.1016/j.cca.2019.08.010] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 08/13/2019] [Accepted: 08/13/2019] [Indexed: 12/14/2022]
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Byron A. Reproducibility and Crossplatform Validation of Reverse-Phase Protein Array Data. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1188:181-201. [PMID: 31820389 DOI: 10.1007/978-981-32-9755-5_10] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
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.
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Affiliation(s)
- Adam Byron
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
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