A Targeted Mass Spectrometry Strategy for Developing Proteomic Biomarkers: A Case Study of Epithelial Ovarian Cancer

Hüttenhain, Ruth; Choi, Meena; Fuente, Laura Martín de la; Oehl, Kathrin; Chang, Chieh-Fu; Zimmermann, Annemarie; Malander, Susanne; Olsson, Håkan; Šurinová, Silvia; Clough, Timothy; Heinzelmann‐Schwarz, Viola; Wild, Peter J.; Dinulescu, Daniela M.; Niméus, Emma; Vitek, Olga; Aebersold, Ruedi

doi:10.1074/mcp.ra118.001221

Cited by 46 publications

(35 citation statements)

References 68 publications

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“…Chang et al provide insights regarding sample size requirements for SRM measurements based on SRM variability in plasma from human ovarian cancer patients, and demonstrate that approximately 50 cases and 50 controls would be required to detect a fold change in a specific protein of 1.2 with 80% power and a 5% type I error rate [ 52 ]. If serum is the focus, these estimates can serve as a starting point for planning pilot studies in serum to evaluate variability for use in full study planning [ 53 ]. Fortunately, tools exist to assist in assessing these study design parameters during the study planning stages, and authors are starting to report information regarding technical and biological variability in addition to fold change, enabling educated parameter estimates for use in calculations [ 52 , 54 , 55 , 56 , 57 ].…”

Section: Experimental Design and Statistical Considerations In Sermentioning

confidence: 99%

“…While it is tempting to take short-cuts and proceed with small numbers or pool specimens due to the time- and resource-intensive nature of proteomics experiments, it has been shown that it is possible to proceed with larger sample sizes with the appropriate use of controls, replication, and statistical analysis tools for quantification and hypothesis testing [ 53 , 58 ]. The pooling of specimens prior to mass analysis without the specimens being labeled should be avoided, as it relies on the assumption of biological averaging and constrains the types of analyses that can be performed [ 59 ].…”

Section: Experimental Design and Statistical Considerations In Sermentioning

confidence: 99%

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Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Bhawal

Oberg

Zhang

et al. 2020

Cancers

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Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

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Section: Experimental Design and Statistical Considerations In Sermentioning

confidence: 99%

Section: Experimental Design and Statistical Considerations In Sermentioning

confidence: 99%

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Bhawal

Oberg

Zhang

et al. 2020

Cancers

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“…The study reports on a novel strategy for the discovery of tumor-derived proteins using a combination of N-glycoproteomics and PDX models. A similar study was performed by Hüttenhain et al [174]. Genetically engineered ovarian cancer mouse models and control mice samples were used for the selection of N-glycoproteomic biomarker candidates which were quantified by SRM in 124 patient sera with epithelial ovarian cancer and 110 healthy controls.…”

Section: Blood-based Proteomicsmentioning

confidence: 97%

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

2020

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Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including posttranslational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

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“…Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH-MS) is one of the DIA methods that has been employed to produce highly reproducible and complete quantitative results [1][2][3] . This property of SWATH-MS enables the general application of SWATH-based quantitative proteomics in biological research and clinical biomarker studies [4][5][6] . SWATH-MS data analysis can be accomplished by two strategies, spectral library-based targeted analysis approach and library-free analysis method.…”

Section: Background and Summarymentioning

confidence: 99%

Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins

Zhong

Qiu

et al. 2020

Sci Data

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targeted SWatH-MS data analysis is critically dependent on the spectral library. Comprehensive spectral libraries of human or several other organisms have been published, but the extensive spectral library for mouse, a widely used model organism is not available. Here, we present a large murine spectral library covering more than 11,000 proteins and 240,000 proteotypic peptides, which included proteins derived from 9 murine tissue samples and one murine L929 cell line. This resource supports the quantification of 67% of all murine proteins annotated by UniProtKB/Swiss-Prot. Furthermore, we applied the spectral library to SWATH-MS data from murine tissue samples. Data are available via SWATHAtlas (PASS01441).

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A Targeted Mass Spectrometry Strategy for Developing Proteomic Biomarkers: A Case Study of Epithelial Ovarian Cancer

Abstract: Highlights • Rigorous experimental design and data analysis for large-scale SRM studies. • Plasma-based biomarker signature combined with CA125 for ovarian cancer detection. • Broadly applicable strategy for the development of diagnostic biomarker assays.

Cited by 46 publications

References 68 publications

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins

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