Discovery of novel candidate urinary protein biomarkers for prostate cancer in a multiethnic cohort of South African patients via label‐free mass spectrometry

Adeola, Henry Ademola; Soares, Nelson C.; Paccez, Juliano D.; Kaestner, Lisa; Blackburn, Jonathan M.; Zerbini, Luiz F.

doi:10.1002/prca.201400197

Cited by 20 publications

(27 citation statements)

References 52 publications

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“…More strictly selected control groups are highly recommended, which recruit patients known to have a disease with a similar perturbation in biological function to the disease of interest. A good example of this is a recent study that sought biomarkers for prostate cancer and included patients with benign prostatic hyperplasia, patients with other uropathies, as well as a healthy control cohort [30]. Recruiting a related disease control group will bring a higher likelihood of discovering true unique markers with higher specificity to the disease of interest.…”

Section: Patient Selectionmentioning

confidence: 99%

“…The identification of candidate protein biomarkers can be achieved by relative quantification through label-free or labelbased approaches. Label-free quantification compares proteins or peptides between different LC-MS runs, usually through spectral counting and peak area or intensity measurements [71][72][73][74]. Since no labeling reagent is involved, the sample preparation is often simpler and relatively inexpensive.…”

Section: Label-free Quantificationmentioning

confidence: 99%

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Biomarker discovery in mass spectrometry‐based urinary proteomics

Thomas

Hao

Ricke

et al. 2016

Proteomics Clinical Apps

118

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Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. Mass spectrometry (MS)-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians.

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Section: Patient Selectionmentioning

confidence: 99%

Section: Label-free Quantificationmentioning

confidence: 99%

Biomarker discovery in mass spectrometry‐based urinary proteomics

Thomas

Hao

Ricke

et al. 2016

Proteomics Clinical Apps

118

View full text Add to dashboard Cite

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“…PCa proteomics has been carried out in African-American populations [87, 88] but there are a limited number of studies among indigenous men of African descent. One such study identified 82 novel potential urinary biomarkers of PCa in a heterogeneous cohort of 45 South African patients composed of Indigenous, Mixed-Ancestry and Caucasian African PCa patients via label-free MS [89]. Among these 82 identified biomarkers, nine biomarkers were identified that suggested racial differences among the ethnicities in the cohort.…”

Section: Proteomics Biomarker Discovery In Africamentioning

confidence: 99%

“…These identified serological autoantibody responses could potentially be used in the construction of mini-arrays as point of care diagnostic tools as well as for therapeutic vaccine development for PCa in Africa. Many of these potential biomarkers have been reported in literature as being associated with other diseases, PCa as well as cancers in other human body organs; however, many are still yet to be described in PCa [89]. A comprehensive list which highlights the emerging potential biomarkers of PCa from those studies in terms of their source, methods used for their discovery and how far down the biomarker discovery pipeline they have moved, is provided in Tables 1A, 1B, 1C, 1D.…”

Section: Proteomics Biomarker Discovery In Africamentioning

confidence: 99%

Emerging proteomics biomarkers and prostate cancer burden in Africa

et al. 2017

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Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers.

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“…These samples were processed routinely for shotgun discovery proteomics and analyzed using ultra-HPLC and mass spectrometry. Postanalytic statistical evaluation revealed a total of 73 potential PCa biomarkers as well as nine biomarkers which demonstrated potential ethnic trends in South Africa [27]. Two pooled samples were prepared for PRM using peptides from 15 PCa samples and 15 normal control samples, respectively.…”

Section: • • Sample Sourcementioning

confidence: 99%