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Rapid label-free profiling of oral cancer biomarker proteins using nano-UPLC-Q-TOF ion mobility mass spectrometry

Nassar AF, Williams BJ, Yaworksy DC, Patel V, Rusling JF

Proteomics Clin Appl, 2016 Mar;10(3):280-9.
PMID: 26684082 DOI: 10.1002/prca.201500025

It has become quite clear that single cancer biomarkers cannot in general provide high sensitivity and specificity for reliable clinical cancer diagnostics. This paper explores the feasibility of rapid detection of multiple biomarker proteins in model oral cancer samples using label-free protein relative quantitation.
Proteomics of endometrial cancer diagnosis, treatment, and prognosis

Mittal P, Klingler-Hoffmann M, Arentz G, Zhang C, Kaur G, Oehler MK, et al.

Proteomics Clin Appl, 2016 Mar;10(3):217-29.
PMID: 26541900 DOI: 10.1002/prca.201500055

This review discusses the current status of proteomics technology in endometrial cancer diagnosis, treatment and prognosis. The first part of this review focuses on recently identified biomarkers for endometrial cancer, their importance in clinical use as well as the proteomic methods used in their discovery. The second part highlights some of the emerging mass spectrometry based proteomic technologies that promise to contribute to a better understanding of endometrial cancer by comparing the abundance of hundreds or thousands of proteins simultaneously.
Proteomic Investigations of In Vitro and In Vivo Models of Periodontal Disease

Binti Badlishah Sham NI, Lewin SD, Grant MM

Proteomics Clin Appl, 2020 05;14(3):e1900043.
PMID: 31419032 DOI: 10.1002/prca.201900043

Proteomics has currently been a developing field in periodontal diseases to obtain protein information of certain samples. Periodontal disease is an inflammatory disorder that attacks the teeth, connective tissues, and alveolar bone within the oral cavity. Proteomics information can provide proteins that are differentially expressed in diseased or healthy samples. This review provides insight into approaches researching single species, multi species, bacteria, non-human, and human models of periodontal disease for proteomics information. The approaches that have been taken include gel electrophoresis and qualitative and quantitative mass spectrometry. This review is carried out by extracting information about in vitro and in vivo studies of proteomics in models of periodontal diseases that have been carried out in the past two decades. The research has concentrated on a relatively small but well-known group of microorganisms. A wide range of models has been reviewed and conclusions across the breadth of these studies are presented in this review.
Translating N-Glycan Analytical Applications into Clinical Strategies for Ovarian Cancer

Briggs MT, Condina MR, Klingler-Hoffmann M, Arentz G, Everest-Dass AV, Kaur G, et al.

Proteomics Clin Appl, 2019 05;13(3):e1800099.
PMID: 30367710 DOI: 10.1002/prca.201800099

Protein glycosylation, particularly N-linked glycosylation, is a complex posttranslational modification (PTM), which plays an important role in protein folding and conformation, regulating protein stability and activity, cell-cell interaction, and cell signaling pathways. This review focuses on analytical techniques, primarily MS-based techniques, to qualitatively and quantitatively assess N-glycosylation while successfully characterizing compositional, structural, and linkage features with high specificity and sensitivity. The analytical techniques explored in this review include LC-ESI-MS/MS and MALDI time-of-flight MS (MALDI-TOF-MS), which have been used to analyze clinical samples, such as serum, plasma, ascites, and tissue. Targeting the aberrant N-glycosylation patterns observed in MALDI-MS imaging (MSI) offers a platform to visualize N-glycans in tissue-specific regions. The studies on the intra-patient (i.e., a comparison of tissue-specific regions from the same patient) and inter-patient (i.e., a comparison of tissue-specific regions between different patients) variation of early- and late-stage ovarian cancer (OC) patients identify specific N-glycan differences that improve understanding of the tumor microenvironment and potentially improve therapeutic strategies for the clinic.
Integrated Eutopic Endometrium and Non-Depleted Serum Quantitative Proteomic Analysis Identifies Candidate Serological Markers of Endometriosis

Manousopoulou A, Hamdan M, Fotopoulos M, Garay-Baquero DJ, Teng J, Garbis SD, et al.

Proteomics Clin Appl, 2019 05;13(3):e1800153.
PMID: 30488576 DOI: 10.1002/prca.201800153

BACKGROUND: Endometriosis affects about 4% of women in the reproductive age and is associated with subfertility. The aim of the present study is to examine the integrated quantitative proteomic profile of eutopic endometrium and serum from women with endometriosis compared to controls in order to identify candidate disease-specific serological markers.
METHODS: Eutopic endometrium and serum from patients with endometriosis (n = 8 for tissue and n = 4 for serum) are, respectively, compared to endometrium and serum from females without endometriosis (n = 8 for tissue and n = 4 for serum) using a shotgun quantitative proteomics method. All study participants are at the proliferative phase of their menstrual cycle.
RESULTS: At the tissue and serum level, 1214 and 404 proteins are differentially expressed (DEPs) in eutopic endometrium and serum, respectively, of women with endometriosis versus controls. Gene ontology analysis shows that terms related to immune response/inflammation, cell adhesion/migration, and blood coagulation are significantly enriched in the DEPs of eutopic endometrium, as well as serum. Twenty-one DEPs have the same trend of differential expression in both matrices and can be further examined as potential disease- and tissue-specific serological markers of endometriosis.
CONCLUSIONS: The present integrated proteomic profiling of eutopic endometrium and serum from women with endometriosis identify promising serological markers that can be further validated in larger cohorts for the minimally invasive diagnosis of endometriosis.