Proteomic alterations in early stage cervical cancer

Laser capture microdissection (LCM) allows the capture of cell types or well-defined structures in tissue. We compared in a semi-quantitative way the proteomes from an equivalent of 8,000 tumor cells from patients with squamous cell cervical cancer (SCC, n = 22) with healthy epithelial and stromal cells obtained from normal cervical tissue (n = 13). Proteins were enzymatically digested into peptides which were measured by high-resolution mass spectrometry and analyzed by “all-or-nothing” analysis, Bonferroni, and Benjamini-Hochberg correction for multiple testing. By comparing LCM cell type preparations, 31 proteins were exclusively found in early stage cervical cancer (n = 11) when compared with healthy epithelium and stroma, based on criteria that address specificity in a restrictive “all-or-nothing” way. By Bonferroni correction for multiple testing, 30 proteins were significantly up-regulated between early stage cervical cancer and healthy control, including six members of the MCM protein family. MCM proteins are involved in DNA repair and expected to be participating in the early stage of cancer. After a less stringent Benjamini-Hochberg correction for multiple testing, we found that the abundances of 319 proteins were significantly different between early stage cervical cancer and healthy controls. Four proteins were confirmed in digests of whole tissue lysates by Parallel Reaction Monitoring (PRM). Ingenuity Pathway Analysis using correction for multiple testing by permutation resulted in two networks that were differentially regulated in early stage cervical cancer compared with healthy tissue. From these networks, we learned that specific tumor mechanisms become effective during the early stage of cervical cancer

Metabolic changes related to the IDH1 mutation in gliomas preserve TCA-cycle activity: An investigation at the protein level

The discovery of the IDH1 R132H (IDH1 mut) mutation in low-grade glioma and the associated change in function of the IDH1 enzyme has increased the interest in glioma metabolism. In an earlier study, we found that changes in expression of genes involved in the aerobic glycolysis and the TCA cycle are associated with IDH1 mut. Here, we apply proteomics to FFPE samples of diffuse gliomas with or without IDH1 mutations, to map changes in protein levels associated with this mutation. We observed significant changes in the enz

Proteomic alterations in early stage cervical cancer

Laser capture microdissection (LCM) allows the capture of cell types or welldefined structures in tissue. We compared in a semi-quantitative way the proteomes from an equivalent of 8,000 tumor cells from patients with squamous cell cervical cancer (SCC, n = 22) with healthy epithelial and stromal cells obtained from normal cervical tissue (n = 13). Proteins were enzymatically digested into peptides which were measured by high-resolution mass spectrometry and analyzed by "all-ornothing" analysis, Bonferroni, and Benjamini-Hochberg correction for multiple testing. By comparing LCM cell type preparations, 31 proteins were exclusively found in early stage cervical cancer (n = 11) when compared with healthy epithelium and stroma, based on criteria that address specificity in a restrictive "all-or-nothing" way. By Bonferroni correction for multiple testing, 30 proteins were significantly up-regulated between early stage cervical cancer and healthy control, including six members of the MCM protein family. MCM proteins are involved in DNA repair and expected to be participating in the early stage of cancer. After a less stringent Benjamini-Hochberg correction for multiple testing, we found that the abundances of 319 proteins were significantly different between early stage cervical cancer and healthy controls. Four proteins were confirmed in digests of whole tissue lysates by Parallel Reaction

Longitudinal Serum Protein Analysis of Women with a High Risk of Developing Breast Cancer Reveals Large Interpatient Versus Small Intrapatient Variations:First Results from the TESTBREAST Study

The prospective, multicenter TESTBREAST study was initiated with the aim of identifying a novel panel of blood-based protein biomarkers to enable early breast cancer detection for moderate-to-high-risk women. Serum samples were collected every (half) year up until diagnosis. Protein levels were longitudinally measured to determine intrapatient and interpatient variabilities. To this end, protein cluster patterns were evaluated to form a conceptual basis for further clinical analyses. Using a mass spectrometry-based bottom-up proteomics strategy, the protein abundance of 30 samples was analyzed: five sequential serum samples from six high-risk women; three who developed a breast malignancy (cases) and three who did not (controls). Serum samples were chromatographically fractionated and an in-depth serum proteome was acquired. Cluster analyses were applied to indicate differences between and within protein levels in serum samples of individuals. Statistical analyses were performed using ANOVA to select proteins with a high level of clustering. Cluster analyses on 30 serum samples revealed unique patterns of protein clustering for each patient, indicating a greater interpatient than intrapatient variability in protein levels of the longitudinally acquired samples. Moreover, the most distinctive proteins in the cluster analysis were identified. Strong clustering patterns within longitudinal intrapatient samples have demonstrated the importance of identifying small changes in protein levels for individuals over time. This underlines the significance of longitudinal serum measurements, that patients can serve as their own controls, and the relevance of the current study set-up for early detection. The TESTBREAST study will continue its pursuit toward establishing a protein panel for early breast cancer detection

Use of universal stable isotope labeling by amino acids in cell culture (SILAC)-based selected reaction monitoring (SRM) approach for verification of breast cancer-related protein markers

Mass spectrometry-based proteomics facilitates high-throughput discovery of protein markers for diagnosis and treatment of breast cancer patients. Hundreds of putative prognostic and predictive markers are being identified every year, but only a very small proportion of them can be validated as clinically relevant markers. A quantitative and cost-efficient verification method is highly desirable to pick up real "nuggets" from the "sand." To fulfill these criteria, we previously introduced a stable isotope labeling by amino acids in cell culture (SILAC)-based selected reaction monitoring (SRM) approach for studying breast cancer-related protein markers. Here we describe a hands-on protocol of using this SILAC-SRM method for verification of breast cancer-related markers, which can also be used for verification of protein markers in other types of solid tumor tissues.</p

Circulating glioma biomarkers

Validated biomarkers for patients suffering from gliomas are urgently needed for standardizing measurements of the effects of treatment in daily clinical practice and trials. Circulating body fluids offer easily accessible sources for such markers. This review highlights various categories of tumor-associated circulating biomarkers identified in blood and cerebrospinal fluid of glioma patients, including circulating tumor cells, exosomes, nucleic acids, proteins, and oncometabolites. The validation and potential clinical utility of these biomarkers is briefly discussed. Although many candidate circulating protein biomarkers were reported, none of these have reached the required validation to be introduced for clinical practice. Recent developments in tracing circulating tumor cells and their derivatives as exosomes and circulating nuclear acids may become more successful in providing useful biomarkers. It is to be expected that current technical developments will contribute to the finding and validation of circulating biomarkers

Peptide profiling of cerebrospinal fluid by mass spectrometry

The search for biomarkers is driven by the increasing clinical importance of early diagnosis. Reliable biomarkers can also assist in directing therapy, monitoring disease activity and the efficacy of treatment. In addition, the discovery of novel biomarkers might provide clues to the pathogenesis of a disease. The dynamic range of protein concentrations in body fluids exceeds 10 orders of magnitude. These huge differences in concentrations complicate the detection of proteins with low expression levels. Since all classical biomarkers have low expression levels (e.g., prostate-specific antigen: 2-4 μg/l; and CA125: 20-35 U/ml), new developments with respect to identification and validation techniques of the low-abundance proteins are required. This review will discuss the current status of profiling cerebrospinal fluid using mass spectrometry-based techniques, and new developments in this area

Effects of the IDH1 R132H Mutation on the Energy Metabolism: A Comparison between Tissue and Corresponding Primary Glioma Cell Cultures

[Image: see text] The R132H mutation in the metabolic enzyme isocitrate dehydrogenase 1 (IDH1) is the most important prognostic factor for the survival of glioma patients. Subsequent studies led to the discovery of a panel of enzymes mainly involved in glutamate anaplerosis and aerobic glycolysis that change in abundance as a result of the IDH1 mutation. To further study these changes, appropriate glioma models are required that accurately mimic in vivo metabolism. To investigate how metabolism is affected by in vitro cell culture, we here compared surgically obtained snap-frozen glioma tissues with their corresponding primary glioma cell culture models with a previously developed targeted mass spectrometry proteomic assay. We determined the relative abundance of a panel of metabolic enzymes. Results confirmed increased glutamate use and decreased aerobic glycolysis in resected IDH1 R132H glioma tissue samples. However, these metabolic profiles were not reflected in the paired glioma primary cell cultures. We suggest that culture conditions and tumor microenvironment play a crucial role in maintaining the in vivo metabolic situation in cell culture models. For this reason, new models that more closely resemble the in vivo microenvironment, such as three-dimensional cell co-cultures or organotypic multicellular spheroid models, need to be developed and investigated