Project description:Objective: The immune system is a key player in fighting cancer. Thus, we seeked to identify a molecular ‘immune response signature’ indicating the presence of epithelial ovarian cancer (EOC) and to combine this with a serum protein biomarker panel to increase the specificity and sensitivity for earlier detection of EOC. Methods: Comparing the expression of 32,000 genes in a leukocytes fraction from 48 EOC patients and 20 controls, three uncorrelated shrunken centroid models were selected, comprised of 7, 14, and 6 genes. A second selection step using RT-qPCR data and significance analysis of microarrays yielded 13 genes which were finally used in 343 samples (90 healthy, 6 cystadenoma, 8 low malignant potential tumor, and 239 EOC patients). Using new 65 controls and 224 EOC patients the abundances of six plasma proteins was determined and used in combination with the expression values from the 13 genes for diagnosis of EOC. Results: Combined diagnostic models using either each five gene expression and plasma protein abundance values or 13 gene expression and six plasma protein abundance values can discriminate controls from patients with EOC with Receiver Operator Characteristics Area Under the Curve values of 0.998 and bootstrap .632+ validated classification errors of 3.1% and 2.8%, respectively. The sensitivities were 97.8% and 95.6%, respectively, at a set specificity of 99.6%. Conclusion: The combination of expression based and plasma protein based biomarkers in one diagnostic model increases the sensitivity and the specificity significantly. Such a diagnostic test may allow earlier diagnosis of epithelial ovarian cancer. The expression of a blood cell fraction from 20 healthy controls and 48 patients with epithelial ovarian cancer was compared.
Project description:Transcriptional profiling of Homo sapiens inflammatory skin diseases (whole skin biospies): Psoriasis (Pso), vs Atopic Dermatitis (AD) vs Lichen planus (Li), vs Contact Eczema (KE), vs Healthy control (KO) In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation. In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation.
Project description:Gene expression profiling of immortalized human mesenchymal stem cells with hTERT/E6/E7 transfected MSCs. hTERT may change gene expression in MSCs. Goal was to determine the gene expressions of immortalized MSCs.
Project description:Protein biomarkers for epithelial ovarian cancer are critical for the early detection of the cancer to improve patient prognosis and for the clinical management of the disease to monitor treatment response and to detect recurrences. Unfortunately, the discovery of protein biomarkers is hampered by the limited availability of reliable and sensitive assays needed for the reproducible quantification of proteins in complex biological matrices such as blood plasma. In recent years, targeted mass spectrometry, exemplified by Selected Reaction Monitoring (SRM) has emerged as a method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing plasma-based protein biomarkers for epithelial ovarian cancer and illustrate how the SRM platform, when combined with rigorous experimental design and statistical analysis, can result in detection of predictive analytes.
Our biomarker development strategy first involved a discovery-driven proteomic effort to derive potential N-glycoprotein biomarker candidates for plasma-based detection of human ovarian cancer from a genetically engineered mouse model of endometrioid ovarian cancer, which accurately recapitulates the human disease. Next, 65 candidate markers selected from proteins of different abundance in the discovery dataset were reproducibly quantified with SRM assays across a large cohort of over 200 plasma samples from ovarian cancer patients and healthy controls. Finally, these measurements were used to derive a 5-protein signature for distinguishing individuals with epithelial ovarian cancer from healthy controls. The sensitivity of the candidate biomarker signature in combination with CA125 ELISA-based measurements currently used in clinic, exceeded that of CA125 ELISA-based measurements alone. The SRM-based strategy in this study is broadly applicable. It can be used in any study that requires accurate and reproducible quantification of selected proteins in a high-throughput and multiplexed fashion.
Project description:Kynureninase is a member of a large family of catalytically diverse but structurally homologous pyridoxal 5'-phosphate (PLP) dependent enzymes known as the aspartate aminotransferase superfamily or alpha-family. The Homo sapiens and other eukaryotic constitutive kynureninases preferentially catalyze the hydrolytic cleavage of 3-hydroxy-l-kynurenine to produce 3-hydroxyanthranilate and l-alanine, while l-kynurenine is the substrate of many prokaryotic inducible kynureninases. The human enzyme was cloned with an N-terminal hexahistidine tag, expressed, and purified from a bacterial expression system using Ni metal ion affinity chromatography. Kinetic characterization of the recombinant enzyme reveals classic Michaelis-Menten behavior, with a Km of 28.3 +/- 1.9 microM and a specific activity of 1.75 micromol min-1 mg-1 for 3-hydroxy-dl-kynurenine. Crystals of recombinant kynureninase that diffracted to 2.0 A were obtained, and the atomic structure of the PLP-bound holoenzyme was determined by molecular replacement using the Pseudomonas fluorescens kynureninase structure (PDB entry 1qz9) as the phasing model. A structural superposition with the P. fluorescens kynureninase revealed that these two structures resemble the "open" and "closed" conformations of aspartate aminotransferase. The comparison illustrates the dynamic nature of these proteins' small domains and reveals a role for Arg-434 similar to its role in other AAT alpha-family members. Docking of 3-hydroxy-l-kynurenine into the human kynureninase active site suggests that Asn-333 and His-102 are involved in substrate binding and molecular discrimination between inducible and constitutive kynureninase substrates.
Project description:Homo sapiens fresh whole blood was infected with Candida tropicalis. RNA-pool of both species extracted at 0min (control), 15, 30, 60, 120, 240 min. Samples are rRNA depleted. Measurement of Candida tropicalis gene expression.