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:Recurrent or metastatic head and neck squamous cell carcinoma (HNSCC) has a poor prognosis with less than 1-year median survival. Platinum-based chemotherapy (cisplatin or carboplatin) remains the first-line treatment for HNSCC. The cancer stem cell (CSC) hypothesis postulates that tumors are maintained by a self-renewing CSC population that is also capable of differentiating into non-self renewing cell populations that constitute the bulk of the tumor. A small population of CSCs exists within HNSCC that are relatively resistant to chemotherapy and clinically predicted to mediate tumor recurrence. These CSCs are identified by high cell-surface expression of CD44 and high intracellular activity of aldehyde dehydrogenase (ALDH) and termed ALDHhighCD44high. We investigated the molecular pathways active in ALDHhighCD44high cells, which remain poorly studied. Additionally, we performed a molecular examination of cisplatin-resistant ALDHhighCD44high cells, which has not been reported. Two HNSCC cell lines, UM-SCC-1 and UM-SCC-22b, were utilized in this study. For microarray analysis, UM-SCC-22b cells were treated for 5 days in vitro with 2uM cisplatin and analyzed by flow cytometry, sorted and submitted for microarray analysis of ALDHhighCD44high and ALDHlowCD44low cells from untreated and cisplatin treated cells. Four separate flow cytometry experiments were performed using Affymetrix Human Gene ST 2.1 microarrays. Microarray data was analyzed using R/Bioconductor. Files were preprocessed by Robust Multiarray Average (RMA) with background substraction, quantile normalization, and median polish (oligo package). Data was fitted with robust probe level linear models to all the probesets (oligo package). Experiment and processing batch differences were accounted for using 'ComBat' within the SVA package. Differentially expressed genes were identified using univariate comparisons after fitting data to a linear model (limma package). Initial statistics were determined using an empirical Bayesian model. Multiple testing comparisons were adjusted using Benjamini and Hochberg (aka FDR). Probes with an adjusted p-value <0.05 were considered statistically significant. Unsupervised hierarchical clustering with complete linkage and Euclidean distance was performed on only statistically significant probes. In four separate experiments, the head and neck squamous cell carcinoma cell line UM-SCC-22b were cultured for 5 days with or without 2uM (micromolar) cisplatin in 6-well plates. Media was replaced every other day. Control and cisplatin treated cells were trypsinized, procesed, and stained for CD44 cell-surface expression and intracellular aldehyde dehydrogenase (ALDH) activity to identify cancer stem cells (ALDH+CD44+). CSCs and non-CSCs (ALDH-CD44-) were collected by flow cytometry from both groups. Total RNA was collected from each fraction (ALDH+CD44+, ALDH-CD44-), treatment (control, cisplatin), and experiment (#1-4). A total of 16 samples were analyzed. One set of 4 (experiment #4) were analyzed on a Human Gene ST 2.1 strip and the rest on a Human Gene ST 2.1 plate. Differential gene expression was determined with R/Bioconductor with Robust Multiarray Average (RMA) and fitting the data to linear models (limma). Experimental and processing batch effects were accounted for using ComBat. Four sets of univariate comparisons were made: 1) Cisplatin ALDH+CD44+ vs Control ALDH+CD44+; 2) Control ALDH+CD44+ vs Control ALDH-CD44-; 3) Cisplatin ALDH+CD44+ vs Cisplatin ALDH-CD44-; 4) Cisplatin ALDH-CD44- vs Control ALDH-CD44-. Multiple testing comparisons were adjusted using Benjamini and Hochberg (aka FDR). Probes with an adjusted p-value <0.05 were considered statistically significant.

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Homo sapiens

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