Characterization of peritoneal reactive ascites collected from acute appendicitis and small bowel obstruction patients.

BACKGROUND: Pathological abdominal adhesions can cause bowel obstructions. A history of appendectomy (appy) increases patient rehospitalization risk directly related to adhesions. To potentially identify strategies for adhesion treatment, we characterized reactive ascites (rA) collected during appy or adhesiolysis for small bowel obstruction (SBO). METHODS: This is a non-randomized, prospective observational study recruiting patients with non-perforated appendicitis or SBO from three Level 1 trauma centers in the United States. rA were analyzed via liquid chromatography-mass spectrometry (LC-MS) (n = 31), bead-based quantification cytokines and chemokines (n = 32) and soluble receptors (n = 30), and LC-MS metabolomics (n = 18). RESULTS: LC-MS showed that samples contained albumin, apolipoprotein A1, and transthyretin and that metabolites increased in SBO vs appy rA were biomarkers of oxidative stress. Multi-plex analyses showed levels of 17 cytokines/chemokines and 6 soluble receptors were significantly different in appy vs SBO rA. Top increased proteins in appy compared to SBO rA by 20.14-, 11.53-, and 8.18-fold were granulocyte-colony stimulating factor, C-X-C motif chemokine ligand 10, and interleukin-10, respectively. CONCLUSIONS: These data further define pro- and anti-inflammatory mediators and metabolites that may drive formation or perpetuate chronic abdominal adhesions. Future research is to further explore whether attenuation of these factors may decrease pathologic adhesion formation.

Effects of cigarette smoke on the human oral mucosal transcriptome.

Use of tobacco is responsible for approximately 30% of all cancer-related deaths in the United States, including cancers of the upper aerodigestive tract. In the current study, 40 current and 40 age- and gender-matched never smokers underwent buccal biopsies to evaluate the effects of smoking on the transcriptome. Microarray analyses were carried out using Affymetrix HGU133 Plus 2 arrays. Smoking altered the expression of numerous genes: 32 genes showed increased expression and 9 genes showed reduced expression in the oral mucosa of smokers versus never smokers. Increases were found in genes involved in xenobiotic metabolism, oxidant stress, eicosanoid synthesis, nicotine signaling, and cell adhesion. Increased numbers of Langerhans cells were found in the oral mucosa of smokers. Interestingly, smoking caused greater induction of aldo-keto reductases, enzymes linked to polycyclic aromatic hydrocarbon-induced genotoxicity, in the oral mucosa of women than men. Striking similarities in expression changes were found in oral compared with the bronchial mucosa. The observed changes in gene expression were compared with known chemical signatures using the Connectivity Map database and suggested that geldanamycin, a heat shock protein 90 inhibitor, might be an antimimetic of tobacco smoke. Consistent with this prediction, geldanamycin caused dose-dependent suppression of tobacco smoke extract-mediated induction of CYP1A1 and CYP1B1 in vitro. Collectively, these results provide new insights into the carcinogenic effects of tobacco smoke, support the potential use of oral epithelium as a surrogate tissue in future lung cancer chemoprevention trials, and illustrate the potential of computational biology to identify chemopreventive agents.

Effects of tobacco smoke on gene expression and cellular pathways in a cellular model of oral leukoplakia.

In addition to being causally linked to the formation of multiple tumor types, tobacco use has been associated with decreased efficacy of anticancer treatment and reduced survival time. A detailed understanding of the cellular mechanisms that are affected by tobacco smoke (TS) should facilitate the development of improved preventive and therapeutic strategies. We have investigated the effects of a TS extract on the transcriptome of MSK-Leuk1 cells, a cellular model of oral leukoplakia. Using Affymetrix HGU133 Plus 2 arrays, 411 differentially expressed probe sets were identified. The observed transcriptome changes were grouped according to functional information and translated into molecular interaction network maps and signaling pathways. Pathways related to cellular proliferation, inflammation, apoptosis, and tissue injury seemed to be perturbed. Analysis of networks connecting the affected genes identified specific modulated molecular interactions, hubs, and key transcription regulators. Thus, TS was found to induce several epidermal growth factor receptor (EGFR) ligands forming an EGFR-centered molecular interaction network, as well as several aryl hydrocarbon receptor-dependent genes, including the xenobiotic metabolizing enzymes CYP1A1 and CYP1B1. Notably, the latter findings in vitro are consistent with our parallel finding that CYP1A1 and CYP1B1 levels were increased in oral mucosa of smokers. Collectively, these results offer insights into the mechanisms underlying the procarcinogenic effects of TS and raise the possibility that inhibitors of EGFR or aryl hydrocarbon receptor signaling will prevent or delay the development of TS-related tumors. Moreover, the inductive effects of TS on xenobiotic metabolizing enzymes may help explain the reduced efficacy of chemotherapy, and suggest targets for chemopreventive agents in smokers.

New molecular diagnostic methods in head and neck cancer.

Initial cancer evaluation includes assessment of histologic appearance, tumor grading, assessment of lymph node status, and presence of metastasis. However, traditional diagnostic methods such as histopathology and radiology are not sensitive enough to detect small numbers of cancer cells and are limited in their ability to predict response to treatment. Recently, there has been considerable progress in molecular diagnostics in these areas. Using molecular-based technologies, it is now possible to detect cancer early in asymptomatic individuals, identify minimal residual disease at histopathologic normal surgical margins, more precisely assess tumor burden in cancer patients, and more accurately assess the prognosis of the patients. Examples of these applications in the evaluation of head and neck cancer are reviewed here. However, despite the great promise of these new molecular approaches for cancer detection, much of the current technology limits their implementation into routine clinical use.