Left atrial giant thrombus infected by Escherichia Coli. Case report

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H2AX a Promising Biomarker for Lung Cancer: A Review

Histone’s H2A variant (H2AX) phosphorylation is an early indicator of DNA double-strand breaks formation and DNA damage response. Thus, it may act as a novel biomarker to monitor genotoxic events that can drive cancer development and tumor progression. This review will focus on the possible applications of H2AX as a key regulator of DNA damage response in lung cancer and as a biomarker of: sensitivity of lung tumors to chemotherapy and radiotherapy, treatment with PARP inhibitors, bystander effect, multistep lung carcinogenesis, environmental smoking, and chemical genotoxicity, chemoprevention, prognosis, and also as therapeutic targets in lung cancers

Prognostic significance of different immunohistochemical S100A2 protein expression patterns in patients with operable nonsmall cell lung carcinoma

S100 proteins are involved in carcinogenesis, metastasis, and survival. S100A2 is a member of the S100 family, and its expression and precise role in patients with non-small cell lung carcinoma (NSCLC) has been debated. Therefore, we examined the immunohistochemical expression patterns of S100A2 in NSCLC in relation to clinicopathological parameters, important molecular biomarkers, and patient outcome. Microarray data for 74 paraffin-embedded specimens from patients with NSCLC were immunostained for S100A2 and p53 proteins. Immunohistochemical staining patterns of S100A2 in the NSCLC tissue samples examined were either nuclear (nS100A2), cytoplasmic (cS100A2), or both. A significant association between nS100A2 positivity and better disease-free interval was observed (hazards ratio 0.47; 95% confidence interval 0.23-0.99; P = 0.047). Similarly, cS100A2 negativity was marginally associated with shorter overall survival (P = 0.07). Patients without lymphatic infiltration and an earlier disease stage had significantly better overall survival and disease-free interval. The S100A2 expression pattern in operable NSCLC varies widely, and this differential expression (nuclear, cytoplasmic or both) seems to correlate with prognosis. Intensity of expression was highest in the early and advanced stages, and equally distributed in the middle stages. This observation may be indicative of a dual role for this protein both during earlier and advanced disease stages, and may also explain the differential immunoexpression of S100A2. Analysis of the disease-free interval showed that nS100A2-negative and p53-positive expression was associated with a statistically significant (P = 0.003) shorter disease-free interval in comparison with nS100A2-positive and p53-negative expression (12 versus 30 months, respectively). Further studies are required to establish whether S100A2 protein may have a substantial role as a prognostic or predictive indicator in this unfavorable group of patients. © 2012 Hountis et al, publisher and licensee Dove Medical Press Ltd

Circuits of cancer drivers revealed by convergent misregulation of transcription factor targets across tumor types

BACKGROUND: Large tumor genome sequencing projects have now uncovered a few hundred genes involved in the onset of tumorigenesis, or drivers, in some two dozen malignancies. One of the main challenges emerging from this catalog of drivers is how to make sense of their heterogeneity in most cancer types. This is key not only to understand how carcinogenesis appears and develops in these malignancies to be able to early diagnose them, but also to open up the possibility to employ therapeutic strategies targeting a driver protein to counteract the alteration of another connected driver. METHODS: Here, I focus on driver transcription factors and their connection to tumorigensis in several tumor types through the alteration of the expression of their targets. First, I explore their involvement in tumorigenesis as mutational drivers in 28 different tumor types. Then, I collect a list of downstream targets of the all driver transcription factors (TFs), and identify which of them exhibit a differential expression upon alterations of driver transcription factors. RESULTS: /nI identify the subset of targets of each TF most likely mediating the tumorigenic effect of their driver alterations in each tumor type, and explore their overlap. Furthermore, I am able to identify other driver genes that cause tumorigenesis through the alteration of very similar sets of targets./nCONCLUSIONS: I thus uncover these circuits of connected drivers which cause tumorigenesis through the perturbation of overlapping cellular pathways in a pan-cancer manner across 15 malignancies. The systematic detection of these circuits may be key to propose novel therapeutic strategies indirectly targeting driver alterations in tumors.AG-P is supported by a Ramon y Cajal scholarship funded by the Spanish Ministry of Econom