Expression of phosphorylated raf kinase inhibitor protein (pRKIP) is a predictor of lung cancer survival

<p>Abstract</p> <p>Background</p> <p>Raf-1 kinase inhibitor protein (RKIP) has been reported to negatively regulate signal kinases of major survival pathways. RKIP activity is modulated in part by phosphorylation on Serine 153 by protein kinase C, which leads to dissociation of RKIP from Raf-1. RKIP expression is low in many human cancers and represents an indicator of poor prognosis and/or induction of metastasis. The prognostic power has typically been based on total RKIP expression and has not considered the significance of phospho-RKIP.</p> <p>Methods</p> <p>The present study examined the expression levels of both RKIP and phospho-RKIP in human lung cancer tissue microarray proteomics technology.</p> <p>Results</p> <p>Total RKIP and phospho-RKIP expression levels were similar in normal and cancerous tissues. phospho-RKIP levels slightly decreased in metastatic lesions. However, the expression levels of phospho-RKIP, in contrast to total RKIP, displayed significant predictive power for outcome with normal expression of phospho-RKIP predicting a more favorable survival compared to lower levels (P = 0.0118); this was even more pronounced in more senior individuals and in those with early stage lung cancer.</p> <p>Conclusions</p> <p>This study examines for the first time, the expression profile of RKIP and phospho-RKIP in lung cancer. Significantly, we found that phospho-RKIP was a predictive indicator of survival.</p

Frequent high-level expression of the immunotherapeutic target Ep-CAM in colon, stomach, prostate and lung cancers

Epithelial cell adhesion molecule (Ep-CAM; CD326) is used as a target by many immunotherapeutic approaches, but little data are available about Ep-CAM expression in major human malignancies with respect to level, frequency, tumour stage, grade, histologic tumour type and impact on survival. We analysed by immunohistochemical staining tissue microarrays with 4046 primary human carcinoma samples from colon, stomach, prostate and lung cancers for both frequency and intensity of Ep-CAM expression under highly standardised conditions. A total of 3360 samples were analysable. High-level Ep-CAM expression was observed in 97.7% (n=1186) of colon, 90.7% of gastric (n=473), and 87.2% of prostate cancers (n=414), and in 63.9% of lung cancers (n=1287). No detectable Ep-CAM staining was found with only 0.4% of colon, 2.5% of gastric, 1.9% of prostate cancers, and 13.5% of lung cancers. The only significant correlation of Ep-CAM expression with tumour grading was observed in colon cancer where high-level Ep-CAM expression on grade 3 tumours was down to 92.1% (P<0.0001). Adenosquamous and squamous carcinomas of the lung had a lower percentage of high-level Ep-CAM expression compared to adenocarcinomas with 35.4 and 53.6%, respectively, and with 45.5 and 17.3% of tumours being Ep-CAM negative. With the exception of moderately differentiated colon carcinoma, where patients not expressing Ep-CAM on their tumours showed an inferior survival (P=0.0014), correlation of Ep-CAM expression with survival did not reach statistical significance for any of the other cancer indications and subgroups. In conclusion, the data strongly support the notion that Ep-CAM is a prime target for immunotherapies in major human malignancies. This is because the most common human cancers show (i) a low frequency of Ep-CAM-negative tumours, (ii) a high frequency of Ep-CAM expression on cells of a given tumour, and (iii) for most cancers, an insignificant influence of tumour staging, grading and histology on Ep-CAM expression

The severity of pandemic H1N1 influenza in the United States, from April to July 2009: A Bayesian analysis

Background: Accurate measures of the severity of pandemic (H1N1) 2009 influenza (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely, resulting in overestimation of the severity of an average case. We sought to estimate the probabilities that symptomatic infection would lead to hospitalization, ICU admission, and death by combining data from multiple sources. Methods and Findings: We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data - medically attended cases in Milwaukee or self-reported influenza-like illness (ILI) in New York - were used to estimate ratios of symptomatic cases to hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic patients who died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information, and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated an sCFR of 0.048% (95% credible interval [CI] 0.026%-0.096%), sCIR of 0.239% (0.134%-0.458%), and sCHR of 1.44% (0.83%-2.64%). Using self-reported ILI, we obtained estimates approximately 7-96lower. sCFR and sCIR appear to be highest in persons aged 18 y and older, and lowest in children aged 5-17 y. sCHR appears to be lowest in persons aged 5-17; our data were too sparse to allow us to determine the group in which it was the highest. Conclusions: These estimates suggest that an autumn-winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with the greatest impact in children aged 0-4 and adults 18-64. These estimates of impact depend on assumptions about total incidence of infection and would be larger if incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the total proportion of the population symptomatically infected were lower than assumed.published_or_final_versio

Molecular marks for epigenetic identification of developmental and cancer stem cells

Epigenetic regulations of genes by reversible methylation of DNA (at the carbon-5 of cytosine) and numerous reversible modifications of histones play important roles in normal physiology and development, and epigenetic deregulations are associated with developmental disorders and various disease states, including cancer. Stem cells have the capacity to self-renew indefinitely. Similar to stem cells, some malignant cells have the capacity to divide indefinitely and are referred to as cancer stem cells. In recent times, direct correlation between epigenetic modifications and reprogramming of stem cell and cancer stem cell is emerging. Major discoveries were made with investigations on reprogramming gene products, also known as master regulators of totipotency and inducer of pluoripotency, namely, OCT4, NANOG, cMYC, SOX2, Klf4, and LIN28. The challenge to induce pluripotency is the insertion of four reprogramming genes (Oct4, Sox2, Klf4, and c-Myc) into the genome. There are always risks of silencing of these genes by epigenetic modifications in the host cells, particularly, when introduced through retroviral techniques. In this contribution, we will discuss some of the major discoveries on epigenetic modifications within the chromatin of various genes associated with cancer progression and cancer stem cells in comparison to normal development of stem cell. These modifications may be considered as molecular signatures for predicting disorders of development and for identifying disease states