The role of P16ink4a and P53 immunostaining in predicting recurrence of HG-CIN after conization treatment

Objective: Io evaluate the expression of p16INK4a and p53 biomarkers in conization specimens from patients with high grade cervical intraepithelial neoplasia (HG-CIN), correlating them with the ability to predict the recurrence. Methods : we conducted a retrospective study of patients with HG-CIN in cervical biopsy treated with conization between January 1999 and January 2006 who had a minimum follow-up of 18 months. The expression of the p16 and p53 was assessed by tissue microarrays and correlated with disease recurrence. For analysis, we used the test of proportions (chi-square), considering value p<0.05, 95% CI and calculations of sensitivity, specificity and accuracy of these immunomarkers in predicting recurrence. Results : the series comprised 83 patients aged between 16 and 86 years (35±11.7), divided into two groups: 30 with HG-CIN recurrence (study group) and 53 without recurrence (control group). Mean age, parity, smoking and conization technique were similar in both groups. The p53 expression was present in 43% of the study group and 57% of the control group, and the p16 was present in 43% of the study group and in 57% of the control group (p>0.05). p53 had a positive predictive value (PPV) of 42% and negative predictive value (NPV) of 73%, sensitivity 70%, specificity of 47% and accuracy of 59%. The p16, PPV 42%, NPV 72%, sensitivity 66%, specificity of 49% and accuracy of 56%. Conclusion : immunohistochemistry expression of p53 and p16 showed low sensitivity and low specificity as predictors of HG-CIN recurrence after conization treatment.

Loss of PTEN expression and AKT activation in HER2-positive breast carcinomas

PURPOSE: To examine the expression of AKT and PTEN in a series of HER2-positive primary invasive breast tumors using immunohistochemistry, and to associate these expression profiles with classic pathologic features such as tumor grade, hormone receptor expression, lymphatic vascular invasion, and proliferation.METHODS: A total of 104 HER2-positive breast carcinoma specimens were prepared in tissue microarrays blocks for immunohistochemical detection of PTEN and phosphorylated AKT (pAKT). Original histologic sections were reviewed to assess pathological features, including HER2 status and Ki-67 index values. The associations between categorical and numeric variables were identified using Pearson's chi-square test and the Mann-Whitney, respectively.RESULTS: Co-expression of pAKT and PTEN was presented in 59 (56.7%) cases. Reduced levels of PTEN expression were detected in 20 (19.2%) cases, and these 20 tumors had a lower Ki-67 index value. In contrast, tumors positive for pAKT expression [71 (68.3%)] were associated with a higher Ki-67 index value.CONCLUSION: A role for AKT in the proliferation of HER2-positive breast cancers was confirmed. However, immunohistochemical detection of PTEN expression did not correlate with an inhibition of cellular proliferation or control of AKT phosphorylation, suggesting other pathways in these mechanisms of control.

Hunting for differentially expressed genes

Differentially expressed genes are usually identified by comparing steady-state mRNA concentrations. Several methods have been used for this purpose, including differential hybridization, cDNA subtraction, differential display and, more recently, DNA chips. Subtractive hybridization has significantly improved after the polymerase chain reaction was incorporated into the original method and many new protocols have been established. Recently, the availability of the well-known coding sequences for some organisms has greatly facilitated gene expression analysis using high-density microarrays. Here, we describe some of these modifications and discuss the benefits and drawbacks of the various methods corresponding to the main advances in this field.

High pressure-sensitive gene expression in Lactobacillus sanfranciscensis

Lactobacillus sanfranciscensis is a Gram-positive lactic acid bacterium used in food biotechnology. It is necessary to investigate many aspects of a model organism to elucidate mechanisms of stress response, to facilitate preparation, application and performance in food fermentation, to understand mechanisms of inactivation, and to identify novel tools for high pressure biotechnology. To investigate the mechanisms of the complex bacterial response to high pressure we have analyzed changes in the proteome and transcriptome by 2-D electrophoresis, and by microarrays and real time PCR, respectively. More than 16 proteins were found to be differentially expressed upon high pressure stress and were compared to those sensitive to other stresses. Except for one apparently high pressure-specific stress protein, no pressure-specific stress proteins were found, and the proteome response to pressure was found to differ from that induced by other stresses. Selected pressure-sensitive proteins were partially sequenced and their genes were identified by reverse genetics. In a transcriptome analysis of a redundancy cleared shot gun library, about 7% of the genes investigated were found to be affected. Most of them appeared to be up-regulated 2- to 4-fold and these results were confirmed by real time PCR. Gene induction was shown for some genes up-regulated at the proteome level (clpL/groEL/rbsK), while the response of others to high hydrostatic pressure at the transcriptome level seemed to differ from that observed at the proteome level. The up-regulation of selected genes supports the view that the cell tries to compensate for pressure-induced impairment of translation and membrane transport.

A conceptual and practical overview of cDNA microarray technology: implications for basic and clinical sciences

cDNA microarray is an innovative technology that facilitates the analysis of the expression of thousands of genes simultaneously. The utilization of this methodology, which is rapidly evolving, requires a combination of expertise from the biological, mathematical and statistical sciences. In this review, we attempt to provide an overview of the principles of cDNA microarray technology, the practical concerns of the analytical processing of the data obtained, the correlation of this methodology with other data analysis methods such as immunohistochemistry in tissue microarrays, and the cDNA microarray application in distinct areas of the basic and clinical sciences.

Rapid, reliable and inexpensive quality assessment of biotinylated cRNA

The interpretation of oligonucleotide array experiments depends on the quality of the target cRNA used. cRNA target quality is assessed by quantitative analysis of the representation of 5' and 3' sequences of control genes using commercially available Test arrays. The Test array provides an economically priced means of determining the quality of labeled target prior to analysis on whole genome expression arrays. This manuscript validates the use of a duplex RT-PCR assay as a faster (6 h) and less expensive (microarrays from Affymetrix. Ten cRNA samples with a ß-actin 3'/5' ratio >6 were chosen and classified as degraded cRNAs, and 31 samples with a ß-actin 3'/5' ratio <6 were selected as good quality cRNAs. Blinded samples were then used for the RT-PCR assay. After gel electrophoresis, optical densities of the amplified 3' and 5' fragments of ß-actin were measured and the 3'/5' ratio was calculated. There was a strong correlation (r² = 0.6802) between the array and the RT-PCR ß-actin 3'/5' ratios. Moreover, the RT-PCR 3'/5' ratio was significantly different (P < 0.0001) between undegraded (mean ± SD, 0.34 ± 0.09) and degraded (1.71 ± 0.83) samples. None of the other parameters analyzed, such as i) the starting amount of RNA, ii) RNA quality assessed using the Bioanalyzer Chip technology, or iii) the concentration and OD260/OD280 ratio of the purified biotinylated cRNA, correlated with cRNA quality.

Differential gene expression profiles of hepatocellular carcinomas associated or not with viral infection

Chronic hepatitis B (HBV) and C (HCV) virus infections are the most important factors associated with hepatocellular carcinoma (HCC), but tumor prognosis remains poor due to the lack of diagnostic biomarkers. In order to identify novel diagnostic markers and therapeutic targets, the gene expression profile associated with viral and non-viral HCC was assessed in 9 tumor samples by oligo-microarrays. The differentially expressed genes were examined using a z-score and KEGG pathway for the search of ontological biological processes. We selected a non-redundant set of 15 genes with the lowest P value for clustering samples into three groups using the non-supervised algorithm k-means. Fisher’s linear discriminant analysis was then applied in an exhaustive search of trios of genes that could be used to build classifiers for class distinction. Different transcriptional levels of genes were identified in HCC of different etiologies and from different HCC samples. When comparing HBV-HCC vs HCV-HCC, HBV-HCC/HCV-HCC vs non-viral (NV)-HCC, HBC-HCC vs NV-HCC, and HCV-HCC vs NV-HCC of the 58 non-redundant differentially expressed genes, only 6 genes (IKBKβ, CREBBP, WNT10B, PRDX6, ITGAV, and IFNAR1) were found to be associated with hepatic carcinogenesis. By combining trios, classifiers could be generated, which correctly classified 100% of the samples. This expression profiling may provide a useful tool for research into the pathophysiology of HCC. A detailed understanding of how these distinct genes are involved in molecular pathways is of fundamental importance to the development of effective HCC chemoprevention and treatment.

Cardiac gene expression and systemic cytokine profile are complementary in a murine model of post-ischemic heart failure

After myocardial infarction (MI), activation of the immune system and inflammatory mechanisms, among others, can lead to ventricular remodeling and heart failure (HF). The interaction between these systemic alterations and corresponding changes in the heart has not been extensively examined in the setting of chronic ischemia. The main purpose of this study was to investigate alterations in cardiac gene and systemic cytokine profile in mice with post-ischemic HF. Plasma was tested for IgM and IgG anti-heart reactive repertoire and inflammatory cytokines. Heart samples were assayed for gene expression by analyzing hybridization to AECOM 32k mouse microarrays. Ischemic HF significantly increased the levels of total serum IgM (by 5.2-fold) and total IgG (by 3.6-fold) associated with a relatively high content of anti-heart specificity. A comparable increase was observed in the levels of circulating pro-inflammatory cytokines such as IL-1β (3.8X) and TNF-α (6.0X). IFN-γ was also increased by 3.1-fold in the MI group. However, IL-4 and IL-10 were not significantly different between the MI and sham-operated groups. Chemokines such as MCP-1 and IL-8 were 1.4- and 13-fold increased, respectively, in the plasma of infarcted mice. We identified 2079 well annotated unigenes that were significantly regulated by post-ischemic HF. Complement activation and immune response were among the most up-regulated processes. Interestingly, 21 of the 101 quantified unigenes involved in the inflammatory response were significantly up-regulated and none were down-regulated. These data indicate that post-ischemic heart remodeling is accompanied by immune-mediated mechanisms that act both systemically and locally.

Whole transcriptome organisation in the dehydrated supraoptic nucleus

The supraoptic nucleus (SON) is part of the central osmotic circuitry that synthesises the hormone vasopressin (Avp) and transports it to terminals in the posterior lobe of the pituitary. Following osmotic stress such as dehydration, this tissue undergoes morphological, electrical and transcriptional changes to facilitate the appropriate regulation and release of Avp into the circulation where it conserves water at the level of the kidney. Here, the organisation of the whole transcriptome following dehydration is modelled to fit Zipf's law, a natural power law that holds true for all natural languages, that states if the frequency of word usage is plotted against its rank, then the log linear regression of this is -1. We have applied this model to our previously published euhydrated and dehydrated SON data to observe this trend and how it changes following dehydration. In accordance with other studies, our whole transcriptome data fit well with this model in the euhydrated SON microarrays, but interestingly, fit better in the dehydrated arrays. This trend was observed in a subset of differentially regulated genes and also following network reconstruction using a third-party database that mines public data. We make use of language as a metaphor that helps us philosophise about the role of the whole transcriptome in providing a suitable environment for the delivery of Avp following a survival threat like dehydration.