Gene expression analysis using agilent DNA microarrays

Prognostic Value of Long Non-Coding RNA HULC and MALAT1 Following the Curative Resection of Hepatocellular Carcinoma

Long non-coding RNAs (lncRNAs) were shown to be the crucial regulators of the many diseases. In this study, the expressions of lncRNAs were investigated in resected 158 hepatocellular carcinomas (HCCs) to evaluate the effects of their expression levels on prognosis. The expression levels of HULC and MALAT1 were shown to be significantly higher in the normal background tissue of HCC than those in the normal liver tissue of metastatic liver tumor without hepatitis (HULC: fold change 14.9, P = 1.7e-06; MALAT1: fold change 17.5, P = 1.2e-06. The formation of capsule was shown to be correlated with the increased expression of HULC (P = 0.041), while the size of HCC under 2 cm was correlated with a decrease in MALAT1 expression (P = 0.019). The levels of serum alpha-fetoprotein above 20 ng/mL indicated a decreased expression of both HULC and MALAT1 (HULC: P = 0.017; MALAT1: P = 0.0036). The increase in the expression levels of MALAT1 in HCC tissues was significantly correlated with better overall survival (HULC: P = 0.099, MALAT1: P = 0.028). Thus, the expression of these lncRNAs in HCC potentially correlates with the HCC malignancy and they represent potential prognostic biomarkers of the resected HCC.

MiR-219-5p Inhibits the Growth and Metastasis of Malignant Melanoma by Targeting BCL-2

Malignant melanoma is a very dangerous tumor which is resistant to conventional therapy. MicroRNA exerts a vital function in promoting or inhibiting tumor development. The research has investigated the expression and function of miR-219-5p in melanoma. As a result, miR-219-5p expression was distinctly reduced in melanoma tissues and cell lines and was negatively correlated with Bcl-2 protein level in melanoma. Patients with low miR-219-5p level represented obviously a low overall survival in comparison with patients with high miR-219-5p level. The upregulation of miR-219-5p inhibited melanoma growth and metastasis and strengthened melanoma cells chemosensitivity by targeting Bcl-2. Therefore, the modulation of miR-219-5p expression may be a novel treatment strategy in melanoma.

Individually Controllable Magnetic Cilia: Mixing Application

This paper introduces a new design for individually controlled magnetic artificial cilia for use in fluid devices and specifically intended to improve the mixing in DNA microarray experiments. The design has been implemented using a low-cost prototype that can be fabricated using polydimethylsiloxane (PDMS) and off-the-shelf parts and achieves large cilium deflections (59% of the cilium length). The device's performance is measured via a series of mixing experiments using different actuation patterns inspired by the blinking vortex theory. The experimental results, quantified using the relative standard deviation of the color when mixing two colored inks, show that exploiting the individual control leads to faster mixing (38% reduction in mixing time) than when operating the device in a simultaneous-actuation mode with the same average cilium beat frequency. Furthermore, the experimental results show an optimal beating pattern that minimizes the mixing time. The existence and character of this optimum is predicted by simulations using a blinking-vortex approach for 2D ideal flow, suggesting that the blinking-vortex model can be used to predict the effect of parameter variation on the experimental system.

Prognostic significance of AKR1B10 gene expression in hepatocellular carcinoma and surrounding non-tumorous liver tissue

When assessing outcome in hepatocellular carcinoma (HCC), it is important to consider prognostic factors in background non-tumorous liver tissue as well as in the tumor, since multiple occurrence is associated with background liver status such as hepatitis. The current study aimed to elucidate molecular prognostic predictors that have an association with HCC background non-tumorous tissue. Microarray expression profiling identified aldo-keto reductase family 1, member B10 (AKR1B10) as a putative non-tumorous prognostic factor, and AKR1B10 gene expression was investigated in 158 curatively resected HCC cases by reverse transcription-quantitative polymerase chain reaction. AKR1B10 expression (AKR1B10 value/GAPDH value × 1,000) was significantly higher in tumor tissue (median, 9.2200; range, 0.0003-611.0200; n=158) than in the corresponding non-tumorous tissue (median, 0.5461; range, 0.0018-69.0300; n=158) (P<0.001). When the samples were grouped according to AKR1B10 expression in tumor tissue relative to non-tumorous tissue, tumor<non-tumorous expression (n=26) significantly correlated with poor recurrence-free survival (P=0.0074) and overall survival (OS) (P<0.0001), and was an independent prognostic factor for OS (P=0.0011) in a multivariate analysis. The ratio of AKR1B10 messenger RNA levels in HCC and corresponding non-tumorous tissues may predict prognosis after curative hepatectomy, with low expression in HCC tissue relative to non-tumorous tissue indicative of poor prognosis.

CCNJ detected by triple combination array analysis as a tumor-related gene of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) has a high likelihood of recurrence and a poor prognosis. To detect cancer-related genes of HCC, we developed a new technique: triple combination array analysis, consisting of a methylation array, a gene expression array and a single nucleotide polymorphism array. A surgical specimen obtained from a 68-year-old female HCC patient was analyzed using triple combination array, which identified cyclin J (CCNJ) as a candidate cancer-related gene of HCC. Subsequently, samples from 85 HCC patients were evaluated for CCNJ promoter hypermethylation and expression status using methylation-specific PCR (MSP) and quantitative reverse transcriptase RT-PCR, respectively. CCNJ was found to be hypermethylated (methylation value, 0.906; range, 0-1.0) in cancer tissue, compared with adjacent non-cancerous tissue (0.112) using a methylation array. MSP revealed that CCNJ was hypermethylated in 67 (78.8%) of the tumor samples. CCNJ expression was significantly decreased in cases with hypermethylation (P<0.0001). Furthermore, cases with both promoter hypermethylation and decreased expression of CCNJ in the tumor tissue had a worse overall survival than the other cases (P=0.0383). In conclusion, our results indicated that CCNJ could be a novel prognostic marker of HCC, and this study indicated that triple combination array analysis was effective in detecting new tumor-related genes and their mechanisms.

High expression of Janus kinase 2 in background normal liver tissue of resected hepatocellular carcinoma is associated with worse prognosis

When assessing hepatocellular carcinoma (HCC), it is important to examine prognostic factors in the background normal liver tissue and consider malignant aspects of the primary lesion. Candidate genes were extracted from the background normal liver samples via multiarray analysis. Control samples, termed supernormal (SN) liver, were obtained from 11 cases of metastatic liver cancer. Corresponding normal (CN) liver tissue was surgically obtained from a typical HCC patient with chronic hepatitis C background for comparison. Expression profile and methylation array demonstrated that Janus kinase 2 (JAK2) gene expression was increased by 2.378‑fold in the CN tissue. Methylation array reported a lower value for CN (0.125) than SN tissues (0.748). We then investigated JAK2 expression by real-time quantitative reverse transcription-polymerase chain reaction in 100 consecutive resected HCC cases. The average expression level of JAK2 (normalized to GAPDH) was significantly lower in CN (9.24±6.43, n=100) than in SN (35.21 ± 21.38, n=11) tissues (P<0.001). As such a result was contrary to our expectation, the case used for array analysis seemed to be a rare incidence. One hundred HCC cases were subsequently divided into two groups based on JAK2 expression in the adjacent normal tissue: one consisting of the upper 70% of cases (n=70) and the other of the remaining 30% (n=30). Higher JAK2 expression in the adjacent tissue demonstrated significant correlation with worse survival (P=0.022). Furthermore, multivariate analysis identified higher JAK2 expression in the background normal liver tissue of HCC as an independent prognostic factor (P=0.032). Our findings suggest that higher JAK2 expression in the background normal liver tissue of HCC may be a good prognostic biomarker for resected HCC.

Expression analysis of THOP1 in background liver, a prognostic predictive factor in hepatocellular carcinoma, extracted by multiarray analysis

BACKGROUND

Hepatocellular carcinoma (HCC) often recurs and multicentric occurrence is more common than intrahepatic metastases after surgery. Prognostic prediction is insufficient when considering only factors in resected primary tumor.

METHODS

Control samples, termed supernormal (SN) liver, were taken from 11 cases of metastatic secondary malignancies of the liver. We selected adjacent nonneoplastic liver tissue from a patient with HCC and liver cirrhosis by hepatitis C (CN) for comparison. Expression profiling and methylation arrays were performed. We identified genes showing differences in both arrays. Prognosis was predicted for 179 cases of HCC based on gene expression.

RESULTS

Expression profiling showed that expression of thimet oligopeptidase (THOP1) gene was decreased 4.119-fold in CN. Methylation array showed a higher value for CN (0.869) than SN (0.488). We studied THOP1 gene expression by real-time reverse transcriptase polymerase chain reaction. The average expression level of THOP1 (THOP1 value × 10(3)/GAPDH) decreased in matching normal tissue (14.53 ± 10.14) relative to SN (78.14 ± 44.50). The group with higher than average THOP1 expression (n = 74) showed significant correlations with prolonged survival (P = 0.0383). Strongly reduced THOP1 expression (<3.0, n = 50) was shown to be an independent prognostic factor by multivariate analysis (P = 0.0024).

CONCLUSIONS

Expression of the THOP1 gene in the background liver of HCC is likely to be a good biomarker for risk of HCC development. When assessing HCC, it is important to extract prognostic factors from background liver tissue as well as considering malignant factors of the primary cancer lesion.

A bird's-eye view on the modern genetics workflow and its potential applicability to the locust problem

Genetics is an immense science and the current developments in its methods and techniques as well as the fast emerging tools make it one of the most powerful biological sciences. Indeed, from taxonomy and ecology to physiology and molecular biology, every biological science makes use of genetics techniques and methods at one time or another. In fact, development in genetics is such that it is now possible to characterize and analyze the expression of the whole set of genes of virtually every living organism, even if it is a non-model one. Locusts are notorious for the damage they cause to the ecosystems and economies of the areas affected by their recurrent population outbreaks. To prevent and deal with these outbreaks, we now count on both biological as well as chemical agents that are proving to be successful in reducing the damage that otherwise locust population outbreaks might cause. However, a better, efficient and environmentally friendly solution is still a hoped-for target. In my opinion, the ideal future pesticide should be both environmentally friendly, risk free and species-specific. To reach the knowledge needed for the development of such species-specific anti-locust agent, deep and accurate knowledge of the locusts' genetics and molecular biology is a must. Since genes and their expression levels lie at the bottom of every biological phenomenon, any species-specific solution to the locust problem requires a good knowledge of these organisms' genes as well as the quantitative and spatio-temporal dynamics of their expression. To reach such knowledge, collaborative work is needed as well as a clear workflow that, given the fast development in the genetics tools, is not always clear to all research groups. For this reason, here I describe a genetics workflow that should allow taking advantage of the most recent genetics tools and techniques to answer question relating to locust biology. My hope is that the adoption of this and other work strategies by different research groups, especially when the work is a collaborative one, would provide precious information on the biology and the biological phenomena that these economically important organisms exhibit.

Use of signal quality measurements to gain efficiency in the analysis of cDNA microarray data

This research provides a new way to measure error in microarray data in order to improve gene expression analysis. Microarray data contains many sources of error. In order to glean information about mRNA expression levels, the true signal must first be segregated from noise. This research focuses on the variation that can be captured at the spot level in cDNA microarray images. Variation at other levels, due to differences at the array, dye, and block levels, can be corrected for by a variety of existing normalization procedures. Two signal quality estimates that capture the reliability of each spot printed on a microarray are described. A parametric estimate of within-spot variance, referred to here as sigma(2)(spot), assumes that pixels follow a normal distribution and are spatially correlated. A non-parametric estimate of error, called the mean square prediction error (MSPE), assumes that spots of high quality possess pixels that are similar to their neighbors. This paper will provide a framework to use either spot quality measure in downstream analysis, specifically as weights in regression models. Using these spot quality estimates as weights can result in greater efficiency, in a statistical sense, when modeling microarray data.