JCV miR-J1-5p detection in CRC patient tissues.

<p>(A) Six FFPE tissue specimens were stained for JCV T-Ag expression to ensure the active presence of JCV in CRC tissues. Figure A1 shows a representative image for strong, and A2 shows weak JCV-T-Ag protein expression. (B) JCV miR-J1-5p expression was evaluated in each of 3 samples with strong and weak JCV T-Ag expression. Normalization of miR-J1-5p expression in FFPE tissues was performed using miR-16, as previously validated. (C & D) miR-J1-5p expression was evaluated in paired normal colonic mucosa and CRC fresh frozen tissues from 21 patients with CRC. In C, miR-J1-5p expression is shown for paired normal colonic mucosa and CRC tissues. miRNA expression is shown as 2^−ΔCt normalized to RNU6b expression. (E) miR-J1-5p expression in CRC tissues is shown correlated with miR-J1-5p expression in normal colon mucosa. The results are presented as 2^−ΔΔCt normalized to RNU6b and matching normal colonic mucosa, and the values are sorted in descending order. From a total of 21 CRC tissues samples, 12 samples (below the line) showed lower, and 6 samples (above the line) higher miR-J1-5p expression in CRC tissues compared to normal mucosa.</p

JCV miRNA sequence and detection.

<p>(A) Schematic presentation of the JCV genome. The black circle marks the transcript location of the JCV miR-J1 stem loop. (B) JCV miR-J1-5p and -3p sequences are compared to the Merkel Cell Polyomavirus-, SV40- and BK virus-miRNA sequences. (C & D) CRC cells were transfected in vitro with a JCVT-Ag-E plasmid, and JCV T-Ag message and miRNA expression were analyzed. In C, GAPDH and β-actin were used as loading controls for mRNA and protein expression, respectively. (D) Vector transfected cells showed no detectable miR-J1-5p expression, while JCV miR-J1-5p expression was high in transfected cells. To measure the expression of miR-J1-5p, expression in the vector was set to a Ct-value of 40, and 2^−ΔΔCt values were calculated using RNU6b for normalization.</p

JCV miR-J1-5p detection in feces.

<p>(A) To test whether JCV miRNA is present in stool, we extracted total RNA from stool samples and performed TaqMan based miRNA expression analyses. Expression of miR-J1-5p was normalized to mean miR-16 and -26b levels and further adjusted to the sample with the lowest miR-J1-5p expression level (1*). (B) To test the reproducibility of miRNA detection, we performed independent RNA extraction from the same samples in the subset of fecal samples from healthy subjects (n = 5). The samples were normalized to mean miR-16 and -26b expression. (C) Concomitant expression analyses of miR-J1-5p and -3p showed no correlation with JCV miRNA expression, arguing for potential cross-reactivity with BKV microRNA. (D&E) To measure JCV miR-J1-5p expression in feces from CRC patients, miR-J1-5p was analyzed by TaqMan PCR in 29 FOBT specimens from patients without and with colorectal neoplasia. Fold-expression was calculated using the 2^−ΔCt method normalized to mean miR-16 and -26b expression. D Represents the single sample values and E the mean values ± SD.</p

Clinico-pathological characteristics of patients and healthy volunteers in the study.

<p>*Clinical characteristics of one patient was incomplete.</p

Methylation status of CpG sites in partially methylated samples (i–iii) were determined by bisulfite sequencing ()

<p><b>Copyright information:</b></p><p>Taken from "Methylation profiles of genes utilizing newly developed CpG island methylation microarray on colorectal cancer patients"</p><p>Nucleic Acids Research 2005;33(5):e46-e46.</p><p>Published online 10 Mar 2005</p><p>PMCID:PMC1064143.</p><p>© The Author 2005. Published by Oxford University Press. All rights reserved</p> Probes 2–4 cover the 10 CpG sites in these samples. () The methylation levels detected by the oligonucleotide microarray were compared with those derived from bisulfite sequencing. The methylation levels by bisulfite sequencing was determined by dividing the total number of methylated CpG sites analyzed by the number of CpG sites at that locus and multiplying by 100, whereas the percentage of methylation levels analyzed by microarray analysis was determined by the use of standard curves derived from the aforementioned calibration controls as shown in . The average signal intensity was taken from two spots on four slides proceeded in parallel. The error bars indicate SD

Clinical impact of endometrial cancer stratified by genetic mutational profiles, <i>POLE</i> mutation, and microsatellite instability

<div><p>Background</p><p>The molecular characterization of endometrial cancer (EC) can facilitate identification of various tumor subtypes. Although EC patients with <i>POLE</i> mutations reproducibly demonstrate better prognosis, the outcome of patients with microsatellite instability (MSI) remains controversial. This study attempted to interrogate whether genetic stratification of EC can identify distinct subsets with prognostic significance.</p><p>Materials and methods</p><p>A cohort of 138 EC patients who underwent surgical resection with curative intent was enrolled. Sanger sequencing was used to evaluate mutations in the <i>POLE</i> and <i>KRAS</i> genes. MSI analysis was performed using four mononucleotide repeat markers and methylation status of the <i>MLH1</i> promoter was measured by a fluorescent bisulfite polymerase chain reaction (PCR). Protein expression for mismatch repair (MMR) proteins was evaluated by immunohistochemistry (IHC).</p><p>Results</p><p>Extensive hypermethylation of the <i>MLH1</i> promoter was observed in 69.6% ECs with MLH1 deficiency and 3.5% with MMR proficiency, but in none of the ECs with loss of other MMR genes (<i>P</i> < .0001). MSI-positive and <i>POLE</i> mutations were found in 29.0% and 8.7% EC patients, respectively. Our MSI analysis showed a sensitivity of 92.7% for EC patients with MMR deficiency, and a specificity of 97.9% for EC patients with MMR proficiency. In univariate and multivariate analyses, <i>POLE</i> mutations and <i>MSI</i> status was significantly associated with progression-free survival (<i>P</i> = 0.0129 and 0.0064, respectively) but not with endometrial cancer-specific survival.</p><p>Conclusions</p><p>This study provides significant evidence that analyses of proofreading <i>POLE</i> mutations and MSI status based on mononucleotide repeat markers are potentially useful biomarkers to identify EC patients with better prognosis.</p></div

Detection of MSI and distribution of number of MSIs in 138 EC patients.

<p>(A) Example of MSI and non-MSI cases analyzed by four mononucleotide repeat markers (BAT26, NR21, NR27, and CAT25). (B) Association between MSI, <i>POLE</i> mutation, <i>MLH-1</i> promoter methylation and MMR protein expression. The number of mononucleotide repeat markers showing MSI are shown by color.</p

Methylation analysis of the promoter region in the <i>MLH1</i> gene.

<p>(A) Schematic depiction of two regions (5’-region and 3’-region) of the <i>MLH1</i> promoter for methylation and results of a panel of representative fluorescent bisulfite PCR following restriction enzyme analysis. Methylated samples had the new fragment cleaved by the restriction enzyme. (B) The frequencies of <i>MLH1</i> promoter methylation according to <i>MLH1</i> expression status. The top panel shows the results of the <i>MLH1</i>-5’ region, the middle panel shows the <i>MLH1</i>-3’ region and the bottom panel shows partial (i.e. only <i>MLH1</i>-5’ methylation) and extensive methylation (i.e. both <i>MLH1</i>-5’ and -3’ methylation).</p

Molecular and clinic-pathological features of 138 ECs.

<p>(A) Molecular and clinic–pathological landscape of 138 ECs. Genetic analysis, focusing on frequent hotspot mutations in the POLE gene, and MSI status result in the identification of three molecular subgroups: (1) <i>POLE</i>-mutant, (2) MSI and (3) non-MSI. (B) Progression-free survival and endometrial cancer-specific survival of 138 EC patients stratified by genetic profiles. <i>P</i> values were calculated by the log-rank test.</p

Association between clinic-pathological features and EC patients stratified by genetic mutational profiles.

<p>Association between clinic-pathological features and EC patients stratified by genetic mutational profiles.</p