No abstract

MicroRNAs (miRNA) are negative regulators of gene expression at the posttranscriptional level, which are involved in tumorigenesis. Two miRNAs, miR-15a and miR-16, which are located at chromosome 13q14, have been implicated in cell cycle control and apoptosis, but little information is available about their role in solid tumors. To address this question, we established a protocol to quantify miRNAs from laser capture microdissected tissues. Here, we show that miR-15a/miR-16 are frequently deleted or down-regulated in squamous cell carcinomas and adenocarcinomas of the lung. In these tumors, expression of miR-15a/miR-16 inversely correlates with the expression of cyclin D1. In non-small cell lung cancer (NSCLC) cell lines, cyclins D1, D2, and E1 are directly regulated by physiologic concentrations of miR-15a/miR-16. Consistent with these results, overexpression of these miRNAs induces cell cycle arrest in G 1 -G 0 . Interestingly, H2009 cells lacking Rb are resistant to miR-15a/miR-16-induced cell cycle arrest, whereas reintroduction of functional Rb resensitizes these cells to miRNA activity. In contrast, down-regulation of Rb in A549 cells by RNA interference confers resistance to these miRNAs. Thus, cell cycle arrest induced by these miRNAs depends on the expression of Rb, confirming that G 1 cyclins are major targets of miR-15a/miR-16 in NSCLC. Our results indicate that miR-15a/miR-16 are implicated in cell cycle control and likely contribute to the tumorigenesis of NSCLC. [Cancer Res 2009;69(13):5553-9]

Current clinical classification of pancreatic ductal adenocarcinoma (PDAC) is unable to predict prognosis or response to chemo- or immunotherapy and does not take into account the host reaction to PDAC cells. Our aim is to classify PDAC according to host- and tumor-related factors into clinically/biologically relevant subtypes by integrating molecular and microenvironmental findings. A well-characterized PDAC cohort ( = 110) underwent next-generation sequencing with a hot spot cancer panel while next-generation tissue microarrays were immunostained for CD3, CD4, CD8, CD20, PD-L1, p63, hyaluronan-mediated motility receptor (RHAMM), and DNA mismatch repair proteins. Previous data on FOXP3 were integrated. Immune cell counts and protein expression were correlated with tumor-derived driver mutations, clinicopathologic features (TNM 8th edition, 2017), survival, and epithelial-mesenchymal transition (EMT)-like tumor budding. Three PDAC subtypes were identified: the "immune escape" (54%), poor in T and B cells and enriched in FOXP3 regulatory T cells (Treg), with high-grade budding, frequent ,, and mutations, and poor outcome; the "immune rich" (35%), rich in T and B cells and poorer in FOXP3 Tregs, with infrequent budding, lower and mutation rate, and better outcome and a subpopulation with tertiary lymphoid tissue (TLT), mutations in DNA damage response genes ( and ), and the best outcome; and the "immune exhausted" (11%), with immunogenic microenvironment and two subpopulations-one with PD-L1 expression and a high mutation rate and a microsatellite-unstable subpopulation with a high prevalence of mutations. The combination of low budding, low stromal FOXP3 counts, presence of TLTs, and absence of mutations confers significant survival advantage in patients with PDAC. Immune host responses correlate with tumor characteristics, leading to morphologically recognizable PDAC subtypes with prognostic/predictive significance. .

Circulating miRNAs are detected in extracellular space and body fluids such as urine. Circulating RNAs can be packaged in secreted urinary extracellular vesicles (uEVs) and thus protected from degradation. Urinary exosome preparations might contain specific miRNAs, relevant as biomarkers in renal and bladder diseases. Major difficulties in application of uEVs into the clinical environment are the high variability and low reproducibility of uEV isolation methods. Here we used five different methods to isolate uEVs and compared the size distribution, morphology, yield, presence of exosomal protein markers and RNA content of uEVs. We present an optimized ultracentrifugation and size exclusion chromatography approach for highly reproducible isolation for 50–150 nm uEVs, corresponding to the exosomes, from 50 ml urine. We profiled the miRNA content of uEVs and total urine from the same samples with the NanoString platform and validated the data using qPCR. Our results indicate that 18 miRNAs, robustly detected in uEVs were always present in the total urine. However, 15 miRNAs could be detected only in the total urine preparations and might represent naked circulating miRNA species. This is a novel unbiased and reproducible strategy for uEVs isolation, content normalization and miRNA cargo analysis, suitable for biomarker discovery studies.

No abstract

By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.

BackgroundmicroRNAs (miRNAs) are small non-coding RNAs that are frequently involved in carcinogenesis. Although many miRNAs form part of integrated networks, little information is available how they interact with each other to control cellular processes. miR-34a and miR-15a/16 are functionally related; they share common targets and control similar processes including G1-S cell cycle progression and apoptosis. The aim of this study was to investigate the combined action of miR-34a and miR-15a/16 in non-small cell lung cancer (NSCLC) cells.MethodsNSCLC cells were transfected with miR-34a and miR-15a/16 mimics and analysed for cell cycle arrest and apoptosis by flow cytometry. Expression of retinoblastoma and cyclin E1 was manipulated to investigate the role of these proteins in miRNA-induced cell cycle arrest. Expression of miRNA targets was assessed by real-time PCR. To investigate if both miRNAs are co-regulated in NSCLC cells, tumour tissue and matched normal lung tissue from 23 patients were collected by laser capture microdissection and compared for the expression of these miRNAs by real-time PCR.ResultsIn the present study, we demonstrate that miR-34a and miR-15a/16 act synergistically to induce cell cycle arrest in a Rb-dependent manner. In contrast, no synergistic effect of these miRNAs was observed for apoptosis. The synergistic action on cell cycle arrest was not due to a more efficient down-regulation of targets common to both miRNAs. However, the synergistic effect was abrogated in cells in which cyclin E1, a target unique to miR-15a/16, was silenced by RNA interference. Thus, the synergistic effect was due to the fact that in concerted action both miRNAs are able to down-regulate more targets involved in cell cycle control than each miRNA alone. Both miRNAs were significantly co-regulated in adenocarcinomas of the lung suggesting a functional link between these miRNAs.ConclusionsIn concerted action miRNAs are able to potentiate their impact on G1-S progression. Thus the combination of miRNAs of the same network rather than individual miRNAs should be considered for assessing a biological response. Since miR-34a and miR-15a/16 are frequently down-regulated in the same tumour tissue, administrating a combination of both miRNAs may also potentiate their therapeutic impact.

Background/Aims: O⁶-methylguanine-methyltransferase (MGMT) is an important enzyme of DNA repair. MGMT promoter methylation is detectable in a subset of pancreatic neuroendocrine neoplasms (pNEN). A subset of pNEN responds to the alkylating agent temozolomide (TMZ). We wanted to correlate MGMT promoter methylation with MGMT protein loss in pNEN, correlate the findings with clinico-pathological data and determine the role of MGMT to predict response to TMZ chemotherapy. Methods: We analysed a well-characterized collective of 141 resected pNEN with median follow-up of 83 months for MGMT protein expression and promoter methylation using methylation-specific PCR (MSP). A second collective of 10 metastasized, pretreated and progressive patients receiving TMZ was used to examine the predictive role of MGMT by determining protein expression and promoter methylation using primer extension-based quantitative PCR. Results: In both collectives there was no correlation between MGMT protein expression and promoter methylation. Loss of MGMT protein was associated with an adverse outcome, this prognostic value, however, was not independent from grade and stage in multivariate analysis. Promoter hypermethylation was significantly associated with response to TMZ. Conclusion: Loss of MGMT protein expression is associated with adverse outcome in a surgical series of pNET. MGMT promoter methylation could be a predictive marker for TMZ chemotherapy in pNEN, but further, favourably prospective studies will be needed to confirm this result and before this observation can influence clinical routine.