Circulating miRNAs miR-34a and miR-150 associated with colorectal cancer progression.

BACKGROUND: Screening for the early detection of colorectal cancer is important to improve patient survival. The aim of this study was to investigate the potential of circulating cell-free miRNAs as biomarkers of CRC, and their efficiency at delineating patients with polyps and benign adenomas from normal and cancer patient groups. METHODS: The expression of 667 miRNAs was assessed in a discovery set of 48 plasma samples comprising normal, polyp, adenoma, and early and advanced cancer samples. Three miRNAs (miR-34a, miR-150, and miR-923) were further examined in a validation cohort of 97 subjects divided into the same five groups, and in an independent public dataset of 40 CRC samples and paired normal tissues. RESULTS: High levels of circulating miR-34a and low miR-150 levels distinguished groups of patients with polyps from those with advanced cancer (AUC = 0.904), and low circulating miR-150 levels separated patients with adenomas from those with advanced cancer (AUC = 0.875). In addition, the altered expression of miR-34a and miR-150 in an independent public dataset of forty CRC samples and paired normal tissues was confirmed. CONCLUSION: We identified two circulating miRNAs capable of distinguishing patient groups with different diseases of the colon from each other, and patients with advanced cancer from benign disease groups.

Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis.

Weighted gene coexpression network analysis (WGCNA) is a powerful 'guilt-by-association'-based method to extract coexpressed groups of genes from large heterogeneous messenger RNA expression data sets. We have utilized WGCNA to identify 11 coregulated gene clusters across 2342 breast cancer samples from 13 microarray-based gene expression studies. A number of these transcriptional modules were found to be correlated to clinicopathological variables (e.g. tumor grade), survival endpoints for breast cancer as a whole (disease-free survival, distant disease-free survival and overall survival) and also its molecular subtypes (luminal A, luminal B, HER2+ and basal-like). Examples of findings arising from this work include the identification of a cluster of proliferation-related genes that when upregulated correlated to increased tumor grade and were associated with poor survival in general. The prognostic potential of novel genes, for example, ubiquitin-conjugating enzyme E2S (UBE2S) within this group was confirmed in an independent data set. In addition, gene clusters were also associated with survival for breast cancer molecular subtypes including a cluster of genes that was found to correlate with prognosis exclusively for basal-like breast cancer. The upregulation of several single genes within this coexpression cluster, for example, the potassium channel, subfamily K, member 5 (KCNK5) was associated with poor outcome for the basal-like molecular subtype. We have developed an online database to allow user-friendly access to the coexpression patterns and the survival analysis outputs uncovered in this study (available at http://glados.ucd.ie/Coexpression/).

BreastMark: an integrated approach to mining publicly available transcriptomic datasets relating to breast cancer outcome.

INTRODUCTION: Breast cancer is a complex heterogeneous disease for which a substantial resource of transcriptomic data is available. Gene expression data have facilitated the division of breast cancer into, at least, five molecular subtypes, namely luminal A, luminal B, HER2, normal-like and basal. Once identified, breast cancer subtypes can inform clinical decisions surrounding patient treatment and prognosis. Indeed, it is important to identify patients at risk of developing aggressive disease so as to tailor the level of clinical intervention. METHODS: We have developed a user-friendly, web-based system to allow the evaluation of genes/microRNAs (miRNAs) that are significantly associated with survival in breast cancer and its molecular subtypes. The algorithm combines gene expression data from multiple microarray experiments which frequently also contain miRNA expression information, and detailed clinical data to correlate outcome with gene/miRNA expression levels. This algorithm integrates gene expression and survival data from 26 datasets on 12 different microarray platforms corresponding to approximately 17,000 genes in up to 4,738 samples. In addition, the prognostic potential of 341 miRNAs can be analysed. RESULTS: We demonstrated the robustness of our approach in comparison to two commercially available prognostic tests, oncotype DX and MammaPrint. Our algorithm complements these prognostic tests and is consistent with their findings. In addition, BreastMark can act as a powerful reductionist approach to these more complex gene signatures, eliminating superfluous genes, potentially reducing the cost and complexity of these multi-index assays. Known miRNA prognostic markers, mir-205 and mir-93, were used to confirm the prognostic value of this tool in a miRNA setting. We also applied the algorithm to examine expression of 58 receptor tyrosine kinases in the basal-like subtype, identifying six receptor tyrosine kinases associated with poor disease-free survival and/or overall survival (EPHA5, FGFR1, FGFR3, VEGFR1, PDGFRß, and TIE1). A web application for using this algorithm is currently available. CONCLUSIONS: BreastMark is a powerful tool for examining putative gene/miRNA prognostic markers in breast cancer. The value of this tool will be in the preliminary assessment of putative biomarkers in breast cancer. It will be of particular use to research groups with limited bioinformatics facilities.

A gene expression profile indicative of early stage HER2 targeted therapy response.

BACKGROUND: Efficacious application of HER2-targetting agents requires the identification of novel predictive biomarkers. Lapatinib, afatinib and neratinib are tyrosine kinase inhibitors (TKIs) of HER2 and EGFR growth factor receptors. A panel of breast cancer cell lines was treated with these agents, trastuzumab, gefitinib and cytotoxic therapies and the expression pattern of a specific panel of genes using RT-PCR was investigated as a potential marker of early drug response to HER2-targeting therapies. RESULTS: Treatment of HER2 TKI-sensitive SKBR3 and BT474 cell lines with lapatinib, afatinib and neratinib induced an increase in the expression of RB1CC1, ERBB3, FOXO3a and NR3C1. The response directly correlated with the degree of sensitivity. This expression pattern switched from up-regulated to down-regulated in the HER2 expressing, HER2-TKI insensitive cell line MDAMB453. Expression of the CCND1 gene demonstrated an inversely proportional response to drug exposure. A similar expression pattern was observed following the treatment with both neratinib and afatinib. These patterns were retained following exposure to traztuzumab and lapatinib plus capecitabine. In contrast, gefitinib, dasatinib and epirubicin treatment resulted in a completely different expression pattern change. CONCLUSIONS: In these HER2-expressing cell line models, lapatinib, neratinib, afatinib and trastuzumab treatment generated a characteristic and specific gene expression response, proportionate to the sensitivity of the cell lines to the HER2 inhibitor.Characterisation of the induced changes in expression levels of these genes may therefore give a valuable, very early predictor of the likely extent and specificity of tumour HER2 inhibitor response in patients, potentially guiding more specific use of these agents.

Gene expression changes as markers of early lapatinib response in a panel of breast cancer cell lines.

BACKGROUND: Lapatinib, a tyrosine kinase inhibitor of HER2 and EGFR and is approved, in combination with capecitabine, for the treatment of trastuzumab-refractory metastatic breast cancer. In order to establish a possible gene expression response to lapatinib, a panel of breast cancer cell lines with varying sensitivity to lapatinib were analysed using a combination of microarray and qPCR profiling. METHODS: Co-inertia analysis (CIA), a data integration technique, was used to identify transcription factors associated with the lapatinib response on a previously published dataset of 96 microarrays. RNA was extracted from BT474, SKBR3, EFM192A, HCC1954, MDAMB453 and MDAMB231 breast cancer cell lines displaying a range of lapatinib sensitivities and HER2 expression treated with 1 µM of lapatinib for 12 hours and quantified using Taqman RT-PCR. A fold change ≥ ± 2 was considered significant. RESULTS: A list of 421 differentially-expressed genes and 8 transcription factors (TFs) whose potential regulatory impact was inferred in silico, were identified as associated with lapatinib response. From this group, a panel of 27 genes (including the 8 TFs) were selected for qPCR validation. 5 genes were determined to be significantly differentially expressed following the 12 hr treatment of 1 µM lapatinib across all six cell lines. Furthermore, the expression of 4 of these genes (RB1CC1, FOXO3A, NR3C1 and ERBB3) was directly correlated with the degree of sensitivity of the cell line to lapatinib and their expression was observed to "switch" from up-regulated to down-regulated when the cell lines were arranged in a lapatinib-sensitive to insensitive order. These included the novel lapatinib response-associated genes RB1CC1 and NR3C1. Additionally, Cyclin D1 (CCND1), a common regulator of the other four proteins, was also demonstrated to observe a proportional response to lapatinib exposure. CONCLUSIONS: A panel of 5 genes were determined to be differentially expressed in response to lapatinib at the 12 hour time point examined. The expression of these 5 genes correlated directly with lapatinib sensitivity. We propose that the gene expression profile may represent both an early measure of the likelihood of sensitivity and the level of response to lapatinib and may therefore have application in early response detection.

Potentially important microRNA cluster on chromosome 17p13.1 in primary peritoneal carcinoma.

MicroRNAs are a group of small non-coding RNAs approximately 22 nucleotides in length. Recent work has shown differential expression of mature microRNAs in human cancers. We characterized the alteration in expression of a select group of microRNAs in primary peritoneal carcinoma relative to matched cases of ovarian serous carcinoma. MicroRNA expression was analysed using semi-quantitative stem-loop RT-PCR on a set of 34 formalin-fixed paraffin-embedded samples. Protein expression of p53 and bcl-2 was quantified in the corresponding tissue microarray. We provide definitive evidence that there is downregulation of a select group of microRNAs in tumours meeting Gynaecological Oncology Group criteria for primary peritoneal carcinoma relative to ovarian serous carcinoma. Specifically, we show decreased p53 expression and downregulation of miR-195 and miR-497 from the microRNA cluster site at chromosome 17p13.1 in primary peritoneal carcinoma relative to ovarian serous carcinoma. miR-195 and miR-497 may have potential roles as tumour-suppressor genes in primary peritoneal tumourigenesis.

Geographical mapping of a multifocal thyroid tumour using genetic alteration analysis & miRNA profiling.

BACKGROUND: Papillary thyroid carcinoma (PTC) frequently presents as multiple tumour-foci within a single thyroid gland or pluriform, with synchronous tumours comprising different histological variants, raising questions regarding its clonality. Among the genetic aberrations described in PTC, the BRAF V600E mutation and ret/PTC activation occur most commonly. Several studies have investigated the genetic alteration status of multifocal thyroid tumours, with discordant results. To address the question of clonality this study examined disparate geographical and morphological areas from a single PTC (classic PTC, insular and anaplastic foci, and tumour cells adjacent to vascular invasion and lymphocytic infiltrate) for the presence of ret/PTC 1 or BRAF mutations. Moreover, we wanted to investigate the consistency of miRNA signatures within disparate areas of a tumour, and geographical data was further correlated with expression profiles of 330 different miRNAs. Putative miRNA gene targets were predicted for differentially regulated miRNAs and immunohistochemistry was performed on tissue sections in an effort to investigate phenotypic variations in microvascular density (MVD), and cytokeratin and p53 protein expression levels. RESULTS: All of the morphological areas proved negative for ret/PTC 1 rearrangement. Two distinct foci with classic morphology harboured the BRAF mutation. All other regions, including the insular and anaplastic areas were negative for the mutation. MiRNA profiles were found to distinguish tumours containing the BRAF mutation from the other tumour types, and to differentiate between the more aggressive insular & anaplastic tumours, and the classic variant. Our data corroborated miRNAs previously discovered in this carcinoma, and additional miRNAs linked to various processes involved in tumour growth and proliferation. CONCLUSION: The initial genetic alteration analysis indicated that pluriform PTC did not necessarily evolve from classic PTC progenitor foci. Analysis of miRNA profiles however provided an interesting variation on the clonality question. While hierarchical clustering analysis of miRNA expression supported the hypothesis that discrete areas did not evolve from clonal expansion of tumour cells, it did not exclude the possibility of independent mutational events suggesting both phenomena might occur simultaneously within a tumour to enhance cancer progression in geographical micro-environments within a tumour.

Manipulating MiRNA Expression to Uncover Hidden Functions.

There are a numerous target prediction algorithms that allow users to identify putative targets of their microRNAs (miRNAs) of interest. Although these tools are useful to gain insight into the potential role of miRNAs in regulating cellular processes, physical manipulation of the expression of the miRNA is the most superior way to truly determine the function of the miRNA in the system of interest. This chapter outlines methods to reveal miRNA function by modulating miRNA expression by transient transfection of miRNA mimics and inhibitors, and stable overexpression and reduction of miRNA expression using plasmid overexpression and sponge vectors.

Altered expression of mir-222 and mir-25 influences diverse gene expression changes in transformed normal and anaplastic thyroid cells, and impacts on MEK and TRAIL protein expression.

Thyroid cancer is the most common endocrine malignancy and accounts for the majority of endocrine cancer-related deaths each year. Our group and others have previously demonstrated dysfunctional microRNA (miRNA or miR) expression in the context of thyroid cancer. The objective of the present study was to investigate the impact of synthetic manipulation of expression of miR-25 and miR-222 in benign and malignant thyroid cells. miR-25 and miR-222 expression was upregulated in 8505C (an anaplastic thyroid cell line) and Nthy-ori (a SV40-immortalised thyroid cell line) cells, respectively. A transcriptomics-based approach was utilised to identify targets of the two miRNAs and real-time PCR and western blotting were used to validate a subset of the targets. Almost 100 mRNAs of diverse functions were found to be either directly or indirectly targeted by both miR-222 and miR-25 [fold change ≥2, false discovery rate (FDR) ≤0.05]. Gene ontology analysis showed the miR-25 gene target list to be significantly enriched for genes involved in cell adhesion. Fluidigm real-time PCR technologies were used to validate the downregulation of 23 and 22 genes in response to miR-25 and miR-222 overexpression, respectively. The reduction of the expression of two miR-25 protein targets, TNF-related apoptosis­inducing ligand (TRAIL) and mitogen-activated protein kinase kinase 4 (MEK4), was also validated. Manipulating the expression of both miR-222 and miR-25 influenced diverse gene expression changes in thyroid cells. Increased expression of miR-25 reduced MEK4 and TRAIL protein expression, and cell adhesion and apoptosis are important aspects of miR-25 functioning in thyroid cells.

Comparative transcriptomic analysis of cultivated limbal epithelium and donor corneal tissue reveals altered wound healing gene expression.

PURPOSE: The improved surgical outcomes associated with transplantation of cultivated amniotic membrane expanded limbal epithelium (AMLE) compared to traditional donor methods has led to substantial adoption of this technique for treatment of limbal stem cell deficiency. METHODS: The mRNA expression profiles of AMLE and CE were assayed using microarrays. Transcripts with a 1.5-fold change in either direction in addition to a Bonferroni adjusted P value < 0.05 were considered to be differentially expressed. Expression changes detected by microarray profiling and important corneal-limbal markers were assessed using quantitative real-time PCR (qRT-PCR) and immunofluorescence staining. RESULTS: A total of 487 probe sets (319 upregulated and 168 downregulated) were found to be differentially expressed between AMLE and CE. Enrichment analysis revealed significant overrepresentation of multiple biological processes (e.g., response to wounding, wound healing, and regulation of cell morphogenesis) within the differentially expressed gene list. The expression of a number of genes that were upregulated (ABCG2, S100A9, ITGA5, TIMP2, FGF5, PDGFC, SEMA3A) and downregulated (KLF4, P63α) in AMLE was confirmed using qRT-PCR. Immunofluorescence confirmed that AMLE cultures were P63α, ABCG2, CK3, CK12, and E-cadherin (E-cad) positive. CONCLUSIONS: In this study, we have shown that genes associated with wound healing processes are upregulated in AMLE. These gene expression changes may contribute to corneal restoration and the positive outcomes associated with transplantation.

Transcriptomic analysis of clonal growth rate variation during CHO cell line development.

The selection of clones displaying a high rate of cell growth is an essential component of Chinese hamster ovary (CHO) cell line development. In recent years various "omics" technologies have been utilised to understand the mechanisms underlying bioprocess phenotypes. In this study, gene expression analysis using a CHO-specific microarray was conducted for a panel of CHO-K1 MAb-secreting cell lines spanning a range of growth rates that were derived from a single cell line development project. In-silico functional analysis of the resulting transcriptomic data revealed the overrepresentation of biological processes such as cell cycle and translation within those genes upregulated during fast growth, while genes associated with cellular homeostasis were downregulated. Using differential expression and correlation analysis we identified a high priority group of 416 transcripts (190 upregulated; 226 downregulated) associated with growth rate. Expression changes of eight of these genes were independently confirmed by qPCR. Finally, we demonstrate the enrichment of predicted mRNA targets of miR17-92, a microRNA (miRNA) cluster known to be upregulated during rapid proliferation, within downregulated transcripts.

Regulation of microRNA biosynthesis and expression in 2102Ep embryonal carcinoma stem cells is mirrored in ovarian serous adenocarcinoma patients.

BACKGROUND: Tumours with high proportions of differentiated cells are considered to be of a lower grade to those containing high proportions of undifferentiated cells. This property may be linked to the differentiation properties of stem cell-like populations within malignancies. We aim to identify molecular mechanism associated with the generation of tumours with differing grades from malignant stem cell populations with different differentiation potentials. In this study we assessed microRNA (miRNA) regulation in two populations of malignant Embryonal Carcinoma (EC) stem cell, which differentiate (NTera2) or remain undifferentiated (2102Ep) during tumourigenesis, and compared this to miRNA regulation in ovarian serous carcinoma (OSC) patient samples. METHODS: miRNA expression was assessed in NTera2 and 2102Ep cells in the undifferentiated and differentiated states and compared to that of OSC samples using miRNA qPCR. RESULTS: Our analysis reveals a substantial overlap between miRNA regulation in 2102Ep cells and OSC samples in terms of miRNA biosynthesis and expression of mature miRNAs, particularly those of the miR-17/92 family and clustering to chromosomes 14 and 19. In the undifferentiated state 2102Ep cells expressed mature miRNAs at up to 15,000 fold increased levels despite decreased expression of miRNA biosynthesis genes Drosha and Dicer. 2102Ep cells avoid differentiation, which we show is associated with consistent levels of expression of miRNA biosynthesis genes and mature miRNAs while expression of miRNAs clustering to chromosomes 14 and 19 is deemphasised. OSC patient samples displayed decreased expression of miRNA biosynthesis genes, decreased expression of mature miRNAs and prominent clustering to chromosome 14 but not 19. This indicates that miRNA biosynthesis and levels of miRNA expression, particularly from chromosome 14, are tightly regulated both in progenitor cells and in tumour samples. CONCLUSION: miRNA biosynthesis and expression of mature miRNAs, particularly the miR-17/92 family and those clustering to chromosomes 14 and 19, are highly regulated in both progenitor cells and tumour samples. Strikingly, 2102Ep cells are not simply malfunctioning but respond to differentiation specifically, a mechanism that is highly relevant to OSC samples. Our identification and future manipulation of these miRNAs may facilitate generation of lower grade malignancies from these high-grade cells.

Altered eIF6 and Dicer expression is associated with clinicopathological features in ovarian serous carcinoma patients.

MicroRNAs are a group of small non-coding RNAs approximately 22 nucleotides in length. Recent work has shown differential expression of mature microRNAs in human cancers. Production and function of microRNAs require coordinated processing by proteins of the microRNA machinery. Dicer and Drosha (RNase III endonucleases) are essential components of the microRNA machinery. Recently, the ribosome anti-association factor eIF6 has also been found to have a role in microRNA-mediated post-transcriptional silencing. We characterized the alterations in the expression of genes encoding proteins of microRNA machinery in ovarian serous carcinoma. Protein expression of eIF6 and Dicer was quantified in a tissue microarray of 66 ovarian serous carcinomas. Dicer, Drosha and eIF6 mRNA expression was analysed using quantitative reverse transcription-PCR on an independent set of 50 formalin-fixed, paraffin-embedded ovarian serous carcinoma samples. Expression profiles of eIF6 and Dicer were correlated with clinicopathological and patient survival data. We provide definitive evidence that eIF6 and Dicer are both upregulated in a significant proportion of ovarian serous carcinomas and are associated with specific clinicopathological features, most notably low eIF6 expression being associated with reduced disease-free survival. The status of eIF6 and proteins of the microRNA machinery may help predict toxicity and susceptibility to future interfering RNA-based therapy.

A molecular expression signature distinguishing follicular lesions in thyroid carcinoma using preamplification RT-PCR in archival samples.

Follicular variant of papillary thyroid carcinoma is a lesion that frequently causes difficulties from a diagnostic perspective in the laboratory. The purpose of this study was to interrogate a cohort of archival thyroid lesions using gene expression analysis of a panel of markers proposed to have utility as adjunctive markers in the diagnosis of thyroid neoplasia and follicular variant of papillary thyroid carcinoma in particular. Laser Capture Microdissection was used to procure pure cell populations for extraction. In addition a novel, multiplex preamplification technique was used to facilitate analysis of multiple targets. The panel comprised: HLA-DMA, HLA-DBQ1, CD74, CSNK1G2, IRF3, KRAS2, LYN, MT1K, MT1X, RAB23, TGFB1 and TOP2A, with CDKN1B as an endogenous control. Expression profiles for each target were generated using TaqMan Real-Time PCR. HLA-DMA, HLA-DQB1, MT1X, CSNK1G2 and RAB23 were found to be differentially expressed (P<0.05) when comparing follicular adenoma and follicular variant of papillary thyroid carcinoma. Comparison of follicular adenoma and follicular thyroid carcinoma groups showed significant differential expression for MT1K, MT1X and RAB23 (P<0.05). Comparison of the papillary thyroid carcinoma group (classic and follicular variants) and the follicular adenoma group showed differential expression for CSNK1G2, HLA-DQB1, MT1X and RAB23 (P<0.05). Finally, KRAS2 was found to be differentially expressed (P<0.05) when comparing the papillary thyroid carcinoma and follicular thyroid carcinoma groups. This panel of molecular targets discriminates between follicular adenoma, papillary thyroid carcinoma, follicular variant of papillary thyroid carcinoma and follicular thyroid carcinoma by their expression repertoires. It may have utility for broader use in the setting of fine-needle aspiration cytology and could improve the definitive diagnosis of certain categories of thyroid malignancy.