Gene expression profiling of breast tumours from New Zealand patients

AIMS: New Zealand has one of the highest rates of breast cancer incidence in the world. We investigated the gene expression profiles of breast tumours from New Zealand patients, compared them to gene expression profiles of international breast cancer cohorts and identified any associations between altered gene expression and the clinicopathological features of the tumours. METHODS: Affymetrix microarrays were used to measure the gene expression profiles of 106 breast tumours from New Zealand patients. Gene expression data from six international breast cancer cohorts were collated, and all the gene expression data were analysed using standard bioinformatic and statistical tools. RESULTS: Gene expression profiles associated with tumour ER and ERBB2 status, molecular subtype and selected gene expression signatures within the New Zealand cohort were consistent with those found in international cohorts. Significant differences in clinicopathological features such as tumour grade, tumour size and lymph node status were also observed between the New Zealand and international cohorts. CONCLUSIONS: Gene expression profiles, which are a sensitive indicator of tumour biology, showed no clear di¬fference between breast tumours from New Zealand patients and those from non-New Zealand patients. This suggests that other factors may contribute to the high and increasing breast cancer incidence in New Zealand compared to international populations

Multimodal assessment of estrogen receptor mRNA profiles to quantify estrogen pathway activity in breast tumors

Background Molecular markers have transformed our understanding of the heterogeneity of breast cancer and have allowed the identification of genomic profiles of estrogen receptor (ER)-α signaling. However, our understanding of the transcriptional profiles of ER signaling remains inadequate. Therefore, we sought to identify the genomic indicators of ER pathway activity that could supplement traditional immunohistochemical (IHC) assessments of ER status to better understand ER signaling in the breast tumors of individual patients. Materials and Methods We reduced ESR1 (gene encoding the ER-α protein) mRNA levels using small interfering RNA in ER+ MCF7 breast cancer cells and assayed for transcriptional changes using Affymetrix HG U133 Plus 2.0 arrays. We also compared 1034 ER+ and ER− breast tumors from publicly available microarray data. The principal components of ER activity generated from these analyses and from other published estrogen signatures were compared with ESR1 expression, ER-α IHC, and patient survival. Results Genes differentially expressed in both analyses were associated with ER-α IHC and ESR1 mRNA expression. They were also significantly enriched for estrogen-driven molecular pathways associated with ESR1, cyclin D1 (CCND1), MYC (v-myc avian myelocytomatosis viral oncogene homolog), and NFKB (nuclear factor kappa B). Despite their differing constituent genes, the principal components generated from these new analyses and from previously published ER-associated gene lists were all associated with each other and with the survival of patients with breast cancer treated with endocrine therapies. Conclusion A biomarker of ER-α pathway activity, generated using ESR1-responsive mRNAs in MCF7 cells, when used alongside ER-α IHC and ESR1 mRNA expression, could provide a method for further stratification of patients and add insight into ER pathway activity in these patients

Cell Cycle Gene Networks Are Associated with Melanoma Prognosis

BACKGROUND: Our understanding of the molecular pathways that underlie melanoma remains incomplete. Although several published microarray studies of clinical melanomas have provided valuable information, we found only limited concordance between these studies. Therefore, we took an in vitro functional genomics approach to understand melanoma molecular pathways. METHODOLOGY/PRINCIPAL FINDINGS: Affymetrix microarray data were generated from A375 melanoma cells treated in vitro with siRNAs against 45 transcription factors and signaling molecules. Analysis of this data using unsupervised hierarchical clustering and Bayesian gene networks identified proliferation-association RNA clusters, which were co-ordinately expressed across the A375 cells and also across melanomas from patients. The abundance in metastatic melanomas of these cellular proliferation clusters and their putative upstream regulators was significantly associated with patient prognosis. An 8-gene classifier derived from gene network hub genes correctly classified the prognosis of 23/26 metastatic melanoma patients in a cross-validation study. Unlike the RNA clusters associated with cellular proliferation described above, co-ordinately expressed RNA clusters associated with immune response were clearly identified across melanoma tumours from patients but not across the siRNA-treated A375 cells, in which immune responses are not active. Three uncharacterised genes, which the gene networks predicted to be upstream of apoptosis- or cellular proliferation-associated RNAs, were found to significantly alter apoptosis and cell number when over-expressed in vitro. CONCLUSIONS/SIGNIFICANCE: This analysis identified co-expression of RNAs that encode functionally-related proteins, in particular, proliferation-associated RNA clusters that are linked to melanoma patient prognosis. Our analysis suggests that A375 cells in vitro may be valid models in which to study the gene expression modules that underlie some melanoma biological processes (e.g., proliferation) but not others (e.g., immune response). The gene expression modules identified here, and the RNAs predicted by Bayesian network inference to be upstream of these modules, are potential prognostic biomarkers and drug targets

MicroRNA profiling of ovarian granulosa cell tumours reveals novel diagnostic and prognostic markers

Abstract Background The aim of this study was to explore the clinical utility of microRNAs (miRNAs) as improved markers of ovarian granulosa cell tumours (GCTs) for cancer diagnosis and prognosis prediction. Current histopathological and genetic markers, such as the presence of a FOXL2 gene mutation to distinguish between the two major subtypes are not wholly accurate and as such novel biomarkers are warranted. Methods The miRNA expression profiles of five formalin-fixed, paraffin-embedded (FFPE) adult-GCTs and five juvenile-GCTs were assessed using Affymetrix miRNA 3.0 Arrays and compared for differential expression. Ten miRNAs were assessed in an additional 33 FFPE tumours and four normal granulosa cell samples by quantitative RT-PCR, and their expression correlated to clinical information. Results MicroRNA array found 37 miRNAs as differentially expressed between the two GCT subtypes (p < 0.05, fold change ≥2 and among these, miRs -138-5p, -184, -204-5p, -29c-3p, -328-3p and -501-3p were validated by RT-qPCR as differentially expressed between the two GCT subtypes (p < 0.05). In addition, the expression of miR-184 was predictive of tumour recurrence in adult-GCTs, specifically for patients diagnosed with stage I and II and stage I only disease (p < 0.001 and p < 0.05, respectively). Conclusions This study is the first to report on global miRNA expression profiles of human ovarian GCTs using FFPE tumour samples. We have validated six miRNAs as novel markers for subtype classification in GCTs with low levels of miR-138-5p correlating with early tumour stage. Low miR-184 abundance was correlated with tumour recurrence in early stage adult-GCT patients as a candidate predictive biomarker. Further studies are now needed to confirm the clinical utility of these miRNAs as diagnostic and recurrence markers, and understand their possible roles in the pathogenesis of GCTs

Additional file 1: of MicroRNA profiling of ovarian granulosa cell tumours reveals novel diagnostic and prognostic markers

Clinico-pathological characteristics of GCT tumours included in this study. *Adult-GCT patient samples with unknown FIGO stage information and excluded from recurrence analysis; †Adult-GCT patient sample with an aggressive clinical progression (progressive disease and tumour recurrence) and excluded from recurrence analysis; aClinical diagnosis based on histopathology; bStaged according to the International Federation of Gynaecology and Obstetrics (FIGO) system. (XLSX 13 kb

Additional file 2: of MicroRNA profiling of ovarian granulosa cell tumours reveals novel diagnostic and prognostic markers

Density distribution of p values between adult-GCT and juvenile-GCT tumours in the miRNA microarray dataset. The red and grey lines represent the p value density distributions for the true GCT groups in the miRNA dataset and for the 100 permuted and resampled groups, respectively. (TIFF 48 kb

Uropathogenic <i>Escherichia coli</i> Releases Extracellular Vesicles That Are Associated with RNA

<div><p>Background</p><p>Bacterium-to-host signalling during infection is a complex process involving proteins, lipids and other diffusible signals that manipulate host cell biology for pathogen survival. Bacteria also release membrane vesicles (MV) that can carry a cargo of effector molecules directly into host cells. Supported by recent publications, we hypothesised that these MVs also associate with RNA, which may be directly involved in the modulation of the host response to infection.</p><p>Methods and Results</p><p>Using the uropathogenic <i>Escherichia coli</i> (UPEC) strain 536, we have isolated MVs and found they carry a range of RNA species. Density gradient centrifugation further fractionated and characterised the MV preparation and confirmed that the isolated RNA was associated with the highest particle and protein containing fractions. Using a new approach, RNA-sequencing of libraries derived from three different ‘size’ RNA populations (<50nt, 50-200nt and 200nt+) isolated from MVs has enabled us to now report the first example of a complete bacterial MV-RNA profile. These data show that MVs carry rRNA, tRNAs, other small RNAs as well as full-length protein coding mRNAs. Confocal microscopy visualised the delivery of lipid labelled MVs into cultured bladder epithelial cells and showed their RNA cargo labelled with 5-EU (5-ethynyl uridine), was transported into the host cell cytoplasm and nucleus. MV RNA uptake by the cells was confirmed by droplet digital RT-PCR of <i>csrC</i>. It was estimated that 1% of MV RNA cargo is delivered into cultured cells.</p><p>Conclusions</p><p>These data add to the growing evidence of pathogenic bacterial MV being associated a wide range of RNAs. It further raises the plausibility for MV-RNA-mediated cross-kingdom communication whereby they influence host cell function during the infection process.</p></div

UPEC MV and their RNA cargo are delivered into human bladder cells <i>in vitro</i>.

<p>A. Confocal image of 5637 cells (red) stained with DAPI blue nuclear stain after treatment for 15 hr with 50μg/mL PKH26 green vesicles. B. Confocal image of 5637 cells (red) after treatment for 15 hr with 50μg/mL 5EU-labelled RNA vesicles (green with an arrow) C. Droplet digital RT-PCR validation of UPEC <i>csrC</i> rRNA into cells treated with 100μg/mL MVs across a 48 hr timeframe. Each treatment timepoint repeated in at least duplicate as represented by a closed spot. Red dotted lines mark the copies of <i>csrC</i> per μL from a standard curve of MV protein equivalents shown on the left.</p

Populations of RNAs found in vesicles from three size separated libraries.

<p>RFAM and RefSeq annotated sequencing reads classified by RNA-type after alignment to UPEC 536 genome.</p

Bacteria release membrane vesicles that associate with protein and RNA.

<p>A. Contrast electron microscopy of budding UPEC with a white arrow pointing to the released MV. B. Contrast electron microscopy of isolated vesicle preparation by ultracentrifugation. C. Coomassie stained protein gel of MVs isolated from UPEC D. Agilent Tapestation gel for RNA from three replicate MVs isolated from UPEC plus one donor cell RNA. Intact ribosomal bands are labelled 23S and 16S as are the small RNA fragments. The green line marks the internal loading marker.</p