MiR-886-3p regulates cell proliferation and migration, and is dysregulated in familial non-medullary thyroid cancer

Background

The molecular basis and characteristics of familial non-medullary thyroid cancer are poorly understood. In this study, we performed microRNA (miRNA) profiling of familial and sporadic papillary thyroid cancer tumor samples.

Methodology/Principal Findings

Genome wide miRNA profiling of sporadic and familial papillary thyroid cancer was performed. Differentially expressed miRNAs were validated by quantitative RT-PCR. Ectopic expression of miR-886-3p in thyroid cancer lines was performed to identify pathways targeted by the miRNA, as well as, to determine its effect on tumor cell biology. We found four differentially expressed miRNAs between familial and sporadic papillary thyroid cancer tumor samples. MiR-886-3p and miR-20a were validated to be differentially expressed by 3- and 4-fold, respectively. Pathway analysis of genome-wide expression data on cells overexpressing miR-886-3p and target prediction analysis showed genes involved in DNA replication and focal adhesion pathways were regulated by miR-886-3p. Overexpression of miR-886-3p in thyroid cancer cell lines significantly inhibited cellular proliferation, the number and size of spheroids and cellular migration. Additionally, overexpression of miR-886-3p increased the number of cells in S phase.

Conclusions/Significance

Our findings for the first time suggest that miR-886-3p plays an important role in thyroid cancer tumor cell biology and regulates genes involved in DNA replication and focal adhesion. Thus, miR-886-3p may play a role in the initiation and or progression of papillary thyroid cancer.     

Simultaneous extraction of nucleic acids and proteins from tissue specimens by ultracentrifugation: A protocol using the high‐salt protein fraction for quantitative proteome analysis

Comprehensive molecular profiling of human tumor tissue specimens at the DNA, mRNA and protein level is often obstructed by a limited amount of available material. Homogenization of frozen tissue samples in guanidine isothiocyanate followed by ultracentrifugation over cesium chloride allows the simultaneous extraction of high‐molecular weight DNA and RNA. Here, we present a protocol for quantitative proteome analysis using the high‐salt protein fraction obtained as supernatant after ultracentrifugation for nucleic acid extraction. We applied this method to extracts from primary human brain tumors and demonstrate its successful application for protein expression profiling in these tumors using 2‐D DIGE, MS and Western blotting.     

Gene expression sigantures, cancer cell evolution and metastatic progression

Global gene expression profiling and molecular cytogenetics for single cells provide new opportunities to resolve important questions, such as the mechanisms of tumor cell selection during cancer progression. While gene expression analyses show that metastatic progression correlates with the deregulation of certain gene sets in the primary tumor, the direct analysis of disseminated cancer cells, the putative precursors of metachronous metastases, suggests that dissemination is a very early event in the genetic development of human cancers.     

Classifying human cancer by analysis of gene expression

With the development and application of DNA microarrays, the expression of almost all human genes can now be systematically examined in human malignancies. This can lead to the identification of candidate molecular targets for therapeutic intervention and biomarkers for early detection of these diseases. However, perhaps the most exciting result to come from this research has been the demonstration that patterns of gene expression can distinguish between tumors of different anatomical origin, and define new subgroups of cancer with similar histological appearance, but distinct molecular profiles. Some of these new molecular subclasses of tumor appear to correlate with clinical behavior. If substantiated in larger studies, this might form a basis for stratifying patients so that they receive optimal therapeutic treatment and follow-up.     

Mixture models for assessing differential expression in complex tissues using microarray data

MOTIVATION: The use of DNA microarrays has become quite popular in many scientific and medical disciplines, such as in cancer research. One common goal of these studies is to determine which genes are differentially expressed between cancer and healthy tissue, or more generally, between two experimental conditions. A major complication in the molecular profiling of tumors using gene expression data is that the data represent a combination of tumor and normal cells. Much of the methodology developed for assessing differential expression with microarray data has assumed that tissue samples are homogeneous. RESULTS: In this paper, we outline a general framework for determining differential expression in the presence of mixed cell populations. We consider study designs in which paired tissues and unpaired tissues are available. A hierarchical mixture model is used for modeling the data; a combination of methods of moments procedures and the expectation-maximization algorithm are used to estimate the model parameters. The finite-sample properties of the methods are assessed in simulation studies; they are applied to two microarray datasets from cancer studies. Commands in the R language can be downloaded from the URL http://www.sph.umich.edu/~ghoshd/COMPBIO/COMPMIX/.     

Gene expression profiling and clinical outcome in breast cancer

Pathologic and clinical heterogeneity of breast cancer reflects the poorly documented, complex, and combinatory molecular basis of the disease and is in part responsible for therapeutic failures. The DNA microarray technique allows the analysis of RNA expression of several thousands of genes simultaneously in a sample. There are multiple potential applications of the technique in cancer research. A number of recent studies have shown the promising role of gene expression profiling in breast cancer by identifying new prognostic subclasses unidentifiable by conventional parameters and new prognostic and/or predictive gene signatures, whose predictive impact is superior to conventional histoclinical prognostic factors. In this review we describe current use of DNA microarrays in the prognosis of breast cancer. We also discuss issues that need to be addressed in the near future to allow the method to reach its full potential.     

Human breast cancer associated fibroblasts exhibit subtype specific gene expression profiles

ABSTRACT: BACKGROUND: Breast cancer is a heterogeneous disease for which prognosis and treatment strategies are largely governed by the receptor status (estrogen, progesterone and Her2) of the tumor cells. Gene expression profiling of whole breast tumors further stratifies breast cancer into several molecular subtypes which also co-segregate with the receptor status of the tumor cells. We postulated that cancer associated fibroblasts (CAFs) within the tumor stroma may exhibit subtype specific gene expression profiles and thus contribute to the biology of the disease in a subtype specific manner. Several studies have reported gene expression profile differences between CAFs and normal breast fibroblasts but in none of these studies were the results stratified based on tumor subtypes. METHODS: To address whether gene expression in breast cancer associated fibroblasts varies between breast cancer subtypes, we compared the gene expression profiles of early passage primary CAFs isolated from twenty human breast cancer samples representing three main subtypes; seven ER+, seven triple negative (TNBC) and six Her2+. RESULTS: We observed significant expression differences between CAFs derived from Her2+ breast cancer and CAFs from TNBC and ER + cancers, particularly in pathways associated with cytoskeleton and integrin signaling. In the case of Her2+ breast cancer, the signaling pathways found to be selectively up regulated in CAFs likely contribute to the enhanced migration of breast cancer cells in transwell assays and may contribute to the unfavorable prognosis of Her2+ breast cancer. CONCLUSIONS: These data demonstrate that in addition to the distinct molecular profiles that characterize the neoplastic cells, CAF gene expression is also differentially regulated in distinct subtypes of breast cancer.     

Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples

Background

Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting.

Methodology

We developed and implemented an optimized mutation profiling platform (“OncoMap”) to interrogate ∼400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact.

Conclusions

Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of “actionable” cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents.     

Expression and genomic profiling of colorectal cancer

Colorectal cancer still represents a paradigm for the elucidation of the cellular, genetic and molecular mechanisms that underly solid tumor initiation, progression to malignancy, and metastasis to distal organ sites. The relative ease with which pathological specimens can be obtained by either surgery or endoscopy from different stages of tumor progression has facilitated the application of omics technologies to allow the genome-wide analysis both at the RNA (gene expression) and DNA (aneuploidy) levels. Here, we have reviewed the multiplicity of studies appeared to date in the scientific literature on the expression and genomic analysis of colorectal cancer, and attempted an integration of the profiling data generated and made available in the public domain. This approach is likely to pinpoint specific chromosomal loci and the corresponding genes which (i) play rate-limiting roles in colorectal cancer, (ii) represent putative diagnostic and prognostic markers for the accurate prediction of clinical outcome and response to treatment, and (iii) encompass potential therapeutic targets. Moreover, cross-species data mining and integration of the human colorectal cancer profiles with those obtained from mouse models of intestinal tumorigenesis will even more contribute to the elucidation of highly conserved pathways and cellular functions underlying malignancy in the GI tract. Notwithstanding the above promises, tumor heterogeneity, limited cohort sizes, and methodological differences among experimental and bioinformatic approaches still poses main obstacles towards the optimal utilization and integration of omics profiles.     

Integration of DNA copy number alterations and transcriptional expression analysis in human gastric cancer

Background

Genomic instability with frequent DNA copy number alterations is one of the key hallmarks of carcinogenesis. The chromosomal regions with frequent DNA copy number gain and loss in human gastric cancer are still poorly defined. It remains unknown how the DNA copy number variations contributes to the changes of gene expression profiles, especially on the global level.

Principal Findings

We analyzed DNA copy number alterations in 64 human gastric cancer samples and 8 gastric cancer cell lines using bacterial artificial chromosome (BAC) arrays based comparative genomic hybridization (aCGH). Statistical analysis was applied to correlate previously published gene expression data obtained from cDNA microarrays with corresponding DNA copy number variation data to identify candidate oncogenes and tumor suppressor genes. We found that gastric cancer samples showed recurrent DNA copy number variations, including gains at 5p, 8q, 20p, 20q, and losses at 4q, 9p, 18q, 21q. The most frequent regions of amplification were 20q12 (7/72), 20q12–20q13.1 (12/72), 20q13.1–20q13.2 (11/72) and 20q13.2–20q13.3 (6/72). The most frequent deleted region was 9p21 (8/72). Correlating gene expression array data with aCGH identified 321 candidate oncogenes, which were overexpressed and showed frequent DNA copy number gains; and 12 candidate tumor suppressor genes which were down-regulated and showed frequent DNA copy number losses in human gastric cancers. Three networks of significantly expressed genes in gastric cancer samples were identified by ingenuity pathway analysis.

Conclusions

This study provides insight into DNA copy number variations and their contribution to altered gene expression profiles during human gastric cancer development. It provides novel candidate driver oncogenes or tumor suppressor genes for human gastric cancer, useful pathway maps for the future understanding of the molecular pathogenesis of this malignancy, and the construction of new therapeutic targets.     

DNA甲基化对子宫内膜异位症(EMs)的作用及其调控机制

表观遗传通过DNA甲基化、组蛋白修饰、染色质重塑、以及microRNA等调控方式来实现对基因表达、DNA复制和基因组稳定性的控制。DNA甲基化是目前研究的最为广泛的表观遗传修饰方式之一,可调控真核生物的基因表达。DNA甲基化在哺乳动物发育、肿瘤发生发展及人类其他疾病中均发挥着至关重要的作用。DNA甲基化状态的改变已被视为人类肿瘤细胞的生物标志之一。EMs虽是一种良性妇科疾病,但伴有细胞增殖、侵袭性及远处种植转移等肿瘤的特点。最新研究发现,DNA甲基化可能与子宫内膜异位症(EMs)的发生存在密切的关系并认为EMs从根本上是一种表观遗传学疾病。由于表观遗传修饰都是可逆的过程,这就为EMs的治疗提供了一种新的途径。本文就DNA甲基化在EMs中的发生发展中的作用及其调控的分子机制,以及在诊断治疗中作用的最新研究进展做一综述。     

DNA甲基化对子宫内膜异位症（EMs）的作用及其调控机制

表观遗传通过DNA甲基化、组蛋白修饰、染色质重塑、以及microRNA等调控方式来实现对基因表达、DNA复制和基因组稳定性的控制。DNA甲基化是目前研究的最为广泛的表观遗传修饰方式之一,可调控真核生物的基因表达。DNA甲基化在哺乳动物发育、肿瘤发生发展及人类其他疾病中均发挥着至关重要的作用。DNA甲基化状态的改变已被视为人类肿瘤细胞的生物标志之一。EMs虽是一种良性妇科疾病,但伴有细胞增殖、侵袭性及远处种植转移等肿瘤的特点。最新研究发现,DNA甲基化可能与子宫内膜异位症（EMs）的发生存在密切的关系并认为EMs从根本上是一种表观遗传学疾病。由于表观遗传修饰都是可逆的过程,这就为EMs的治疗提供了一种新的途径。本文就DNA甲基化在EMs中的发生发展中的作用及其调控的分子机制,以及在诊断治疗中作用的最新研究进展做一综述。     

Widespread Molecular Patterns Associated with Drug Sensitivity in Breast Cancer Cell Lines,with Implications for Human Tumors

Background

Recent landmark studies have profiled cancer cell lines for molecular features, along with measuring the corresponding growth inhibitory effects for specific drug compounds. These data present a tool for determining which subsets of human cancer might be more responsive to particular drugs. To this end, the NCI-DREAM-sponsored DREAM7: Drug Sensitivity Prediction Challenge (sub-challenge 1) set out to predict the sensitivities of 18 breast cancer cell lines to 31 previously untested compounds, on the basis of molecular profiling data and a training subset of cell lines.

Methods and Results

With 47 teams submitting blinded predictions, team Creighton scored third in terms of overall accuracy. Team Creighton''s method was simple and straightforward, incorporated multiple expression data types (RNA-seq, gene array, RPPA), and incorporated all profiled features (not only the “best” predictive ones). As an extension of the approach, cell line data, from public datasets of expression profiling coupled with drug sensitivities (Barretina, Garnett, Heiser) were used to “predict” the drug sensitivities in human breast tumors (using data from The Cancer Genome Atlas). Drug sensitivity correlations within human breast tumors showed differences by expression-based subtype, with many associations in line with the expected (e.g. Lapatinib sensitivity in HER2-enriched cancers) and others inviting further study (e.g. relative resistance to PI3K inhibitors in basal-like cancers).

Conclusions

Molecular patterns associated with drug sensitivity are widespread, with potentially hundreds of genes that could be incorporated into making predictions, as well as offering biological clues as to the mechanisms involved. Applying the cell line patterns to human tumor data may help generate hypotheses on what tumor subsets might be more responsive to therapies, where multiple cell line datasets representing various drugs may be used, in order to assess consistency of patterns.     

Biochemical markers predicting response to radiation- and radiochemo-therapy in cancer patients

Ongoing studies carried out worldwide using banks of tumor and non-tumor samples give evidence that perspective markers predicting response of individual patients to intended radiation therapy may be found among some apoptotic indexes, spectrum of specialized proteins, and DNA-based microarray molecular profiling analysis as well determination of single nucleotide polymorphisms in genome of the patients. In the last years there is increasing interest in radiogenomics and characterization of gene expression profiles by DNA (micro)array technique that can predict radioresponse of tumor and non-tumor tissues. So far there are only a few reliable molecular markers predicting response of tumor and non-tumor tissues to radiation.