Identification of a novel aspartic-like protease differentially expressed in human breast cancer cell lines

Four different human breast cancer cell lines were examined to search for genes associated with tumor growth and metastasis. Each of these cell lines, MDA-MB-453, MCF-7, MDA-MB-231 and MDA-MB-435, displays different phenotypic characteristics ranging from poorly to highly tumorigenic and metastatic. The differences in gene expression profiles of these cell lines generated by differential display technique should allow one to identify candidates as putative oncogenes or tumor/metastasis suppressor genes. A novel cDNA expressed in the highly tumorigenic and metastatic cell line, MDA-MB-435, was identified and isolated by this approach. The function for this gene, designated ALP56 (aspartic-like protease 56 kDa), in tumor progression is suggested by the homology of the encoded protein to aspartic proteases, such as cathepsin D. The amino acid residues in two catalytic domains of this family are highly conserved in those domains of ALP56. Northern hybridization indicated that the expression of ALP56 is associated with growth and metastasis of MDA-MB-435 tumors in immunodeficient mice. In situ hybridization of biopsies from breast cancer and colon cancer patients indicated that ALP56 is upregulated in human primary tumors and liver metastasis. These results suggest that this novel gene correlates with human tumor progression.     

Profiling and integrated analysis of differentially expressed circRNAs as novel biomarkers for breast cancer

Breast cancer (BC) is a globally common cancer with the highest and increasing morbidity and mortality among females. Novel biomarkers are warranted to be discovered for the early detection, treatment, and prognosis of BC. In this study, we investigated the profiles of differentially expressed (DE) circular RNAs (circRNAs) by competing endogenous RNAs (ceRNA) microarray to construct a genome-wide circRNA profile. Then, we performed Gene Ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis of the host genes (HGs) of circRNAs. A total of 4,370 DE circRNAs were detected and GO and KEGG analysis showed that they were significantly associated with cell cycle, DNA replication, BC, and familial BC. We validated the differential circRNAs and relevant HGs through quantitative real-time polymerase chain reaction and constructed a putative circRNA–microRNA–messenger RNA regulatory network. Eight circRNAs, including hsa_circ_0069094, hsa_circ_0062558, hsa_circ_0074026, hsa_circ_0079876, hsa_circ_0017536, hsa_circ_0023302, hsa_circ_0017650, and hsa_circ_0017545, were validated significantly DE in BC tissue and associated with TNM staging, lymph node infiltration, and Ki67. Hsa_circ_0069094, hsa_circ_0079876, hsa_circ_0017650, and hsa_circ_0017526 were upregulated in plasma. This study revealed the general expression characteristics of specific DE circRNAs in BC and hsa_circ_0069094, hsa_circ_0079876, hsa_circ_0017650, and hsa_circ_0017526 might be promising candidate targets.     

A novel serine protease highly expressed in the pancreas is expressed in various kinds of cancer cells

We have isolated a cDNA that encodes a novel serine protease, prosemin, from human brain. The cDNA of human prosemin is 1306 bp, encoding 317 amino acids. It showed significant homology with the sequence of a chromosome 16 cosmid clone (accession no. NT_037887.4). The prosemin gene contains six exons and five introns. The amino acid sequence of prosemin shows significant homology to prostasin, gamma-tryptase, and testisin (43%, 41%, and 38% identity, respectively), the genes of which are also located on chromosome 16. Northern hybridization showed that prosemin is expressed predominantly in the pancreas and weakly in the prostate and cerebellum. However, western blot and RT-PCR analyses showed that prosemin is expressed and secreted from various kinds of cancer cells, such as glioma, pancreas, prostate, and ovarian cell lines. Prosemin is secreted in the cystic fluid of clinical ovarian cancers. Furthermore, immunohistochemistry showed prosemin protein localized in the apical parts of ovarian carcinomas. Recombinant prosemin was expressed in COS cells and was purified by immunoaffinity chromatography. Recombinant prosemin preferentially cleaved benzyloxycarbonyl (Z)-His-Glu-Lys-methylcoumaryl amidide (MCA) and t-butyloxycarbonyl (Boc)-Gln-Ala-Arg-MCA. Our results suggest that prosemin is a novel serine protease of the chromosome 16 cluster that is highly expressed in the pancreas. The usefulness of this serine protease as a candidate tumor marker should be further examined.     

miRNA normalization enables joint analysis of several datasets to increase sensitivity and to reveal novel miRNAs differentially expressed in breast cancer

Different miRNA profiling protocols and technologies introduce differences in the resulting quantitative expression profiles. These include differences in the presence (and measurability) of certain miRNAs. We present and examine a method based on quantile normalization, Adjusted Quantile Normalization (AQuN), to combine miRNA expression data from multiple studies in breast cancer into a single joint dataset for integrative analysis. By pooling multiple datasets, we obtain increased statistical power, surfacing patterns that do not emerge as statistically significant when separately analyzing these datasets. To merge several datasets, as we do here, one needs to overcome both technical and batch differences between these datasets. We compare several approaches for merging and jointly analyzing miRNA datasets. We investigate the statistical confidence for known results and highlight potential new findings that resulted from the joint analysis using AQuN. In particular, we detect several miRNAs to be differentially expressed in estrogen receptor (ER) positive versus ER negative samples. In addition, we identify new potential biomarkers and therapeutic targets for both clinical groups. As a specific example, using the AQuN-derived dataset we detect hsa-miR-193b-5p to have a statistically significant over-expression in the ER positive group, a phenomenon that was not previously reported. Furthermore, as demonstrated by functional assays in breast cancer cell lines, overexpression of hsa-miR-193b-5p in breast cancer cell lines resulted in decreased cell viability in addition to inducing apoptosis. Together, these observations suggest a novel functional role for this miRNA in breast cancer. Packages implementing AQuN are provided for Python and Matlab: https://github.com/YakhiniGroup/PyAQN.     

Identification of differentially expressed genes from ovarian cancer cells by MICROMAX cDNA microarray system

Using the MICROMAX cDNA microarray system, we were able to identify genes that are differentially overexpressed in ovarian cancer. A total of 30 putative genes, which are differentially overexpressed in ovarian cancer cell lines, were identified. The differential expression of some of these genes was further confirmed by real-time RT-PCR. Using this strategy, we have identified genes that either overexpress in all cancer cell lines or in only some cancer cell lines. Further characterization of these genes will allow them to be exploited in diagnosis, prognosis, anticancer therapy, and molecular classification of ovarian cancer.     

P190-B, a Rho-GTPase-activating protein, is differentially expressed in terminal end buds and breast cancer.

Microdissection and differential display PCR were used to identify genes preferentially expressed in the highly proliferative terminal end buds (TEBs) in the mammary gland of 45-day-old virgin rats. One clone exhibited 87% homology to the human p190-B gene encoding a novel Rho-Gap. Using in situ hybridization, p190-B was detected in both the TEBs and the terminal ducts, with the highest expression observed in the outer layer of TEBs. During normal mammary gland development, p190-B mRNA expression was highest in the virgin mammary gland and decreased during late pregnancy and lactation. Interestingly, increased levels of p190-B mRNA relative to the normal mammary gland were seen in a subset of murine mammary tumors that appeared to be less well differentiated and potentially more aggressive. Transient transfection of a p190-B expression construct into MCF-10A human mammary epithelial cells resulted in disruption of the actin cytoskeleton, which suggests a role for p190-B in regulating the signaling pathways that influence cell migration and invasion. These results suggest that p190-B may be required for virgin mammary gland development, and its aberrant expression may occur in breast cancer.     

Identification of differentially expressed genes associated with HER-2/neu overexpression in human breast cancer cells.

Amplification and resulting overexpression of the HER-2/ neu proto-oncogene is found in approximately 30% of human breast and 20% of human ovarian cancers. To better understand the molecular events associated with overexpression of this gene in human breast cancer cells, differential hybridization was used to identify genes whose expression levels are altered in cells overexpressing this receptor. Of 16 000 clones screened from an overexpression cell cDNA library, a total of 19 non-redundant clones were isolated including seven whose expression decreases (C clones) and 12 which increase (H clones) in association with HER-2/ neu overexpression. Of these, five C clones and 11 H clones have been confirmed to be differentially expressed by northern blot analysis. This group includes nine genes of known function, three previously sequenced genes of relatively uncharacterized function and four novel genes without a match in GenBank. Examination of the previously characterized genes indicates that they represent sequences known to be frequently associated with the malignant phenotype, suggesting that the subtraction cloning strategy used identified appropriate target genes. In addition, differential expression of 12 of 16 (75%) cDNAs identified in the breast cancer cell lines are also seen in HER-2/ neu -overexpressing ovarian cancer cells, indicating that they represent generic associations with HER-2/ neu overexpression. Finally, up-regulation of two of the identified cDNAs, one novel and one identified but as yet uncharacterized gene, was confirmed in human breast cancer specimens in association with HER-2/ neu overexpression. Further characterization of these genes may yield insight into the fundamental biology and pathogenetic effects of HER-2/ neu overexpression in human breast and ovarian cancer cells.     

A categorical network approach for discovering differentially expressed regulations in cancer

Background

The problem of efficient utilization of genome-wide expression profiles for identification and prediction of complex disease conditions is both important and challenging. Polygenic pathologies such as most types of cancer involve disregulation of many interacting genes which has prompted search for suitable statistical models for their representation. By accounting for changes in gene regulations between comparable conditions, graphical statistical models are expected to improve prediction precision.

Methods

In comparison problems with two or more experimental conditions, we represent the classes by categorical Bayesian networks that share one and the same graph structure but have class-specific probability parameters. The graph structure is learned by a score-based procedure that maximizes the difference between class probabilities using a suitable measure of divergence. The proposed framework includes an indirect model selection by adhering to a principle of optimal class separation and identifies interactions presenting significant difference between the compared conditions.

Results

We evaluate the performance of the new model against some benchmark algorithms such as support vector machine, penalized linear regression and linear Gaussian networks. The classifiers are compared by prediction accuracy across 15 different data sets from breast, lung, gastric and renal cancer studies. In addition to the demonstrated strong performance against the competitors, the proposed method is able to identify disease specific changes in gene regulations which are inaccessible by other approaches. The latter is illustrated by analyzing some gene interactions differentiating adenocarcinoma and squamous cell lung cancers.

     

Spotlight on differentially expressed genes in urinary bladder cancer

Introduction

We previously identified common differentially expressed (DE) genes in bladder cancer (BC). In the present study we analyzed in depth, the expression of several groups of these DE genes.

Materials and Methods

Samples from 30 human BCs and their adjacent normal tissues were analyzed by whole genome cDNA microarrays, qRT-PCR and Western blotting. Our attention was focused on cell-cycle control and DNA damage repair genes, genes related to apoptosis, signal transduction, angiogenesis, as well as cellular proliferation, invasion and metastasis. Four publicly available GEO Datasets were further analyzed, and the expression data of the genes of interest (GOIs) were compared to those of the present study. The relationship among the GOI was also investigated. GO and KEGG molecular pathway analysis was performed to identify possible enrichment of genes with specific biological themes.

Results

Unsupervised cluster analysis of DNA microarray data revealed a clear distinction in BC vs. control samples and low vs. high grade tumors. Genes with at least 2-fold differential expression in BC vs. controls, as well as in non-muscle invasive vs. muscle invasive tumors and in low vs. high grade tumors, were identified and ranked. Specific attention was paid to the changes in osteopontin (OPN, SPP1) expression, due to its multiple biological functions. Similarly, genes exhibiting equal or low expression in BC vs. the controls were scored. Significant pair-wise correlations in gene expression were scored. GO analysis revealed the multi-facet character of the GOIs, since they participate in a variety of mechanisms, including cell proliferation, cell death, metabolism, cell shape, and cytoskeletal re-organization. KEGG analysis revealed that the most significant pathway was that of Bladder Cancer (p = 1.5×10⁻³¹).

Conclusions

The present work adds to the current knowledge on molecular signature identification of BC. Such works should progress in order to gain more insight into disease molecular mechanisms.     

A Passiflora homolog of a D-type cyclin gene is differentially expressed in response to sucrose, auxin, and cytokinin

In higher plants, one of the major components of developmental processes is cell division. The cell division cycle in plants is controlled by cyclins and cyclin-dependend kinases. Nutrient and hormonal signals can influence the roles that D-type cyclins play in the G1-to-S phase transition. Auxins and cytokinins are long known to be important plant hormones controlling plant growth. Additionally, as sucrose is the major transported carbon source in higher plants, it is possible that it plays a major role in cell division. To access the molecular aspects of the effect of auxin, cytokinin and sucrose on the regulation of cell cycle machinery and plant development, we cloned a Passiflora morifolia putative homolog to a D-type cyclin, PmCYCD1, which showed high sequence similarity to other known plant D-type cyclins. We examined the expression patterns of PmCYCD1 during callus induction and growth in in vitro conditions. We observed incremented expression levels of PmCYCD1 correlated to increasing concentrations of sucrose, α-naphthalene acetic acid and 6-benzyladenine in the culture medium. Additionally, the results of in situ hybridization experiments indicated a dynamic spatial expression pattern for PmCYCD1 during callus growth.     

DEPD: a novel database for differentially expressed proteins

SUMMARY: The Differentially Expressed Protein Database was designed to store the output of comparative proteomics studies and provides a publicly available query and analysis platform for data mining. The database contains information about more than 3000 differentially expressed proteins (DEPs) manually extracted from the published literature, including relevant biological, experimental and methodological elements. Tools for visualization and functional analysis of DEPs are provided via a user-friendly webinterface. AVAILABILITY: http://protchem.hunnu.edu.cn/depd/.