Aneuploid IMR90 cells induced by depletion of pRB, DNMT1 and MAD2 show a common gene expression signature.

Chromosome segregation defects lead to aneuploidy which is a major feature of solid tumors. How diploid cells face chromosome mis-segregation and how aneuploidy is tolerated in tumor cells are not completely defined yet. Thus, an important goal of cancer genetics is to identify gene networks that underlie aneuploidy and are involved in its tolerance. To this aim, we induced aneuploidy in IMR90 human primary cells by depleting pRB, DNMT1 and MAD2 and analyzed their gene expression profiles by microarray analysis. Bioinformatic analysis revealed a common gene expression profile of IMR90 cells that became aneuploid. Gene Set Enrichment Analysis (GSEA) also revealed gene-sets/pathways that are shared by aneuploid IMR90 cells that may be exploited for novel therapeutic approaches in cancer. Furthermore, Protein-Protein Interaction (PPI) network analysis identified TOP2A and KIF4A as hub genes that may be important for aneuploidy establishment

RIP-Chip analysis supports different roles for AGO2 and GW182 proteins in recruiting and processing microRNA targets

MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. To discern further RISC functions, we analyzed the activities of two RISC proteins, AGO2 and GW182, in the MCF-7 human breast cancer cell lin

Relazione tra l’espressione del repressore trascrizionale MBP-1 e di miRNAs nel carcinoma mammario

MBP-1 (Myc-promoter-binding-protein-1) è una proteina di 37 kDa, prodotta dalla traduzione alternativa del mRNA del gene ENO1, codificante per l’enzima glicolitico α-enolasi. MBP-1 svolge il ruolo di repressore trascrizionale agendo direttamente sul promotore di c-MYC, ERBB2 e COX2, tutti geni coinvolti in diverse fasi della progressione tumorale (1-3). Nei carcinomi duttali infiltranti della mammella (IDC), l’espressione di MBP-1 è inversamente correlata alla comparsa di metastasi linfonodali e di recidive (4). In diverse linee cellulari tumorali l’overespressione di MBP-1 risulta nella riduzione della proliferazione cellulare e dell’invasività e in un aumento nella morte cellulare per apoptosi. Recentemente è stato osservato che, in cellule di carcinoma prostatico, MBP-1 attiva la trascrizione del miR-29b che, a sua volta, regola negativamente l’espressione di proteine anti-apoptotiche e pro-metastatiche, coinvolte nella progressione tumorale (5). Per approfondire le relazioni funzionali tra MBP-1, miR-29b ed eventuali altri miRNAs, l’espressione della proteina MBP-1 e di miRNAs è stata analizzata in una linea cellulare di carcinoma mammario ed in tumori primari mammari (IDC) tramite qRT-PCR, western blot ed analisi microarray. Differenze nei livelli relativi d’espressione di MBP-1 e miR-29b sono state rilevate sia nelle cellule che nei tumori. L’analisi tramite microarray ha permesso di identificare altri 52 miRNAs differenzialmente espressi in un modello cellulare che permette l’overespressione di MBP-1. Dall’analisi bioinformatica dei dati ottenuti emerge che i geni target di alcuni dei miRNA identificati sono espressi differenzialmente in tumori positivi e negativi per MBP-1, e che questi geni agiscono a livello di rilevanti network regolativi, che riguardano l’adesione e la regolazione della migrazione cellulare. I dati ottenuti permettono di ipotizzare che MBP-1 intervenga nella regolazione della proliferazione e della progressione tumorale agendo direttamente sull’espressione dei geni coinvolti in questi processi o indirettamente mediante la regolazione dell’espressione di microRNA. Bibliografia: 1. Ray R, Miller DM: Cloning and characterization of a human c-myc promoter-binding protein. Mol Cell Biol 1991, 11(4):2154-2161 2. Contino F, Mazzarella C, Ferro A, Lo Presti M, Roz E, Lupo C, Perconti G, Giallongo A, Feo S: Negative transcriptional control of ERBB2 gene by MBP-1 and HDAC1: diagnostic implications in breast cancer. BMC cancer 2013, 13:81. 3. Hsu KW, Hsieh RH, Wu CW, Chi CW, Lee YH, Kuo ML, Wu KJ, Yeh TS: MBP-1 suppresses growth and metastasis of gastric cancer cells through COX-2. Mol Biol Cell 2009, 20(24):5127-5137 4. Lo Presti M, Ferro A, Contino F, Mazzarella C, Sbacchi S, Roz E, Lupo C, Perconti G, Giallongo A, Migliorini P et al: Myc promoter-binding protein-1 (MBP-1) is a novel potential prognostic marker in invasive ductal breast carcinoma. PLoS One 2010, 5(9):e12961 5. Steele R, Mott JL, Ray RB: MBP-1 upregulates miR-29b that represses Mcl-1, collagens, and matrix-metalloproteinase-2 in prostate cancer cells. Genes & cancer 2010, 1(4):381-38

A multiomics analysis of S100 protein family in breast cancer

The S100 gene family is the largest subfamily of calcium binding proteins of EFhand type, expressed in tissue and cell-specific manner, acting both as intracellular regulators and extracellular mediators. There is a growing interest in the S100 proteins and their relationships with different cancers because of their involvement in a variety of biological events closely related to tumorigenesis and cancer progression. However, the collective role and the possible coordination of this group of proteins, as well as the functional implications of their expression in breast cancer (BC) is still poorly known. We previously reported a large-scale proteomic investigation performed on BC patients for the screening of multiple forms of S100 proteins. Present study was aimed to assess the functional correlation between protein and gene expression patterns and the prognostic values of the S100 family members in BC. By using data mining, we showed that S100 members were collectively deregulated in BC, and their elevated expression levels were correlated with shorter survival and more aggressive phenotypes of BC (basal like, HER2 enriched, ER-negative and high grading). Moreover a multi-omics functional network analysis highlighted the regulatory effects of S100 members on several cellular pathways associated with cancer and cancer progression, expecially immune response and inflammation. Interestingly, for the first time, a pathway analysis was successfully applied on different omics data (transcriptomics and proteomics) revealing a good convergence between pathways affected by S100 in BC. Our data confirm S100 members as a promising panel of biomarkers for BC prognosis

Dal trascrittoma all’interattoma di miRNA: identificazione sperimentale e bioinformatica delle interazioni funzionali miRNA:mRNA

I miRNA, piccole molecole endogene di RNA non codificante, regolano l’espressione genica attraverso la degradazione dei messaggeri (mRNA) o l’inibizione della traduzione. I miRNA maturi interagiscono con le proteine del complesso RISC (RNA-induced silencing complex) tra cui le proteine Argonaute (Ago), capaci di legare direttamente i miRNA e di mediare la regolazione dell’espressione genica in seguito alla interazione del miRNA con il proprio mRNA target. Un singolo miRNA può legare diversi mRNA e ciascun mRNA può essere regolato da diversi miRNA. La maggior parte dei software di predizione oggi disponibili individuano i putativi target di singoli miRNA ignorando caratteristiche di tipo globale, come i livelli di espressione di mRNA e miRNA coespressi. Obiettivo del nostro lavoro è sviluppare un sistema per lo studio e la predizione delle interazioni funzionali miRNA:mRNA che tenga conto di tutti i miRNA e degli mRNA coespressi in una cellula in determinate condizioni. Allo scopo di misurare e mettere in relazione i livelli di espressione di mRNA e miRNA, abbiamo messo a punto una immunoprecipitazione ad alta efficienza del complesso RISC-Ago2 da estratti citoplasmatici della linea cellulare di tumore mammario MCF-7. I profili di espressione di mRNA e miRNA dei campioni ottenuti sono stati ricavati mediante microarray. Tale tecnica ci ha consentito di caratterizzare separatamente l’insieme di mRNA e miRNA legati e non legati ai complessi RISC. E’ stata inoltre utilizzata la centrifugazione su gradiente di densità per separare gli mRNA in fase di traduzione da quelli non tradotti e i miRNA associati a ciascuna di queste frazioni. Anche questi campioni saranno analizzati mediante microarray. L’analisi dei dati ottenuti ci consentirà di individuare tra tutti i miRNA ed gli mRNA espressi nella cellula quelli coinvolti nel processo di regolazione ed identificare le interazioni miRNA:mRNA che inducono un blocco della traduzione o la degradazione del messaggero target. Utilizzando i dati ottenuti ci proponiamo di mettere a punto un modello matematico per predire l’insieme delle interazioni funzionali tra i miRNA e i relativi target in qualsiasi condizione cellulare in cui siano noti i profili di espressione dei miRNA e degli mRNA

Identification of a prognostic gene signature associated with MBP-1 expression in ErbB2-negative breast carcinomas

The ENO1 transcript, which encodes the glycolitic enzyme alpha-enolase, can be translated into a shorter nuclear protein called Myc-promoter Binding Protein-1 (MBP-1) by using an alternative translation start site. MBP-1 acts as a negative regulator of c-Myc, ErbB2 and Cox2 genes (1). Several evidences indicate that MBP-1 acts as a tumor suppressor in breast carcinoma and prostate cancer and its expression results in a reduced invasive ability (2). In our previous studies, we showed that MBP-1 is expressed and easily detectable in normal breast epithelial cells, but a loss of expression occurs in most primary invasive ductal carcinomas (IDC) of the breast. Furthermore, in these tumors MBP-1 expression inversely correlated with the expression levels of the ErbB2 and Ki67 proteins (3). In order to better understand the role of MBP-1 in breast cancer and to correlate its expression to a gene signature with prognostic value, we evaluated the expression of approximately 21,000 genes in primary breast carcinoma by using the Agilent microarray technology. A comparison of the gene expression profiles obtained from MBP-1+ve and MBP-1-ve ErbB2-negative IDCs led to the identification of differentially expressed (DE) genes that may underlie the different clinical behaviors of these two subtypes of breast carcinoma. Owing to the prognostic influence of nuclear MBP-1 expression in a subgroup of tumors from patients with node-negative and ErbB2-negative carcinomas, the combination of immunohistochemical analyses of MBP-1 and proteins encoded by genes we found DE by expression profiling, may prove to be a clinically valuable prognostic variable for breast cancer patients

RIP-Chip analysis supports different roles for AGO2 and GW182 proteins in recruiting and processing microRNA targets

Abstract Background MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. To discern further RISC functions, we analyzed the activities of two RISC proteins, AGO2 and GW182, in the MCF-7 human breast cancer cell line. Methods We performed three RIP-Chip experiments using either anti-AGO2 or anti-GW182 antibodies and compiled a data set made up of the miRNA and mRNA expression profiles of three samples for each experiment. Specifically, we analyzed the input sample, the immunoprecipitated fraction and the unbound sample resulting from the RIP experiment. We used the expression profile of the input sample to compute several variables, using formulae capable of integrating the information on miRNA binding sites, both in the 3’UTR and coding regions, with miRNA and mRNA expression level profiles. We compared immunoprecipitated vs unbound samples to determine the enriched or underrepresented genes in the immunoprecipitated fractions, independently for AGO2 and GW182 related samples. Results For each of the two proteins, we trained and tested several support vector machine algorithms capable of distinguishing the enriched from the underrepresented genes that were experimentally detected. The most efficient algorithm for distinguishing the enriched genes in AGO2 immunoprecipitated samples was trained by using variables involving the number of binding sites in both the 3’UTR and coding region, integrated with the miRNA expression profile, as expected for miRNA targets. On the other hand, we found that the best variable for distinguishing the enriched genes in the GW182 immunoprecipitated samples was the length of the coding region. Conclusions Due to the major role of GW182 in GW/P-bodies, our data suggests that the AGO2-GW182 RISC recruits genes based on miRNA binding sites in the 3’UTR and coding region, but only the longer mRNAs probably remain sequestered in GW/P-bodies, functioning as a repository for translationally silenced RNAs