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Pizzini, Silvia/P.S. (2012) A bioinformatic approach to the study of gene, microRNA expression and alternative splicing regulation in colorectal cancer progression and liver metastasis. [Ph.D. thesis]

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Abstract (english)

Expression profiles are increasingly used in cancer research, and a growing number of microarray data is available in public databases such as Gene Expression Omnibus (GEO) and ArrayExpress. Therefore, it is possible to compare studies with similar research aims through a meta-analysis approach. Colorectal cancer (CRC) is a very common disease and represents a fundamental biological model of tumorigenesis. Many experiments comparing the expression profiles of normal colonic mucosa and colorectal cancer (CRC) samples have been conducted and results are available. Using A-MADMAN, a web application that allows the retrieval, annotation, organization and analysis of public available gene expression datasets, we downloaded from the GEO and collected the largest-collected normal colon, adenoma and primary colorectal tumor, with and without metastasis, gene expression dataset which includes 1,795 experiments pertaining to 27 distinct series, obtained from two different generations of Affymetrix, HG-U133A and HG-U133 plus2.0. After we performed the quality control of the downloaded data and have designed three different workflows for signal reconstruction, we conducted preliminary analysis of differential expression. In this first project we focused on right and left colon differences. In particularly, we analyzed normal, adenoma and tumor expression profiles focusing on changes among topologically different samples, under the hypothesis that the use of site-specific normal tissue as reference for the study of right and left tumor samples may facilitate to shed light on specific cell functions, pathways and regulatory circuits altered in each tumor type, and help deepening our understanding of this complex disease. From preliminary data, we concluded that the workflow based on the virtual chips production and on a chip-specific background correction is the most robust. Higher numbers of differentially expressed genes were identified when comparing, respectively, tumor and adenoma versus normal tissue (647 and 683 genes). These tissue samples were then pairwise compared by topology to identify those genes that are differentially expressed, when the matched by topology set of normal samples is considered. We found 72 genes colon left-specific and 1183 colon-right specific in the comparison from adenoma with normal tissues, and 46 genes and 69 genes, respectively, in colon left- and colon right- specific in the comparison from CRC and adenoma tissues. We focused also to the functional information associated to gene expression differences between tumor and normal tissue samples, compared considering only right or left samples, to identify specific functions and pathways involved with cancer present, such as DNA repair, adhesion and cell interaction.
In the second project we reconstructed regulatory networks of colon cancer by integrating gene expression, alternative splicing and microRNA (miRNAs) expression data. We carried out a genome-wide integrative analysis of miRNA and genes and exon expression profiles in tissues of 55 colon cancer patients, comprehensive of normal colon mucosa, primary tumor and liver metastasis. GeneChip Human Exon 1.0 ST (Affymetrix) and Affymetrix GeneChip miRNA arrays have been used to obtain high quality gene, exon and miRNA expression quantification respectively. We analyzed both differential gene expression and alternative splicing applying AltAnalyze software to exon-level analysis, identifying 33,740 genes involved in alternative splicing events. We considered a custom set of expression signals of 449,810 probesets, using MIDAS and FIRMA statistics, and we combined the results with MMBGX software output, to identify a more restricted, but perhaps more robust set of candidate alternative splicing events, possibly relevant for colon cancer biology. When comparing liver metastasis with normal colon tissue whereas 182 genes were identified; comparable numbers of genes were identified when comparing metastasis versus colorectal tumor and colorectal tumor versus normal tissue (51 and 10 respectively). We validated two genes with alternative splicing events, VCL and CALD1.
We then identified respectively 62, 63 and 11 differentially expressed miRNAs in tumors and metastases compared to normal tissue, and comparing metastasis with primary tumors. To assess the reproducibility and robustness of the miRNA signature identified, we measured by qRT-PCR the expression of 5 miRNA in all samples (hsa miR-150, hsa miR-10b, has miR-146a, miR-210 and has miR-122). For each considered contrast, KEGG pathways enriched in genes resulting supported target of differentially expressed miRNAs were identified. The integrated analysis of miRNA and genes expression profiles with target predictions was performed with the purpose of reconstruct post-transcriptional regulatory networks governing tumor and metastases development. Considering expression profiles in the same set of samples of 305 miRNAs and 12,748 genes with variable expression profile, we reconstructed post-transcriptional regulatory networks involving modulated miRNAs. In particular, considering the network associated to the tumor versus normal contrast, we experimentally validated miR-145 – c-Myc and miR-182 – ENTPD5 relationships. This latter is new and may have a relevant pathogenetic role. Looking at our results, we can say that the regulatory signatures that affect tumor progression are complex and difficult to interpret. They involve interactions involving different modulated miRNAs that control the expression of multiple genes belonging to the same pathway in different ways, and alternative transcripts of genes that are differentially expressed in normal tissues, tumors and metastases.

Abstract (italian)

Nella ricerca oncologica sono sempre più utilizzati i profili di espressione genica e un numero crescente di dati di microarray è disponibile in database pubblici come NCBI GEO e ArrayExpress. Diventa quindi possibile il confronto di studi con obiettivi di ricerca simili attraverso approcci di “meta-analisi”. Il cancro colorettale (CRC) rappresenta un fondamentale modello biologico di tumorigenesi, oltre ad essere una patologia molto diffusa.
Sono a disposizione nei database pubblici molti esperimenti sul CRC, che confrontano mucosa normale con mucosa tumorale del colon attraverso metodologia microarray. Noi abbiamo utilizzato A-MADMAN, un’applicazione web open source di supporto per la meta-analisi di dati grezzi d’espressione genica ottenuti con microarray, per scaricare dal database dell’NCBI Gene Expression Omnibus (GEO), 27 collezioni di esperimenti per un totale di 1045 campioni ottenuti da mucosa normale, adenoma e CRC con e senza metastasi di colon-retto su cui erano state eseguite analisi di espressione genica con tecnologia gene chip Affymetrix. Dopo aver effettuato un controllo di qualità dei dati scaricati e aver disegnato 3 diversi flussi di lavoro per la ricostruzione del segnale d’espressione, sono state condotte delle analisi preliminari di espressione differenziale. In questo primo progetto ci siamo focalizzati sulle differenze molecolari sito–specifiche. Abbiamo quindi analizzato campioni di mucosa sana, di adenoma e di CRC suddivisi per localizzazione in colon destro e colon sinistro. Prendendo come riferimento il tessuto normale destro e sinistro, abbiamo ipotizzato che è possibile discriminare pattern di espressione genica tumorale sede specifica. Dal disegno dei tre flussi di lavoro abbiamo dedotto che il flusso di lavoro basato sulla generazione di chip virtuali e su una correzione del background chip-specifica è il più affidabile. Abbiamo identificato 647 geni differenzialmente espressi confrontando tessuto tumorale con tessuto normale e 683 geni nel confronto adenoma con tessuto normale, poi abbiamo individuato 72 geni nel confronto adenoma-tessuto normale specifici del colon sinistro e 1183 geni nello stesso confronto, colon destro specifici, mentre per quanto riguarda il confronto CRC e adenoma, 46 geni sono colon sinistro specifici e 69 sono colon destro specifici. Abbiamo inoltre trovato termini funzionali e pathway diversi sovra-rappresentati in colon destro rispetto a colon sinistro e rispetto ai corrispondenti normali.
Nel secondo progetto, abbiamo ricostruito una rete regolatoria riguardante il CRC e la metastasi epatica da CRC integrando dati di originali di espressione genica, di splicing alternativo e di espressione di microRNA (miRNA). Lo studio si basa sulla raccolta di biopsie di tumore primario al colon, mucosa adiacente normale e metastasi al fegato di 55 pazienti, che sono state analizzate utilizzando piattaforme Affymetrix per l'analisi di espressione genica/esonica (GeneChip Human Exon 1,0 ST), e di microRNA (GeneChip® miRNA Array ). Analizzando l’ espressione differenziale a livello genico ed esonico mediante il software AltAnalyze identificando 33.740 geni coinvolti in probabili eventi di splicing alternativo. Integrando i dati risultati dalle statistiche di questo programma con i risultati ottenuti con un software basato su un approccio Bayesiano, MMBGX, abbiamo identificato una lista più ristretta ma anche più robusta di candidati eventi di splicing possibilmente rilevanti per la formazione e la progressione del CRC. Confrontando metastasi epatiche con tessuto normale del colon sono stati identificati 182 geni, mentre un numero inferiore di geni sono stati identificati nel confronto contro le metastasi del tumore colorettale e del tumore del colon-retto rispetto al tessuto normale (51 e 10 rispettivamente). A partire da questi risultati, abbiamo scoperto il coinvolgimento di trascritti alternativi di due geni, VCL e CALD1, nella progressione tumorale.
In parallelo, sono stati identificati microRNA modulati in seguito allo sviluppo del tumore e della metastasi, trovandone rispettivamente 62, 63 e 11 differenzialmente espressi nel tumore rispetto al normale, nella metastasi rispetto al normale e nella metastasi rispetto al tumore. Abbiamo quindi confermato la robustezza dei risultati validando cinque miRNA presenti nella lista dei differenzialmente espressi (hsa miR-150, hsa miR-10b, has miR-146a, miR-210 and has miR-122) mediante RT-PCR. Per ogni contrasto considerato, sono stati identificati i KEGG pathway modulate e quindi sotto putativamente controllate dai miRNA. Grazie all’analisi integrata di profili di espressione di miRNA e dei loro geni target anti-correlati, sono state definite le principali reti di regolazione post-trascrizionale coinvolte nella cancerogenesi. Particolarmente rilevante è la rete che coinvolge il sottoinsieme dei miRNA differenzialmente espressi nel tumore rispetto al normale. Tra le interazioni inferite, abbiamo convalidato sperimentalmente le relazioni miR-145 - c-Myc e miR-182 - ENTPD5. Quest’ultima rappresenta una relazione nuova, il cui ruolo patogenetico può essere rilevante.
Dai nostri risultati possiamo concludere che le vie di regolazione che interessano la progressione tumorale sono complesse e difficili da interpretare, che implicano interazioni che coinvolgono miRNA diversamente modulati che agiscono in diversi modi sull’espressione di più geni appartenenti ad una stessa pathway e da trascritti alternativi di geni che vengono espressi in modo differenziale nei tessuti sani, nei tumori e nelle metastasi.

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EPrint type:Ph.D. thesis
Tutor:Zanovello, Paola
Supervisor:Bortoluzzi, Stefania and Bisognin, Andrea
Ph.D. course:Ciclo 24 > Scuole 24 > ONCOLOGIA E ONCOLOGIA CHIRURGICA
Data di deposito della tesi:26 January 2012
Anno di Pubblicazione:26 January 2012
Key Words:cancro colorettale, microarray, geni, trascritti alternativi, microRNA, meta-analisi / colorectal cancer, microarray, genes, alternative transcripts, microRNA, meta-analysis
Settori scientifico-disciplinari MIUR:Area 06 - Scienze mediche > MED/06 Oncologia medica
Struttura di riferimento:Dipartimenti > pre 2012 - Dipartimento di Scienze Oncologiche e Chirurgiche
Codice ID:4524
Depositato il:20 Dec 2012 14:16
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