The development and progression of Colorectal Cancer (CRC) is a multi-step process leading to the accumulation of chromosomal instability (CIN) that occurs over the lifetime of a tumor (Shen et al, 2007; Vogelstein et al, 1988; Fearon et al, 1990). CINs include DNA copy number alterations (CNAs), i.e., regions of aberrantly increased or decreased DNA. For this reason, it is a challenge to identify both the regions that have CNAs and the genes whose expression could be deregulated because of gain or loss of their copies. In this paper we focus on the role of copy number alteration in assessing prognosis of patients with CRC. Specifically, we show that the inference of the CRC progression benefits from exploiting CNA information when a particular relational representation of patients is given. The employed framework outperforms standard approaches where patients are represented through a set of available attributes. The data set for this analysis was provided by IRCCS Istituto Nazionale dei Tumori Milano (INT) and deposited at NCBI Gene Expression Omnibus (GSE16125).
Cava, C., Zoppis, I., Gariboldi, M., Reid, J., Antoniotti, M., Mauri, G. (2012). Chromosome instability for tumor progression inference. EMBNET JOURNAL, 18(B), 97-99 [10.14806/ej.18.B.564].
Chromosome instability for tumor progression inference
CAVA, CLAUDIA;ZOPPIS, ITALO FRANCESCO;ANTONIOTTI, MARCO;MAURI, GIANCARLO
2012
Abstract
The development and progression of Colorectal Cancer (CRC) is a multi-step process leading to the accumulation of chromosomal instability (CIN) that occurs over the lifetime of a tumor (Shen et al, 2007; Vogelstein et al, 1988; Fearon et al, 1990). CINs include DNA copy number alterations (CNAs), i.e., regions of aberrantly increased or decreased DNA. For this reason, it is a challenge to identify both the regions that have CNAs and the genes whose expression could be deregulated because of gain or loss of their copies. In this paper we focus on the role of copy number alteration in assessing prognosis of patients with CRC. Specifically, we show that the inference of the CRC progression benefits from exploiting CNA information when a particular relational representation of patients is given. The employed framework outperforms standard approaches where patients are represented through a set of available attributes. The data set for this analysis was provided by IRCCS Istituto Nazionale dei Tumori Milano (INT) and deposited at NCBI Gene Expression Omnibus (GSE16125).File | Dimensione | Formato | |
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