Gene network analyses point to the importance of human tissue kallikreins in melanoma progression
1 Hospital A.C. Camargo, São Paulo, Brazil
2 Ludwig Institute for Cancer Research, São Paulo, Brazil
3 Instituto de Matemática e Estatística, Universidade de São Paulo, Brazil
4 Instituto de Ciências Biomédicas, Universidade de São Paulo, Brazil
5 Instituto de Química, Universidade de São Paulo, Brazil
6 Centro de Ciências e Tecnologia da Universidade Estadual da Paraíba, Paraíba, Brazil
7 Hospital Sírio-Libanês, São Paulo, Brazil
BMC Medical Genomics 2011, 4:76 doi:10.1186/1755-8794-4-76Published: 27 October 2011
A wide variety of high-throughput microarray platforms have been used to identify molecular targets associated with biological and clinical tumor phenotypes by comparing samples representing distinct pathological states.
The gene expression profiles of human cutaneous melanomas were determined by cDNA microarray analysis. Next, a robust analysis to determine functional classifications and make predictions based on data-oriented hypotheses was performed. Relevant networks that may be implicated in melanoma progression were also considered.
In this study we aimed to analyze coordinated gene expression changes to find molecular pathways involved in melanoma progression. To achieve this goal, ontologically-linked modules with coordinated expression changes in melanoma samples were identified. With this approach, we detected several gene networks related to different modules that were induced or repressed during melanoma progression. Among them we observed high coordinated expression levels of genes involved in a) cell communication (KRT4, VWF and COMP); b) epidermal development (KLK7, LAMA3 and EVPL); and c) functionally related to kallikreins (EVPL, KLK6, KLK7, KLK8, SERPINB13, SERPING1 and SLPI). Our data also indicated that hKLK7 protein expression was significantly associated with good prognosis and survival.
Our findings, derived from a different type of analysis of microarray data, highlight the importance of analyzing coordinated gene expression to find molecular pathways involved in melanoma progression.