Molecular profiles of allograft rejection following inhibition of CD40 ligand costimulation differentiated by cluster analysis.

Recent technological advances in biomedical research, such as genome sequences and DNA microarrays, have dramatically increased the size of relevant databases. A major challenge is the extraction of a limited number of parameters from these databases that can differentiate and diagnose complex biological states. In a model of cardiac transplantation investigating immunosuppression by inhibition of CD40 ligand costimulation, we have applied a combination of cluster algorithms and self-organizing maps to analyze a panel of 60 candidate genes. Dendrograms generated by cluster analysis distinguished different molecular bases of rejection. Using self-organizing maps, we identified nine genes (CD4, CCR3, CCR5, LT beta, MIP-1 alpha, MIP-2, CD8 alpha, IP-10, and RANTES), each with a unique profile of transcriptional expression, that reproduce the differentiation of states of rejection in dendrograms. Using histology and immunohistochemistry, we correlated differential regulation of CD4 and CD8 at the levels of mRNA and protein. Our strategy of data reduction successfully decreased the number of genes to nine, which are sufficient to differentiate distinct states of rejection in our experimental protocol.