Metabolic regulation can play key role in normal and pathological states. In particular in cancer cells, alterations in metabolic pathways can drive the growth and survival of cancer cells. Among these alterations, many occur at the transcriptional level leading to the overexpression of metabolic genes. However, not every metabolically upregulated genes may be necessary for tumor growth. Therefore, functional validation approaches are required to distinguish metabolically overexpressed genes that are necessary for tumor growth versus the ones that are not. One of the experimental approaches to do this is to use the approach of RNA interference to systematically survey the transcriptionally upregulated metabolic genes for their requirement in tumor growth. Here, we describe an integrative genomics approach to identify metabolic genes that are necessary for tumor growth. The approach we describe is a general integrative genomics approach that combines bioinformatics-based identification of overexpressed metabolic genes in cancer patient samples and then uses RNAi-based knockdown approach to identify genes that are necessary for tumor growth.