With apologies for the jargon, we have coined the term “integromics” for the assembly of information from multiple types of molecular profiling data. The underlying hypothesis is that different types of molecular information can combine “synergistically” for identification of new cancer drugs and biomarkers. One example is our research [1] using the panel of 60 human cancer cell lines (NCI-60) used by the U.S. NCI to screen >100,000 compounds for anticancer activity. We and our collaborators have profiled those cells extensively at the DNA, RNA, protein, chromosomal, functional, and pharmacological levels using >20 microarray platforms overall. The enterprise can be thought of as a forerunner of The Cancer Genome Atlas project - on cultured cells, rather than clinical tumors, but with a wider variety of profiling platforms. I will discuss five biomedical proof-of-principle cases for the integromic approach. To aid in integrating the different types of molecular information, we have developed the Miner Suite of publicly available, widely used, web-based bioinformatic tools and molecular profile databases. The most recent tool is an engine for dealing with splice variation [5]. The Miner Suite complements the very impressive KEGG pathway databases and bioinformatic tools. In 2006, we and our collaborators launched the “Spotlight on Molecular Profiling” series [2-4] in Molecular Cancer Therapeutics to make the profile data widely available for an integrative, systems-oriented approach to drug and biomarker discovery as part of the drive toward “personalized medicine” [6,7]. http://discover.nci.nih.gov.