Lack of homogeneity in lineages of tumour cell population, in addition to constant evolution of abnormal cells, results in intratumour heterogeneity. Tumour prognosis, to a great extent, depends on the permutations and combinations in which one or more clonal lineage prevails. This directly affects therapeutic decisions as tumour sensitivity, or resistance to a particular treatment is refl ected in the heterogeneity it presents. In this context, geographic predisposition presents a different dimension which may drive this heterogeneity in a particular direction and is probably the larger set of cause followed by subsets of causes like clonal evolution or cancer stem cells which result in the idiopathic nature of tumour heterogeneity. However, the geographic pervasiveness of cancers has not been studied in depth in context to tumour heterogeneity. The suffi x “-omics” denotes a study in total of that particular stream of science. For example, the study of genome is referred to as genomics. Off late, multi-omics approaches encompassing a systemic understanding of cancer tissues have shed immense light in understanding the molecular basis of tumour heterogeneity with regard to the classical models traditionally proposed to explain the heterogeneity. Genomics, proteomics, metabolomics and transcriptomics have received an enormous boost with emergence and evolution of high- throughput technology like mass spectrometry and next-generation sequencing. This chapter discusses briefl y about the type of tumour heterogeneity noticed especially in context of the developing world and how OMICS-based research can bring about a revolution in understanding any geographic bias that may exist and contribute to tumour heterogeneity. © Springer India 2016.