Molecular analysis: an invaluable approach to improve diagnosis and tailor therapy

Neoplastic transformation can start in nearly every cell type in the human body. It is recognisable as cells acquiring the ability to divide uncontrollably and to escape aging mechanisms and naturally occurring cell death, resulting in the growth of a tumour. Tumours have different features, depending on the organ of origin and the level of differentiation of the tumour cells. At certain points in development, a tumour will be influencing its microenvironment, ensuring, among other things, vascularisation and cooperation with the immune system. A tumour can progress further, evolving into malignant disease, by invading the surrounding tissue, disseminating into the bloodstream or lymphatic channels, and establishing metastases in other parts of the body, often with fatal consequences for the affected individual. The diversity of cancer, in both biological and clinical terms, is well acknowledged and has been extensively studied. Today, with increasingly sophisticated technologies at our disposal, highly detailed molecular features of individual tumours can be described. Such features are often referred to as being layered, occurring at the genomic (DNA), transcriptomic (mRNA) and functional proteomic (protein) levels. Proteins are the key functional elements of cells, resulting from transcription of a gene into mRNA, which is further translated into a protein. This simplistic way of describing the relationship between the layers has gradually changed during the past decades of functional and molecular insight. Protein synthesis is no longer perceived as a linear process, but as an intricate network of a multitude of operational molecules. Astonishing progress has been made in the discovery of molecules that are able to influence transcription and translation, such as DNA-modifying enzymes and non-translated RNAs, and of mechanisms that are able to control the processing, localisation and activation of proteins. A picture is emerging of individual cells within a tumour that can differ at the genomic, epigenomic and transcriptional levels, as well as at the functional level. Mutations and epigenetic alterations create the required phenotypic diversity that, under the influence of shifting selective pressures imposed by the environment, determines the sub-clonal expansion and selection of specific cells. The development of solid tumours thus follows the same basic principles as Darwinian evolution. Most single nucleotide polymorphism (SNP) variants that arise in human evolution are neutral with respect to survival advantage; over a period of time, these variants are typically fixed in or die out from the genome according to chance. Other variants provide a survival advantage and will, over time, dominate the cell population, leading to distinct haploid signatures. Cancer may involve hundreds or thousands of mutations, with each mutation potentially contributing to tumour fitness. Most of these mutations are assumed to be passengers, but a limited number have driver capability, sometimes only in a sub-population of cells. There is an intricate interplay between sub-populations of tumour cells and among tumour and normal cells in the microenvironment, and tumour topology is likely to play a role in this context. Our knowledge of molecular mechanisms in cancer development and progression are mainly derived from model systems such as in vitro cell cultures and animal models, as well as from descriptive molecular analyses of tissue samples. Model systems have been crucial for understanding molecular interactions and their implications in cancer, but they cannot fully mimic tumour conditions in vivo. Tissue samples, on the other hand, contain both a microenvironment and sub-populations of cancer cells, but they represent only a snapshot in an individual tumour’s life history. Until recently, cancer studies mainly considered only one or a few molecular levels at a time. Altered protein expression can have several causes; it can be due to copy number gain, a translocation event that combines the gene with an active promoter, alteration of factors that modify DNA or influence the transcription machinery, or modifications of mRNA or the protein itself. Revealing the various downstream effects of such alterations is potentially useful for tumour classification and for prediction of treatment response and prognosis.