“Unmixing” Tissue Gene Expression Signatures from Tumor Biopsies

Emergent molecular measurement methods, such as DNA microarray, qRTPCR, and many others, offer tremendous promise for the personalized treatment of cancer. These technologies measure the amount of specific proteins, RNA, DNA or other molecular targets from tumor specimens with the goal of “fingerprinting” individual cancers. Tumor specimens are heterogeneous; an individual specimen typically contains unknown amounts of multiple tissues types. Thus, the measured molecular concentrations result from an unknown mixture of tissue types, and must be normalized to account for the composition of the mixture. For example, a breast tumor biopsy may contain normal, dysplastic and cancerous epithelial cells, as well as stromal components (fatty and connective tissue) and blood and lymphatic vessels. Our diagnostic interest focuses solely on the dysplastic and cancerous epithelial cells. The remaining tissue components serve to “contaminate” the signal of interest. The proportion of each of the tissue components changes as a function of patient characteristics (e.g., age), and varies spatially across the tumor region. Because each of the tissue components produces a different molecular signature, and the amount of each tissue type is specimen dependent, we must estimate the tissue composition of the specimen, and adjust the molecular signal for this composition. Using the idea of a chemical mass balance, we consider the total measured concentrations to be a weighted sum of the individual tissue signatures, where weights are determined by the relative amounts of the different tissue types. We develop a compositional source apportionment model to estimate the relative amounts of tissue components in a tumor specimen. We then use these estimates to infer the tissuespecific concentrations of key molecular targets for sub-typing individual tumors. We anticipate these specific measurements will greatly improve our ability to discriminate between different classes of tumors, and allow more precise matching of each patient to the appropriate treatment

Glycan alterations of serum proteins as tumour markers. Prostate-specific antigen in prostate cancer and acute-phase proteins in pancreatic cancer

Els pacients amb càncer presenten una taxa de supervivència superior si es diagnostiquen a estadis inicials, per la qual cosa és indispensable disposar de marcadors tumorals adequats. Glicoformes de proteïnes específiques es podrian utilizar com marcadors tumorals. S’han investigat les subformes i glicosilació de l’Antígen Prostàtic Específic (PSA) per millorar la seva capacitat de diagnosis de pacients amb càncer de pròstata vs aquells amb hiperplàsia benigna prostàtica. També s’han avaluat glicoproteïnes sèriques amb alteracions glucídiques en pacients de càncer de pàncrees, comparat amb pacients amb pancreatitis crònica i controls. S’ha observat una disminució de la fucosilació core i sialilació del PSA en càncer de pròstata i un augment de la fucosilació core i Sialyl-Lewis X en algunes Proteïnes de fase Aguda en càncer de pàncrees. Aquest canvis s’haurien d’avaluar en un cohort de pacients més gran per determinar el seu paper en el cribratge, diagnòstic o monitorització dels cancers estudiats.