Cancer and Genetics

Advances in next-generation sequencing technology are enabling the systematic analyses of whole cancer genomes, providing insights into the landscape of somatic mutations and the great genetic heterogeneity that defines the unique signature of an individual tumor. Moreover, integrated studies of the genome, epigenome, and transcriptome reveal mechanisms of tumorigenesis at multiple levels. Progress in sequencing technologies and bioinformatics will improve the costs, sensitivity, and accuracy of detecting somatic mutations, while large-scale projects are underway to coordinate cancer genome sequencing at the global level to facilitate the generation and dissemination of high-quality uniform genetic data. These developments will create opportunities for deeper studies of cancer genetics and the clinical application of genome sequencing, and will motivate further research in cancer pathogenesis.

Endometrial cancer (EC) is the most frequent of the invasive tumors of the female genital tract. Although usually detected in its initial stages, a 20% of the patients present with advanced disease. To date, no characterized molecular marker has been validated for the diagnosis of EC. In addition, new methods for prognosis and classification of EC are needed to combat this deadly disease. We thus aimed to identify new molecular markers of EC and to evaluate their validity on endometrial aspirates. Gene expression screening on 52 carcinoma samples and series of real-time quantitative PCR validation on 19 paired carcinomas and normal tissue samples and on 50 carcinoma and noncarcinoma uterine aspirates were performed to identify and validate potential biomarkers of EC. Candidate markers were further confirmed at the protein level by immunohistochemistry and Western blot. We identified ACAA1, AP1M2, CGN, DDR1, EPS8L2, FASTKD1, GMIP, IKBKE, P2RX4, P4HB, PHKG2, PPFIBP2, PPP1R16A, RASSF7,

Inter-individual variation in response to opioids for cancer pain is a well-established phenomenon. Variation occurs in the dose of opioid required, the analgesic efficacy of the opioid and also in the side-effects experienced by the individual taking the drug. To date, no clinical factor has been identified that can reliably explain or predict such variation. In recent years there has been growing interest in the possibility that genetic factors may play a role in the variability in opioid response. The aims of this review are to present the evidence supporting pharmacogenetic research in this area, to evaluate some of the studies and results that have been published to date and to present some of the challenges for future research in this area.