Genomic Profiling of Advanced-Stage Oral Cancers Reveals Chromosome 11q Alterations as Markers of Poor Clinical Outcome

Identifying oral cancer lesions associated with high risk of relapse and predicting clinical outcome remain challenging questions in clinical practice. Genomic alterations may add prognostic information and indicate biological aggressiveness thereby emphasizing the need for genome-wide profiling of oral cancers. High-resolution array comparative genomic hybridization was performed to delineate the genomic alterations in clinically annotated primary gingivo-buccal complex and tongue cancers (n = 60). The specific genomic alterations so identified were evaluated for their potential clinical relevance. Copy-number changes were observed on chromosomal arms with most frequent gains on 3q (60%), 5p (50%), 7p (50%), 8q (73%), 11q13 (47%), 14q11.2 (47%), and 19p13.3 (58%) and losses on 3p14.2 (55%) and 8p (83%). Univariate statistical analysis with correction for multiple testing revealed chromosomal gain of region 11q22.1–q22.2 and losses of 17p13.3 and 11q23–q25 to be associated with loco-regional recurrence (P = 0.004, P = 0.003, and P = 0.0003) and shorter survival (P = 0.009, P = 0.003, and P 0.0001) respectively. The gain of 11q22 and loss of 11q23-q25 were validated by interphase fluorescent in situ hybridization (I-FISH). This study identifies a tractable number of genomic alterations with few underlying genes that may potentially be utilized as biological markers for prognosis and treatment decisions in oral cancers

Recurrence in oral and pharyngeal cancer is associated with quantitative MGMT promoter methylation

<p>Abstract</p> <p>Background</p> <p>Biomarkers that predict clinical response, tumor recurrence or patient survival are severely lacking for most cancers, particularly for oral and pharyngeal cancer. This study examines whether gene-promoter methylation of tumor DNA correlates with survival and recurrence rates in a population of patients with oral or pharyngeal cancer.</p> <p>Methods</p> <p>The promoter methylation status of the DNA repair gene <it>MGMT </it>and the tumor suppressor genes <it>CDKN2A and RASSF1 </it>were evaluated by methylation-specific PCR in 88 primary oral and pharyngeal tumors and correlated with survival and tumor recurrence. Quantitative <it>MGMT </it>methylation was also assessed.</p> <p>Results</p> <p>29.6% of the tumors presented with <it>MGMT </it>methylation, 11.5% with <it>CDKN2A </it>methylation and 12.1% with <it>RASSF1 </it>methylation. <it>MGMT </it>promoter methylation was significantly associated with poorer overall and disease-free survival. No differences in methylation status of <it>MGMT </it>and <it>RASSF1 </it>with HPV infection, smoking or drinking habits were observed. A significant inverse trend with the amount of <it>MGMT </it>methylation and overall and disease-free survival was observed (p_trend= 0.002 and 0.001 respectively).</p> <p>Conclusion</p> <p>These results implicate <it>MGMT </it>promoter methylation as a possible biomarker for oral and pharyngeal cancer prognosis. The critical role of MGMT in DNA repair suggests that defective DNA repair may be correlative in the observed association between <it>MGMT </it>promoter methylation and tumor recurrence. Follow-up studies should include further quantitative MSP-PCR measurement, global methylation profiling and detailed analysis of downstream DNA repair genes regulated by promoter methylation.</p

Acknowledging crossing-avoidance heuristic violations when solving the Euclidean travelling salesperson problem

If a salesperson aims to visit a number of cities only once before returning home, which route should they take to minimise the total distance/cost? This combinatorial optimization problem is called the travelling salesperson problem (TSP) and has a rapid growth in the number of possible solutions as the number of cities increases. Despite its complexity, when cities and routes are represented in 2D Euclidean space (ETSP), humans solve the problem with relative ease, by applying simple visual heuristics. One of the most important heuristics appears to be the avoidance of path crossings, which will always result in more optimal solutions than tours that contain crossings. This study systematically investigates whether the occurrence of crossings is impacted by geometric properties by modelling their relationship using binomial logistic regression as well as random forests. Results show that properties, such as the number of nodes making up the convex hull, the standard deviation of the angles between nodes, the average distance between all nodes in the graph, the total number of nodes in the graph, and the tour cost (i.e., a measure of performance), are significant predictors of whether crossings are likely to occur