Factors associated with HPV16 status and survival among patients with squamous cell carcinoma of the oropharynx

Background: Squamous cell carcinoma of the oropharynx (SCCOP) is characterized by local tumor aggressiveness, high recurrence rates, a high incidence of second primary tumors, and medical comorbidities. Significant trends in demographic and clinical characteristics as well as survival among SCCOP patients have been observed over time, likely owing to the changing etiology of the disease. Human papillomavirus type 16 (HPV16) infection is associated with a significant proportion of these cancers. Biomarkers that may aid in identifying patients that are at higher risk of recurrence and death are important so that these patients may be followed more closely to improve their quality of life. ^ Study population and methods: The retrospective review (Specific Aim 2) included 3891 newly diagnosed, previously untreated patients presenting to our institution between 1955 and 2004. A total of 2299 patients treated at our institution were included in survival and recursive partitioning analysis. The prospective cohort study (Specific Aim 3) included 266 patients presenting to our institution between January 2006 and September 2009. ^ Results: The results from the retrospective review showed that over time, patients presented at younger ages and were more likely to have base of tongue/tonsil tumors and to be never/former smokers and moreover survival improved significantly over time. In survival and recursive partitioning analyses, the TNM staging system was efficient in prognosticating patients prior to 1995. However, in the recent decade, the TNM staging system was completely inadequate. The factors having the greatest positive effect on overall survival since 1995 were those common to HPV-associated SCCOP. The results from the prospective cohort study indicate that patients with high nodal stage and those with late stage disease have increased levels of pretreatment serum HPV DNA. ^ Conclusions: We saw a distinct improvement in survival among SCCOP patients over the past 50 years at our institution. The main factors contributing to this were changes in clinical characteristics, in particular surrogates for HPV status. The current TNM staging system for SCCOP is inadequate and incorporation of HPV status (and perhaps smoking status) is encouraged. Furthermore, although pretreatment circulating levels of HPV DNA was associated with higher N category and overall disease stage, it has limited utility as a marker for recurrence among SCCOP patients.^

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^