Multi-group diagnostic classification of high-dimensional data using differential scanning calorimetry plasma thermograms.

The thermoanalytical technique differential scanning calorimetry (DSC) has been applied to characterize protein denaturation patterns (thermograms) in blood plasma samples and relate these to a subject's health status. The analysis and classification of thermograms is challenging because of the high-dimensionality of the dataset. There are various methods for group classification using high-dimensional data sets; however, the impact of using high-dimensional data sets for cancer classification has been poorly understood. In the present article, we proposed a statistical approach for data reduction and a parametric method (PM) for modeling of high-dimensional data sets for two- and three- group classification using DSC and demographic data. We compared the PM to the non-parametric classification method K-nearest neighbors (KNN) and the semi-parametric classification method KNN with dynamic time warping (DTW). We evaluated the performance of these methods for multiple two-group classifications: (i) normal versus cervical cancer, (ii) normal versus lung cancer, (iii) normal versus cancer (cervical + lung), (iv) lung cancer versus cervical cancer as well as for three-group classification: normal versus cervical cancer versus lung cancer. In general, performance for two-group classification was high whereas three-group classification was more challenging, with all three methods predicting normal samples more accurately than cancer samples. Moreover, specificity of the PM method was mostly higher or the same as KNN and DTW-KNN with lower sensitivity. The performance of KNN and DTW-KNN decreased with the inclusion of demographic data, whereas similar performance was observed for the PM which could be explained by the fact that the PM uses fewer parameters as compared to KNN and DTW-KNN methods and is thus less susceptible to the risk of overfitting. More importantly the accuracy of the PM can be increased by using a greater number of quantile data points and by the inclusion of additional demographic and clinical data, providing a substantial advantage over KNN and DTW-KNN methods.

Characterization and classification of lupus patients based on plasma thermograms.

OBJECTIVE: Plasma thermograms (thermal stability profiles of blood plasma) are being utilized as a new diagnostic approach for clinical assessment. In this study, we investigated the ability of plasma thermograms to classify systemic lupus erythematosus (SLE) patients versus non SLE controls using a sample of 300 SLE and 300 control subjects from the Lupus Family Registry and Repository. Additionally, we evaluated the heterogeneity of thermograms along age, sex, ethnicity, concurrent health conditions and SLE diagnostic criteria. METHODS: Thermograms were visualized graphically for important differences between covariates and summarized using various measures. A modified linear discriminant analysis was used to segregate SLE versus control subjects on the basis of the thermograms. Classification accuracy was measured based on multiple training/test splits of the data and compared to classification based on SLE serological markers. RESULTS: Median sensitivity, specificity, and overall accuracy based on classification using plasma thermograms was 86%, 83%, and 84% compared to 78%, 95%, and 86% based on a combination of five antibody tests. Combining thermogram and serology information together improved sensitivity from 78% to 86% and overall accuracy from 86% to 89% relative to serology alone. Predictive accuracy of thermograms for distinguishing SLE and osteoarthritis / rheumatoid arthritis patients was comparable. Both gender and anemia significantly interacted with disease status for plasma thermograms (p<0.001), with greater separation between SLE and control thermograms for females relative to males and for patients with anemia relative to patients without anemia. CONCLUSION: Plasma thermograms constitute an additional biomarker which may help improve diagnosis of SLE patients, particularly when coupled with standard diagnostic testing. Differences in thermograms according to patient sex, ethnicity, clinical and environmental factors are important considerations for application of thermograms in a clinical setting.

Clinical application of plasma thermograms. Utility, practical approaches and considerations.

Differential scanning calorimetry (DSC) studies of blood plasma are part of an emerging area of the clinical application of DSC to biofluid analysis. DSC analysis of plasma from healthy individuals and patients with various diseases has revealed changes in the thermal profiles of the major plasma proteins associated with the clinical status of the patient. The sensitivity of DSC to the concentration of proteins, their interactions with other proteins or ligands, or their covalent modification underlies the potential utility of DSC analysis. A growing body of literature has demonstrated the versatility and performance of clinical DSC analysis across a range of biofluids and in a number of disease settings. The principles, practice and challenges of DSC analysis of plasma are described in this article.

Structure and stability of higher-order human telomeric quadruplexes.

G-quadruplex formation in the sequences 5'-(TTAGGG)(n) and 5'(TTAGGG)(n)TT (n = 4, 8, 12) was studied using circular dichroism, sedimentation velocity, differential scanning calorimetry, and molecular dynamics simulations. Sequences containing 8 and 12 repeats formed higher-order structures with two and three contiguous quadruplexes, respectively. Plausible structures for these sequences were determined by molecular dynamics simulations followed by experimental testing of predicted hydrodynamic properties by sedimentation velocity. These structures featured folding of the strand into contiguous quadruplexes with mixed hybrid conformations. Thermodynamic studies showed the strands folded spontaneous to contain the maximum number contiguous quadruplexes. For the sequence 5'(TTAGGG)(12)TT, more than 90% of the strands contained completely folded structures with three quadruplexes. Statistical mechanical-based deconvolution of thermograms for three quadruplex structures showed that each quadruplex melted independently with unique thermodynamic parmameters. Thermodynamic analysis revealed further that quadruplexes in higher-ordered structures were destabilized relative to their monomeric counterparts, with unfavorable coupling free energies. Quadruplex stability thus depends critically on the sequence and structural context.

Sedimentation velocity ultracentrifugation analysis for hydrodynamic characterization of G-quadruplex structures.

Analytical ultracentrifugation (AUC) is a powerful technique for the characterization of hydrodynamic and thermodynamic properties. The intent of this article is to demonstrate the utility of sedimentation velocity (SV) studies to obtain hydrodynamic information for G-quadruplex (GQ) systems and to provide insights into one part of this process, namely, data analysis of existing SV data. An array of data analysis software is available, mostly written and continually developed by established researchers in the AUC field, with particularly rapid advances in the analysis of SV data. Each program has its own learning curve, and this article is intended as a resource in the data analysis process for beginning researchers in the field. We discuss the application of three of the most commonly used data analysis programs, DCDT+, Sedfit, and SedAnal, to the interpretation of SV data obtained in our laboratory on two GQ systems.

Differential scanning calorimetry of blood plasma for clinical diagnosis and monitoring.

Differential scanning calorimetry (DSC) provides a useful method to study the unfractionated plasma proteome. Plasma from healthy individuals yields a reproducible signature thermogram which results from the weighted sum of the thermal denaturation of the most abundant plasma proteins. Further investigation of the thermogram for healthy individuals showed it to be sensitive to ethnicity and gender. DSC analysis of plasma from diseased individuals revealed significant changes in the thermogram which are suggested to result not from changes in the concentration of the major plasma proteins but from interactions of small molecules or peptides with these proteins. Closer examination of the diseased thermograms showed a thermogram characteristic of each disease. For cervical cancer, the DSC method yields a progressively shifted thermogram as the disease advances from pre-invasive conditions to late stage cancer. Our application of the DSC method has provided a potential tool for the early diagnosis, monitoring and screening of cancer patients.

Effect of O6-methylguanine on the stability of G-quadruplex DNA.

The effects of substitution of O6-methylguanine on the structure and stability of a human telomere quadruplex was studied by circular dichroism, thermal denaturation, analytical ultracentrifugation, and molecular dynamics simulations. The results show that, while quadruplex structures can form containing the modified base, they are much less stable than the normal unmodified structure. The extent of destabilization is critically dependent on the exact position of the modified base within the quadruplex structure.