Molecular and genetic targets in early detection.
ABSTRACT Recent research has revealed the existence of specific mutations in cancer. These mutations are being investigated as targets to find subjects at high risk for cancer, to detect early cancer, to detect the early recurrence of established cancer, and to find micrometastasis. These mutations are reviewed for the major anatomic sites. Some of the clinical issues related to the application of these mutations and the limitations of using molecular targets are also considered. Current methods for determining the risk of cancer are reviewed. Risk assessment is essential for defining cohorts for chemoprevention and other interventions. The concept of using surrogate anatomic and functional sites for estimating risk is introduced. Finally, the increasing complexity of molecular genetic analysis and the biologic heterogeneity of cancer are discussed in relation to early detection.
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ABSTRACT: In a medical diagnostic testing problem, multiple diagnostic tests are often available in distinguishing between diseased and nondiseased subjects. Different diagnostic tests are usually sensitive to different aspects of the disease. A desirable approach is to combine multiple diagnostic tests so as to obtain an optimal composite diagnostic test with higher sensitivity and specificity that detects the presence of the disease more accurately. To accomplish this, it has been observed via signal detection theory developed in the 1950s and 1960s, that the optimal combination of different diagnostic variables (i.e. the diagnostic test results) is determined by the likelihood ratio function for the diseased and nondiseased groups. The conventional approach is to fit parametric models for the diseased and nondiseased groups separately and then to use the fitted likelihood ratio function for the best combination of test results. However, this approach is not so robust if the underlying distribution functions are misspecified. Since the optimal combination depends only on the likelihood ratio function, it would be more appropriate to model this function directly. A two-sample semiparametric inference technique is applied to the model for the likelihood ratio function. We consider the best combination of multiple diagnostic tests, and study semiparametric likelihood estimation of the optimal receiver operating characteristic curve and the area under the curve. We present a bootstrap procedure along with some results on simulation and on analysis of two real data sets.Statistics in Medicine 12/2010; 29(28):2905-19. · 2.04 Impact Factor
- JNCI Journal of the National Cancer Institute 08/2001; · 14.34 Impact Factor
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ABSTRACT: Detection of mutations by gel electrophoresis and allele-specific amplification by PCR (AS-PCR) is not easily scaled to accommodate a large number of samples. Alternative electrophoretic formats, such as capillary electrophoresis (CE) and microchip electrophoresis, may provide powerful platforms for simple, fast, automated, and high-throughput mutation detection after allele-specific amplification. DNA samples heterozygous for four mutations (185delAG, 5382insC, 3867G-->T, and 6174delT) in BRCA1 and BRCA2, and homozygous for one mutation (5382insC) in BRCA1 and two mutations (16delAA and 822delG) in PTEN were chosen as the model system to evaluate the capillary and microchip electrophoresis methods. To detect each mutation, three primers, of which one was labeled with the fluorescent dye 6-carboxyfluorescein and one was the allele-specific primer (mutation-specific primer), were used to amplify the DNA fragments in the range of 130-320 bp. AS-PCR was combined with heteroduplex (HD) analysis, where the DNA fragments obtained by AS-PCR were analyzed with the conditions developed for CE-based HD analysis (using a fluorocarbon-coated capillary and hydroxyethylcellulose). The CE conditions were transferred into the microchip electrophoresis format. Three genotypes, homozygous wild type, homozygous mutant, and heterozygous mutant, could be identified by CE-based AS-PCR-HD analysis after 10-25 min of analysis time. Using the conditions optimized with CE, we translated the AS-PCR-HD analysis mutation detection method to the microchip electrophoresis format. The detection of three heterozygous mutations (insertion, deletion, and substitution) in BRCA1 could be accomplished in 180 s or less. It is possible to develop a CE-based method that exploits both AS-PCR and HD analysis for detecting specific mutations. Fast separation and the capacity for automated operation create the potential for developing a powerful electrophoresis-based mutation detection system. Fabrication of multichannel microchip platforms may enable mutation detection with high throughput.Clinical Chemistry 02/2001; 47(2):173-85. · 7.15 Impact Factor