Cancer Biomarkers - Volume 2, issue 3-4

Authors: Feng, Ziding

Article Type: Editorial

DOI: 10.3233/CBM-2006-23-401

Citation: Cancer Biomarkers, vol. 2, no. 3-4, pp. 87-88, 2006

Authors: Simon, Richard

Article Type: Research Article

Abstract: Physicians need improved tools for selecting treatments for individual patients. Many syndromes traditionally viewed as individual diseases are heterogeneous in molecular pathogenesis and treatment responsiveness. This results in treatment of many patients with ineffective drugs and leads to the conduct of large clinical trials to identify small average treatment benefits for heterogeneous groups of patients. New genomic and proteomic technologies provide powerful tools for the selection of patients likely to benefit from a therapeutic without unacceptable adverse events. In spite of the large literature on developing predictive biomarkers and on statistical methodology for analysis of high dimensional data, there is …considerable uncertainty about the validation of biomarker based diagnostic classifiers for treatment selection. In this paper we attempt to clarify these issues and to provide guidance on the design of clinical trials for evaluating the clinical utility and robustness of pharmacogenomic classifiers. Show more

Keywords: Pharmacogenomics, biomarker, genomics, DNA microarray, clinical trial design, validation

DOI: 10.3233/CBM-2006-23-402

Citation: Cancer Biomarkers, vol. 2, no. 3-4, pp. 89-96, 2006

Authors: Huang, Xuelin | Biswas, Swati | Estey, Elihu H. | Berry, Donald A.

Article Type: Research Article

Abstract: An important aspect of modern cancer research is identifying molecular and genetic markers that predict an individual's risk of recurrence and response to treatment. Increasingly, a large number of biomarkers are included in studies, even though at most a small proportion of them will be prognostic. This article considers the selection and validation of prognostic biomarkers, and proposes a method for building and validating a prognostic index based on potentially many markers. We use simulation to show that our proposed method controls false-positive rate while retaining reasonable power. The prognostic index gets its power from combining prognostic biomarkers. It can …be very powerful even when there are few markers that are predictive. Show more

Keywords: Biomarkers, data splitting, false-positive rate, prognostic power, prognostic index

DOI: 10.3233/CBM-2006-23-403

Citation: Cancer Biomarkers, vol. 2, no. 3-4, pp. 97-101, 2006

Authors: He, Yudong D.

Article Type: Research Article

Abstract: This paper discusses selected activities, issues, and challenges in recent development of analytical methods and applications in biomarker identification and validation using state-of-the-art genomic approaches. Molecular profiling via genomics, proteomics, and metabonomics has opened new windows to study disease states and biological systems. It has also provided exciting opportunities for novel applications in clinical research as well as in drug discovery and development. In the past several years, we have witnessed enormous progress resulting particularly from gene expression profiling of mRNA or transcriptomics. After a brief review on technology advances in gene expression profiling using microarrays, I mainly discuss recent …developments of the genomic approaches to biomarker identification and validation in two major types of applications. The first type involves examples in cancer diagnostics and prognostics based on tumor gene expression profiling, whereas the second type involves biomarker applications in drug discovery and development. The focus will be on analytical methods and algorithms that have been developed in recent years facilitating biomarker discovery and application by leveraging genome-wide expression profiles derived from microarrays. Technical issues in experimental design, data processing, error modeling, quality control, figures of merit for performance evaluation, and meta-analysis related to biomarker discovery and application are also discussed. A case study of disease outcome prognosis for breast cancer patients based on tumor expression pattern is presented before closing remarks. Show more

Keywords: Biomarker, genomics, expression profile, microarray, oncology, drug discovery

DOI: 10.3233/CBM-2006-23-404

Citation: Cancer Biomarkers, vol. 2, no. 3-4, pp. 103-133, 2006

Authors: Randolph, Timothy W.

Article Type: Research Article

Abstract: Classification of data that arise as signals or images often requires a standardization step so that information extracted from biologically equivalent signals can be quantified for comparison across classes. Differences in global trend, total energy, high-frequency noise and/or local background can arise from variabilities due to instrumentation or conditions during data collection. This article considers some common ways in which such variation is adjusted for and introduces a generalization of the popular “standard normal variate” transformation. Based on a wavelet decomposition this generalization provides increased flexibility for normalizing spectral data affected by local background noise. Examples from three types of …spectroscopy data illustrate the method and its properties. Show more

Keywords: Normalization, spectroscopy, preprocessing, standard normal variate, wavelet

DOI: 10.3233/CBM-2006-23-405

Citation: Cancer Biomarkers, vol. 2, no. 3-4, pp. 135-144, 2006

Authors: Saunders, Ian W.

Article Type: Research Article

Abstract: The statistical properties required for effective biomarkers for disease are examined. It is shown that an “effectiveness parameter” D can be calculated that summarises the performance of a given biomarker and can distinguish between effective and ineffective biomarkers. D can be readily calculated from published summaries of biomarker levels and provides a simpler alternative to the commonly used “Area under the Curve” statistic. The impact of within-individual and between-individual variation in biomarker levels is also evaluated. An approach to the choice of sample size for experiments to estimate D is described.

Keywords: Biomarker effectiveness, sensitivity, specificity

DOI: 10.3233/CBM-2006-23-406

Citation: Cancer Biomarkers, vol. 2, no. 3-4, pp. 145-150, 2006

Authors: Sato, Alicia H. | Anderson, Garnet L. | Urban, Nicole | McIntosh, Martin W.

Article Type: Research Article

Abstract: It may be possible to reduce cancer mortality by monitoring the concentrations of serum biomarkers over time in men and women to detect their cancer early, when it is most curable. The simplest approach to using a biomarker for screening is to sequentially use fixed thresholds as a means to determine an abnormal test (e.g., PSA exceeding 4 mg/ml, CA 125 exceeding 30 U/ml). Alternatives to the simplest single threshold (ST) rules include more sophisticated algorithms that make use of screening history that accumulates over time and determines abnormal tests using individualized reference ranges. Although in principle longitudinal algorithms should …out perform fixed threshold rules, the actual benefit gained will depend on behavior of the biomarker, the screening algorithm, and the screening frequency. Little information has been available to help predict when conditions should compel the adoption of the more sophisticated algorithms and when conditions suggest the simpler algorithms should suffice, or indeed be preferred. In this manuscript we evaluate the conditions under which one should expect great benefit, and when one should not expect benefit, by comparing the ability of simple and complex algorithms to detect cancer early under a variety of biomarker behaviors and screening frequencies. Show more

Keywords: CA 125, SMR, HE4, screening

DOI: 10.3233/CBM-2006-23-407

Citation: Cancer Biomarkers, vol. 2, no. 3-4, pp. 151-162, 2006

Authors: Cobb, Michael J. | Chen, Yuchuan | Bailey, S. Lawrence | Kemp, Christopher J. | Li, Xingde

Article Type: Research Article

Abstract: Background and Objective: Improved diagnostics capable of non-invasive detection of early stage carcinogenesis would benefit basic research, and potentially aid in clinical cancer diagnosis and management. The two-stage carcinogenesis protocol is widely used for studying the multi-stage nature of tumor development in mice and provides insight into tumor development in other animal models and humans. The objective of this study was to investigate the feasibility of non-invasive optical coherence tomography (OCT) for in vivo imaging of microanatomical changes in the epidermis and dermis during early carcinogenesis using a mouse skin model. Materials and Methods: 10 NIH mice were …treated with DMBA and TPA following the well-established two-stage carcinogenesis protocol. OCT imaging of treated skin from live mice was performed at five time points (Week 4–8) after tumor initiation to reveal the structural changes in the epidermis and dermis associated with the earliest, premalignant stages of tumor development. OCT images were compared with histology findings. In addition, OCT signals were quantitatively analyzed to evaluate tissue optical property changes during early carcinogenesis. Results: Early structural changes in the epidermis, dermis and hair follicles during carcinogenesis were clearly delineated in vivo using OCT. OCT images correlated well with histological findings. Quantitative OCT signal analysis revealed a statistically significant change in the extinction coefficient for untreated (40.5 ± 17.0 mm-1 ) and treated (9.6 ± 3.6 mm-1 ) mouse epidermis (P<0.005). The dermis extinction coefficient for the treated mouse skin (3.7 ± 0.9 mm-1 ) was lower than the untreated one (4.7 ± 1.6 mm-1 ), but was not statistically significant (P>0.10). Furthermore, the papilloma extinction coefficient (2.9 ± 0.3 mm-1 ) was significantly lower than the extinction coefficient for the treated epidermis (P<0.005) and dermis (P<0.01). Conclusion: OCT is a viable tool for assessing the earliest stages of carcinogenesis and has potential for early detection of neoplasia in skin, as well as in epithelial linings of other organs. Show more

DOI: 10.3233/CBM-2006-23-408

Citation: Cancer Biomarkers, vol. 2, no. 3-4, pp. 163-173, 2006