Molecular and genetic targets in early detection

Evaluating biomarkers for prognostic enrichment of clinical trials

BACKGROUND/AIMS

A potential use of biomarkers is to assist in prognostic enrichment of clinical trials, where only patients at relatively higher risk for an outcome of interest are eligible for the trial. We investigated methods for evaluating biomarkers for prognostic enrichment.

METHODS

We identified five key considerations when considering a biomarker and a screening threshold for prognostic enrichment: (1) clinical trial sample size, (2) calendar time to enroll the trial, (3) total patient screening costs and the total per-patient trial costs, (4) generalizability of trial results, and (5) ethical evaluation of trial eligibility criteria. Items (1)-(3) are amenable to quantitative analysis. We developed the Biomarker Prognostic Enrichment Tool for evaluating biomarkers for prognostic enrichment at varying levels of screening stringency.

RESULTS

We demonstrate that both modestly prognostic and strongly prognostic biomarkers can improve trial metrics using Biomarker Prognostic Enrichment Tool. Biomarker Prognostic Enrichment Tool is available as a webtool at http://prognosticenrichment.com and as a package for the R statistical computing platform.

CONCLUSION

In some clinical settings, even biomarkers with modest prognostic performance can be useful for prognostic enrichment. In addition to the quantitative analysis provided by Biomarker Prognostic Enrichment Tool, investigators must consider the generalizability of trial results and evaluate the ethics of trial eligibility criteria.

Biomarkers and the genetics of early neoplastic lesions

It has become increasingly evident that the study of DNA is inadequate to explain many, if not most, aspects of the development and progression of neoplastic lesions from pre-invasive lesions to metastasis. Thus, the term "genetic" can no longer refer to just the study of the genome. Much of the action in genetic research now shifts to the methods by which the pre-mRNA from one gene is processed to yield multiple different proteins, different quantities of the same protein as well as other forms of regulating RNA. Thus, the age of post-transcriptional processing and epigenetic control of the transfer of information from the genome has arrived. The mechanisms of post-transcriptional processing and epigenetic control that must be characterized in greater detail including alternate splicing, regulation of mRNA degradation, RNA regulatory factors including those factors which extensively edit mRNAs, control of translation, and control of protein stability and degradation. This chapter reviews many of the processes that control information from the genome to proteins and how these factors lead from less than 40,000 genes to more than an order of magnitude increase more proteins which actually control the phenotypes of cells - normal or neoplastic. It is usually the products of genes (e.g., mRNA, microRNA and proteins) that are the molecular markers that will control translational research and ultimately, individualized (personal) medical approaches to disease. This chapter emphasizes how the process of neoplasia "hijacks" the normal processes of cellular operations, especially those processes that are important in the normal development of the organisms - including proliferation, cellular death, angiogenesis, cellular mobility and invasion, and immunoregulation to ensure neoplastic development, survival and progression. This chapter reviews the wide range of processes controlling the information that flows from the genome to proteins and emphasizes how molecular steps in pure processes can be used as biomarkers to study prevention, treatment and/or management of diseases.

Salivary proteomics for oral cancer biomarker discovery

PURPOSE

This study aims to explore the presence of informative protein biomarkers in the human saliva proteome and to evaluate their potential for detection of oral squamous cell carcinoma (OSCC).

EXPERIMENTAL DESIGN

Whole saliva samples were collected from patients (n = 64) with OSCC and matched healthy subjects (n = 64). The proteins in pooled whole saliva samples of patients with OSCC (n = 16) and matched healthy subjects (n = 16) were profiled using shotgun proteomics based on C4 reversed-phase liquid chromatography for prefractionation, capillary reversed-phase liquid chromatography with quadruple time-of-flight mass spectrometry, and Mascot sequence database searching. Immunoassays were used for validation of the candidate biomarkers on a new group of OSCC (n = 48) and matched healthy subjects (n = 48). Receiver operating characteristic analysis was exploited to evaluate the diagnostic value of discovered candidate biomarkers for OSCC.

RESULTS

Subtractive proteomics revealed several salivary proteins at differential levels between the OSCC patients and matched control subjects. Five candidate biomarkers were successfully validated using immunoassays on an independent set of OSCC patients and matched healthy subjects. The combination of these candidate biomarkers yielded a receiver operating characteristic value of 93%, sensitivity of 90%, and specificity of 83% in detecting OSCC.

CONCLUSION

Patient-based saliva proteomics is a promising approach to searching for OSCC biomarkers. The discovery of these new targets may lead to a simple clinical tool for the noninvasive diagnosis of oral cancer. Long-term longitudinal studies with large populations of individuals with oral cancer and those who are at high risk of developing oral cancer are needed to validate these potential biomarkers.

The role of osteopontin in tumor progression and metastasis in breast cancer

The use of cancer biomarkers to anticipate the outlines of disease has been an emerging issue, especially as cancer treatment has made such positive steps in the last few years. Progress in the development of consistent malignancy markers is imminent because advances in genomics and bioinformatics have allowed the examination of immense amounts of data. Osteopontin is a phosphorylated glycoprotein secreted by activated macrophages, leukocytes, and activated T lymphocytes, and is present in extracellular fluids, at sites of inflammation, and in the extracellular matrix of mineralized tissues. Several physiologic roles have been attributed to osteopontin, i.e., in inflammation and immune function, in mineralized tissues, in vascular tissue, and in kidney. Osteopontin interacts with a variety of cell surface receptors, including several integrins and CD44. Binding of osteopontin to these cell surface receptors stimulates cell adhesion, migration, and specific signaling functions. Overexpression of osteopontin has been found in a variety of cancers, including breast cancer, lung cancer, colorectal cancer, stomach cancer, ovarian cancer, and melanoma. Moreover, osteopontin is present in elevated levels in the blood and plasma of some patients with metastatic cancers. Therefore, suppression of the action of osteopontin may confer significant therapeutic activity, and several strategies for bringing about this suppression have been identified. This review looks at the recent advances in understanding the possible mechanisms by which osteopontin may contribute functionally to malignancy, particularly in breast cancer. Furthermore, the measurement of osteopontin in the blood or tumors of patients with cancer, as a way of providing valuable prognostic information, will be discussed based on emerging clinical data.

Disease mechanism and biomarkers of oral squamous cell carcinoma

PURPOSE OF REVIEW

This review focuses on oral cancer disease mechanisms and discusses ongoing research to identify molecular signatures or biomarkers for oral cancer. Other areas covered include the analysis, validation, and predictive value of these markers.

RECENT FINDINGS

During the past years, progress has been made in the oral cancer genetic markers field, which includes alterations of the p53 tumor suppressor protein, the inactivation of cyclin dependant kinase inhibitors (e.g. p16) and the overexpression of the epidermal growth factor receptor. Many of these markers are thought to have potential clinical interest, yet few of them are being used in a clinical setting for oral cancer management. The particular modifications that characterize each step of oral cancer progression can now be profiled by several high throughput discovery techniques. Genomic and proteomic studies of oral cancer tissues, plasma, and saliva of oral cancer patients, have allowed the identification of several promising cancer signatures.

SUMMARY

Important progress has been made in the molecular understanding of oral cancer and its application for diagnosis, prognosis and treatment. The increased efforts in translational research will result in earlier diagnosis of oral cancer, better knowledge of prognostic factors, and the development of targeted treatment regimens based on patients' clinical and biological characteristics at presentation.

Combining several screening tests: optimality of the risk score

The development of biomarkers for cancer screening is an active area of research. While several biomarkers exist, none is sufficiently sensitive and specific on its own for population screening. It is likely that successful screening programs will require combinations of multiple markers. We consider how to combine multiple disease markers for optimal performance of a screening program. We show that the risk score, defined as the probability of disease given data on multiple markers, is the optimal function in the sense that the receiver operating characteristic (ROC) curve is maximized at every point. Arguments draw on the Neyman-Pearson lemma. This contrasts with the corresponding optimality result of classic decision theory, which is set in a Bayesian framework and is based on minimizing an expected loss function associated with decision errors. Ours is an optimality result defined from a strictly frequentist point of view and does not rely on the notion of associating costs with misclassifications. The implication for data analysis is that binary regression methods can be used to yield appropriate relative weightings of different biomarkers, at least in large samples. We propose some modifications to standard binary regression methods for application to the disease screening problem. A flexible biologically motivated simulation model for cancer biomarkers is presented and we evaluate our methods by application to it. An application to real data concerning two ovarian cancer biomarkers is also presented. Our results are equally relevant to the more general medical diagnostic testing problem, where results of multiple tests or predictors are combined to yield a composite diagnostic test. Moreover, our methods justify the development of clinical prediction scores based on binary regression.

Applications of advances in molecular biology and genomics to clinical cancer care

Genetics technologies, methods, and discoveries are being integrated rapidly into medical and nursing practices in a variety of ways. The purpose of this article is to familiarize nurses with how new genetic technologies and discoveries are being incorporated into various phases of clinical oncology practice. The scope of this article is broad to provide an overview of the of ways in which cancer prevention, surveillance, diagnosis, prognosis, monitoring, treatment, and gene therapy are evolving due to advances in the molecular biology of cancer. We use specific examples to demonstrate the use of genetic information to achieve these objectives and to illustrate principles and strategies that may be applied to a variety of cancers.

Capillary and Microchip Electrophoresis for Rapid Detection of Known Mutations by Combining Allele-specific DNA Amplification with Heteroduplex Analysis

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Effective capillary electrophoresis-based heteroduplex analysis through optimization of surface coating and polymer networks

The efficacy of capillary electrophoresis for detecting DNA mutations via heteroduplex analysis (HDA) is dependent upon both the effective passivition of the capillary surface and the choice of the correct polymer network for sieving. Using HDA with laser-induced fluorescence detection of fluorescently labeled DNA fragments, an effective coating and optimal polymer matrix were sought. Optimized separation conditions were determined through the methodological evaluation of a number of different silanizing reagents, polymeric coatings, and polymer networks for resolving the PCR-amplified DNA fragments associated with five mutations (185delAG, 1294del40, 4446C > G, 5382insC, 5677insA) in the breast cancer susceptibility gene (BRCA1). For capillary coating, allyldimethylchlorosilane, 4-chlorobutyldimethylchlorosilane, (gamma-methacryloxypropyl)trimethoxysilane, chlorodimethyloctylsilane (OCT), and 7-octenyltrimethoxysilane were evaluated as silanizing reagents in combination with poly(vinylprrolidone) (PVP) and polyacrylamide (PA) as the polymeric coat. The HDA results were compared with those obtained using a commercial (FC) coated capillary. Of these, the OCT-PVP combination was found to be most effective. Using this modified capillary, HDA with polymer networks that included hydroxyethylcellulose (HEC), linear polyacrylamide, and PVP showed that a PVP-, PA-, or FC-coated capillary, in combination with HEC as the sieving polymer, could be used effectively to discriminate the mutations in less than 10 min. However, optimal performance was observed with the OCT-PVP-coated capillary and HEC as the polymer network.