Abstract
Cancer is not a single disease but an accumulation of several events, genetic and epigenetic, arising in a single cell over a long time interval. A high priority in the cancer field is to identify these events. This can be achieved by characterizing cancer-associated genes and their protein products. Identifying the molecular alterations that distinguish any particular cancer cell from a normal cell will ultimately help to define the nature and predict the pathologic behavior of that cancer cell. It will also indicate the responsiveness to treatment of that particular tumor. Understanding the profile of molecular changes in any particular cancer will be extremely useful as it will become possible to correlate the resulting phenotype of that cancer with molecular events. Achieving these goals and knowledge will provide an opportunity for discovering new biomarkers for early cancer detection and developing prevention approaches. This will also help us identify new targets for therapeutic development. Advancement in technology includes methods and tools that enable research including, but not limited to, instrumentation, techniques, devices, and analysis tools (e.g., computer software). Resources such as databases, reagents, and tissue repositories are different than technologies. The identification and definition of the molecular profiles of cancer will require the development and dissemination of high-throughput molecular analysis technologies, as well as elucidation of all of the molecular species embedded in the genome of cancer and normal cells. The main challenge in cancer control and prevention is to detect the cancer early. This could then enable effective interventions and therapies contributing to reduction in mortality and morbidity. At a specific time, biomarkers serve as molecular signposts of the physiologic state of a cell. These signposts are the result of genes, their products (proteins) and other organic chemicals made by the cell. Biomarkers could prove to be vital for the identification of early cancer and subjects at risk of developing cancer as a normal cell progresses through the complex process of transformation to a cancerous state. This chapter discusses ongoing research in genetic and proteomic approaches to identify molecular signatures such as protein profiles, microsatellite instability, hypermethylation, and single nucleotide polymorphisms. Other topics covered here include the use of genomics and proteomics as high-throughput technology platforms to facilitate biomarker-aided detection of early cancer. Other areas covered include issues surrounding the analysis, validation, and predictive value of biomarkers using such technologies. Recent advances in noninvasive techniques, such as buccal cell isolates serving as viable sources of biomarkers, complementary to traditional sources such as serum or plasma, are also presented. The review also brings attention to the efforts of the Early Detection Research Network (EDRN) at the National Cancer Institute (NCI), in bringing together scientific expertise from leading national and international institutions, to identify and validate biomarkers for the detection of precancerous and cancerous cells in determining risk for developing cancer. The network’s serious determined efforts in linking discovery to process development, resulting in early detection tests and clinical assessment, are also discussed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ando S, Kimura H, Iwai M, et al (2001) Optimal combination of seven tumor markers in prediction of advanced stage at first examination of patients with nonsmall cell lung cancer. Anticancer Res 21:3085–3092
Banks RE, Dunn MJ, Forbes MA, et al (1999) The potential use of laser capture microdissection to selectively obtain distinct populations of cells for proteomic analysis-preliminary findings. Electrophoresis 20:689–700
Dwek MV, Ross HA, Leathem AJ (2001) Proteome and glycosylation mapping identifies posttranslational modifications associated with aggressive breast cancer. Proteomics 6:756–762
Fung ET, Wright GL, Dalmasso EA (2000) Proteomic strategies for biomarker identification: progress and challenges. Curr Opin Mol Ther 2:643–650
Hakomori S (1996) Tumor malignancy defined by aberrant glycosylation and sphingo(glyco) lipid metabolism. Cancer Res 56:5309–5318
Hanash S, Brichory F, Beer D (2001) A proteomic approach to the identification of lung cancer markers. Dis Markers 17:295–300
Hirsch FR, Franklin WA, Gazdar AF, Bunn PA (2001) Early detect ion of lung cancer: clinical perspectives of recent advances in biology and radiology. Clin Cancer Res 7:5–22
Kobata A (1998) A retrospective and prospective view of glycopathology. Glycoconj J 15:323–331
Mattu TS, Royle L, Langridge J, et al (2000) O-glycan analysis of natural human neutrophil gelatinase B using a combination of normal phase-HPLC and online tandem mass spectrometry: implications for the domain organization of the enzyme. Biochemistry 39:15695–15704
Mehta A, Carrouee S, Conyers B, et al (2001) Inhibition of hepatitis B virus DNA replication by imino sugars without the inhibition of the DNA polymerase: therapeutic implications. Hepatology 33:1488–1495
Oh JM, Brichory F, Puravs E, et al (2001) A database of protein expression in lung cancer. Proteomics 1:1303–1319
Petricoin EF, Ardekani AM, Hitt BA, et al (2002) Use of proteomic patterns in serum to identify ovarian cancer. Lancet 359:572–577
Sato F, Harpaz N, Shibata D, et al (2002) Hypermethylation of the p14(ARF) gene in ulcerative colitis-associated colorectal carcinogenesis. Cancer Res 62:1148–1151
Selaru FM, Xu Y, Yin J, et al (2002) Artificial neural networks distinguish among subtypes of neoplastic colorectallesions. Gastroenterology 122:606–613
Steel LF, Mattu TS, Mehta A, et al (2001) A proteomic approach for the discovery of early detection markers of hepatocellular carcinoma. Dis Markers 17:179–189
Verma M, Baraniuk J, Blass C, et al (1999) CFTR antisense phosphorothioate oligodeoxynu cleotides (S-ODNs) induce tracheo-bronchial mucin (TBM) mRNA expression in human airways mucosa. Glycoconj J 16:7–11
Verma M, Davidson EA (1999) MUC1 upregulation by ethanol. Cancer Biochem Biophys 17:1–11
Verma M, Wright G L, Hanash SM, et al (2001) Proteomic approaches within the NCI Early Detection Research Network for the discovery and identification of cancer biomarkers. Ann N YAcad Sci 945:103–115
Virmani AK, Tsou JA, Siegmund KD, et al (2002) Hierarchical clustering of lung cancer cell lines using DN Amethylation markers. Cancer Epidemiol Biomarkers Prev 11:291–297
Wright GL, Cazares LH, Leung SM, et al (1999) ProteinChip surface enhanced laser desorption/ ionization (SELDI) mass spectrometry: A novel protein biochip technology for detection of prostate cancer biomarkers in complex protein mixtures. Prostate Cancer Prostatic Dis 2: 264–276
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Verma, M., Srivastava, S. (2003). New Cancer Biomarkers Deriving from NCI Early Detection Research. In: Senn, HJ., Morant, R. (eds) Tumor Prevention and Genetics. Recent Results in Cancer Research, vol 163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55647-0_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-55647-0_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-62892-4
Online ISBN: 978-3-642-55647-0
eBook Packages: Springer Book Archive