Hormone-dependent cancers: new approaches to identification of potential diagnostic and/or therapeutic biomarkers

• Published in: Asia-Pacific journal of molecular biology and biotechnology Vol. 18; no. 1; pp. 63 - 66
• Main Authors: Herington, A C, Chopin, L K, Jeffery, P, de Amorim, L, Veveris-Lowe, T, Bui, L, Clements, JA
• Format: Journal Article
• Language: English
• Published: 01-01-2010
• Subjects: Bioinformatics; biomarkers; Cancer; Clinical trials; DNA microarrays; Drug development; genomics; ghrelin; Growth factors; kallikrein; Mass spectroscopy; Metastases; Prostate; Prostate cancer; proteomics; Serine proteinase; Toxicity testing; Translation
• ISSN: 0128-7451

Hormone-dependent cancers of the prostate and breast are the most common cancers in men and women, respectively, in the Western world and are major causes of illness and death. Current diagnostic/prognostic tests are invasive or lack specificity and "certainty" with respect to detecting these cancers early and in differentiating between different phenotypes. More specific diagnostic/prognostic markers are needed to better define treatment options for individuals. Classical approaches have focussed on candidate genes/proteins that are involved in tumour cell growth, invasion and metastasis. Using genomic, proteomic, molecular and cell biology approaches in vitro, we have identified additional proteins - the ghrelin growth factor axis and variants within the kallikrein family of serine proteases - that may serve as potential candidate markers and therapeutic targets. However, with recent advances in high through-put technologies (gene tissue microarrays, 2D gel and mass spectrometry proteome analyses, bioinformatics) relevant genes/proteins can now be more efficiently screened, identified and validated. These technologies can readily be coupled with proof-of-principle experiments - in vitro and in vivo assays using gain and loss of function models, targeted drug design and pharmacological/toxicological studies and subsequent clinical trials - to develop a fully integrated, translational research model which has the capacity to deliver clinical outcomes more rapidly.