Research Papers:
Probing the prostate tumour microenvironment I: impact of glucose deprivation on a cell model of prostate cancer progression
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Abstract
Claire Tonry1, John Armstrong2 and Stephen R. Pennington1
1 Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, Co. Dublin
2 St. Luke’s Hospital, Rathgar, Dublin, Co. Dublin
Correspondence to:
Claire Tonry, email:
Keywords: prostate cancer; tumour microenvironment; biomarkers; proteomics; mass spectrometry
Received: June 13, 2016 Accepted: October 19, 2016 Published: January 12, 2017
Abstract
In the developed world, prostate cancer is the most common cancer diagnosis in men. Although prostate cancer initially presents as a non life-threatening disease, 90% of patients will develop castration resistant prostate cancer (CRPC), which preludes distant metastasis and is largely accountable for prostate cancer associated deaths. This is because as yet, there are no viable molecular therapeutic targets for effective treatment of CRPC. It is now widely accepted that cancer cells can alter their metabolic profile during the course of tumourgenesis and metastasis such that they are able to survive in oxygen and nutrient-poor environments. This work was aimed towards gaining greater mechanistic understanding of how such ‘stresses’ in the tumour microenvironment impact on both androgen sensitive (LNCaP) and androgen independent (LNCaP-abl and LNCaP-abl-Hof) prostate cancer cell lines. Here we have applied technically robust and reproducible label-free liquid chromatography mass spectrometry analysis for comprehensive proteomic profiling of prostate cancer cell lines under nutrient deficient (low glucose) conditions. This led to the identification of approximately 4,000 proteins - one of the largest protein datasets for prostate cancer cell lines established to date. The biological and clinical significance of proteins showing a significant change in expression as result of low glucose conditions was established. Novel, intuitive workflows were subsequently implemented to ensure the verification of selected proteins of interest in a robust, reproducible and high throughput manner. Overall, these data suggest that this strategy supports identification of protein biomarkers of prostate cancer progression and potential therapeutic targets for CRPC.
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