Prostate cancer is a highly prevalent disease in older men of the Western world. Multiple complex molecular events characterize prostate cancer initiation, unregulated growth, invasion, and metastasis. Deciphering the molecular networks that distinguish progressive disease from non-progressive disease will shed light into the biology of aggressive prostate cancer as well as lead to the identification of biomarkers that will aid in the selection of patients that should be treated. Gene expression profiling of prostate cancer by microarrays has been done extensively and to a lesser extent and depth, proteomic profiling of prostate tumors using mass spectrometry has also been explored. By contrast, very little has been done in the area of metabolomic profiling of prostate cancer, which may provide additional information content beyond that available from conventional transcriptomics and proteomics. Subtle alterations in mRNA expression or protein function/activity may manifest as an enormous change in the concentration of specific metabolites resulting in a more sensitive detection of the perturbation. Global profiling of the metabolites in prostate cancer will enhance our understanding of the pathway alterations occurring during disease progression and could lead to the development of novel biomarkers and pathways to target. The current proposal around a rich compendium of metabolomic profiles of prostate tissues that would be mined to define class-specific as well as lethal or aggressive metabolomic markers of prostate cancer progression. Thus the overarching goal of this proposal is to define and validate a subset of clinically relevant metabolomic markers of prostate cancer progression and determine their utility in predicting aggressive disease. Given this, the aims are as follows:
Specific Aim 1 : Delineate Potential Metabolomic Markers of Prostate Cancer Progression.
Specific Aim 2 : Establish the Predictive/Causal/Consequential Role for the Lethal Metabolomic Markers of Prostate Cancer Using Preclinical Models of Cancer Invasion.
Specific Aim 3 : Clinical Association of Candidate Metabolomic Biomarkers of Prostate Cancer Progression
Prostate cancer is the second largest cause of cancer-related death in US. The disease is often curable if detected early, while metastatic disease is often fatal. Furthermore, there is an imminent need to define additional biomarkers for prostate cancer detection owing to the low specificity of prostate specific antigen (PSA), the current clinical standard used for its early detection. The long term goal of this proposal is to define a subset of clinically relevant metabolomic markers and define their association with the process of disease progression using validated prostate cancer animal models. Our hope is that such a systematic molecular analysis of prostate cancer metabolites would lead to identification of pathway alterations that could be one day targeted for therapy. Further, with the ultimate objective of transitioning these markers to the clinical setting, we intent to validate them across additional prostate-related clinical biospecimens.
|von Rundstedt, Friedrich-Carl; Rajapakshe, Kimal; Ma, Jing et al. (2016) Integrative Pathway Analysis of Metabolic Signature in Bladder Cancer: A Linkage to The Cancer Genome Atlas Project and Prediction of Survival. J Urol 195:1911-9|
|Kaushik, Akash K; Shojaie, Ali; Panzitt, Katrin et al. (2016) Inhibition of the hexosamine biosynthetic pathway promotes castration-resistant prostate cancer. Nat Commun 7:11612|
|Shafi, Ayesha A; Putluri, Vasanta; Arnold, James M et al. (2015) Differential regulation of metabolic pathways by androgen receptor (AR) and its constitutively active splice variant, AR-V7, in prostate cancer cells. Oncotarget 6:31997-2012|
|Dasgupta, Subhamoy; Putluri, Nagireddy; Long, Weiwen et al. (2015) Coactivator SRC-2-dependent metabolic reprogramming mediates prostate cancer survival and metastasis. J Clin Invest 125:1174-88|
|Kang, Yun Kyoung; Putluri, Nagireddy; Maity, Suman et al. (2015) CAPER is vital for energy and redox homeostasis by integrating glucose-induced mitochondrial functions via ERR-Î±-Gabpa and stress-induced adaptive responses via NF-ÎºB-cMYC. PLoS Genet 11:e1005116|
|Jin, Feng; Bhowmik, Salil Kumar; Putluri, Vasanta et al. (2015) A Novel [(15)N] Glutamine Flux using LC-MS/MS-SRM for Determination of Nucleosides and Nucleobases. J Anal Bioanal Tech 6:|
|Kaushik, Akash K; Vareed, Shaiju K; Basu, Sumanta et al. (2014) Metabolomic profiling identifies biochemical pathways associated with castration-resistant prostate cancer. J Proteome Res 13:1088-100|
|Narayanan, S P; Xu, Z; Putluri, N et al. (2014) Arginase 2 deficiency reduces hyperoxia-mediated retinal neurodegeneration through the regulation of polyamine metabolism. Cell Death Dis 5:e1075|
|Terunuma, Atsushi; Putluri, Nagireddy; Mishra, Prachi et al. (2014) MYC-driven accumulation of 2-hydroxyglutarate is associated with breast cancer prognosis. J Clin Invest 124:398-412|
|Khan, Amjad P; Rajendiran, Thekkelnaycke M; Ateeq, Bushra et al. (2013) The role of sarcosine metabolism in prostate cancer progression. Neoplasia 15:491-501|
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