Pathology-Driven Comprehensive Proteomic Profiling of the Prostate Cancer Tumor Microenvironment

Staunton, Lisa; Tonry, Claire; Lis, Rosina T.; Espina, Virginia; Liotta, Lance A.; Inzitari, Rosanna; Bowden, Michaela; Fabre, Aurélie; O’Leary, John; Finn, Stephen P.; Loda, Massimo

doi:10.1158/1541-7786.mcr-16-0358

Cited by 16 publications

(14 citation statements)

References 62 publications

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“…Recent developments in mass spectrometric methods 11 – 13 have enabled high throughput analysis of clinical patient samples, and the first integrative studies involving large scale, mass spectrometry-based proteomics of human cancer have recently been published 14 – 16 . For prostate cancer, recent proteomic advancements have included high scale, mass spectrometry-based studies performed in diagnostic body fluids 17 , 18 , as well as primary tumors 19 and the tumor microenvironment 20 . So far, the only integrative proteogenomic analysis of clinical prostate cancer involved genomic and transcriptomic data of CRPC combined with phosphoproteomic analysis 21 .…”

Section: Introductionmentioning

confidence: 99%

Integrative proteomics in prostate cancer uncovers robustness against genomic and transcriptomic aberrations during disease progression

et al. 2018

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To understand functional consequences of genetic and transcriptional aberrations in prostate cancer, the proteomic changes during disease formation and progression need to be revealed. Here we report high-throughput mass spectrometry on clinical tissue samples of benign prostatic hyperplasia (BPH), untreated primary prostate cancer (PC) and castration resistant prostate cancer (CRPC). Each sample group shows a distinct protein profile. By integrative analysis we show that, especially in CRPC, gene copy number, DNA methylation, and RNA expression levels do not reliably predict proteomic changes. Instead, we uncover previously unrecognized molecular and pathway events, for example, several miRNA target correlations present at protein but not at mRNA level. Notably, we identify two metabolic shifts in the citric acid cycle (TCA cycle) during prostate cancer development and progression. Our proteogenomic analysis uncovers robustness against genomic and transcriptomic aberrations during prostate cancer progression, and significantly extends understanding of prostate cancer disease mechanisms.

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Section: Introductionmentioning

confidence: 99%

Integrative proteomics in prostate cancer uncovers robustness against genomic and transcriptomic aberrations during disease progression

et al. 2018

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“…With a larger sample size (n = 16 for high-risk PCa and n = 12 for low risk PCa), Iglesias-Gato et al found that 130 proteins were differentially ( p < 0.05 and FC > 1.6) expressed between low-risk and high-risk PCa groups [11]. Via label-free quantitative proteomics comparison of LCM-isolated epithelial cells from Gleason grade 3 versus 4 tumors (n = 4 for each), Staunton et al identified 120 DEPs (FDR < 0.05) [12]. A comparison of the three datasets suggested that only three DEPs (ADH5, ALDH2, and CSRP1) are shared between our and Iglesias-Gato studies, three DEPs (CPE, QDPR, and PACSIN3) are shared between our and Staunton studies, and five DEPs (ABAT, COL6A2, COL6A3, EPHX2, and PFKP) are shared between the Iglesias-Gato and Staunton studies (Additional file 2: Table S6).…”

Section: Discussionmentioning

confidence: 99%

Quantitative proteomic analysis of prostate tissue specimens identifies deregulated protein complexes in primary prostate cancer

et al. 2019

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Background Prostate cancer (PCa) is the most frequently diagnosed non-skin cancer and a leading cause of mortality among males in developed countries. However, our understanding of the global changes of protein complexes within PCa tissue specimens remains very limited, although it has been well recognized that protein complexes carry out essentially all major processes in living organisms and that their deregulation drives the pathogenesis and progression of various diseases. Methods By coupling tandem mass tagging-synchronous precursor selection-mass spectrometry/mass spectrometry/mass spectrometry with differential expression and co-regulation analyses, the present study compared the differences between protein complexes in normal prostate, low-grade PCa, and high-grade PCa tissue specimens. Results Globally, a large downregulated putative protein–protein interaction (PPI) network was detected in both low-grade and high-grade PCa, yet a large upregulated putative PPI network was only detected in high-grade but not low-grade PCa, compared with normal controls. To identify specific protein complexes that are deregulated in PCa, quantified proteins were mapped to protein complexes in CORUM (v3.0), a high-quality collection of 4274 experimentally verified mammalian protein complexes. Differential expression and gene ontology (GO) enrichment analyses suggested that 13 integrin complexes involved in cell adhesion were significantly downregulated in both low- and high-grade PCa compared with normal prostate, and that four Prothymosin alpha (ProTα) complexes were significantly upregulated in high-grade PCa compared with normal prostate. Moreover, differential co-regulation and GO enrichment analyses indicated that the assembly levels of six protein complexes involved in RNA splicing were significantly increased in low-grade PCa, and those of four subcomplexes of mitochondrial complex I were significantly increased in high-grade PCa, compared with normal prostate. Conclusions In summary, to the best of our knowledge, the study represents the first large-scale and quantitative, albeit indirect, comparison of individual protein complexes in human PCa tissue specimens. It may serve as a useful resource for better understanding the deregulation of protein complexes in primary PCa. Electronic supplementary material The online version of this article (10.1186/s12014-019-9236-2) contains supplementary material, which is available to authorized users.

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“…Despite the small number of clinical samples analyzed and limited proteome coverage, some proteins like MYO6 were found as differentially regulated between ERG+ and ERG− tumors ( 11 ). Another example of initial proteomic study tackling a relevant PCa question is the analysis of epithelial and microenvironment tissue that were micro-dissected from tumors graded with different Gleason scores ( 12 ). Despite similar limitations as the previously described study, this investigation served as a proof of principle for the existence of major differences in tumor microenvironment.…”

Section: Proteomic Profiling Of Pca Tissuesmentioning

confidence: 99%

Quantitative Mass Spectrometry-Based Proteomic Profiling for Precision Medicine in Prostate Cancer

Flores‐Morales

Iglesias-Gato

2017

Front. Oncol.

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Prostate cancer (PCa) is one of the most frequently diagnosed cancer among men in the western societies. Many PCa patients bear tumors that will not threat their lives if left untreated or if treatment is delayed. Our inability for early identification of these patients has resulted in massive overtreatment. Therefore, there is a great need of finding biomarkers for patient stratification according to prognostic risk; as well as there is a need for novel targets that can allow the development of effective treatments for patients that progress to castration-resistant PCa. Most biomarkers in cancer are proteins, including the widely-used prostate-specific antigen (PSA). Recent developments in mass spectrometry allow the identification and quantification of thousands of proteins and posttranslational modifications from small amounts of biological material, including formalin-fixed paraffin-embedded tissues, and biological fluids. Novel diagnostic and prognostic biomarkers have been identified in tissue, blood, urine, and seminal plasma of PCa patients, and new insights in the ethology and progression of this disease have been achieved using this technology. In this review, we summarize these findings and discuss the potential of this technology to pave the way toward the clinical implementation of precision medicine in PCa.

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Pathology-Driven Comprehensive Proteomic Profiling of the Prostate Cancer Tumor Microenvironment

Cited by 16 publications

References 62 publications

Integrative proteomics in prostate cancer uncovers robustness against genomic and transcriptomic aberrations during disease progression

Integrative proteomics in prostate cancer uncovers robustness against genomic and transcriptomic aberrations during disease progression

Quantitative proteomic analysis of prostate tissue specimens identifies deregulated protein complexes in primary prostate cancer

Quantitative Mass Spectrometry-Based Proteomic Profiling for Precision Medicine in Prostate Cancer

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