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

Proteomics reveals MRPL4 as a high-risk factor and a potential diagnostic biomarker for prostate cancer

Through digital rectal examinations (DRE) and routine prostate-specific antigen (PSA) screening, early prostate cancer (PC) treatment has become possible. However, PC is a complex and heterogeneous disease. In vivo, cancer cells can invade adjacent tissues and metastasize to other tissues resulting in hard cures. Therefore, the key to improving PC patients' survival time is preventing cancer cells' metastasis. We used mass spectrometry to profile primary PC in patients with versus without metastatic PC. We named these two groups of PC patients as high-risk primary PC (n = 11) and low-risk primary PC (n = 7), respectively. At the same time, patients with benign prostatic hyperplasia (BPH, n = 6) were used as controls to explore the possible factors driving PC metastasis. Based on comprehensive mass spectrometry analysis and biological validation, we found significant upregulation of MRPL4 expression in high-risk primary PC relative to low-risk primary PC and BPH. Further, through research of the extensive clinical cohort data in the database, we discovered that MRPL4 could be a high-risk factor for PC and serve as a potential diagnostic biomarker. The MRPL4 might be used as an auxiliary indicator for clinical status/stage of primary PC to predict patient survival time.

Cancer proteogenomics: current impact and future prospects

Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of the vast majority of somatic mutations and copy number variants in tumours remain unknown, and the causes of resistance to targeted therapies and methods to overcome them are poorly defined. Recent improvements in mass spectrometry-based proteomics now enable direct examination of the consequences of genomic aberrations, providing deep and quantitative characterization of tumour tissues. Integration of proteins and their post-translational modifications with genomic, epigenomic and transcriptomic data constitutes the new field of proteogenomics, and is already leading to new biological and diagnostic knowledge with the potential to improve our understanding of malignant transformation and therapeutic outcomes. In this Review we describe recent developments in proteogenomics and key findings from the proteogenomic analysis of a wide range of cancers. Considerations relevant to the selection and use of samples for proteogenomics and the current technologies used to generate, analyse and integrate proteomic with genomic data are described. Applications of proteogenomics in translational studies and immuno-oncology are rapidly emerging, and the prospect for their full integration into therapeutic trials and clinical care seems bright.

Proteomic Profiling of the Tumor Microenvironment

The tumor microenvironment forms a complex pro-tumorigenic milieu constituted by extracellular matrix, surrounding stroma, infiltrating cell populations, and signaling molecules. Proteomic studies have the potential to reveal how individual cell populations within the tumor tissue modulate the microenvironment through protein secretion and consequently alter their protein expression and localization to adapt to this milieu. As a result, proteomic approaches have uncovered how these dynamic components communicate and promote tumor development and progression. The characterization of these mechanisms is relevant for the identification of clinically targetable pathways and for the development of diagnostic tools. Here we describe a method based on the isolation of individual cell compartments and the chromatographic fractionation of intact proteins, followed by enzymatic digestion of individual fractions, and mass-spectrometry analysis, for the profiling of tumor microenvironment cell populations.

On the Road to Accurate Protein Biomarkers in Prostate Cancer Diagnosis and Prognosis: Current Status and Future Advances

Prostate cancer (PC) is a leading cause of morbidity and mortality among men worldwide. Molecular biomarkers work in conjunction with existing clinicopathologic tools to help physicians decide who to biopsy, re-biopsy, treat, or re-treat. The past decade has witnessed the commercialization of multiple PC protein biomarkers with improved performance, remarkable progress in proteomic technologies for global discovery and targeted validation of novel protein biomarkers from clinical specimens, and the emergence of novel, promising PC protein biomarkers. In this review, we summarize these advances and discuss the challenges and potential solutions for identifying and validating clinically useful protein biomarkers in PC diagnosis and prognosis. The identification of multi-protein biomarkers with high sensitivity and specificity, as well as their integration with clinicopathologic parameters, imaging, and other molecular biomarkers, bodes well for optimal personalized management of PC patients.

Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes

Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate cancer (PCa) to metastatic and castration-resistant prostate cancer (CRPC). While multiple aspects of prostate adenocarcinoma proteomes have been studied, less is known about proteomes of neuroendocrine prostate cancer (NEPC). In this review, we summarize recent developments in prostate cancer proteomics, concentrating on the proteomic landscapes of clinical prostate cancer, cell line and mouse model proteomes interrogating prostate cancer-relevant signaling and alterations, and key prostate cancer regulator interactomes, such as those of the androgen receptor (AR). Compared to genomic and transcriptomic analyses, the view provided by proteomics brings forward changes in prostate cancer metabolism, post-transcriptional RNA regulation, and post-translational protein regulatory pathways, requiring the full attention of studies in the future.

The Mitochondrial Proteome of Tumor Cells: A SnapShot on Methodological Approaches and New Biomarkers

Simple Summary

Mitochondria are central hubs of cellular signaling, energy metabolism, and redox balance. The plasticity of these cellular organelles is an essential requisite for the cells to cope with different stimuli and stress conditions. Cancer cells are characterized by changes in energy metabolism, mitochondrial signaling, and dynamics. These changes are driven by alterations in the mitochondrial proteome. For this reason, in the last years a focus of basic and cancer research has been the implementation and optimization of technologies to investigate changes in the mitochondrial proteome during cancer initiation and progression. This review presents an overview of the most used technologies to investigate the mitochondrial proteome and recent evidence on changes in the expression levels and delocalization of certain proteins in and out the mitochondria for shaping the functional properties of tumor cells.

Abstract

Mitochondria are highly dynamic and regulated organelles implicated in a variety of important functions in the cell, including energy production, fatty acid metabolism, iron homeostasis, programmed cell death, and cell signaling. Changes in mitochondrial metabolism, signaling and dynamics are hallmarks of cancer. Understanding whether these modifications are associated with alterations of the mitochondrial proteome is particularly relevant from a translational point of view because it may contribute to better understanding the molecular bases of cancer development and progression and may provide new potential prognostic and diagnostic biomarkers as well as novel molecular targets for anti-cancer treatment. Making an inventory of the mitochondrial proteins has been particularly challenging given that there is no unique consensus targeting sequence that directs protein import into mitochondria, some proteins are present at very low levels, while other proteins are expressed only in some cell types, in a particular developmental stage or under specific stress conditions. This review aims at providing the state-of-the-art on methodologies used to characterize the mitochondrial proteome in tumors and highlighting the biological relevance of changes in expression and delocalization of proteins in and out the mitochondria in cancer biology.

Ion Channel Profiling in Prostate Cancer: Toward Cell Population-Specific Screening

In the last three decades, a growing number of studies have implicated ion channels in all essential processes of prostate carcinogenesis, including cell proliferation, apoptosis, migration, and angiogenesis. The changes in the expression of individual ion channels show a specific profile, making these proteins promising clinical biomarkers that may enable better molecular subtyping of the disease and lead to more rapid and accurate clinical decision-making. Expression profiles and channel function are mainly based on the tumoral tissue itself, in this case, the epithelial cancer cell population. To date, little data on the ion channel profile of the cancerous prostate stroma are available, even though tumor interactions with the microenvironment are crucial in carcinogenesis and each distinct population plays a specific role in tumor progression. In this review, we describe ion channel expression profiles specific for the distinct cell population of the tumor microenvironment (stromal, endothelial, neuronal, and neuroendocrine cell populations) and the technical approaches used for efficient separation and screening of these cell populations.

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

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.

High sensitivity proteomics of prostate cancer tissue microarrays to discriminate between healthy and cancerous tissue

Biopsies, in the form of tissue microarrays (TMAs) were studied to identify anomalies indicative of prostate cancer at the proteome level. TMAs offer a valuable source of well-characterized biological material. However, because of the small tissue sample size method development was essential to provide the sensitivity and reliability necessary for the analysis. Surface digestion of TMA cores was followed by peptide extraction and shotgun proteomics analysis. About 5 times better sensitivity was achieved by the optimized surface digestion compared to bulk digestion of the same TMA spot and it allowed the identification of over 500 proteins from individual prostate TMA cores. Label-free quantitation showed that biological variability among all samples was about 3 times larger than the technical reproducibility. We have identified 189 proteins which showed statistically significant changes (t-test p-value <.05) in abundance between healthy and cancerous tissue samples. The proteomic profile changed according to cancer grade, but did not show a correlation with cancer stage. Results of this pilot study were further evaluated using bioinformatics tools, identifying various protein pathways affected by prostate cancer progression indicating the usefulness of studying TMA cores to identify quantitative changes in tissue proteomics. SIGNIFICANCE: Detailed proteomics analysis of TMAs presents a good alternative for tissue analysis. Here we present a novel method, based on tissue surface digestion and nano-LC-MS measurements, which is capable of identifying and quantifying over 500 proteins from a 1.5 mm diameter tissue section. We compared healthy and cancerous prostate tissue samples, and tissues with various grades and stages of cancer. Tissue proteomics clearly distinguished healthy and cancerous samples, furthermore the results correlated well with cancer grade, but not with cancer stage. Over 100 proteins showed statistically significant abundance changes (t-test p-value <.05) between various groups. This was sufficient for a meaningful bioinformatics evaluation; showing e.g. increased abundance of proteins in cancer in the KEGG ribosome pathway, GO mRNA splicing via spliceosome, and chromatin assembly biological processes. The results highlight the feasibility of the developed method for future large-scale tissue proteomics studies using commercially available TMAs.

Direct molecular dissection of tumor parenchyma from tumor stroma in tumor xenograft using mass spectrometry-based glycoproteomics

The most widely used cancer animal model is the human-murine tumor xenograft. Unbiased molecular dissection of tumor parenchyma versus stroma in human-murine xenografts is critical for elucidating dysregulated protein networks/pathways and developing therapeutics that may target these two functionally codependent compartments. Although antibody-reliant technologies (e.g., immunohistochemistry, imaging mass cytometry) are capable of distinguishing tumor-proper versus stromal proteins, the breadth or extent of targets is limited. Here, we report an antibody-free targeted cross-species glycoproteomic (TCSG) approach that enables direct dissection of human tumor parenchyma from murine tumor stroma at the molecular/protein level in tumor xenografts at a selectivity rate presently unattainable by other means. This approach was used to segment/dissect and obtain the protein complement phenotype of the tumor stroma and parenchyma of the metastatic human lung adenocarcinoma A549 xenograft, with no need for tissue microdissection prior to mass-spectrometry analysis. An extensive molecular map of the tumor proper and the associated microenvironment was generated along with the top functional N-glycosylated protein networks enriched in each compartment. Importantly, immunohistochemistry-based cross-validation of selected parenchymal and stromal targets applied on human tissue samples of lung adenocarcinoma and normal adjacent tissue is indicative of a noteworthy translational capacity for this unique approach that may facilitate identifications of novel targets for next generation antibody therapies and development of real time preclinical tumor models.

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

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.

Understanding of molecular events in cancer requires proteome-level characterisation. Here, proteome profiling of patient samples representing primary and progressed prostate cancer enables the authors to identify pathway alterations that are not reflected at the genomic and transcriptomic levels.

Prostate cancer proteomics: clinically useful protein biomarkers and future perspectives

INTRODUCTION

Although prostate cancer constitutes one of the most important, death-related diseases in the male population, there is still a need for identification of sensitive biomarkers that could precociously detect the disease and differentiate aggressive from indolent cancers, in order to decrease overtreatment. Proteomics research has improved understanding on mechanisms underlying tumorigenesis, cancer cells migration and invasion potential, and castration resistance. This review has focused on proteomic studies of prostate cancer published in the recent years, with a special emphasis on determination of biomarkers for cancer progression and diagnosis. Areas covered: Shotgun and targeted-proteomic studies of prostate cancer in different matrices are reviewed, i.e., prostate tissue, prostate cell lines, blood (serum and plasma), urine, seminal plasma, and exosomes. The most important biomarkers for cancer diagnosis and aggressiveness characterization are highlighted. Expert commentary: In general, results demonstrate alteration in cell cycle control, DNA repair, proteasomal degradation, and metabolic activity. However, these studies suffer from low reproducibility due to heterogeneity of the cancer itself, as well as to techniques utilized for protein identification/quantification. Downstream confirmatory studies in separate cohorts are warranted in order to demonstrate accuracy of these results.

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

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.