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

Uncovering New Biomarkers for Prostate Cancer Through Proteomic and Network Analysis

BACKGROUND

Prostate cancer (PCa), is the second most prevalent solid tumor among men worldwide (7.3%), and the leading non-skin cancer in USA where it represents 14.9% of all new cancer cases diagnosed in 2024. This multifactorial disease exhibits substantial variation in incidence and mortality across different ethnic groups and geographic regions. Although prostate-specific antigen (PSA) remains widely used as a biomarker for PCa, its limitations reduce its effectiveness for accurate detection. Consequently, finding molecules that can either complement PSA and other biomarkers is a major goal in PCa research.

METHODS

Urine samples were collected from healthy donors (n = 5) and patients with low- and high-risk PCa (4 and 7 subjects, respectively) and were analyzed using proteomic data-derived systems and biology approaches. The most promising proteins were further investigated by means of The Cancer Genome Atlas (TCGA) database to assess their associations with clinical and histopathological characteristics in a larger in silico patient population.

RESULTS

By evaluating the variations in the urinary proteome as a mirror of the changes occurring in prostate tumor tissue, components of complement and coagulation cascades and glutathione metabolism emerged as hallmarks of low- and high-risk PCa patients, respectively. Moreover, our integrated approach highlighted new potential biomarkers, including CPM, KRT8, ITIH2, and RCN1.

CONCLUSIONS

The good overlap of our results with what is already reported in the literature supports the new findings in the perspective of improving the knowledge on PCa. Furthermore, they increase the panel of biomarkers that could enhance PCa management. Of course, further investigations on larger patient cohorts are required.

Molecular Insights into the Breast and Prostate Cancer Cells in Response to the Change of Extracellular Zinc

Zinc dyshomeostasis is manifested in breast and prostate cancer cells. This study attempted to uncover the molecular details prodded by the change of extracellular zinc by employing a panel of normal and cancerous breast and prostate cell lines coupled with the top-down proteomics with two-dimensional gel electrophoresis followed by liquid chromatography-tandem mass spectrometry. The protein samples were generated from MCF-7 breast cancer cells, MCF10A normal breast cells, PC3 prostate cancer cells, and RWPE-1 normal prostate cells with or without exogenous zinc exposure in a time course (T0 and T120). By comparing the cancer cells vs respective normal epithelial cells without zinc treatment (T0), differentially expressed proteins (23 upregulated and 18 downregulated in MCF-7 cells; 14 upregulated and 30 downregulated in PC3 cells) were identified, which provides insights into the intrinsic differences of breast and prostate cancer cells. The dynamic protein landscapes in the cancer cells prodded by the extracellular zinc treatment reveal the potential roles of the identified zinc-responsive proteins (e.g., triosephosphate isomerase, S100A13, tumour proteins hD53 and hD54, and tumour suppressor prohibitin) in breast and prostate cancers. This study, for the first time, simultaneously investigated the two kinds of cancer cells related to zinc dyshomeostasis, and the findings shed light on the molecular understanding of the breast and prostate cancer cells in response to extracellular zinc variation.

Registration of hyperspectral images and mass spectrometry data for the correlation of tissue optical spectra and molecular profiles

Hyperspectral imaging (HSI) is a label-free imaging modality that is emerging for non-invasive detection of various diseases including cancers. HSI provides high-resolution spatial images where each pixel has a spectral curve with numerous wavelength bands from the visible to infrared ranges. The rich spatial and spectral information can be used to discriminate various types of tissues and pathophysiological conditions. However, it can be difficult to explain spectral data with respect to the underline cellular and molecular mechanism. In this study, we developed an approach that registers hyperspectral images and mass spectrometry (MS) data where MS provides tissue molecular profiles. Human prostate tissues that were obtained after prostatectomy were used in the experiments. The whole prostate was first sliced every six mm. A customized hyperspectral surgical microscope was used to acquire HSI data from the sliced tissue. For MS data analysis, the sliced tissue of the prostate was divided into 51 small regions and then processed separately for each region. The immediately adjacent tissue was sliced and processed histologically for H&E staining. The MS molecular profiles were correlated with the hyperspectral images in this study.

Integrated omics analysis unveils a DNA damage response to neurogenic injury

Spinal cord injury (SCI) evokes profound bladder dysfunction. Current treatments are limited by a lack of molecular data to inform novel therapeutic avenues. Previously, we showed systemic inosine treatment improved bladder function following SCI in rats. Here, we applied multi-omics analysis to explore molecular alterations in the bladder and their sensitivity to inosine following SCI. Canonical pathways regulated by SCI included those associated with protein synthesis, neuroplasticity, wound healing, and neurotransmitter degradation. Upstream regulator analysis identified MYC as a key regulator, whereas causal network analysis predicted multiple regulators of DNA damage response signaling following injury, including PARP-1. Staining for both DNA damage (γH2AX) and PARP activity (poly-ADP-ribose) markers in the bladder was increased following SCI, and attenuated in inosine-treated tissues. Proteomics analysis suggested that SCI induced changes in protein synthesis-, neuroplasticity-, and oxidative stress-associated pathways, a subset of which were shown in transcriptomics data to be inosine-sensitive. These findings provide novel insights into the molecular landscape of the bladder following SCI, and highlight a potential role for PARP inhibition to treat neurogenic bladder dysfunction.

Collagen VI deposition mediates stromal T cell trapping through inhibition of T cell motility in the prostate tumor microenvironment

The tumor extracellular matrix (ECM) is a barrier to anti-tumor immunity in solid tumors by disrupting T cell-tumor cell interaction underlying the need for elucidating mechanisms by which specific ECM proteins impact T cell motility and activity within the desmoplastic stroma of solid tumors. Here, we show that Collagen VI (Col VI) deposition correlates with stromal T cell density in human prostate cancer specimens. Furthermore, motility of CD4+ T cells is completely ablated on purified Col VI surfaces when compared with Fibronectin and Collagen I. Importantly, T cells adhered to Col VI surfaces displayed reduced cell spreading and fibrillar actin, indicating a reduction in traction force generation accompanied by a decrease in integrin β1 clustering. We found that CD4+ T cells largely lack expression of integrin α1 in the prostate tumor microenvironment and that blockade of α1β1 integrin heterodimers inhibited CD8+ T cell motility on prostate fibroblast-derived matrix, while re-expression of ITGA1 improved motility. Taken together, we show that the Col VI-rich microenvironment in prostate cancer reduces the motility of CD4+ T cells lacking integrin α1, leading to their accumulation in the stroma, thus putatively inhibiting anti-tumor T cell responses.

Salivary Biomarker Evaluation of Chronic Pancreatitis Patients Reveals Alterations in Human Proteins, Cytokines, Prostaglandin E2 Levels, and Bacterial Diversity

OBJECTIVES

Chronic pancreatitis (CP) is a chronic fibroinflammatory condition of the pancreas difficult to diagnose in early stages. Novel biomarkers useful to facilitate early diagnosis or treatment responses may be found in biofluids. Although saliva can be easily and noninvasively collected from patients, useful salivary biomarkers from CP patients have not yet been identified.

METHODS

Here, we analyzed the proteome by quantitative proteomics, cytokine/chemokine levels by Luminex analysis, prostaglandin E2 (PGE2) levels by a mass spectrometry-based assay, and bacterial species diversity by 16S ribosomal ribonucleic acid sequencing in saliva samples from confirmed CP patients and healthy controls.

RESULTS

Our results indicate the presence of various differentially expressed proteins, cytokines/chemokines, and a loss of oral bacterial diversity in the saliva of CP patients. The PGE2 levels trend toward elevation in CP patients. Area under the receiver operating characteristic curve models for proteomic, cytokine, and PGE2 assays ranged from 0.59 to 0.90.

CONCLUSIONS

Collectively, our studies identify a range of putative CP biomarkers and alterations in human saliva requiring further validation. The biomarker discovery approaches we used might lead to identification of biomarkers useful for CP diagnosis and monitoring.

Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics

With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture), and tandem mass tag (TMT) isobaric tandem mass tags technology for quantitative phosphosite profiling in tumor tissue. Compared to the classic SILAC method, spike-in-SILAC is not limited to cell culture analysis, making it suitable for quantitative analysis of tumor tissue samples. TMT offered the lowest accuracy and the highest precision and robustness toward different phosphosite abundances and matrices. Spike-in-SILAC offered the best compromise between these features but suffered from a low phosphosite coverage. LFQ offered the lowest precision but the highest number of identifications. Both spike-in-SILAC and LFQ presented susceptibility to matrix effects. Match between run (MBR)-based analysis enhanced the phosphosite coverage across technical replicates in LFQ and spike-in-SILAC but further reduced the precision and robustness of quantification. The choice of quantitative methodology is critical for both study design such as sample size in sample groups and quantified phosphosites and comparison of published cancer phosphoproteomes. Using ovarian cancer tissue as an example, our study builds a resource for the design and analysis of quantitative phosphoproteomic studies in cancer research and diagnostics.

An optimized MALDI MSI protocol for spatial detection of tryptic peptides in fresh frozen prostate tissue

MALDI MS imaging (MSI) is a powerful analytical tool for spatial peptide detection in heterogeneous tissues. Proper sample preparation is crucial to achieve high quality, reproducible measurements. Here we developed an optimized protocol for spatially resolved proteolytic peptide detection with MALDI time-of-flight MSI of fresh frozen prostate tissue sections. The parameters tested included four different tissue washes, four methods of protein denaturation, four methods of trypsin digestion (different trypsin densities, sprayers, and incubation times), and five matrix deposition methods (different sprayers, settings, and matrix concentrations). Evaluation criteria were the number of detected and excluded peaks, percentage of high mass peaks, signal-to-noise ratio, spatial localization, and average intensities of identified peptides, all of which were integrated into a weighted quality evaluation scoring system. Based on these scores, the optimized protocol included an ice-cold EtOH+H2 O wash, a 5 min heating step at 95°C, tryptic digestion incubated for 17h at 37°C and CHCA matrix deposited at a final amount of 1.8 μg/mm2 . Including a heat-induced protein denaturation step after tissue wash is a new methodological approach that could be useful also for other tissue types. This optimized protocol for spatial peptide detection using MALDI MSI facilitates future biomarker discovery in prostate cancer and may be useful in studies of other tissue types.

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.

BoxCar and shotgun proteomic analyses reveal molecular networks regulated by UBR5 in prostate cancer

Prostate cancer (PC) is a major health and economic problem in industrialized countries, yet our understanding of the molecular mechanisms of PC progression and drug response remains limited. Accumulating evidence showed that certain E3 ubiquitin ligases such as SIAH2, RNF7, and SPOP play important roles in PC development and progression. However, the roles and mechanisms of other E3s in PC progression remain largely unexplored. Through an integration analysis of clinical genomic and transcriptomic profiles of PC tumors, this study identified UBR5 as a top PC-relevant E3 ubiquitin ligase whose expression levels are strongly associated with PC progression and aggressiveness. BoxCar and shotgun proteomic analyses of control and UBR5-knockdown PC3 cells complementarily identified 75 UBR5-regulated proteins. Bioinformatic analysis suggested that the 75 proteins form four molecular networks centered around FANCD2, PAF1, YY1, and LAMB3 via direct protein-protein interactions. Experimental analyses demonstrated that UBR5 associates with and downregulates two key DNA damage repair proteins (XRCC3 and FANCD2) and confers PC cell sensitivity to olaparib, a PARP inhibitor in clinical use for cancer therapy. This study represents the first application of BoxCar in PC research, provides new insights into the molecular functions of UBR5 in PC, and suggests that PC patients with UBR5-high tumors may potentially benefit from PARP inhibitor treatment.

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.

Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research

Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.

S-Palmitoylation as a Functional Regulator of Proteins Associated with Cisplatin Resistance in Bladder Cancer

Protein S-palmitoylation is a powerful post-translational modification that regulates protein trafficking, localization, turnover, and signal transduction. Palmitoylation controls several important cellular processes, and, if dysregulated, can lead to cancer, cardiovascular disease, and neurological disorders. The role of protein palmitoylation in mediating resistance to systemic cisplatin-based chemotherapies in cancer is currently unknown. This is of particular interest because cisplatin is currently the gold standard of treatment for bladder cancer (BC), and there are no feasible options after resistance is acquired. Using unbiased global proteomic profiling of purified S-palmitoylated peptides combined with intensive bioinformatics analyses, we identified 506 candidate palmitoylated proteins significantly enriched in cisplatin-resistant BC cells. One of these proteins included PD-L1, which is highly palmitoylated in resistant cells. Pharmacological inhibition of fatty acid synthase (FASN) suppressed PD-L1 palmitoylation and expression, which suggests the potential use of FASN-PD-L1-targeted therapeutic strategies in BC patients. Taken together, these results highlight the role of protein palmitoylation in mediating BC chemoresistance.

Comprehensive palmitoyl-proteomic analysis identifies distinct protein signatures for large and small cancer-derived extracellular vesicles

Extracellular vesicles (EVs) are membrane-enclosed particles that play an important role in cancer progression and have emerged as a promising source of circulating biomarkers. Protein S-acylation, frequently called palmitoylation, has been proposed as a post-translational mechanism that modulates the dynamics of EV biogenesis and protein cargo sorting. However, technical challenges have limited large-scale profiling of the whole palmitoyl-proteins of EVs. We successfully employed a novel approach that combines low-background acyl-biotinyl exchange (LB-ABE) with label-free proteomics to analyse the palmitoyl-proteome of large EVs (L-EVs) and small EVs (S-EVs) from prostate cancer cells. Here we report the first palmitoyl-protein signature of EVs, and demonstrate that L- and S-EVs harbour proteins associated with distinct biological processes and subcellular origin. We identified STEAP1, STEAP2, and ABCC4 as prostate cancer-specific palmitoyl-proteins abundant in both EV populations. Importantly, localization of the above proteins in EVs was reduced upon inhibition of palmitoylation in the producing cells. Our results suggest that this post-translational modification may play a role in the sorting of the EV-bound secretome and possibly enable selective detection of disease biomarkers.