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

Machine learning models for enhanced diagnosis and risk assessment of prostate cancer with 68Ga-PSMA-617 PET/CT

OBJECTIVE

Prostate cancer (PCa) is highly heterogeneous, making early detection of adverse pathological features crucial for improving patient outcomes. This study aims to predict PCa aggressiveness and identify radiomic and protein biomarkers associated with poor pathology, ultimately developing a multi-omics marker model for better clinical risk stratification.

METHODS

In this retrospective study, 191 patients with PCa or benign prostatic hyperplasia confirmed via 68Ga-PSMA-617 PET/CT scans were analyzed. Radiomic features were extracted from scan contours, and six machine learning algorithms were used to predict malignancy and adverse pathological features like Gleason score, ISUP group, tumor stage, lymph node infiltration, and perineural invasion. Feature selection and dimensionality reduction were performed using minimum redundancy maximum relevance and least absolute shrinkage and selection operator methods. Proteomics analysis on 39 patients identified protein biomarkers, followed by correlation analysis between radiomic features and identified proteins.

RESULTS

The radiomics model showed an AUC of 0.938 for predicting malignant prostate lesions and 0.916 for adverse pathological features in the test set, with validation set AUCs of 0.918 and 0.855, respectively. Three quantitative radiomic features and ten protein molecules associated with adverse pathology were identified, with significant correlations observed between radiomic features and protein biomarkers. Radioproteomic analysis revealed that molecular changes in protein molecules could influence imaging biomarkers.

CONCLUSIONS

The machine learning models based on 68 Ga-PSMA-617 PET/CT radiomic features performed well in stratifying patients, supporting clinical risk stratification and highlighting connections between radiomic characteristics and protein biomarkers.

A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics

Effective classification methods and prognostic models enable more accurate classification and treatment of hepatocellular carcinoma (HCC) patients. However, the weak correlation between RNA and protein data has limited the clinical utility of previous RNA-based prognostic models for HCC. In this work, we constructed a novel prognostic framework for HCC patients using seven differentially expressed proteins associated with ferroptosis and iron metabolism. Furthermore, this prognostic model robustly classifies HCC patients into three clinically relevant risk groups. Significant differences in overall survival, age, tumor differentiation, microvascular invasion, distant metastasis, and alpha-fetoprotein levels were observed among the risk groups. Based on the prognostic model and known biological pathways, we explored the potential mechanisms underlying the inconsistent differential expression patterns of FTH1 (Ferritin heavy chain 1) mRNA and protein. Our findings demonstrated that tumor tissues in HCC patients promote liver cancer progression by downregulating FTH1 protein expression, rather than upregulating FTH1 mRNA expression, ultimately leading to poor prognosis. Subsequently, based on risk score and tumor size, we developed a nomogram for predicting the prognosis of HCC patients, which demonstrated superior predictive performance in both the training and validation cohorts (C-index: 0.774; AUC for 1-5 years: 0.783-0.964). Additionally, our findings demonstrated that the adverse prognosis of high-risk HCC patients was closely correlated with ferroptosis in liver cancer tissues, alterations in iron metabolism, and changes in the tumor immune microenvironment. In conclusion, our prognostic model and predictive nomogram offer novel insights and tools for the effective classification of HCC patients, potentially enhancing clinical decision-making and outcomes.

Circulatory prostate cancer proteome landscapes and prognostic biomarkers in metastatic castrate resistant prostate cancer

BACKGROUND

Plasma-based high-plex proteomic profiling were performed in prostate cancer (PC) patients using the Olink® Explore Proximity Extension Assay to identify plasma proteins associated in different PC states and to explore potential prognostic biomarkers. The progressive PC states include local, organ-confined PC (local PC), metastatic hormone-sensitive PC (mHSPC) and metastatic castrate-resistant PC (mCRPC).

METHODS

Plasma samples were uniformly processed from 84 PC patients (10 patients with local PC; 29 patients with mHSPC; 45 patients with mCRPC). A proteome-wide association study was performed to identify proteins differentially overexpressed in progressive cancer states. Specifically, a sequential screening approach was employed where proteins overexpressed from one disease state were assessed for overexpression in the progressive disease state. Linear regression, analysis of variance, and t-tests were used for this approach. Differentially expressed proteins (DEPs) in mCRPC were then used to construct a prognostic model for overall survival (OS) in mCRPC patients using the Cox Proportional Hazard Model. The predictive performance of this model was assessed using time-dependent area under the receiver operating characteristic curves (tAUC) in an independent sample of mCRPC patients. The tAUC of the prognostic model was then compared to that of a model excluding DEPs to evaluate the added value of circulatory proteins in predicting survival.

RESULTS

Of 736 tumor-associated proteins, 26 were differentially expressed across local PC, mHSPC, and mCRPC states. Among these, 20 were overexpressed in metastatic states compared to local, and in mCRPC compared to mHSPC states. Of these 20 proteins, Ribonucleoside-diphosphate reductase subunit M2 (RRM2) was identified as a prognostic biomarker for OS in mCRPC, with a hazard ratio of 2.30 (95% confidence interval (CI) 1.17-4.51) per normalized expression unit increase. The tAUC of the model including previously identified clinical prognostic factors was 0.62 (95% CI 0.29-0.91), whereas the model that includes RRM2 with clinical prognostic factors was 0.87 (95% CI 0.51-0.98).

CONCLUSIONS

Plasma proteome profiling can identify novel circulatory DEPs associated with mCRPC state survivals. Overexpression of RRM2 is linked to poor mCRPC survival and its inclusion alongside conventional prognostic factors enhances the predictive performance of the prognostic model.

Downregulation of Aging-Associated Gene SUCLG1 Marks the Aggressiveness of Liver Disease

INTRODUCTION

The most common liver disease is nonalcoholic fatty liver disease, characterized by an intrahepatic accumulation of lipids that most often accompanies obesity. Fatty liver can evolve, in the presence of oxidative stress and inflammation, into disabling and deadly liver diseases such as cirrhosis, hepatocellular carcinoma (HCC), and cholangiocarcinoma (CC). Old age seems to favor HCC and CC, in agreement with the inflammaging theory, according to which aging accrues inflammation. Cancer, in general, is an age-related disease, as incidence and mortality for most types of cancer increase with age. However, how molecular drivers in tumors differ or are mutated more frequently among patients of different ages remains scarcely investigated. A recent integrative analysis of the age-associated multi-omic landscape across cancers and healthy tissues demonstrated that age-related gene expression changes are linked to numerous biological processes. HCC and CC have among the lowest five-year survival estimates due to their aggressive progression.

MATERIALS AND METHODS

In this study, we extracted top gene candidates from the above-mentioned pan-analyses (i.e., B2M, C1qA, SUCLG1) and tested by qPCR their expression and their correlation with disease progression in 48 tissue samples covering liver disease stages (fatty liver, hepatitis, cirrhosis, HCC and CC) and normal tissues.

RESULTS

Here, we report a significant downregulation in the expression of the age-associated gene SUCLG1 during the progression of liver disease toward HCC and CC, which also associates with poor patient survival.

CONCLUSION

SUCGL1, a mitochondrial enzyme gene that catalyzes the conversion of succinyl CoA to succinate, might be therapeutically targeted for the development and progression of age-associated liver cancers with low survival rates.

Quantitative proteomic analysis unveils a critical role of VARS1 in hepatocellular carcinoma aggressiveness through the modulation of MAGI1 expression

BACKGROUND

Hepatocellular carcinoma (HCC) genetic/transcriptomic signatures have been widely described. However, its proteomic characterization is incomplete. We performed non-targeted quantitative proteomics of HCC samples and explored its clinical, functional, and molecular consequences.

METHODS

Non-targeted quantitative proteomics were performed on cytosolic and nuclear fractions of liver samples [HCC vs. non-tumour adjacent tissue (NTAT), n = 42 patients]. Changes were confirmed in 7 in silico HCC cohorts. Functional and molecular implications were evaluated on HCC-derived cell lines after silencing/overexpressing VARS1 and/or MAGI1. VARS1-overexpressing Hep3B cells were used for in vivo studies [Extreme Limiting Dilution Assay (ELDA) and orthotopic tumour formation]. Quantitative proteomics were performed on VARS1-overexpressing HCC cell lines.

RESULTS

Quantitative proteomics revealed the dysregulation of the cytosolic and nuclear proteomes in HCC, and defined two proteomic HCC subgroups, the most aggressive associated to the dysregulation of the aminoacyl-tRNA synthetases (ARSs). ARSs dysregulation was corroborated in in silico HCC cohorts and associated to poor prognosis. Patients with ARSs upregulation had genomic/transcriptomic characteristics of the proliferative HCC. Valine tRNA-aminoacyl synthetase (VARS1) was the ARSs most consistently overexpressed and associated to aggressiveness. VARS1 modulation (silencing/overexpression) altered tumour establishment-associated parameters in vitro and/or in vivo. Quantitative proteomics on cells overexpressing VARS1 and rescue experiments identified the downregulation of MAGI1, a tumour suppressor in HCC, as a mediator of VARS1 function.

CONCLUSIONS

Quantitative proteomics defines two prognosis-related proteomic HCC subgroups. ARSs machinery is dysregulated in the aggressive subgroup, bearing potential as prognostic biomarkers. VARS1 promotes aggressiveness through the modulation of MAGI1, representing a novel targetable vulnerability in HCC.

Proteogenomics offers a novel avenue in neoantigen identification for cancer immunotherapy

Cancer neoantigens are tumor-specific non-synonymous mutant peptides that activate the immune system to produce an anti-tumor response. Personalized cancer vaccines based on neoantigens are currently one of the most promising therapeutic approaches for cancer treatment. By utilizing the unique mutations within each patient's tumor, these vaccines aim to elicit a strong and specific immune response against cancer cells. However, the identification of neoantigens remains challenging due to the low accuracy of current prediction tools and the high false-positive rate of candidate neoantigens. Since the concept of "proteogenomics" emerged in 2004, it has evolved rapidly with the increased sequencing depth of next-generation sequencing technologies and the maturation of mass spectrometry-based proteomics technologies to become a more comprehensive approach to neoantigen identification, allowing the discovery of high-confidence candidate neoantigens. In this review, we summarize the reason why cancer neoantigens have become attractive targets for immunotherapy, the mechanism of cancer vaccines and the advances in cancer immunotherapy. Considerations relevant to the application emerging of proteogenomics technologies for neoantigen identification and challenges in this field are described.

Proceedings of the 5th Meeting of Translational Hepatology, organized by the Spanish Association for the Study of the Liver (AEEH)

This is the summary report of the 5th Translational Hepatology Meeting, endorsed by the Spanish Association for the Study of the Liver (AEEH) and held in Seville, Spain, in October 2023. The meeting aimed to provide an update on the latest advances in the field of basic and translational hepatology, covering different molecular, cellular, and pathophysiological aspects of the most relevant clinical challenges in liver pathologies. This includes the identification of novel biomarkers and diagnostic tools, the understanding of the relevance of immune response and inflammation in liver diseases, the characterization of current medical approaches to reverse liver diseases, the incorporation of novel molecular insights through omics techniques, or the characterization of the impact of toxic and metabolic insults, as well as other organ crosstalk, in liver pathophysiology.

Iroquois homeobox 4 (IRX4) derived micropeptide promotes prostate cancer progression and chemoresistance through Wnt signalling dysregulation

BACKGROUND

Prostate cancer (PCa) is a commonly diagnosed cancer. Genome-wide association studies have implicated Iroquois homeobox 4 (IRX4) in PCa susceptibility, yet its functional roles remain unclear. We discovered a 78-amino acid micropeptide (miPEP, IRX4_PEP1), encoded from the alternative start site within the IRX4 gene. The miPEPs, encoded through short open reading frames (sORFs) have emerged as regulators of diverse biological processes. However, the significance of miPEPs in prostate tumorigenesis and therapy response remains unexplored to date. Here, we demonstrated the unique role of IRX4_PEP1 in PCa.

METHODS

The role of IRX4_PEP1 was evaluated in PCa in vitro via functional assays and comprehensive pathway analysis. The interacting partners of IRX4_PEP1 were identified using an immunoprecipitation assay, and the impact of IRX4_PEP1 on PCa stem cells was assessed through a stem cell enrichment assay. Additionally, the expression of IRX4_PEP1 was evaluated in PCa patient samples for its potential diagnostic and prognostic significance.

RESULTS

Here we show IRX4_PEP1 promotes PCa cell proliferation, migration, and invasion by interacting with heterogeneous nuclear ribonucleoprotein K (HNRPK). Notably, IRX4_PEP1 dysregulates Wnt signalling by interacting with Catenin beta 1 (β catenin; CTNB1), elevating PCa stemness markers, and fostering docetaxel resistance. Clinically, IRX4_PEP1 expression is elevated in PCa tissues and correlates positively with disease aggressiveness. CTNNB1, HNRNPK levels, and ssGSEA enrichment score of WNT/CTNB1 signalling correlate positively with IRX4_PEP1 in PCa tissues.

CONCLUSIONS

These findings highlight IRX4_PEP1 role in PCa stemness and chemoresistance, suggesting it as a therapeutic target and potential diagnostic marker.

Raman spectroscopy reveals oxidative stress-induced metabolic vulnerabilities in early-stage AR-negative prostate-cancer versus normal-prostate cell lines

Quantitative Raman spectroscopy provides information-rich imaging of complex tissues. To illustrate its ability to characterise early-stage disease, we compared live P4E6, a low-grade Gleason-3 prostate-cancer cell line, to PNT2-C2, a normal prostate cell-line equivalent, thereby elucidating key molecular and mechanistic differences. Spectral changes from statistically relevant population sampling show P4E6 is defined by reduced DNA/RNA signatures (primarily base-pair modifications), increased protein-related signatures (synthesis), decreased whole-cell measured saturated and unsaturated fatty acids, and increased cholesterol and cholesterol ester (lipid storage). Signatures in the live-cell disease state point to the Warburg effect for aerobic glycolysis as the mechanism for cellular energy generation. A follow-on study involving catastrophic desiccation showed a key survival pathway in the cancer state in the structural robustness of DNA/RNA. Metabolic changes, namely in Warburg-to-oxidative-phosphorylation rerouting and reduced protein synthesis, were also shown. Such modifications limit cancer's resistance to oxidative damage, and thus its ability to utilise a higher redox homeostasis for metabolic advantage. The results demonstrate the ability of quantitative Raman spectroscopy to uncover, with full molecular-heterogeneity capture, mechanistic vulnerabilities in lowest-grade tumorigenic prostate cancer, thereby revealing underlying targets for disease disruption at early stage.

Long noncoding RNA EPCART regulates translation through PI3K/AKT/mTOR pathway and PDCD4 in prostate cancer

While hundreds of cancer-associated long noncoding RNAs (lncRNAs) have been discovered, their functional role in cancer cells is still largely a mystery. An increasing number of lncRNAs are recognized to function in the cytoplasm, e.g., as modulators of translation. Here, we investigated the detailed molecular identity and functional role of EPCART, a lncRNA we previously discovered to be a potential oncogene in prostate cancer (PCa). First, we interrogated the transcript structure of EPCART and then confirmed EPCART to be a non-peptide-coding lncRNA using in silico methods. Pathway analysis of differentially expressed protein-coding genes in EPCART knockout cells implied that EPCART modulates the translational machinery of PCa cells. EPCART was also largely located in the cytoplasm and at the sites of translation. With quantitative proteome analysis on EPCART knockout cells we discovered PDCD4, an inhibitor of protein translation, to be increased by EPCART reduction. Further studies indicated that the inhibitory effect of EPCART silencing on translation was mediated by reduced activation of AKT and inhibition of the mTORC1 pathway. Together, our findings identify EPCART as a translation-associated lncRNA that functions via modulation of the PI3K/AKT/mTORC1 pathway in PCa cells. Furthermore, we provide evidence for the prognostic potential of PDCD4 in PCa tumors in connection with EPCART.

Prostate Cancer: A Review of Genetics, Current Biomarkers and Personalised Treatments

BACKGROUND

Prostate cancer is the second leading cause of cancer deaths in men, second only to lung cancer. Despite this, diagnosis and prognosis methods remain limited, with effective treatments being few and far between. Traditionally, prostate cancer is initially tested for through a prostate serum antigen (PSA) test and a digital rectum examination (DRE), followed by confirmation through an invasive prostate biopsy. The DRE and biopsy are uncomfortable for the patient, so less invasive, accurate diagnostic tools are needed. Current diagnostic tools, along with genes that hold possible biomarker uses in diagnosis, prognosis and indications for personalised treatment plans, were reviewed in this article.

RECENT FINDINGS

Several genes from multiple families have been identified as possible biomarkers for disease, including those from the MYC and ETS families, as well as several tumour suppressor genes, Androgen Receptor signalling genes and DNA repair genes. There have also been advances in diagnostic tools, including MRI-targeted and liquid biopsies. Several personalised treatments have been developed over the years, including those that target metabolism-driven prostate cancer or those that target inflammation-driven cancer.

CONCLUSION

Several advances have been made in prostate cancer diagnosis and treatment, but the disease still grows year by year, leading to more and more deaths annually. This calls for even more research into this disease, allowing for better diagnosis and treatment methods and a better chance of patient survival.

Integrative proteogenomic profiling of high-risk prostate cancer samples from Chinese patients indicates metabolic vulnerabilities and diagnostic biomarkers

Prostate cancer (PCa) exhibits significant geoethnic disparities as reflected by distinct variations in the cancer genome and disease progression. Here, we perform a comprehensive proteogenomic characterization of localized high-risk PCa utilizing paired tumors and nearby tissues from 125 Chinese male patients, with the primary objectives of identifying potential biomarkers, unraveling critical oncogenic events and delineating molecular subtypes with poor prognosis. Our integrated analysis highlights the utility of GOLM1 as a noninvasive serum biomarker. Phosphoproteomics analysis reveals the crucial role of Ser331 phosphorylation on FOXA1 in regulating FOXA1-AR-dependent cistrome. Notably, our proteomic profiling identifies three distinct subtypes, with metabolic immune-desert tumors (S-III) emerging as a particularly aggressive subtype linked to poor prognosis and BCAT2 catabolism-driven PCa progression. In summary, our study provides a comprehensive resource detailing the unique proteomic and phosphoproteomic characteristics of PCa molecular pathogenesis and offering valuable insights for the development of diagnostic and therapeutic strategies.

Proteomic landscape profiling of primary prostate cancer reveals a 16-protein panel for prognosis prediction

Prostate cancer (PCa) is the most common malignant tumor in men. Currently, there are few prognosis indicators for predicting PCa outcomes and guiding treatments. Here, we perform comprehensive proteomic profiling of 918 tissue specimens from 306 Chinese patients with PCa using data-independent acquisition mass spectrometry (DIA-MS). We identify over 10,000 proteins and define three molecular subtypes of PCa with significant clinical and proteomic differences. We develop a 16-protein panel that effectively predicts biochemical recurrence (BCR) for patients with PCa, which is validated in six published datasets and one additional 99-biopsy-sample cohort by targeted proteomics. Interestingly, this 16-protein panel effectively predicts BCR across different International Society of Urological Pathology (ISUP) grades and pathological stages and outperforms the D'Amico risk classification system in BCR prediction. Furthermore, double knockout of NUDT5 and SEPTIN8, two components from the 16-protein panel, significantly suppresses the PCa cells to proliferate, invade, and migrate, suggesting the combination of NUDT5 and SEPTIN8 may provide new approaches for PCa treatment.

Metabolic imaging across scales reveals distinct prostate cancer phenotypes

Hyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer.

Proteomic profiling of prostate cancer reveals molecular signatures under antiandrogen treatment

BACKGROUND

Tumorigenesis and progression of prostate cancer (PCa) are indispensably dependent on androgen receptor (AR). Antiandrogen treatment is the principal preference for patients with advanced PCa. However, the molecular characteristics of PCa with antiandrogen intervention have not yet been fully uncovered.

METHODS

We first performed proteome analysis with 32 PCa tumor samples and 10 adjacent tissues using data-independent acquisition (DIA)- parallel accumulation serial fragmentation (PASEF) proteomics. Then label-free quantification (LFQ) mass spectrometry was employed to analyze protein profiles in LNCaP and PC3 cells.

RESULTS

M-type creatine kinase CKM and cartilage oligomeric matrix protein COMP were demonstrated to have the potential to be diagnostic biomarkers for PCa at both mRNA and protein levels. Several E3 ubiquitin ligases and deubiquitinating enzymes (DUBs) were significantly altered in PCa and PCa cells under enzalutamide treatment, and these proteins might reprogram proteostasis at protein levels in PCa. Finally, we discovered 127 significantly varied proteins in PCa samples with antiandrogen therapy and further uncovered 4 proteins in LNCaP cells upon enzalutamide treatment.

CONCLUSIONS

Our research reveals new potential diagnostic biomarkers for prostate cancer and might help resensitize resistance to antiandrogen therapy.

Adaptations of membrane trafficking in cancer and tumorigenesis

Membrane trafficking, a fundamental cellular process encompassing the transport of molecules to specific organelles, endocytosis at the plasma membrane and protein secretion, is crucial for cellular homeostasis and signalling. Cancer cells adapt membrane trafficking to enhance their survival and metabolism, and understanding these adaptations is vital for improving patient responses to therapy and identifying therapeutic targets. In this Review, we provide a concise overview of major membrane trafficking pathways and detail adaptations in these pathways, including COPII-dependent endoplasmic reticulum (ER)-to-Golgi vesicle trafficking, COPI-dependent retrograde Golgi-to-ER trafficking and endocytosis, that have been found in cancer. We explore how these adaptations confer growth advantages or resistance to cell death and conclude by discussing the potential for utilising this knowledge in developing new treatment strategies and overcoming drug resistance for cancer patients.

Alternative splicing in prostate cancer progression and therapeutic resistance

Prostate cancer (CaP) remains the second leading cause of cancer deaths in western men. CaP mortality results from diverse molecular mechanisms that mediate resistance to the standard of care treatments for metastatic disease. Recently, alternative splicing has been recognized as a hallmark of CaP aggressiveness. Alternative splicing events cause treatment resistance and aggressive CaP behavior and are determinants of the emergence of the two major types of late-stage treatment-resistant CaP, namely castration-resistant CaP (CRPC) and neuroendocrine CaP (NEPC). Here, we review recent multi-omics data that are uncovering the complicated landscape of alternative splicing events during CaP progression and the impact that different gene transcript isoforms can have on CaP cell biology and behavior. We discuss renewed insights in the molecular machinery by which alternative splicing occurs and contributes to the failure of systemic CaP therapies. The potential for alternative splicing events to serve as diagnostic markers and/or therapeutic targets is explored. We conclude by considering current challenges and promises associated with splicing-modulating therapies, and their potential for clinical translation into CaP patient care.

Proteomic-based stratification of intermediate-risk prostate cancer patients

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

Mass Spectrometry-Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine

Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.

Platinum-based drugs induce phenotypic alterations in nucleoli and Cajal bodies in prostate cancer cells

PURPOSE

Platinum-based drugs are cytotoxic drugs commonly used in cancer treatment. They cause DNA damage, effects of which on chromatin and cellular responses are relatively well described. Yet, the nuclear stress responses related to RNA processing are incompletely known and may be relevant for the heterogeneity with which cancer cells respond to these drugs. Here, we determine the type and extent of nuclear stress responses of prostate cancer cells to clinically relevant platinum drugs.

METHODS

We study nucleolar and Cajal body (CB) responses to cisplatin, carboplatin, and oxaliplatin with immunofluorescence-based methods in prostate cancer cells. We utilize organelle-specific markers NPM, Fibrillarin, Coilin, and SMN1, and study CB-regulatory proteins FUS and TDP-43 using siRNA-mediated downregulation.

RESULTS

Different types of prostate cancer cells have different sensitivities to platinum drugs. With equally cytotoxic doses, cisplatin, and oxaliplatin induce prominent nucleolar and CB stress responses while the nuclear stress phenotypes to carboplatin are milder. We find that Coilin is a stress-specific marker for platinum drug response heterogeneity. We also find that CB-associated, stress-responsive RNA binding proteins FUS and TDP-43 control Coilin and CB biology in prostate cancer cells and, further, that TDP-43 is associated with stress-responsive CBs in prostate cancer cells.

CONCLUSION

Our findings provide insight into the heterologous responses of prostate cancer cells to different platinum drug treatments and indicate Coilin and TDP-43 as stress mediators in the varied outcomes. These results help understand cancer drug responses at a cellular level and have implications in tackling heterogeneity in cancer treatment outcomes.

Fatty-Acid-Binding Proteins: From Lipid Transporters to Disease Biomarkers

Fatty-acid-binding proteins (FABPs) serve a crucial role in the metabolism and transport of fatty acids and other hydrophobic ligands as an intracellular protein family. They are also recognized as a critical mediator in the inflammatory and ischemic pathways. FABPs are found in a wide range of tissues and organs, allowing them to contribute to various disease/injury developments that have not been widely discussed. We have collected and analyzed research journals that have investigated the role of FABPs in various diseases. Through this review, we discuss the findings on the potential of FABPs as biomarkers for various diseases in different tissues and organs, looking at their expression levels and their roles in related diseases according to available literature data. FABPs have been reported to show significantly increased expression levels in various tissues and organs associated with metabolic and inflammatory diseases. Therefore, FABPs are a promising novel biomarker that needs further development to optimize disease diagnosis and prognosis methods along with previously discovered markers.

A pathway activity-based proteomic classifier stratifies prostate tumors into two subtypes

Prostate cancer (PCa) is the second most common cancer in males worldwide. The risk stratification of PCa is mainly based on morphological examination. Here we analyzed the proteome of 667 tumor samples from 487 Chinese PCa patients and characterized 9576 protein groups by PulseDIA mass spectrometry. Then we developed a pathway activity-based classifier concerning 13 proteins from seven pathways, and dichotomized the PCa patients into two subtypes, namely PPS1 and PPS2. PPS1 is featured with enhanced innate immunity, while PPS2 with suppressed innate immunity. This classifier exhibited a correlation with PCa progression in our cohort and was further validated by two published transcriptome datasets. Notably, PPS2 was significantly correlated with poor biochemical recurrence (BCR)/metastasis-free survival (log-rank P-value < 0.05). The PPS2 was also featured with cell proliferation activation. Together, our study presents a novel pathway activity-based stratification scheme for PCa.

Emerging proteins involved in castration‑resistant prostate cancer via the AR‑dependent and AR‑independent pathways (Review)

Despite achieving optimal initial responses to androgen deprivation therapy, most patients with prostate cancer eventually progress to a poor prognosis state known as castration‑resistant prostate cancer (CRPC). Currently, there is a notable absence of reliable early warning biomarkers and effective treatment strategies for these patients. Although androgen receptor (AR)‑independent pathways have been discovered and acknowledged in recent years, the AR signaling pathway continues to play a pivotal role in the progression of CRPC. The present review focuses on newly identified proteins within human CRPC tissues. These proteins encompass both those involved in AR‑dependent and AR‑independent pathways. Specifically, the present review provides an in‑depth summary and analysis of the emerging proteins within AR bypass pathways. Furthermore, the significance of these proteins as potential biomarkers and therapeutic targets for treating CRPC is discussed. Therefore, the present review offers valuable theoretical insights and clinical perspectives to comprehensively enhance the understanding of CRPC.

Fatty acid binding protein 5 regulates docetaxel sensitivity in taxane-resistant prostate cancer cells

Prostate cancer is a leading cause of cancer-related deaths in men in the United States. Although treatable when detected early, prostate cancer commonly transitions to an aggressive castration-resistant metastatic state. While taxane chemotherapeutics such as docetaxel are mainstay treatment options for prostate cancer, taxane resistance often develops. Fatty acid binding protein 5 (FABP5) is an intracellular lipid chaperone that is upregulated in advanced prostate cancer and is implicated as a key driver of its progression. The recent demonstration that FABP5 inhibitors produce synergistic inhibition of tumor growth when combined with taxane chemotherapeutics highlights the possibility that FABP5 may regulate other features of taxane function, including resistance. Employing taxane-resistant DU145-TXR cells and a combination of cytotoxicity, apoptosis, and cell cycle assays, our findings demonstrate that FABP5 knockdown sensitizes the cells to docetaxel. In contrast, docetaxel potency was unaffected by FABP5 knockdown in taxane-sensitive DU145 cells. Taxane-resistance in DU145-TXR cells stems from upregulation of the P-glycoprotein ATP binding cassette subfamily B member 1 (ABCB1). Expression analyses and functional assays confirmed that FABP5 knockdown in DU145-TXR cells markedly reduced ABCB1 expression and activity, respectively. Our study demonstrates a potential new function for FABP5 in regulating taxane sensitivity and the expression of a major P-glycoprotein efflux pump in prostate cancer cells.

Complementary analysis of proteome-wide proteomics reveals changes in RNA binding protein-profiles during prostate cancer progression

BACKGROUND

Accumulating evidence indicates importance of RNA regulation in cancer. This includes events such as splicing, translation, and regulation of noncoding RNAs, functions which are governed by RNA binding proteins (RBPs).

AIMS

To find which RBPs could be relevant for prostate cancer, we performed systematic screening of RBP expression in clinical prostate cancer.

METHODS AND RESULTS

We interrogated four proteome-wide proteomics datasets including tumor samples of primary, castration resistant, and metastatic prostate cancer. We found that, while the majority of RBPs are expressed but not significantly altered during prostate cancer development and progression, expression of several RBPs increases in advanced disease. Interestingly, most of the differentially expressed RBPs are not targets of differential posttranscriptional phosphorylation during disease progression. The RBPs undergoing expression changes have functions in, especially, poly(A)-RNA binding, nucleocytoplasmic transport, and cellular stress responses, suggesting that these may play a role in formation of castration resistance. Pathway analyzes indicate that increased ribosome production and chromatin-related functions of RBPs are also linked to castration resistant and metastatic prostate cancers. We selected a group of differentially expressed RBPs and studied their role in cultured prostate cancer cells. With siRNA screens, several of these were indicated in survival (DDX6, EIF4A3, PABPN1), growth (e.g., EIF5A, HNRNPH2, LRRC47, and NVL), and migration (e.g., NOL3 and SLTM) of prostate cancer cells. Our analyzes further show that RRP9, a U3 small nucleolar protein essential for ribosome formation, undergoes changes at protein level during metastasis in prostate cancer.

CONCLUSION

In this work, we recognized significant molecular alterations in RBP profiles during development and evolution of prostate cancer. Our study further indicates several functionally significant RBPs warranting further investigation for their functions and possible targetability in prostate cancer.

Proteome-wide mendelian randomization study implicates therapeutic targets in common cancers

BACKGROUND

The interest in targeted cancer therapies has been growing rapidly. While numerous cancer biomarkers and targeted treatment strategies have been developed and employed, there are still significant limitations and challenges in the early diagnosis and targeted treatment of cancers. Accordingly, there is an urgent need to identify novel targets and develop new targeted drugs.

METHODS

The study was conducted using combined cis-Mendelian randomization (cis-MR) and colocalization analysis. We analyzed data from 732 plasma proteins to identify potential drug targets associated with eight site-specific cancers. These findings were further validated using the UK Biobank dataset. Then, a protein-protein interaction network was also constructed to examine the interplay between the identified proteins and the targets of existing cancer medications.

RESULTS

This MR analysis revealed associations between five plasma proteins and prostate cancer, five with breast cancer, and three with lung cancer. Subsequently, these proteins were classified into four distinct target groups, with a focus on tier 1 and 2 targets due to their higher potential to become drug targets. Our study indicatied that genetically predicted KDELC2 (OR: 0.89, 95% CI 0.86-0.93) and TNFRSF10B (OR: 0.74, 95% CI 0.65-0.83) are inversely associated with prostate cancer. Furthermore, we observed an inverse association between CPNE1 (OR: 0.96, 95% CI 0.94-0.98) and breast cancer, while PDIA3 (OR: 1.19, 95% CI 1.10-1.30) were found to be associated with the risk of breast cancer. In addition, we also propose that SPINT2 (OR: 1.05, 95% CI 1.03-1.06), GSTP1 (OR: 0.82, 95% CI 0.74-0.90), and CTSS (OR: 0.91, 95% CI 0.88-0.95) may serve as potential therapeutic targets in prostate cancer. Similarly, GDI2 (OR: 0.85, 95% CI 0.80-0.91), ISLR2 (OR: 0.87, 95% CI 0.82-0.93), and CTSF (OR: 1.14, 95% CI 1.08-1.21) could potentially be targets for breast cancer. Additionally, we identified SFTPB (OR: 0.93, 95% CI 0.91-0.95), ICAM5 (OR: 0.95, 95% CI 0.93-0.97), and FLRT3 (OR: 1.10, 95% CI 1.05-1.15) as potential targets for lung cancer. Notably, TNFRSF10B, GSTP1, and PDIA3 were found to interact with the target proteins of current medications used in prostate or breast cancer treatment.

CONCLUSIONS

This comprehensive analysis has highlighted thirteen plasma proteins with potential roles in three site-specific cancers. Continued research in this area may reveal their therapeutic potential, particularly KDELC2, TNFRSF10B, CPNE1, and PDIA3, paving the way for more effective cancer treatments.

Identifying Patients With Rapid Progression From Hormone-Sensitive to Castration-Resistant Prostate Cancer: A Retrospective Study

Prostate cancer (PCa) is the second most prevalent malignancy and the fifth cause of cancer-related deaths in men. A crucial challenge is identifying the population at risk of rapid progression from hormone-sensitive prostate cancer (HSPC) to lethal castration-resistant prostate cancer (CRPC). We collected 78 HSPC biopsies and measured their proteomes using pressure cycling technology and a pulsed data-independent acquisition pipeline. We quantified 7355 proteins using these HSPC biopsies. A total of 251 proteins showed differential expression between patients with a long- or short-term progression to CRPC. Using a random forest model, we identified seven proteins that significantly discriminated long- from short-term progression patients, which were used to classify PCa patients with an area under the curve of 0.873. Next, one clinical feature (Gleason sum) and two proteins (BGN and MAPK11) were found to be significantly associated with rapid disease progression. A nomogram model using these three features was generated for stratifying patients into groups with significant progression differences (p-value = 1.3×10-4). To conclude, we identified proteins associated with a fast progression to CRPC and an unfavorable prognosis. Based on these proteins, our machine learning and nomogram models stratified HSPC into high- and low-risk groups and predicted their prognoses. These models may aid clinicians in predicting the progression of patients, guiding individualized clinical management and decisions.

Oncogenic Proteomics Approaches for Translational Research and HIV-Associated Malignancy Mechanisms

Recent advances in the field of proteomics have allowed extensive insights into the molecular regulations of the cell proteome. Specifically, this allows researchers to dissect a multitude of signaling arrays while targeting for the discovery of novel protein signatures. These approaches based on data mining are becoming increasingly powerful for identifying both potential disease mechanisms as well as indicators for disease progression and overall survival predictive and prognostic molecular markers for cancer. Furthermore, mass spectrometry (MS) integrations satisfy the ongoing demand for in-depth biomarker validation. For the purpose of this review, we will highlight the current developments based on MS sensitivity, to place quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data for future applications in cancer precision medicine. We will also discuss malignancies associated with oncogenic viruses such as Acquire Immunodeficiency Syndrome (AIDS) and suggest novel mechanisms behind this phenomenon. Human Immunodeficiency Virus type-1 (HIV-1) proteins are known to be oncogenic per se, to induce oxidative and endoplasmic reticulum stresses, and to be released from the infected or expressing cells. HIV-1 proteins can act alone or in collaboration with other known oncoproteins, which cause the bulk of malignancies in people living with HIV-1 on ART.

A new tumorgraft panel to accelerate precision medicine in prostate cancer

Background

Despite the significant advances in the management of advanced prostate cancer (PCa), metastatic PCa is currently considered incurable. For further investigations in precision treatment, the development of preclinical models representing the complex prostate tumor heterogeneity are mandatory. Accordingly, we aimed to establish a resource of patient-derived xenograft (PDX) models that exemplify each phase of this multistage disease for accurate and rapid evaluation of candidate therapies.

Methods

Fresh tumor samples along with normal corresponding tissues were obtained directly from patients at surgery. To ensure that the established models reproduce the main features of patient's tumor, both PDX tumors at multiple passages and patient's primary tumors, were processed for histological characteristics. STR profile analyses were also performed to confirm patient identity. Finally, the responses of the PDX models to androgen deprivation, PARP inhibitors and chemotherapy were also evaluated.

Results

In this study, we described the development and characterization of 5 new PDX models of PCa. Within this collection, hormone-naïve, androgen-sensitive and castration-resistant (CRPC) primary tumors as well as prostate carcinoma with neuroendocrine differentiation (CRPC-NE) were represented. Interestingly, the comprehensive genomic characterization of the models identified recurrent cancer driver alterations in androgen signaling, DNA repair and PI3K, among others. Results were supported by expression patterns highlighting new potential targets among gene drivers and the metabolic pathway. In addition, in vivo results showed heterogeneity of response to androgen deprivation and chemotherapy, like the responses of patients to these treatments. Importantly, the neuroendocrine model has been shown to be responsive to PARP inhibitor.

Conclusion

We have developed a biobank of 5 PDX models from hormone-naïve, androgen-sensitive to CRPC primary tumors and CRPC-NE. Increased copy-number alterations and accumulation of mutations within cancer driver genes as well as the metabolism shift are consistent with the increased resistance mechanisms to treatment. The pharmacological characterization suggested that the CRPC-NE could benefit from the PARP inhibitor treatment. Given the difficulties in developing such models, this relevant panel of PDX models of PCa will provide the scientific community with an additional resource for the further development of PDAC research.

Identification of a novel recurrent EEF2 gene amplification in familial prostate tumors

Recurrent tumor copy number variations (CNVs) in prostate cancer (PrCa) have predominantly been discovered in sporadic tumor cohorts. Here, we examined familial prostate tumors for novel CNVs as prior studies suggest these harbor distinct CNVs. Array comparative genomic hybridization of 12 tumors from an Australian PrCa family, PcTas9, highlighted multiple recurrent CNVs, including amplification of EEF2 (19p13.3) in 100% of tumors. The EEF2 CNV was examined in a further 26 familial and seven sporadic tumors from the Australian cohort and in 494 tumors unselected for family history from The Cancer Genome Atlas (TCGA). EEF2 overexpression was observed in seven PcTas9 tumors, in addition to seven other predominantly familial tumors (n_total  = 34%). EEF2 amplification was only observed in 1.4% of TCGA tumors, however 7.5% harbored an EEF2 deletion. Analysis of genes co-expressed with EEF2 revealed significant upregulation of two genes, ZNF74 and ADSL, and downregulation of PLSCR1 in both EEF2 amplified familial tumors and EEF2 deleted TCGA tumors. Furthermore, in TCGA tumors, EEF2 amplification and deletion were significantly associated with a higher Gleason score. In summary, we identified a novel PrCa CNV that was predominantly amplified in familial tumors and deleted in unselected tumors. Our results provide further evidence that familial tumors harbor distinct CNVs, potentially due to an inherited predisposition, but also suggest that regardless of how EEF2 is dysregulated, a similar set of genes involved in key cancer pathways are impacted. Given the current lack of gene-based biomarkers and clinical targets in PrCa, further investigation of EEF2 is warranted.

Identification of LncRNAs and Functional Analysis of ceRNA Related to Fatty Acid Synthesis during Flax Seed Development

Flax is a flowering plant cultivated for its oil and contains various unsaturated fatty acids. Linseed oil is known as the "deep-sea fish oil" of plants, and is beneficial to brain and blood lipids, among other positive effects. Long non-coding RNAs (lncRNAs) play an important role in plant growth and development. There are not many studies assessing how lncRNAs are related to the fatty acid synthesis of flax. The relative oil contents of the seeds of the variety Heiya NO.14 (for fiber) and the variety Macbeth (for oil) were determined at 5 day, 10 day, 20 day, and 30 day after flowering. We found that 10-20 day is an important period for ALA accumulation in the Macbeth variety. The strand-specific transcriptome data were analyzed at these four time points, and a series of lncRNAs related to flax seed development were screened. A competing endogenous RNA (ceRNA) network was constructed and the accuracy of the network was verified using qRT-PCR. MSTRG.20631.1 could act with miR156 on the same target, squamosa promoter-binding-like protein (SPL), to influence fatty acid biosynthesis through a gluconeogenesis-related pathway during flax seed development. This study provides a theoretical basis for future studies assessing the potential functions of lncRNAs during seed development.

Variant biomarker discovery using mass spectrometry-based proteogenomics

Genomic diversity plays critical roles in risk of disease pathogenesis and diagnosis. While genomic variants-including single nucleotide variants, frameshift variants, and mis-splicing isoforms-are commonly detected at the DNA or RNA level, their translated variant protein or polypeptide products are ultimately the functional units of the associated disease. These products are often released in biofluids and could be leveraged for clinical diagnosis and patient stratification. Recent emergence of integrated analysis of genomics with mass spectrometry-based proteomics for biomarker discovery, also known as proteogenomics, have significantly advanced the understanding disease risk variants, precise medicine, and biomarker discovery. In this review, we discuss variant proteins in the context of cancers and neurodegenerative diseases, outline current and emerging proteogenomic approaches for biomarker discovery, and provide a comprehensive proteogenomic strategy for detection of putative biomarker candidates in human biospecimens. This strategy can be implemented for proteogenomic studies in any field of enquiry. Our review timely addresses the need of biomarkers for aging related diseases.

HBV-infected hepatocellular carcinoma can be robustly classified into three clinically relevant subgroups by a novel analytical protocol

Liver cancer is the third leading cause of cancer-related death worldwide, and hepatocellular carcinoma (HCC) accounts for a relatively large proportion of all primary liver malignancies. Among the several known risk factors, hepatitis B virus (HBV) infection is one of the important causes of HCC. In this study, we demonstrated that the HBV-infected HCC patients could be robustly classified into three clinically relevant subgroups, i.e. Cluster1, Cluster2 and Cluster3, based on consistent differentially expressed mRNAs and proteins, which showed better generalization. The proposed three subgroups showed different molecular characteristics, immune microenvironment and prognostic survival characteristics. The Cluster1 subgroup had near-normal levels of metabolism-related proteins, low proliferation activity and good immune infiltration, which were associated with its good liver function, smaller tumor size, good prognosis, low alpha-fetoprotein (AFP) levels and lower clinical stage. In contrast, the Cluster3 subgroup had the lowest levels of metabolism-related proteins, which corresponded with its severe liver dysfunction. Also, high proliferation activity and poor immune microenvironment in Cluster3 subgroup were associated with its poor prognosis, larger tumor size, high AFP levels, high incidence of tumor thrombus and higher clinical stage. The characteristics of the Cluster2 subgroup were between the Cluster1 and Cluster3 groups. In addition, MCM2-7, RFC2-5, MSH2, MSH6, SMC2, SMC4, NCPAG and TOP2A proteins were significantly upregulated in the Cluster3 subgroup. Meanwhile, abnormally high phosphorylation levels of these proteins were associated with high levels of DNA repair, telomere maintenance and proliferative features. Therefore, these proteins could be identified as potential diagnostic and prognostic markers. In general, our research provided a novel analytical protocol and insights for the robust classification, treatment and prevention of HBV-infected HCC.

Unraveling the Peculiar Features of Mitochondrial Metabolism and Dynamics in Prostate Cancer

Prostate cancer (PCa) is the second leading cause of cancer deaths among men in Western countries. Mitochondria, the "powerhouse" of cells, undergo distinctive metabolic and structural dynamics in different types of cancer. PCa cells experience peculiar metabolic changes during their progression from normal epithelial cells to early-stage and, progressively, to late-stage cancer cells. Specifically, healthy cells display a truncated tricarboxylic acid (TCA) cycle and inefficient oxidative phosphorylation (OXPHOS) due to the high accumulation of zinc that impairs the activity of m-aconitase, the enzyme of the TCA cycle responsible for the oxidation of citrate. During the early phase of cancer development, intracellular zinc levels decrease leading to the reactivation of m-aconitase, TCA cycle and OXPHOS. PCa cells change their metabolic features again when progressing to the late stage of cancer. In particular, the Warburg effect was consistently shown to be the main metabolic feature of late-stage PCa cells. However, accumulating evidence sustains that both the TCA cycle and the OXPHOS pathway are still present and active in these cells. The androgen receptor axis as well as mutations in mitochondrial genes involved in metabolic rewiring were shown to play a key role in PCa cell metabolic reprogramming. Mitochondrial structural dynamics, such as biogenesis, fusion/fission and mitophagy, were also observed in PCa cells. In this review, we focus on the mitochondrial metabolic and structural dynamics occurring in PCa during tumor development and progression; their role as effective molecular targets for novel therapeutic strategies in PCa patients is also discussed.

Small nucleolar RNA host gene 25 is a long non-coding RNA helps diagnose and predict outcomes in prostate cancer

BACKGROUND

The role of a long non-coding RNA called small nucleolar RNA host gene 25 (SNHG25) has been studied in some tumor types but the correlation between SNHG25 and PCA remains unknown.

METHODS

The relationship between clinicopathologic characteristics and SNHG25 expression was evaluated using The Cancer Genome Atlas data. The binary classifier value of SNHG25 was calculated using areas under receiver operating characteristic (ROC) curves. Outcomes were evaluated using Kaplan-Meier and Cox regression analyses. Gene set enrichment was performed to identify potential SNHG25 functions.

RESULTS

SNHG25 expression was significantly increased in PCA and correlated with age, primary therapy outcome, N stage, Gleason score, and residual tumor (p < 0.05). ROC curves demonstrated the effect of SNHG25 on diagnosis and outcomes (area under the curve = 0.923). Higher SNHG25 expression predicted shorter progression-free interval (PFI) (p < 0.001), and Cox regression showed that SNHG25 expression was an independent risk factor for reduced PFI (p = 0.028). SNHG25 expression was associated with mRNA and protein metabolism.

CONCLUSIONS

SNHG25 expression increases significantly in PCA and is negatively associated with PFI. It is a potential diagnostic and prognostic biomarker in PCA.

Comparative Proteomic and Transcriptomic Analysis of the Impact of Androgen Stimulation and Darolutamide Inhibition

Several inhibitors of androgen receptor (AR) function are approved for prostate cancer treatment, and their impact on gene transcription has been described. However, the ensuing effects at the protein level are far less well understood. We focused on the AR signaling inhibitor darolutamide and confirmed its strong AR binding and antagonistic activity using the high throughput cellular thermal shift assay (CETSA HT). Then, we generated comprehensive, quantitative proteomic data from the androgen-sensitive prostate cancer cell line VCaP and compared them to transcriptomic data. Following treatment with the synthetic androgen R1881 and darolutamide, global mass spectrometry-based proteomics and label-free quantification were performed. We found a generally good agreement between proteomic and transcriptomic data upon androgen stimulation and darolutamide inhibition. Similar effects were found both for the detected expressed genes and their protein products as well as for the corresponding biological programs. However, in a few instances there was a discrepancy in the magnitude of changes induced on gene expression levels compared to the corresponding protein levels, indicating post-transcriptional regulation of protein abundance. Chromatin immunoprecipitation DNA sequencing (ChIP-seq) and Hi-C chromatin immunoprecipitation (HiChIP) revealed the presence of androgen-activated AR-binding regions and long-distance AR-mediated loops at these genes.

Potential Role of Seven Proteomics Tissue Biomarkers for Diagnosis and Prognosis of Prostate Cancer in Urine

As the currently available tests for the clinical management of prostate cancer (PCa) are still far from providing precise diagnosis and risk stratification, the identification of new molecular marker(s) remains a pertinent clinical need. Candidate PCa biomarkers from the published proteomic comparative studies of prostate tissue (2002-2020) were collected and systematically evaluated. AZGP1, MDH2, FABP5, ENO1, GSTP1, GSTM2, and EZR were chosen for further evaluation in the urine of 85 PCa patients and controls using ELISA. Statistically significant differences in protein levels between PCa and BPH showed FABP5 (p = 0.019) and ENO1 (p = 0.015). A biomarker panel based on the combination of FABP5, ENO1, and PSA provided the highest accuracy (AUC = 0.795) for PCa detection. The combination of FABP5, EZR, AZGP1, and MDH2 showed AUC = 0.889 in PCa prognosis, with 85.29% of the samples correctly classified into low and high Gleason score (GS) groups. The addition of PSA to the panel slightly increased the AUC to 0.914. AZGP1, FABP5, and EZR showed significant correlation with GS, stage, and percentage of positive biopsy cores. Although validation using larger patient cohorts will be necessary to establish the credibility of the proposed biomarker panels in a clinical context, this study opens a way for the further testing of more high-quality proteomics biomarkers, which could ultimately add value to the clinical management of PCa.

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.

Comparative Analysis of Proteomes and Phosphoproteomes in Patients with Prostate Cancer Using Different Surgical Conditions

Purpose

To establish the standard of procedure in preparing benign and cancerous prostate tissues and evaluate the quality of proteomics and phosphoproteomics during transurethral resection of the prostate (TUR-P) with different surgical conditions.

Materials and Methods

TUR-P tissue samples from three patients, two diagnosed with prostate cancer and one with benign prostatic hyperplasia, were each analyzed under three different conditions, based on differences in energy values, tissue locations, and surgical techniques. Global- and phosphorylated proteomic profiles of prostate tissues were analyzed by liquid chromatography-tandem mass spectrometry.

Results

A total of 6,019 global proteins and 4,280 phosphorylated peptides were identified in the nine tissues. The quantitative distributions of proteins and phosphorylation in tissues from the same patient were not affected by changes in the surgical conditions, but indirect relative comparisons differed among patients. Phosphorylation levels, especially of proteins involved in the androgen receptor pathway, important in prostate cancer, were preserved in each patient.

Conclusions

Proteomic profiles of prostate tissue collected by TUR-P were not significantly affected by energy levels, tissue location, or surgical technique. In addition, since protein denaturation of samples through TUR-P is rarely confirmed in this study, we think that it will be an important guide for tissue samples in castration resistant prostate cancer patients, where it is difficult to obtain tissue. This result is the first report about proteomic and phosphoproteomic results with TUR-P samples in prostate cancer and will be theoretical basis in protein analysis research with prostate cancer tissues.

Proteomics and liquid biopsy characterization of human EMT-related metastasis in colorectal cancer

Tumor cells undergo epithelial-mesenchymal transition (EMT), however, there is a room of disagreement in role of EMT heterogeneity to colorectal cancer metastasis (mCRC) evolution. To uncover new EMT-related metastasis proteins and pathways, we addressed the EMT status in colorectal cancer liver metastasis patient-derived CTCs to identify proteins that promote their distant metastasis. And then, we performed a comparative proteomic analysis in matched pairs of primary tumor tissues, adjacent mucosa tissues and liver metastatic tissues. By integrative analysis we show that, unstable Epithelial/Mesenchymal (E/M)-type CTCs had the strongest liver metastases formation ability and the proportion of E/M-type CTCs correlated with distant metastases. Using an optimized proteomic workflow including data independent acquisition (DIA) and parallel reaction monitoring (PRM), we identified novel EMT-related protein cluster (GNG2, COL6A1, COL6A2, DCN, COL6A3, LAMB2, TNXB, CAVIN1) and well-described (ERBB2) core protein level changes in EMT-related metastasis progression, and the proteomic data indicate ERBB2, COL6A1 and CAVIN1 are promising EMT-related metastatic biomarker candidates. This study contributes to our understanding of the role that EMT plays in CRC metastasis and identifies heterogeneous EMT phenotypes as a key piece for tumor progression and prognosis. We further propose that therapies targeting this aggressive subset (E/M-type) of CTCs and related protein may be worthy of exploration as potential suppressors of metastatic evolution.

Prostate cancer resistance leads to a global deregulation of translation factors and unconventional translation

Emerging evidence associates translation factors and regulators to tumorigenesis. However, our understanding of translational changes in cancer resistance is still limited. Here, we generated an enzalutamide-resistant prostate cancer (PCa) model, which recapitulated key features of clinical enzalutamide-resistant PCa. Using this model and poly(ribo)some profiling, we investigated global translation changes that occur during acquisition of PCa resistance. We found that enzalutamide-resistant cells exhibit an overall decrease in mRNA translation with a specific deregulation in the abundance of proteins involved in mitochondrial processes and in translational regulation. However, several mRNAs escape this translational downregulation and are nonetheless bound to heavy polysomes in enzalutamide-resistant cells suggesting active translation. Moreover, expressing these corresponding genes in enzalutamide-sensitive cells promotes resistance to enzalutamide treatment. We also found increased association of long non-coding RNAs (lncRNAs) with heavy polysomes in enzalutamide-resistant cells, suggesting that some lncRNAs are actively translated during enzalutamide resistance. Consistent with these findings, expressing the predicted coding sequences of known lncRNAs JPX, CRNDE and LINC00467 in enzalutamide-sensitive cells drove resistance to enzalutamide. Taken together, this suggests that aberrant translation of specific mRNAs and lncRNAs is a strong indicator of PCa enzalutamide resistance, which points towards novel therapeutic avenues that may target enzalutamide-resistant PCa.

Prostate cancer in omics era

Recent advances in omics technology have prompted extraordinary attempts to define the molecular changes underlying the onset and progression of a variety of complex human diseases, including cancer. Since the advent of sequencing technology, cancer biology has become increasingly reliant on the generation and integration of data generated at these levels. The availability of multi-omic data has transformed medicine and biology by enabling integrated systems-level approaches. Multivariate signatures are expected to play a role in cancer detection, screening, patient classification, assessment of treatment response, and biomarker identification. This review reports current findings and highlights a number of studies that are both novel and groundbreaking in their application of multi Omics to prostate cancer.

Fecal microbiome transplantation attenuates manganese-induced neurotoxicity through regulation of the apelin signaling pathway by inhibition of autophagy in mouse brain

Manganese (Mn) is a common environmental pollutant. Mn exposure can lead to neurodegenerative diseases resembling Parkinson's disease, and has become a major public health concern. However, the mechanism of Mn-induced neurotoxicity in the brain is not clear. Fecal microbiome transplantation (FMT) may alleviate the neurotoxicity of Mn exposure by remodeling the gut microbiota. In this study, MnCl₂ (manganese chloride) was administered to mice as in drinking water (Mn: 200 mg/L), and fecal matter from donor mice was administered by oral gavage every other day to the recipient mice. The Mn exposure model (Mn group) and FMT model (Mn+FMT group) were established and analyzed 5 weeks post-exposure. The Wipi1 gene exhibited the most significant increase associated with Mn exposure and Mn+FMT treatment groups based on transcriptome analysis. Combined analysis of transcriptomics and proteomics demonstrated that the apelin signaling pathway is the main pathway affected by FMT during Mn exposure. Immunofluorescence and Western blot showed that the expression of key proteins (Beclin-1, LC-3B, and PINK1) associated with autophagy in the hippocampus was robustly activated in the Mn exposure group, but attenuation was observed in Mn+FMT mice, suggesting a critical role of autophagy in neurotoxicity induced by Mn exposure. Our research provides evidence for the neurotoxic effects of Mn exposure through autophagy activation and provides an underlying mechanism of FMT protection against Mn-induced neurotoxicity through regulation of the apelin signaling pathway.

Disassembly of α6β4-mediated hemidesmosomal adhesions promotes tumorigenesis in PTEN-negative prostate cancer by targeting plectin to focal adhesions

Loss of α6β4-dependent hemidesmosomal adhesions has been observed during prostate cancer progression. However, the significance and underlying mechanisms by which aberrant hemidesmosome assembly may modulate tumorigenesis remain elusive. Using an extensive CRISPR/Cas9-mediated genetic engineering approaches in different prostate cancer cell lines combined with in vivo tumorigenesis studies in mice, bone marrow-on-chip assays and bioinformatics, as well as histological analysis of prostate cancer patient cohorts, we demonstrated that simultaneous loss of PTEN and hemidesmosomal adhesions induced several tumorigenic properties including proliferation, migration, resistance to anoikis, apoptosis, and drug treatment in vitro, and increased metastatic capacity in vivo. These effects were plectin-depended and plectin was associated with actin-rich adhesions upon hemidesmosome disruption in PTEN-negative prostate cancer cells leading to activation of EGFR/PI3K/Akt- and FAK/Src-pathways. These results suggest that analysis of PTEN and hemidesmosomal proteins may have diagnostic value helping to stratify prostate cancer patients with high risk for development of aggressive disease and highlight actin-associated plectin as a potential therapeutic target specifically in PTEN/hemidesmosome dual-negative prostate cancer.

The Integration of Metabolomics with Other Omics: Insights into Understanding Prostate Cancer

Our understanding of prostate cancer (PCa) has shifted from solely caused by a few genetic aberrations to a combination of complex biochemical dysregulations with the prostate metabolome at its core. The role of metabolomics in analyzing the pathophysiology of PCa is indispensable. However, to fully elucidate real-time complex dysregulation in prostate cells, an integrated approach based on metabolomics and other omics is warranted. Individually, genomics, transcriptomics, and proteomics are robust, but they are not enough to achieve a holistic view of PCa tumorigenesis. This review is the first of its kind to focus solely on the integration of metabolomics with multi-omic platforms in PCa research, including a detailed emphasis on the metabolomic profile of PCa. The authors intend to provide researchers in the field with a comprehensive knowledge base in PCa metabolomics and offer perspectives on overcoming limitations of the tool to guide future point-of-care applications.

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.

Mechanisms of Resistance to Second-Generation Antiandrogen Therapy for Prostate Cancer: Actual Knowledge and Perspectives

Prostate cancer therapy for locally advanced and metastatic diseases includes androgen deprivation therapy (ADT). Second-generation antiandrogens have a role in castration-resistant prostate cancer. Nevertheless, some patients do not respond to this therapy, and eventually all the patients became resistant. This is due to modifications to intracellular signaling pathways, genomic alteration, cytokines production, metabolic switches, constitutional receptor activation, overexpression of some proteins, and regulation of gene expression. The aim of this review is to define the most important mechanisms that drive this resistance and the newest discoveries in this field, specifically for enzalutamide and abiraterone, with potential implications for future therapeutic targets. Furthermore, apalutamide and darolutamide share some resistance mechanisms with abiraterone and enzalutamide and could be useful in some resistance settings.

Assessing the Potential Prognostic and Immunological Role of TK1 in Prostate Cancer

Background: It has been reported that thymidine kinase 1 (TK1) was up-regulated in multiple malignancies and participated in the regulation of tumor malignant behavior. However, its specific role in prostate cancer (PCa) remains unclear. Methods: TK1 expression in PCa patients and cell lines was identified via crossover analysis of the public datasets. A series of in vitro experiments and in vivo models was applied to investigate the function of TK1 in PCa. Functional enrichment analyses were further conducted to explore the underlying mechanism. Additionally, TISIDB was applied to explore the correlation between TK1 expression and tumor-infiltrating lymphocytes, immune subtypes, and immune regulatory factors. Results: TK1 expression was significantly up-regulated in PCa patients and cell lines. TK1 ablation inhibited tumor cell proliferation and migration potential, and in vivo experiments showed that TK1 inactivation can significantly restrain tumor growth. Functional enrichment analysis revealed TK1-related hub genes (AURKB, CCNB2, CDC20, CDCA5, CDK1, CENPA, CENPM, KIF2C, NDC80, NUF2, PLK1, SKA1, SPC25, ZWINT), and found that TK1 was closely involved in the regulation of cell cycle. Moreover, elevated mRNA expression of TK1 was related with higher Gleason score, higher clinical stage, higher pathological stage, higher lymph node stage, shorter overall survival, and DFS in PCa patients. Particularly, TK1 represented attenuated expression in C3 PCa and was related with infiltration of CD4+, CD8+ T cells, and dendritic cells as well as immunomodulator expression. Conclusion: Our study indicates that TK1 is a prognostic predictor correlated with poor outcomes of PCa patients, and for the first time represented that TK1 can promote the progression of PCa. Therefore, TK1 may be a potential diagnostic and prognostic biomarker, as well as a therapeutic target for PCa.

Peroxisome Proliferator Activated Receptor Gamma Coactivator-1 Alpha: A Double-Edged Sword in Prostate Cancer

Peroxisome proliferator activated receptor gamma coactivator-1 alpha (PGC-1α/PPARGC1A) is a pivotal transcriptional coactivator involved in the regulation of mitochondrial metabolism, including biogenesis and oxidative metabolism. PGC-1α is finely regulated by AMP-activated protein kinases (AMPKs), the role of which in tumors remains controversial to date. In recent years, a growing amount of research on PGC-1α and tumor metabolism has emphasized its importance in a variety of tumors, including prostate cancer (PCA). Compelling evidence has shown that PGC-1α may play dual roles in promoting and inhibiting tumor development under certain conditions. Therefore, a better understanding of the critical role of PGC-1α in PCA pathogenesis will provide new insights into targeting PGC-1α for the treatment of this disease. In this review, we highlight the procancer and anticancer effects of PGC-1α in PCA and aim to provide a theoretical basis for targeting AMPK/PGC-1α to inhibit the development of PCA. In addition, our recent findings provide a candidate drug target and theoretical basis for targeting PGC-1α to regulate lipid metabolism in PCA.

miR-32 promotes MYC-driven prostate cancer

miR-32 is an androgen receptor (AR)-regulated microRNA, expression of which is increased in castration-resistant prostate cancer (PC). We have previously shown that overexpression of miR-32 in the prostate of transgenic mice potentiates proliferation in prostate epithelium. Here, we set out to determine whether increased expression of miR-32 influences growth or phenotype in prostate adenocarcinoma in vivo. We studied transgenic mice expressing MYC oncogene (hiMYC mice) to induce tumorigenesis in the mouse prostate and discovered that transgenic overexpression of miR-32 resulted in increased tumor burden as well as a more aggressive tumor phenotype in this model. Elevated expression of miR-32 increased proliferation as assessed by Ki-67 immunohistochemistry, increased nuclear density, and higher mitotic index in the tumors. By gene expression analysis of the tumorous prostate tissue, we confirmed earlier findings that miR-32 expression regulates prostate secretome by modulating expression levels of several PC-related target genes such as Spink1, Spink5, and Msmb. Further, we identified Pdk4 as a tumor-associated miR-32 target in the mouse prostate. Expression analysis of PDK4 in human PC reveals an inverse correlation with miR-32 expression and Gleason score, a decrease in castration-resistant and metastatic tumors compared to untreated primary PC, and an association of low PDK4 expression with a shorter recurrence-free survival of patients. Although decreased PDK4 expression induces the higher metabolic activity of PC cells, induced expression of PDK4 reduces both mitotic respiration and glycolysis rates as well as inhibits cell growth. In conclusion, we show that miR-32 promotes MYC-induced prostate adenocarcinoma and identifies PDK4 as a PC-relevant metabolic target of miR-32-3p.