Metabolomic profiling for the identification of novel diagnostic markers and therapeutic targets in prostate cancer: an update

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.

Efficacy of liquid biopsy for genetic mutations determination in non-small cell lung cancer: a systematic review on literatures

BACKGROUND

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide and is often diagnosed at advanced stages, limiting treatment options. This systematic review aims to evaluate the efficacy of liquid biopsy in detecting genetic mutations in NSCLC, focusing on its sensitivity, specificity, clinical utility, and potential to guide personalized treatment strategies.

METHODS

A systematic search was conducted in PubMed, Scopus, Embase, Web of Science, and Cochrane Library to identify relevant studies published between 1990 and September 2024. Eligible studies included comparative analyses of liquid biopsy techniques for NSCLC diagnosis, prognosis, progression, or treatment response. This review adheres to the PRISMA 2020 guidelines and assesses study quality using the QUADAS framework.

RESULTS

A total of 30 studies were included. Digital droplet PCR (ddPCR) demonstrated the highest sensitivity, detecting low-frequency mutations such as EGFR T790M at levels as low as 0.01%. Next-generation sequencing (NGS) provided comprehensive mutational profiling, revealing tumor heterogeneity and co-existing mutations but required high-quality plasma samples. The cobas EGFR Mutation Test, while less sensitive than ddPCR, remains widely used due to its clinical accessibility. Emerging methods, including extracellular vesicle analysis, show promise but require further validation. Additionally, liquid biopsy effectively identified non-EGFR mutations, such as KRAS, ALK, and MET amplifications, expanding its clinical applicability.

CONCLUSION

Liquid biopsy is a transformative tool in NSCLC management, offering a minimally invasive approach for mutation detection, disease monitoring, and treatment guidance. Future research should focus on multicenter trials and emerging technologies to enhance clinical integration and broaden applicability across different cancer types.

Prostate cancer risk biomarkers from large cohort and prospective metabolomics studies: A systematic review

Prostate cancer (PCa) is one of the leading causes of cancer-related deaths among men. The heterogeneous nature of this disease presents challenges in its diagnosis, prognosis, and treatment. Numerous potential predictive, diagnostic, prognostic, and risk assessment biomarkers have been proposed through various population studies. However, to date, no metabolite biomarker has been approved or validated for the diagnosis, prognosis, or risk assessment of PCa. Recognizing that systematic reviews of case reports or heterogenous studies cannot reliably establish causality, this review analyzed 29 large prospective metabolomics studies that utilized harmonized criteria for patient selection, consistent methodologies for blood sample collection and storage, data analysis, and that are available in public repositories. By focusing on these large prospective studies, we identified 42 metabolites that were consistently replicated by different authors and across cohort studies. These metabolites have the potential to serve as PCa risk-assessment or predictive biomarkers. A discussion on their associations with dietary sources or dietary patterns is also provided. Further detailed exploration of the relationship with diet, supplement intake, nutrition patterns, contaminants, lifestyle factors, and pre-existing comorbidities that may predispose individuals to PCa is warranted for future research and validation.

Tumor upgrading among very favorable intermediate-risk prostate cancer patients treated with robot-assisted radical prostatectomy: how can it impact the clinical course?

PURPOSE

We sought to investigate predictors of unfavorable tumor upgrading in very favorable intermediate-risk (IR) prostate cancer (PCa) patients treated with robot-assisted radical prostatectomy, in addition to evaluate how it may affect the risk of disease progression.

METHODS

A very favorable subset of IR PCa patients presenting with prostate-specific antigen (PSA) < 10 ng/mL, percentage of biopsy positive cores (BPC) < 50%, and either International Society of Urological Pathology (ISUP) grade group 1 and clinical stage T2b or ISUP grade group 2 and clinical stage T1c-2b was identified. Unfavorable pathology at radical prostatectomy was defined as the presence of ISUP grade group > 2 (unfavorable tumor upgrading), extracapsular extension (ECE), and seminal vesicle invasion (SVI). Disease progression was defined as the event of biochemical recurrence and/or local recurrence and/or distant metastases. Associations were evaluated by Cox regression and logistic regression analyses.

RESULTS

Overall, 210 patients were identified between January 2013 and October 2020. Unfavorable tumor upgrading was detected in 71 (33.8%) cases, and adverse tumor stage, including ECE or SVI in 18 (8.6%) and 11 (5.2%) patients, respectively. Median (interquartile range) follow-up was 38.5 (16-61) months. PCa progression occurred in 24 (11.4%) patients. Very favorable IR PCa patients with unfavorable tumor upgrading at final pathology showed a persistent risk of disease progression, which hold significance after adjustment for all factors (Hazard Ratio [HR]: 5.95, 95% Confidence Interval [CI]: 1.97-17.92, p = 0.002) of which PSA was an independent predictor (HR: 1.52, 95% CI 1.12-2.08, p = 0.008). Moreover, these subjects were more likely to belong to the biopsy ISUP grade group 2.

CONCLUSIONS

Very favorable IR PCa patients hiding unfavorable tumor upgrading were more likely to experience disease progression. Unfavorable tumor upgrading involved about one-third of cases and was less likely to occur in patients presenting with biopsy ISUP grade group 1. Tumor misclassification is an issue to discuss, when counseling this subset of patients for active surveillance because of the risk of delayed active treatment.

Homologous Recombination Repair Gene Mutations in Prostate Cancer: Prevalence and Clinical Value

Despite advances in our understanding of the molecular landscape of prostate cancer and the development of novel biomarker-driven therapies, the prognosis of patients with metastatic prostate cancer that is resistant to conventional hormonal therapy remains poor. Data suggest that a significant proportion of patients with metastatic castration-resistant prostate cancer (mCRPC) have mutations in homologous recombination repair (HRR) genes and may benefit from poly(ADP-ribose) polymerase (PARP) inhibitors. However, the adoption of HRR gene mutation testing in prostate cancer remains low, meaning there is a missed opportunity to identify patients who may benefit from targeted therapy with PARP inhibition, with or without novel hormonal agents. Here, we review the current knowledge regarding the clinical significance of HRR gene mutations in prostate cancer and discuss the efficacy of PARP inhibition in patients with mCRPC. This comprehensive overview aims to increase the clinical implementation of HRR gene mutation testing and inform future efforts in personalized treatment of prostate cancer.

Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications

Prostate cancer (PCa) is a significant global contributor to mortality, predominantly affecting males aged 65 and above. The field of omics has recently gained traction due to its capacity to provide profound insights into the biochemical mechanisms underlying conditions like prostate cancer. This involves the identification and quantification of low-molecular-weight metabolites and proteins acting as crucial biochemical signals for early detection, therapy assessment, and target identification. A spectrum of analytical methods is employed to discern and measure these molecules, revealing their altered biological pathways within diseased contexts. Metabolomics and proteomics generate refined data subjected to detailed statistical analysis through sophisticated software, yielding substantive insights. This review aims to underscore the major contributions of multi-omics to PCa research, covering its core principles, its role in tumor biology characterization, biomarker discovery, prognostic studies, various analytical technologies such as mass spectrometry and Nuclear Magnetic Resonance, data processing, and recent clinical applications made possible by an integrative "omics" approach. This approach seeks to address the challenges associated with current PCa treatments. Hence, our research endeavors to demonstrate the valuable applications of these potent tools in investigations, offering significant potential for understanding the complex biochemical environment of prostate cancer and advancing tailored therapeutic approaches for further development.

Evaluation of HNF1B, KLK3, ELAC2, TMPRSS2-ERG, and CTNNB1 polymorphisms associated with prostate cancer in samples of patients from HUPE-UERJ

PURPOSE

Prostate cancer (PCa) is the leading cause of death among men in 48 countries. Genetic alterations play a significant role in PCa carcinogenesis. For the hypothesis of this research, five unique polymorphisms (SNP) were investigated in different genes that showed to be associated in different ways with PCa: rs4430796, rs2735839, rs4792311, rs12329760, and rs28931588, respectively for the genes HNF1B, KLK3, ELAC2, TMPRSS2-ERG, and CTNNB1.

PATIENTS AND METHODS

Blood samples from 426 subjects were evaluated: 290 controls (161 females and 129 males) and 136 PCa patients. SNP were determined by real-time polymerase chain reaction. TaqMan SNP genotyping assay. In the control samples, the SNPs were defined in association with the self-reported ethnicity, and in 218 control samples with markers with ancestry indicators. The genes were in Hardy-Weinberg equilibrium. One hundred and seventy control samples were matched by ethnicity for comparison with the PCa samples.

RESULTS

The G allele at rs28931588 was monomorphic in both patients and controls studied. Significant differences were observed in allelic and genotypic frequencies between the control and Pca samples in rs2735839 (KLK3; p = 0.002 and χ2  = 8.73 and p = 0.01, respectively), by the global frequency and in the dominant model rs2735839_GG (odds ratio [OR] = 0.51, p = 0.02). AA and GA genotypes at rs4792311 (ELAC2) were more frequent in patients with Gleason 7(4 + 3), 8, and 9 (n = 37%-59.7%) compared to patients with Gleason 6 and 7(3 + 4) (n = 26%-40.0%) conferring a protective effect on the GG genotype (OR = 0.45, p = 0.02). The same genotype showed an OR = 2.71 (p = 0.01) for patients with low severity. The HNF1B-KLK3-ELAC2-TMPRSS2-ERG haplotypes: GAAT, AAAT, GAGT, and AAGT were more frequent in patients with Pca with OR ranging from 4.65 to 2.48.

CONCLUSIONS

Higher frequencies of risk alleles were confirmed in the SNPs, KLK3 rs2735839_A, ELAC2 rs4792311_A, and TMPRSS2 rs12329760_T in patients with Pca. Rs2735839_A was associated with risk of Pca and rs4792311_A with severity and Gleason score of 7(4 + 3) or greater. There is a need for careful observation of rs2735839 and rs4792311 in association with the prostatic biopsy due to the increased risk of Pca.

Management of Pediatric Urolithiasis in an Italian Tertiary Referral Center: A Retrospective Analysis

Background and Objectives: In recent years, the prevalence of pediatric urolithiasis has increased in North America and Western countries, though it is endemic in developing countries. The aim of this study is to describe the experience of a tertiary pediatric referral center in the surgical management of pediatric urolithiasis. Materials and Methods: We retrospectively reviewed the experience of patients ≤ 16 years old affected by urinary stones who underwent surgery. Results: From April 2021 to September 2023, 31 pediatric patients underwent surgical procedures for stone diseases at our department: 13 preschool-aged (1-5 years) and 18 school-aged (6-16 years) children. During this period, 12 URSs, 17 RIRSs, and 2 PCNLs were recorded. Five patients had residual fragments at first, so three of them underwent a second endourological lithotripsy (2 RIRSs and 1 URS). Complete clearance was finally achieved in 27 patients. The stone composition was evaluated in 25 cases. Conclusions: Numerous innovations in the surgical treatment of pediatric urolithiasis have resulted from the development of smaller devices and new technology. Our results show how, in experienced centers, retrograde and percutaneous lithotripsy are safe and effective procedures for use in pediatric populations.

A sialyltransferases-related gene signature serves as a potential predictor of prognosis and therapeutic response for bladder cancer

BACKGROUND

Aberrant glycosylation, catalyzed by the specific glycosyltransferase, is one of the dominant features of cancers. Among the glycosyltransferase subfamilies, sialyltransferases (SiaTs) are an essential part which has close linkages with tumor-associated events, such as tumor growth, metastasis and angiogenesis. Considering the relationship between SiaTs and cancer, the current study attempted to establish an effective prognostic model with SiaTs-related genes (SRGs) to predict patients' outcome and therapeutic responsiveness of bladder cancer.

METHODS

RNA-seq data, clinical information and genomic mutation data were downloaded (TCGA-BLCA and GSE13507 datasets). The comprehensive landscape of the 20 SiaTs was analyzed, and the differentially expressed SiaTs-related genes were screened with "DESeq2" R package. ConsensusClusterPlus was applied for clustering, following with survival analysis with Kaplan-Meier curve. The overall survival related SRGs were determined with univariate Cox proportional hazards regression analysis, and the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to generate a SRGs-related prognostic model. The predictive value was estimated with Kaplan-Meier plot and the receiver operating characteristic (ROC) curve, which was further validated with the constructed nomogram and decision curve.

RESULTS

In bladder cancer tissues, 17 out of the 20 SiaTs were differentially expressed with CNV changes and somatic mutations. Two SiaTs_Clusters were determined based on the expression of the 20 SiaTs, and two gene_Clusters were identified based on the expression of differentially expressed genes between SiaTs_Clusters. The SRGs-related prognostic model was generated with 7 key genes (CD109, TEAD4, FN1, TM4SF1, CDCA7L, ATOH8 and GZMA), and the accuracy for outcome prediction was validated with ROC curve and a constructed nomogram. The SRGs-related prognostic signature could separate patients into high- and low-risk group, where the high-risk group showed poorer outcome, more abundant immune infiltration, and higher expression of immune checkpoint genes. In addition, the risk score derived from the SRGs-related prognostic model could be utilized as a predictor to evaluate the responsiveness of patients to the medical therapies.

CONCLUSIONS

The SRGs-related prognostic signature could potentially aid in the prediction of the survival outcome and therapy response for patients with bladder cancer, contributing to the development of personalized treatment and appropriate medical decisions.

Cancer Stem Cells in Renal Cell Carcinoma: Origins and Biomarkers

The term "cancer stem cell" (CSC) refers to a cancer cell with the following features: clonogenic ability, the expression of stem cell markers, differentiation into cells of different lineages, growth in nonadhesive spheroids, and the in vivo ability to generate serially transplantable tumors that reflect the heterogeneity of primary cancers (tumorigenicity). According to this model, CSCs may arise from normal stem cells, progenitor cells, and/or differentiated cells because of striking genetic/epigenetic mutations or from the fusion of tissue-specific stem cells with circulating bone marrow stem cells (BMSCs). CSCs use signaling pathways similar to those controlling cell fate during early embryogenesis (Notch, Wnt, Hedgehog, bone morphogenetic proteins (BMPs), fibroblast growth factors, leukemia inhibitory factor, and transforming growth factor-β). Recent studies identified a subpopulation of CD133+/CD24+ cells from ccRCC specimens that displayed self-renewal ability and clonogenic multipotency. The development of agents targeting CSC signaling-specific pathways and not only surface proteins may ultimately become of utmost importance for patients with RCC.

Androgen receptor knockdown enhances prostate cancer chemosensitivity by down-regulating FEN1 through the ERK/ELK1 signalling pathway

PURPOSE

Flap endonuclease 1 (FEN1) is highly upregulated in prostate cancer and promotes the growth of prostate cancer cells. Androgen receptor (AR) is the most critical determinant of the occurrence, progression, metastasis, and treatment of prostate cancer. However, the effect of FEN1 on docetaxel (DTX) sensitivity and the regulatory mechanisms of AR on FEN1 expression in prostate cancer need to be further studied.

METHODS

Bioinformatics analyses were performed using data from the Cancer Genome Atlas and the Gene Expression Omnibus. Prostate cancer cell lines 22Rv1 and LNCaP were used. FEN1 siRNA, FEN1 overexpression plasmid, and AR siRNA were transfected into cells. Biomarker expression was evaluated by immunohistochemistry and Western blotting. Apoptosis and the cell cycle were explored using flow cytometry analysis. Luciferase reporter assay was performed to verify the target relationship. Xenograft assays were conducted using 22Rv1 cells to evaluate the in vivo conclusions.

RESULTS

Overexpression of FEN1 inhibited cell apoptosis and cell cycle arrest in the S phase induced by DTX. AR knockdown enhanced DTX-induced cell apoptosis and cell cycle arrest at the S phase in prostate cancer cells, which was attenuated by FEN1 overexpression. In vivo experiments showed that overexpression of FEN1 significantly increased tumour growth and weakened the inhibitory effect of DTX on prostate tumour growth, while AR knockdown enhance the sensitivity of DTX to prostate tumour. AR knockdown resulted in FEN1, pho-ERK1/2, and pho-ELK1 downregulation, and the luciferase reporter assay confirmed that ELK1 can regulate the transcription of FEN1.

CONCLUSION

Collectively, our studies demonstrate that AR knockdown improves the DTX sensitivity of prostate cancer cells by downregulating FEN1 through the ERK/ELK1 signalling pathway.

Recent advances in the molecular targeted drugs for prostate cancer

CONTEXT

Prostate cancer (PCa) is the second largest male tumor in the world and one of the most common malignant tumors in the urinary system. In recent years, the incidence rate of PCa in China has been increasing year by year. Meanwhile, refractory hormone resistance and adverse drug reactions of advanced PCa cause serious harm to patients.

OBJECTIVE

The present study aims to systematically review the recent advances in molecularly targeted drugs for prostate cancer and to use the retrieval and analysis of the literature library to summarize the adverse effects of different drugs so as to maximize the treatment benefits of targeted therapies.

EVIDENCE ACQUISITION

We performed a systematic literature search of the Medline, EMBASE, PubMed, and Cochrane databases up to March 2022 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Medical Subject Heading (MeSH) terms and keywords such as (prostate cancer) AND (molecular target drugs) AND (side effect) were used. No language restrictions were set on the search process, and all these results were processed independently by two authors. Consensus was reached through discussion once met with any disagreements. The primary endpoint was differential features between different molecular targeted drugs. Secondary endpoints were side effects of different drugs on the body and corresponding prognostic values.

EVIDENCE SYNTHESIS

The Cochrane Collaboration risk of bias tool was used to assess the study quality in terms of sequence generation, allocation concealment, blinding, the completeness of outcome data, selective reporting and other biases. We retrieved 332 articles, of which 49 met the criteria for inclusion. Included studies show that prostatic tumor cells, tumor neovascularization and immune checkpoints are the main means for targeted therapy. Common drugs include 177 Lu-PSMA, Olaparib, Rucaparib, Bevacizumab, Pazopanib, Sorafenib, Cabozantinib, Aflibercept, Ipilimumab, Atezolizumab, Avelumab, Durvalumab. A series of publicly available data suitable for further analysis of side effects. An over-representation analysis of these datasets revealed reasonable dosage and usage is the key to controlling the side effects of targeted drugs. Important information such as the publication year, the first author, location and outcome observation of adverse effects was extracted from the original article. If the study data has some insufficient data, contacting the corresponding authors is necessary. All the studies included prospective nonrandomized and randomized research. Retrospective reviews were also screened according to the relevant to the purpose of this study. Meeting abstracts as well as letters to the editor and editorials were excluded.

STATISTICAL ANALYSIS

Data analysis was based on Cochrane's risk of bias tools to obtain the quality assessment. The included randomized studies used RoB2 and non-randomized ones corresponded to ROBINS-I. Standardized mean differences (SMD) were used to determine relative risk (RR) and side effects between groups. The eggers' test was used to check the publication bias from variable information in the included studies. All p < 0.05 were considered to be significant, and 95% was set as the confidence interval.

CONCLUSIONS

With the approval of a variety of targeted drugs, targeted therapy will be widely used in the treatment of advanced or metastatic prostate cancer. Despite the existence of adverse reactions related to targeted drug treatment, it is still meaningful to adjust the drug dosage or treatment cycle to reduce the occurrence of adverse reactions, improving the treatment benefits of patients.

CDCP1 (CUB domain containing protein 1) is a potential urine-based biomarker in the diagnosis of low-grade urothelial carcinoma

Urine-based cytology is non-invasive and widely used for clinical diagnosis of urothelial carcinoma (UC), but its sensitivity is less than 40% for low-grade UC detection. As such, there is a need for new diagnostic and prognostic biomarkers of UC. CUB domain containing protein 1 (CDCP1) is a type I transmembrane glycoprotein highly expressed in various cancers. Using tissue array analysis, we demonstrated that CDCP1 expression in UC patients (n = 133), especially in those with low-grade UC, was significantly higher than in 16 normal persons. In addition, CDCP1 expression in urinary UC cells could also be detected by using immunocytochemistry method (n = 11). Furthermore, in 5637-CD cells, overexpression of CDCP1 affected the expression of epithelial mesenchymal transition-related markers and increased matrix metalloproteinase 2 expression and migration ability. Conversely, the knockdown of CDCP1 in T24 cells had the opposite effects. Using specific inhibitors, we demonstrated the involvement of c-Src/PKCδ signaling in the CDCP1-regulated migration of UC. In conclusion, our data suggest that CDCP1 contributes to the malignant progression of UC and may have the potential as a urine-based biomarker for detecting low-grade UC. However, a cohort study needs to be conducted.

Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects

Renal cancer management is challenging from diagnosis to treatment and follow-up. In cases of small renal masses and cystic lesions the differential diagnosis of benign or malignant tissues has potential pitfalls when imaging or even renal biopsy is applied. The recent artificial intelligence, imaging techniques, and genomics advancements have the ability to help clinicians set the stratification risk, treatment selection, follow-up strategy, and prognosis of the disease. The combination of radiomics features and genomics data has achieved good results but is currently limited by the retrospective design and the small number of patients included in clinical trials. The road ahead for radiogenomics is open to new, well-designed prospective studies, with large cohorts of patients required to validate previously obtained results and enter clinical practice.

Autophagy: A challengeable paradox in cancer treatment

OBJECTIVE

Autophagy is an intracellular degradation pathway conserved in all eukaryotes from yeast to humans. This process plays a quality-control role by destroying harmful cellular components under normal conditions, maintaining cell survival, and establishing cellular adaptation under stressful conditions. Hence, there are various studies indicating dysfunctional autophagy as a factor involved in the development and progression of various human diseases, including cancer. In addition, the importance of autophagy in the development of cancer has been highlighted by paradoxical roles, as a cytoprotective and cytotoxic mechanism. Despite extensive research in the field of cancer, there are many questions and challenges about the roles and effects suggested for autophagy in cancer treatment. The aim of this study was to provide an overview of the paradoxical roles of autophagy in different tumors and related cancer treatment options.

METHODS

In this study, to find articles, a search was made in PubMed and Google scholar databases with the keywords Autophagy, Autophagy in Cancer Management, and Drug Design.

RESULTS

According to the investigation, some studies suggest that several advanced cancers are dependent on autophagy for cell survival, so when cancer cells are exposed to therapy, autophagy is induced and suppresses the anti-cancer effects of therapeutic agents and also results in cell resistance. However, enhanced autophagy from using anti-cancer drugs causes autophagy-mediated cell death in several cancers. Because autophagy also plays roles in both tumor suppression and promotion further research is needed to determine the precise mechanism of this process in cancer treatment.

CONCLUSION

We concluded in this article, autophagy manipulation may either promote or hinder the growth and development of cancer according to the origin of the cancer cells, the type of cancer, and the behavior of the cancer cells exposed to treatment. Thus, before starting treatment it is necessary to determine the basal levels of autophagy in various cancers.

Emerging Hallmarks of Metabolic Reprogramming in Prostate Cancer

Prostate cancer (PCa) is the most common male malignancy and the fifth leading cause of cancer death in men worldwide. Prostate cancer cells are characterized by a hybrid glycolytic/oxidative phosphorylation phenotype determined by androgen receptor signaling. An increased lipogenesis and cholesterogenesis have been described in PCa cells. Many studies have shown that enzymes involved in these pathways are overexpressed in PCa. Glutamine becomes an essential amino acid for PCa cells, and its metabolism is thought to become an attractive therapeutic target. A crosstalk between cancer and stromal cells occurs in the tumor microenvironment because of the release of different cytokines and growth factors and due to changes in the extracellular matrix. A deeper insight into the metabolic changes may be obtained by a multi-omic approach integrating genomics, transcriptomics, metabolomics, lipidomics, and radiomics data.

Targeting Glutamine Metabolism in Prostate Cancer

Glutamine is a conditionally essential amino acid important for cancer cell proliferation through intermediary metabolism leading to de novo synthesis of purine and pyrimidine nucleotides, hexosamine biosytnehsis, fatty acid synthesis through reductive carboxylation, maintenance of redox homeostasis, glutathione synthesis, production of non-essential amino acids, and mitochondrial oxidative phosphorylation. Prostate cancer has increasingly been characterized as a tumor type that is heavily dependent on glutamine for growth and survival. In this review, we highlight the preclinical evidence that supports a relationship between glutamine signaling and prostate cancer progression. We focus on the regulation of glutamine metabolism in prostate cancer through key pathways involving the androgen receptor pathway, MYC, and the PTEN/PI3K/mTOR pathway. We end with a discussion on considerations for translation of targeting glutamine metabolism as a therapeutic strategy to manage prostate cancer. Here, it is important to understand that the tumor microenvironment also plays a role in facilitating glutamine signaling and resultant prostate cancer growth. The druggability of prostate cancer glutamine metabolism is more readily achievable with our greater understanding of tumor metabolism and the advent of selective glutaminase inhibitors that have proven safe and tolerable in early-phase clinical trials.

TMEM27 expression and clinical characteristics and survival in clear cell renal cell carcinoma

BACKGROUND

Transmembrane protein 27 (TMEM27/collectrin), a glycoprotein and homolog of angiotensin-converting enzyme 2 (ACE2), is a regulator of renal amino acid uptake in the proximal tubule and may have a protective role in hypertension. Two previous reports have shown that the absence of TMEM27 expression in clear cell renal cell carcinoma (ccRCC) correlates with poorer cancer-related survival. We report our findings of TMEM27 expression in ccRCC and clinical outcomes in an independent third cohort.

MATERIAL AND METHODS

We conducted a retrospective analysis to identify all 321 cases of ccRCC diagnosed between 2010 and 2015 at the University of Rochester Medical Center. The intensity of TMEM27 immunostaining on tumor tissue was semi-quantitatively graded on a scale of 0, 0.5, 1, 1.5, 2, 2.5, and 3 by a single pathologist, and correlated with tumor characteristics and survival.

RESULTS

There was evidence of metastasis at time of nephrectomy in 36 (11.2%) cases, and at the latest follow-up in 70 (21.8%) cases. As of Spring 2021, 82 (25.5%) had died. TMEM27 staining intensity correlated inversely with various tumor characteristics. Kaplan-Meier survival analysis showed worse overall all-cause mortality (p = 0.02) and disease-free survival (p = 0.028) for tumors without any TMEM27 staining (0) compared to 0.5 or higher by log-rank test.

CONCLUSION

The absence of TMEM27 expression is associated with more aggressive tumor characteristics and poorer all-cause mortality and disease-free survival in ccRCC. TMEM27 may be a useful biomarker to assess cancer prognosis. Further studies are needed to better assess if TMEM27 is protective in RCC, and its potential role in active surveillance and prediction of response to target therapy.

Renal Cell Carcinoma as a Metabolic Disease: An Update on Main Pathways, Potential Biomarkers, and Therapeutic Targets

Clear cell renal cell carcinoma (ccRCC) is the most frequent histological kidney cancer subtype. Over the last decade, significant progress has been made in identifying the genetic and metabolic alterations driving ccRCC development. In particular, an integrated approach using transcriptomics, metabolomics, and lipidomics has led to a better understanding of ccRCC as a metabolic disease. The metabolic profiling of this cancer could help define and predict its behavior in terms of aggressiveness, prognosis, and therapeutic responsiveness, and would be an innovative strategy for choosing the optimal therapy for a specific patient. This review article describes the current state-of-the-art in research on ccRCC metabolic pathways and potential therapeutic applications. In addition, the clinical implication of pharmacometabolomic intervention is analyzed, which represents a new field for novel stage-related and patient-tailored strategies according to the specific susceptibility to new classes of drugs.

MUC1 Tissue Expression and Its Soluble Form CA15-3 Identify a Clear Cell Renal Cell Carcinoma with Distinct Metabolic Profile and Poor Clinical Outcome

An altered metabolism is involved in the development of clear cell renal carcinoma (ccRCC). MUC1 overexpression has been found to be associated with advanced disease and poor prognosis. In this study, we evaluated the metabolomic profile of human ccRCC, according to MUC1 expression, and integrated it with transcriptomic data. Moreover, we analyzed the role of MUC1 in sustaining ccRCC aggressiveness and the prognostic value of its soluble form CA15-3. Integrated metabolomic and transcriptomic analysis showed that MUC1-expressing ccRCC was characterized by metabolic reprogramming involving the glucose and lipid metabolism pathway. In addition, primary renal cancer cells treated with a small interfering RNA targeting MUC1 (siMUC1) migrated and proliferated at a slower rate than untreated cancer cells. After cisplatin treatment, the death rate of cancer cells treated with siMUC1 was significantly greater than that of untreated cells. Kaplan-Meier curves showed significant differences in CSS and PFS among groups of patients with high versus low levels of CA15-3. In a multivariate analysis, CA15-3 was an independent adverse prognostic factor for cancer-specific and progression-free survival. In conclusion, MUC1 expressing ccRCC is characterized by a particular metabolic reprogramming. The inhibition of MUC1 expression decreases cell motility and viability and improves cisplatin susceptibility, suggesting that this pathway can regulate de novo chemotherapy resistance in ccRCC.

Prostate cancer-associated urinary proteomes differ before and after prostatectomy

BACKGROUND

A wide range of disorders can be detected in the urine. Tumor-modifying proteins in the urine may serve as a diagnostic tool for cancer patients and the alterations in their profiles may indicate efficacies of chemotherapy, radiotherapy, and surgery.

METHODS

We focused on urinary proteomes of patients with prostate cancer and identified tumor-modifying proteins in the samples before and after prostatectomy. Protein array analysis was conducted to evaluate a differential profile of tumor-promoting cytokines, while mass spectrometry-based global proteomics was conducted to identify tumor-suppressing proteins.

RESULTS

The result revealed striking differences by prostatectomy. Notably, the urine from the post-prostatectomy significantly decreased the tumorigenic behaviors of prostate tumor cells as well as breast cancer cells. We observed that angiogenin, a stimulator of blood vessel formation, was reduced in the post-prostatectomy urine. By contrast, the levels of three cell-membrane proteins such as prostasin (PRSS8), nectin 2 (PVRL2), and nidogen 1 (NID1) were elevated and they acted as extracellular tumor-suppressing proteins. These three proteins, given extracellularly, downregulated tumorigenic genes such as Runx2, Snail, and transforming growth factor beta and induced apoptosis of tumor cells. However, the role of NID1 differed depending on the location, and intracellular NID1 was tumorigenic and reduced the percent survival.

CONCLUSIONS

This study demonstrated that prostatectomy remarkably altered the profile of urinary proteomes, and the post-prostatectomy urine provided tumor-suppressive proteomes. The result sheds novel light on the dynamic nature of the urinary proteomes and a unique strategy for predicting tumor suppressors.

Energy Metabolism-Related Gene Prognostic Index Predicts Biochemical Recurrence for Patients With Prostate Cancer Undergoing Radical Prostatectomy

Background

We aimed to construct and validate an energy metabolism-related gene prognostic index (EMRGPI) to predict biochemical recurrence (BCR) in patients undergoing radical prostatectomy.

Methods

We used Lasso and COX regression analysis to orchestrate the EMRGPI in the TCGA database, and the prognostic value of EMRGPI was further validated externally using the GSE46602. All analyses were conducted with R version 3.6.3 and its suitable packages.

Results

SDC1 and ADH1B were finally used to construct the risk formula. We classified the 430 tumor patients in the TCGA database into two groups, and patients in the high-risk group had a higher risk of BCR than those in the low-risk group (HR: 1.98, 95%CI: 1.18-3.32, p=0.01). Moreover, in the GSE46602, we confirmed that the BCR risk in the high-risk group was 3.86 times higher than that in the low-risk group (95%CI: 1.61-9.24, p=0.001). We found that patients in the high-risk group had significantly higher proportions of residual tumor, older age, and T stage. SDC1 and ADH1B were significantly expressed low in the normal tissues when compared to the tumor tissues, which were opposite at the protein level. The spearman analysis showed that EMRGPI was significantly associated with B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score. In addition, the EMRGPI was positively associated with the 54 immune checkpoints, among which CD80, ADORA2A, CD160, and TNFRSF25 were significantly related to the BCR-free survival of PCa patients undergoing RP.

Conclusions

The EMRGPI established in this study might serve as an independent risk factor for PCa patients undergoing radical prostatectomy.

Sex Steroid Hormones in Urinary Exosomes as Biomarkers for the Prediction of Prostate Cancer

BACKGROUND

Although they are involved in the progression of PCa, the use of sex steroid hormones in urinary exosomes as biomarkers for PCa remains obscure. Here, the potential use of sex steroid hormones in urinary exosomes as biomarkers was investigated for the prediction of early-stage PCa to assist in clinical diagnosis.

METHODS

Two hundred and eighty-six participants were randomly recruited, 231 patients with PCa and 55 healthy controls. According to their Gleason scores (GSs), the patients with PCa were divided into two groups, mild PCa (GS6) (n=116) and severe (≥ GS7) group (n=115),. The concentrations of 8 sex steroid hormones in urinary exosomes were quantitated using liquid chromatography tandem mass spectrometry with atmospheric pressure chemical ionization (LC-APCI-MS/MS).

RESULTS

The results showed that the levels of 7 out of 8 sex steroids including dehydroepiandrosterone (DHEA), dehydroepiandrosteronesulfate (DHEAS), androstenedione (A4), testosterone (T), progesterone (P), dihydrotestosterone (DHT), and estrone (E1), but not estradiol (E2) in urinary exosomes, were not only distinguished the PCa patients from healthy controls, can also differentiate between patients with mild and severe PCa. Of the 8 selected urinary exosomal biomarkers, DHEA, DHEAS, T, and DHT were finally screened further to build the regression model, and the detection method of the 4 biomarkers-combined achieved an area under the ROC curve (AUC) of 0.854 and predictive accuracy of 78.2%.

CONCLUSION

Our data showed the use of exosomal sex steroids in urine could be as biomarkers for predicting PCa for the first time. This finding would supply a novel insight for PCa diagnosis.

Metabolomic Approaches for Detection and Identification of Biomarkers and Altered Pathways in Bladder Cancer

Metabolomic analysis has proven to be a useful tool in biomarker discovery and the molecular classification of cancers. In order to find new biomarkers, and to better understand its pathological behavior, bladder cancer also has been studied using a metabolomics approach. In this article, we review the literature on metabolomic studies of bladder cancer, focusing on the different available samples (urine, blood, tissue samples) used to perform the studies and their relative findings. Moreover, the multi-omic approach in bladder cancer research has found novel insights into its metabolic behavior, providing excellent start-points for new diagnostic and therapeutic strategies. Metabolomics data analysis can lead to the discovery of a “signature pathway” associated with the progression of bladder cancer; this aspect could be potentially valuable in predictions of clinical outcomes and the introduction of new treatments. However, further studies are needed to give stronger evidence and to make these tools feasible for use in clinical practice.

Novel Insights into Autophagy and Prostate Cancer: A Comprehensive Review

Autophagy is a complex process involved in several cell activities, including tissue growth, differentiation, metabolic modulation, and cancer development. In prostate cancer, autophagy has a pivotal role in the regulation of apoptosis and disease progression. Several molecular pathways are involved, including PI3K/AKT/mTOR. However, depending on the cellular context, autophagy may play either a detrimental or a protective role in prostate cancer. For this purpose, current evidence has investigated how autophagy interacts within these complex interactions. In this article, we discuss novel findings about autophagic machinery in order to better understand the therapeutic response and the chemotherapy resistance of prostate cancer. Autophagic-modulation drugs have been employed in clinical trials to regulate autophagy, aiming to improve the response to chemotherapy or to anti-cancer treatments. Furthermore, the genetic signature of autophagy has been found to have a potential means to stratify prostate cancer aggressiveness. Unfortunately, stronger evidence is needed to better understand this field, and the application of these findings in clinical practice still remains poorly feasible.

Epicatechin gallate prevents the de novo synthesis of fatty acid and the migration of prostate cancer cells

Lipid metabolism disorder caused by the upregulation of lipogenic genes is a typical feature of prostate cancer. The synthesis of fatty acids is enhanced to accelerate the development of prostate cancer and is considered as a potential therapeutic target. Epicatechin gallate, an active compound of green tea, has been reported to modulate lipid metabolism. In this research, the potential role of epicatechin gallate in prostate cancer cells was evaluated. The results indicated that epicatechin gallate downregulates the expression of acetyl-CoA carboxylase, ATP citrate lyase, and fatty acid synthase in prostate cancer cells and prostate xenograft tissues, suggesting that epicatechin gallate can inhibit de novo fatty acid synthesis. Moreover, epicatechin gallate significantly restrains the migration rather than the viability of prostate cancer cells. PI3K/AKT/mTOR signaling pathway, which exhibits regulatory effect on lipogenesis, is also inhibited under epicatechin gallate treatment, while pretreatment with AKT activator SC79 or mTOR activator MHY1485 blocks the inhibitory effect of epicatechin gallate on the expression of lipogenic genes and the migration of prostate cancer cells. In conclusion, this study revealed that epicatechin gallate impairs the synthesis of fatty acids via inhibition PI3K/AKT/mTOR signaling pathway and then attenuates the migration of prostate cancer cells.

Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization

Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.

Delta-like ligand 4 level in colorectal cancer is associated with tumor aggressiveness, body mass index and clinical outcome

BACKGROUND

The Notch signaling regulates numerous cell growth, differentiation, and death. However, the expression pattern of its ligand Delta-like 4 (DLL4) in tumors is still uncertain.

OBJECTIVE

In the present study, we examined DLL4 expression in colorectal cancer as well as assessed its role as a prognostic indicator in the present study.

METHODS

DLL4 expression was examined by immunohistochemistry in 265 surgically resected specimens of colorectal cancer and adjacent normal tissues. The relationship between DLL4 expression and clinicopathological characteristics was analyzed. The association of DLL4 expression with the patients' overall survival rate was assessed by Kaplan-Meier and Cox proportional-hazards regression.

RESULTS

Increased DLL4 level was detected in colorectal cancer compared with that of normal tissues. Elevated DLL4 level in colorectal cancer was associated with increased body mass index of patients. Moreover, increased DLL4 level was also found to be correlated with tumor invasion, metastases and unfavorable clinical outcom of patients.

CONCLUSIONS

DLL4 level is increased in colorectal cancer, especially in patients with increased body mass index, indicating potential involvement of obesity-related tumorigenesis and development. It might also serve as a novel molecular marker to predicate outcome of patients.

Increased Body Mass Index Is a Risk Factor for Poor Clinical Outcomes after Radical Prostatectomy in Men with International Society of Urological Pathology Grade Group 1 Prostate Cancer Diagnosed with Systematic Biopsies

INTRODUCTION

The association between obesity and clinically significant prostate cancer (PCa) is still a matter of debate. In this study, we evaluated the effect of body mass index (BMI) on the prediction of pathological unfavorable disease (UD), positive surgical margins (PSMs), and biochemical recurrence (BCR) in patients with clinically localized (≤cT2c) International Society of Urological Pathology (ISUP) grade group 1 PCa at biopsy.

METHODS

427 patients with ISUP grade group 1 PCa who have undergone radical prostatectomy and BMI evaluation were included. The outcome of interest was the presence of UD (defined as ISUP grade group ≥3 and pT ≥3a), PSM, and BCR.

RESULTS

Statistically significant differences resulted in comparing BMI with prostate-specific antigen (PSA) and serum testosterone levels (both p < 0.0001). Patients with UD and PSM had higher BMI values (p < 0.0001 and p = 0.006, respectively). BCR-free survival was significantly decreased in patients with higher BMI values (p < 0.0001). BMI was an independent risk factor for BCR and PSM. Receiver-operating characteristic analysis testing PSA accuracy in different BMI groups, showed that PSA had a reduced predictive value (area under the curve [AUC] = 0.535; 95% confidence interval [CI] = 0.422-0.646), in obese men compared to overweight (AUC = 0.664; 95% CI = 0.598-0.725) and normal weight patients (AUC = 0.721; 95% CI = 0.660-0.777).

CONCLUSION

Our findings show that increased BMI is a significant predictor of UD and PSM at RP in patients with preoperative low-to intermediate-risk diseases, suggesting that BMI evaluation may be useful in a clinical setting to identify patients with favorable preoperative disease characteristics harboring high-risk PCa.

Novel Insights into the Molecular Mechanisms of Ischemia/Reperfusion Injury in Kidney Transplantation

Ischemia reperfusion injury (IRI) is one of the most important mechanisms involved in delayed or reduced graft function after kidney transplantation. It is a complex pathophysiological process, followed by a pro-inflammatory response that enhances the immunogenicity of the graft and the risk of acute rejection. Many biologic processes are involved in its development, such as transcriptional reprogramming, the activation of apoptosis and cell death, endothelial dysfunction and the activation of the innate and adaptive immune response. Recent evidence has highlighted the importance of complement activation in IRI cascade, which expresses a pleiotropic action on tubular cells, on vascular cells (pericytes and endothelial cells) and on immune system cells. The effects of IRI in the long term lead to interstitial fibrosis and tubular atrophy, which contribute to chronic graft dysfunction and subsequently graft failure. Furthermore, several metabolic alterations occur upon IRI. Metabolomic analyses of IRI detected a “metabolic profile” of this process, in order to identify novel biomarkers that may potentially be useful for both early diagnosis and monitoring the therapeutic response. The aim of this review is to update the most relevant molecular mechanisms underlying IRI, and also to discuss potential therapeutic targets in future clinical practice.

A novel expressed prostatic secretion (EPS)-urine metabolomic signature for the diagnosis of clinically significant prostate cancer

OBJECTIVE

Significant efforts are currently being made to identify novel biomarkers for the diagnosis and risk stratification of prostate cancer (PCa). Metabolomics can be a very useful approach in biomarker discovery because metabolites are an important read-out of the disease when characterized in biological samples. We aimed to determine a metabolomic signature which can accurately distinguish men with clinically significant PCa from those affected by benign prostatic hyperplasia (BPH).

METHODS

We first performed untargeted metabolomics using ultrahigh-performance liquid chromatography tandem mass spectrometry on expressed prostatic secretion urine (EPS-urine) from 25 patients affected by BPH and 25 men with clinically significant PCa (defined as Gleason score ≥ 3 + 4). Diagnosis was histologically confirmed after surgical treatment. The EPS-urine metabolomic approach was then applied to a larger, prospective cohort of 92 consecutive patients undergoing multiparametric magnetic resonance imaging for clinical suspicion of PCa prior to biopsy.

RESULTS

We established a novel metabolomic signature capable of accurately distinguishing PCa from benign tissue. A metabolomic signature was associated with clinically significant PCa in all subgroups of the Prostate Imaging Reporting and Data System (PI-RADS) classification (100% and 89.13% of accuracy when the PI-RADS was in range of 1-2 and 4-5, respectively, and 87.50% in the more critical cases when the PI-RADS was 3).

CONCLUSIONS

A combination of metabolites and clinical variables can effectively help in identifying PCa patients that might be overlooked by current imaging technologies. Metabolites from EPS-urine should help in defining the diagnostic pathway of PCa, thus improving PCa detection and decreasing the number of unnecessary prostate biopsies.

Sperm Cholesterol Content Modifies Sperm Function and TRPV1-Mediated Sperm Migration

Transient receptor potential channels-vanilloid receptor 1 (TRPV1) regulates thermotaxis in sperm-oriented motility. We investigated the role of membrane cholesterol (Chol) on TRPV1-mediated human sperm migration. Semen samples were obtained from five normozoospemic healthy volunteers. Sperm membrane Chol content, quantified by liquid chromatography-mass spectrometry, was modified by incubating cells with 2-hydroxypropyl-ß-cyclodextrin (CD) or the complex between CD and Chol (CD:Chol). The effect on sperm migration on a 10 μM capsaicin gradient (CPS), a TRPV1 agonist, was then investigated. Motility parameters were evaluated by Sperm Class Analyser. Intracellular calcium concentration and acrosome reaction were measured by staining with calcium orange and FITC-conjugated anti-CD46 antibody, respectively. TRPV1-Chol interaction was modelled by computational molecular-modelling (MM). CD and CD:Chol, respectively, reduced and increased membrane Chol content in a dose-dependent manner, resulting in a dose-dependent increase and reduction of sperm migration in a CPS gradient. MM confirmed a specific interaction of Chol with a TRPV1 domain that appeared precluded to the Chol epimer epicholesterol (Epi-Chol). Accordingly, CD:Epi-Chol was significantly less efficient than CD:Chol, in reducing sperm migration under CPS gradient. Chol inhibits TRPV1-mediated sperm function by directly interacting with a consensus sequence of the receptor.

NMR metabolomic profiles associated with long-term risk of prostate cancer

INTRODUCTION

Prostate cancer is a multifactorial disease whose aetiology is still not fully understood. Metabolomics, by measuring several hundred metabolites simultaneously, could enhance knowledge on the metabolic changes involved and the potential impact of external factors.

OBJECTIVES

The aim of the present study was to investigate whether pre-diagnostic plasma metabolomic profiles were associated with the risk of developing a prostate cancer within the following decade.

METHODS

A prospective nested case-control study was set up among the 5141 men participant of the SU.VI.MAX cohort, including 171 prostate cancer cases, diagnosed between 1994 and 2007, and 171 matched controls. Nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples using NOESY1D and CPMG sequences. Multivariable conditional logistic regression models were computed for each individual NMR signal and for metabolomic patterns derived using principal component analysis.

RESULTS

Men with higher fasting plasma levels of valine (odds ratio (OR) = 1.37 [1.07-1.76], p = .01), glutamine (OR = 1.30 [1.00-1.70], p = .047), creatine (OR = 1.37 [1.04-1.80], p = .02), albumin lysyl (OR = 1.48 [1.12-1.95], p = .006 and OR = 1.51 [1.13-2.02], p = .005), tyrosine (OR = 1.40 [1.06-1.85], p = .02), phenylalanine (OR = 1.39 [1.08-1.79], p = .01), histidine (OR = 1.46 [1.12-1.88], p = .004), 3-methylhistidine (OR = 1.37 [1.05-1.80], p = .02) and lower plasma level of urea (OR = .70 [.54-.92], p = .009) had a higher risk of developing a prostate cancer during the 13 years of follow-up.

CONCLUSIONS

This exploratory study highlighted associations between baseline plasma metabolomic profiles and long-term risk of developing prostate cancer. If replicated in independent cohort studies, such signatures may improve the identification of men at risk for prostate cancer well before diagnosis and the understanding of this disease.

Integration of Lipidomics and Transcriptomics Reveals Reprogramming of the Lipid Metabolism and Composition in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is fundamentally a metabolic disease. Given the importance of lipids in many cellular processes, in this study we delineated a lipidomic profile of human ccRCC and integrated it with transcriptomic data to connect the variations in cancer lipid metabolism with gene expression changes. Untargeted lipidomic analysis was performed on 20 ccRCC and 20 paired normal tissues, using LC-MS and GC-MS. Different lipid classes were altered in cancer compared to normal tissue. Among the long chain fatty acids (LCFAs), significant accumulations of polyunsaturated fatty acids (PUFAs) were found. Integrated lipidomic and transcriptomic analysis showed that fatty acid desaturation and elongation pathways were enriched in neoplastic tissue. Consistent with these findings, we observed increased expression of stearoyl-CoA desaturase(SCD1) and FA elongase 2 and 5 in ccRCC. Primary renal cancer cells treated with a small molecule SCD1 inhibitor (A939572) proliferated at a slower rate than untreated cancer cells. In addition, after cisplatin treatment, the death rate of tumor cells treated with A939572 was significantly greater than that of untreated cancer cells. In conclusion, our findings delineate a ccRCC lipidomic signature and showed that SCD1 inhibition significantly reduced cancer cell proliferation and increased cisplatin sensitivity, suggesting that this pathway can be involved in ccRCC chemotherapy resistance.

Cribriform pattern does not have a significant impact in Gleason Score ≥7/ISUP Grade ≥2 prostate cancers submitted to radical prostatectomy

INTRODUCTION

The aim of this study was to correlate cribriform pattern (CP) with other parameters in a large prospective series of Gleason score ≥7/ISUP grade ≥2 prostate cancer (PC) cases undergoing radical prostatectomy (RP).

METHODS

This is a prospective single-center study on 210 consecutive patients. Gleason pattern 4 and individual tumor growth patterns determination were performed either in biopsy or in surgical specimens for all patients.

RESULTS

At multiparametric magnetic resonance, a higher percentage of PI-RADS 5 was associated to CP (53.3% vs 17.7%, P = .038). CP was significantly and inversely (r = -0.261; P = .001) correlated with perineural invasion (PNI) but not with other pathological parameters. Kaplan-Meier analysis showed that mean biochemical (Bp) and radiological (Rp) progression-free survival were similar (Bp = χ 0.906; P = .341; Rp = χ 1.880; P = .170) independently to CP. In PNI positive cases, Bp-free survival was higher (χ = 3.617; P = .057) in cases without CP.

CONCLUSIONS

In a homogeneous population excluding ISUP 1 cases, CP showed limited prognostic value. We first described an association with PNI and a prognostic value influenced by PNI status.

Identification of metabolites associated with prostate cancer risk: a nested case-control study with long follow-up in the Northern Sweden Health and Disease Study

BACKGROUND

Prostate cancer is the second most frequently diagnosed cancer in men. Metabolomics can potentially provide new insights into the aetiology of prostate cancer by identifying new metabolic risk factors. This study investigated the prospective association between plasma metabolite concentrations and prostate cancer risk, both overall and by stratifying for disease aggressiveness and baseline age.

METHODS

In a case-control study nested in the Northern Sweden Health and Disease Study, pre-diagnostic concentrations of 148 plasma metabolites were determined using targeted mass spectrometry- and nuclear magnetic resonance-based metabolomics in 777 prostate cancer cases (follow-up ≥ 5 years) and 777 matched controls. Associations between prostate cancer risk and metabolite concentrations were investigated using conditional logistic regression conditioned on matching factors (body mass index, age and sample storage time). Corrections for multiple testing were performed using false discovery rate (20%) and Bonferroni. Metabolomics analyses generated new hypotheses, which were investigated by leveraging food frequency questionnaires (FFQs) and oral glucose tolerance tests performed at baseline.

RESULTS

After correcting for multiple testing, two lysophosphatidylcholines (LPCs) were positively associated with risk of overall prostate cancer (all ages and in older subjects). The strongest association was for LPC C17:0 in older subjects (OR = 2.08; 95% CI 1.45-2.98; p < 0.0001, significant also after the Bonferroni correction). Observed associations with risk of overall prostate cancer in younger subjects were positive for glycine and inverse for pyruvate. For aggressive prostate cancer, there were positive associations with six glycerophospholipids (LPC C17:0, LPC C20:3, LPC C20:4, PC ae C38:3, PC ae C38:4 and PC ae C40:2), while there was an inverse association with acylcarnitine C18:2. Moreover, plasma LPC C17:0 concentrations positively correlated with estimated dietary intake of fatty acid C17:0 from the FFQs. The associations between glycerophospholipids and prostate cancer were stronger in case-controls with normal glucose tolerance.

CONCLUSIONS

Several glycerophospholipids were positively associated with risk of overall and aggressive prostate cancer. The strongest association was observed for LPC C17:0. The associations between glycerophospholipids and prostate cancer risk were stronger in case-controls with normal glucose tolerance, suggesting a link between the glucose metabolism status and risk of prostate cancer.

XPC exon15 Lys939Gln variant increase susceptibility to prostate adenocarcinoma: Evidence based on 4306 patients and 4779 controls

BACKGROUND

Previous studies have investigated the correlation between xeroderma pigmentosumcomplementation group C (XPC) variants and prostate adenocarcinoma (PA) risk. Nevertheless, research findings remain inconclusive.

METHODS

We conducted a pooled analysis to obtain a more accurate estimation of the relationship on XPC exon15 Lys939Gln polymorphism with susceptibility to PA. Moreover, in silico tools were employed to investigate the effect of XPC expression on PA patients' survival time.

RESULTS

A total of 4306 patients and 4779 control subjects were assessed. The overall results indicated that XPC Lys939Gln variant was associated with PA risk (recessive genetic model: odds ratio = 1.15, 95% confidence interval = 1.02-1.30, Pheterogeneity= .044, P = .021, I= 45.2), especially in Asian descendants. Population-based studies revealed similar results (odds ratio = 1.15, 95% confidence interval = 1.01-1.32, Pheterogeneity= .146, P = .040, I = 39.0). In silico tools showed that XPC expression in Caucasian patients was lower than in the normal group. No positive association was observed in African patients. PA subjects with high XPC expression had a longer overall survival time than low expression group.

CONCLUSION

Our findings indicated that XPC Lys939Gln variant might contribute to increased PA susceptibility, especially for Asian patients.

Human Prostate Cancer is Characterized by an Increase in Urea Cycle Metabolites

Despite it being the most common incident of cancer among men, the pathophysiological mechanisms contributing to prostate cancer (PCa) are still poorly understood. Altered mitochondrial metabolism is postulated to play a role in the development of PCa. To determine the key metabolites (which included mitochondrial oncometabolites), benign prostatic and cancer tissues of patients with PCa were analyzed using capillary electrophoresis and liquid chromatography coupled with mass spectrometry. Gene expression was studied using real-time PCR. In PCa tissues, we found reduced levels of early tricarboxylic acid cycle metabolites, whereas the contents of urea cycle metabolites including aspartate, argininosuccinate, arginine, proline, and the oncometabolite fumarate were higher than that in benign controls. Fumarate content correlated positively with the gene expression of oncogenic HIF1α and NFκB pathways, which were significantly higher in the PCa samples than in the benign controls. Furthermore, data from the TCGA database demonstrated that prostate cancer patients with activated NFκB pathway had a lower survival rate. In summary, our data showed that fumarate content was positively associated with carcinogenic genes.

Plasma metabolomic profile in prostatic intraepithelial neoplasia and prostate cancer and associations with the prostate-specific antigen and the Gleason score

INTRODUCTION

The metabolic alterations reflecting the influence of prostate cancer cells can be captured through metabolomic profiling.

OBJECTIVE

To characterize the plasma metabolomic profile in prostatic intraepithelial neoplasia (PIN) and prostate cancer (PCa).

METHODS

Metabolomics analyses were performed in plasma samples from individuals classified as non-cancerous control (n = 36), with PIN (n = 16), or PCa (n = 27). Untargeted [26 moieties identified after pre-processing by gas chromatography/mass spectrometry (GC/MS)] and targeted [46 amino acids, carbohydrates, organic acids and fatty acids by GC/MS, and 16 nucleosides and amino acids by ultra performance liquid chromatography-triple quadrupole/mass spectrometry (UPLC-TQ/MS)] analyses were performed. Prostate specific antigen (PSA) concentrations were measured in all samples. In PCa patients, the Gleason scores were determined.

RESULTS

The metabolites that were best discriminated (p < 0.05, FDR < 0.2) for the Kruskal-Wallis test with Dunn's post-hoc comparing the control versus the PIN and PCa groups included isoleucine, serine, threonine, cysteine, sarcosine, glyceric acid, among several others. PIN was mainly characterized by alterations on steroidogenesis, glycine and serine metabolism, methionine metabolism and arachidonic acid metabolism, among others. In the case of PCa, the most predominant metabolic alterations were ubiquinone biosynthesis, catecholamine biosynthesis, thyroid hormone synthesis, porphyrin and purine metabolism. In addition, we identified metabolites that were correlated to the PSA [i.e. hypoxanthine (r = - 0.60, p < 0.05; r = - 0.54, p < 0.01) and uridine (r = - 0.58, p < 0.05; r = - 0.50, p < 0.01) in PIN and PCa groups, respectively] and metabolites that were significantly different in PCa patients with Gleason score < 7 and ≥ 7 [i.e. arachidonic acid, median (P25-P75) = 883.0 (619.8-956.4) versus 570.8 (505.6-651.8), respectively (p < 0.01)].

CONCLUSIONS

This human plasma metabolomic assessment contributes to the understanding of the unique metabolic features exhibited in PIN and PCa and provides a list of metabolites that can have the potential to be used as biomarkers for early detection of disease progression and management.

Comprehensive analysis of biomarkers for prostate cancer based on weighted gene co-expression network analysis

BACKGROUND

Prostate cancer (PCa) is one of the leading causes of cancer-related death. In the present research, we adopted a comprehensive bioinformatics method to identify some biomarkers associated with the tumor progression and prognosis of PCa.

METHODS

Differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA) were applied for exploring gene modules correlative with tumor progression and prognosis of PCa. Clinically Significant Modules were distinguished, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to Annotation, Visualization and Integrated Discovery (DAVID). Protein-protein interaction (PPI) networks were used in selecting potential hub genes. RNA-Seq data and clinical materials of prostate cancer from The Cancer Genome Atlas (TCGA) database were used for the identification and validation of hub genes. The significance of these genes was confirmed via survival analysis and immunohistochemistry.

RESULTS

2688 DEGs were filtered. Weighted gene co-expression network was constructed, and DEGs were divided into 6 modules. Two modules were selected as hub modules which were highly associated with the tumor grades. Functional enrichment analysis was performed on genes in hub modules. Thirteen hub genes in these hub modules were identified through PPT networks. Based on TCGA data, 4 of them (CCNB1, TTK, CNN1, and ACTG2) were correlated with prognosis. The protein levels of CCNB1, TTK, and ACTG2 had a degree of differences between tumor tissues and normal tissues.

CONCLUSION

Four hub genes were identified as candidate biomarkers and potential therapeutic targets for further studies of exploring molecular mechanisms and individual therapy on PCa.

Biomarkers of response to advanced prostate cancer therapy

Introduction: Prostate cancer (PCa) is one of the most common adult malignancies worldwide, and a major leading cause of cancer-related death in men in Western societies. In the last years, the prognosis of advanced PCa patients has been impressively improved thanks to the development of different therapeutic agents, including taxanes (docetaxel and cabazitaxel), second-generation anti-hormonal agents (abiraterone and enzalutamide), and the radiopharmaceutical Radium-223. However, great efforts are still needed to properly select the most appropriate treatment for each single patient.Areas covered: Several prognostic or predictive biomarkers have been studied, none of which has an established validated role in daily clinical practice. This paper analyzed the major biomarkers (including PSA, androgen receptor (AR) splice variants, βIII-tubulin, ALP, circulating tumor cells, and DNA repair genes) with a potential prognostic and/or predictive role in advanced PCa patients.Expert commentary: Surrogate biomarkers - measurable, reproducible, closely associated with tumor behavior and linked to relevant clinical outcomes - are urgently needed to improve PCa patient management.

Platelet-to-lymphocyte ratio and systemic immune-inflammation index versus circulating prostate cells to predict significant prostate cancer at first biopsy

OBJECTIVE

It has been reported that the systemic immune-inflammation index (SII) and platelet-to-lymphocyte ratio (PLR) are higher in men with prostate cancer. We compare their use with the percentage of free prostate-specific antigen (PSA), PSA density, and primary circulating prostate cells (CPCs) to predict clinically significant prostate cancer at first biopsy in men with a PSA of 4-10 ng/mL.

MATERIAL AND METHODS

Consecutive men with suspicion of prostate cancer underwent a 12-core transrectal ultrasound-guided prostate biopsy; total serum PSA, the percentage of free PSA, prostate ultrasound to calculate PSA density, and absolute neutrophil, lymphocyte, and platelet counts were used for risk assessment. CPCs were detected using differential gel centrifugation and immunocytochemistry with anti-PSA and anti-P504S. A malignant CPC was defined as a cell-expressing PSA and P504S and defined as positive or negative. Biopsies were classified as indicating cancer or no cancer. Areas under the curve for each parameter were calculated and compared, and diagnostic yields were calculated.

RESULTS

A total of 1223 men participated, and 467 (38%) had a biopsy positive for cancer, whereas 353/467 (76%) had clinically significant prostate cancer. The PLR was significantly higher in men with prostate cancer; there was no significant difference for the SII. The areas under the curves were CPC 0.84, the percentage of free PSA was 0.79, PLR 0.65, PSA density 0.62, and SII 0.46. Neither the PLR nor the SII discriminated between patients with clinically significant prostate cancer, indolent cancer, and benign prostatic disease.

CONCLUSION

Based on the results of this study, neither the SII nor PLR could differentiate between clinically significant prostate cancer and indolent cancer/benign disease at initial biopsy.

Association of Hsa-miR-23a rs3745453 variation with prostate cancer risk among Chinese Han population: A case-control study

Prostate cancer (PCa) is a frequently diagnosed malignant solid tumor in men. The etiology of PCa has been attributed to both environmental and genetic factors. In recent years, many studies have reported that miRNA gene single-nucleotide polymorphisms (SNPs) influence the susceptibility to several diseases such as cancer. To date, the mechanisms of PCa have remained unknown. The main aim of this study was to evaluate the association between PCa susceptibility and miRNA gene SNPs. A total of 156 PCa cases and 188 control subjects were included in this case-control study. The data were collected from hospitalized cases. We collected the demographic characteristic information, which included age, body mass index, tobacco smoking, alcohol consumption, and family history of cancer. Polymorphisms were analyzed by the ligase detection reaction. Unconditional logistic and stratified analyses were used to analyze the association between these SNPs and PCa susceptibility and to calculate the adjusted odds ratios (ORs) and the 95% confidence intervals (CIs). Cox regression model and the log-rank test were used to test the association between genetic variants and the overall survival. We found that miR-23a gene polymorphism rs3745453 carrying CC homozygotes had a 4.16-fold increased risk (95% CI = 1.30-13.25) than those carrying the TT/CT genotypes (P = .02), and the C allele displayed a higher prevalence of PCa than the T allele (OR = 1.68, 95% CI = 1.16-2.45, P = .01). Moreover, miR-23a showed that the homozygous carriers of the C-variant significantly increased the risk of survival rate as compared to the carriers of the TT/CT genotype (OR = 9.67, 95% CI = 2.83-33.09, P = .001). The rs3745453 polymorphism was potentially associated with PCa in the Chinese Han population and had an interactive relationship with the environmental factors.

An evaluation of current prostate cancer diagnostic approaches with emphasis on liquid biopsies and prostate cancer

Introduction: Knowledge of the complex biology of prostate cancer is constantly growing, opening the field up to new therapeutic advances. The selection of patients on the basis of prognostic and predictive biomarkers is a challenging and emerging clinical need, not yet completely fulfilled. In this scenario, liquid biopsy offers a noninvasive and attractive approach to give important information about tumor biology and eventual resistance to treatments.Areas covered: The aim of this review of the literature is to evaluate the current knowledge and the promising value of liquid biopsy in prostate cancer. Circulating tumor cells and circulating tumor DNA identified by liquid biopsies are currently under evaluation to guide therapeutic decisions in prostate cancer management, even though practical applications of these approaches are still very limited. We examined the current areas of interest in which circulating tumor cells and circulating tumor DNA are being investigated, such as their prognostic and predictive role in response to chemotherapy or androgen receptor signaling inhibition, especially in the castration-resistant setting.Expert opinion: As the body of knowledge on liquid biopsy rapidly grows, we need to identify which can be the real applications of this technique in clinical practice and to overcome the problems that are limiting its routinely use.

Assessment of biochemical recurrence of prostate cancer (Review)

The assessment of the risk of biochemical recurrence (BCR) is critical in the management of males with prostate cancer (PC). Over the past decades, a comprehensive effort has been focusing on improving risk stratification; a variety of models have been constructed using PC-associated pathological features and molecular alterations occurring at the genome, protein and RNA level. Alterations in RNA expression (lncRNA, miRNA and mRNA) constitute the largest proportion of the biomarkers of BCR. In this article, we systemically review RNA-based BCR biomarkers reported in PubMed according to the PRISMA guidelines. Individual miRNAs, mRNAs, lncRNAs and multi-gene panels, including the commercially available signatures, Oncotype DX and Prolaris, will be discussed; details related to cohort size, hazard ratio and 95% confidence intervals will be provided. Mechanistically, these individual biomarkers affect multiple pathways critical to tumorigenesis and progression, including epithelial-mesenchymal transition (EMT), phosphatase and tensin homolog (PTEN), Wnt, growth factor receptor, cell proliferation, immune checkpoints and others. This variety in the mechanisms involved not only validates their associations with BCR, but also highlights the need for the coverage of multiple pathways in order to effectively stratify the risk of BCR. Updates of novel biomarkers and their mechanistic insights are considered, which suggests new avenues to pursue in the prediction of BCR. Additionally, the management of patients with BCR and the potential utility of the stratification of the risk of BCR in salvage treatment decision making for these patients are briefly covered. Limitations will also be discussed.

Biomarker Potential of Plasma MicroRNA-150-5p in Prostate Cancer

Background and Objectives: Over decades, prostate cancer (PCa) has become one of the leading causes of cancer mortality in men. Extensive evidence exists that microRNAs (miRNAs or miRs) are key players in PCa and a new class of non-invasive cancer biomarkers. Materials and Methods: We performed miRNA profiling in plasma and tissues of PCa patients and attempted the validation of candidate individual miRs as biomarkers. Results: The comparison of tissue and plasma profiling results revealed five commonly dysregulated miRs, namely, miR-130a-3p, miR-145-5p, miR-148a-3p, miR-150-5p, and miR-365a-3p, of which only three show concordant changes—miR-130a-3p and miR-150-5p were downregulated and miR-148a-3p was upregulated in both tissue and plasma samples, respectively. MiR-150-5p was validated as significantly downregulated in both plasma and tissue cancer samples, with a fold change of −2.697 (p < 0.001), and −1.693 (p = 0.035), respectively. ROC analysis showed an area under the curve (AUC) of 0.817 (95% CI: 0.680–0.995) for plasma samples and 0.809 (95% CI: 0.616–1.001) for tissue samples. Conclusions: We provide data indicating that miR-150-5p plasma variations in PCa patients are associated with concordant changes in prostate cancer tissues; however, given the heterogeneous nature of previous findings of miR-150-5p expression in PCa cells, additional future studies of a larger sample size are warranted in order to confirm the biomarker potential and role of miRNA-150-5p in PCa biology.