Effects of glutamate and aspartate on prostate cancer and breast cancer: a Mendelian randomization study

Study on the Material Basis and Mechanisms of Achyrocline satureioides in the Treatment of Nonsmall Cell Lung Cancer Based on Network Pharmacology and Spatial Metabolomics

Achyrocline satureioides have good therapeutic effects on nonsmall cell lung cancer (NSCLC). Nevertheless, it is still challenging to elucidate the active ingredients and mechanism of action due to their complex chemical composition. To address this, we innovatively combined network pharmacology with spatial metabolomics to comprehensively investigate the active components and the action mechanism in the present study. First, metabolomics of cells treated with the methanol extract of A. satureioides (ASM) utilizing high-resolution ultrahigh-performance liquid chromatography tandem mass spectrometry (HR-UHPLC-MS/MS) revealed 32 changed metabolites and 7 enriched metabolic pathways, confirming the anti-NSCLC effect of ASM and its impact on endogenous metabolites at the cellular level. Then, 69 chemical components in the ASM were identified using HR-UHPLC-MS/MS, followed by the screening of 6 core components and 10 core targets of anti-NSCLC with the help of network pharmacology and molecular docking. Lastly, quercetin, the most abundant compound among the six core active ingredients, was chosen for evaluating its anti-NSCLC effect and the potential mechanism using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). 51 altered endogenous metabolites were screened, and pathway enrichment analysis results were consistent with cell metabolomics, corroborating our network pharmacology predictions. In addition, we also observed the accumulation of three metabolites of quercetin in the tumor tissues. Network pharmacology combined with MSI elucidated the metabolic mechanisms by which A. satureioides treats NSCLC, offering new insights into herbal cancer therapies.

Pre-diagnostic circulating metabolomics and prostate cancer risk: A systematic review and meta-analysis

Background

Metabolomic dysregulation contributes to prostate cancer (PCa) pathogenesis, and studies suggest that circulating metabolites have strong clinical potential to act as biomarkers. However, evidence of circulating metabolite associations has not been quantitively aggregated.

Methods

Systematic searches were performed in PubMed and Embase (October 17th, 2024) to identify pre-diagnostic untargeted serum metabolomic studies of PCa risk. After harmonizing metabolite names across studies, restricted maximum likelihood was used to conduct meta-analyses to quantify associations between metabolites and risk of overall PCa, low- to intermediate-risk PCa, high- to very high-risk PCa and lethal PCa, as defined by the NCCN. Statistical significance was defined as FDR-adjusted P<0.05. Enrichment analyses were conducted on significant metabolites to identify biologically relevant pathways. Correlation of effect estimates between PCa outcomes was assessed via Pearson correlation.

Results

We identified 12 untargeted pre-diagnostic circulating metabolomic studies in a systematic review and meta-analyzed associations between up to 408 metabolites with four PCa outcomes. Three, eleven and nineteen metabolites were significantly associated with risk of overall, high/very high-risk and lethal PCa, respectively. Metabolites associated with high/very high-risk PCa were significantly enriched for lipids. Limited evidence of correlation between metabolite effects across outcomes was identified, highlighting potentially unique metabolite drivers of high-risk and lethal PCa. Follow-up analyses found that 13 of the significant metabolites were drug and/or dietary modifiable.

Conclusions

These findings suggest the strong potential for metabolites to inform risk of lethal PCa, which could inform risk-stratified screening strategies and facilitate the identification of targets for PCa prevention.

Exploring the causal role of plasma metabolites and metabolite ratios in prostate cancer: a two-sample Mendelian randomization study

Background

Prostate cancer (PCa), the most prevalent malignant neoplasm in males, involves complex biological mechanisms and risk factors, many of which remain unidentified. By employing a novel two-sample Mendelian randomization (MR) approach, this study aims to elucidate the causal relationships between the circulating metabolome and PCa risk, utilizing comprehensive data on genetically determined plasma metabolites and metabolite ratios.

Methods

For the MR analysis, we utilized data from the GWAS Catalog database to analyze 1,091 plasma metabolites and 309 ratios in relation to PCa outcomes within two independent GWAS datasets. The inverse variance weighted (IVW) method was the primary approach for determining the existence of the causal relationship, supplemented by additional MR methods for heterogeneity, pleiotropy, and cross-validation. The false discovery rate (FDR) and Bonferroni correction were applied to identify the most significant causative associations. Additionally, reverse MR and Steiger filtering were conducted to ascertain whether PCa influenced the observed metabolite levels. Furthermore, metabolic pathway analysis was conducted with MetaboAnalyst 6.0 software.

Results

In the MR analysis, our findings reveal three overlapped metabolite ratios (arginine to glutamate, phosphate to uridine, and glycerol to mannitol/sorbitol) inversely associated with PCa risk. Following FDR correction (FDR < 0.05), cysteinylglycine disulfide was identified as a potential reducer of PCa risk, whereas Uridine and N-acetyl-L-glutamine (NAG) were pinpointed as potential risk factors. Notably, NAG (OR 1.044; 95% CI 1.025-1.063) emerged as a metabolite with significant causal influence, as confirmed by stringent Bonferroni correction (P < 0.05/1400). Steiger's directionality test (P < 0.001) and reverse MR confirmed the proposed causal direction. Furthermore, metabolic pathway analysis revealed a significant association between the "Glutathione Metabolism" pathway and PCa development.

Conclusion

This study provides novel insights into the potential causal effects of plasma metabolites and metabolite ratios on PCa. The identified metabolites and ratios could serve as candidate biomarkers, contributing to the elucidation of PCa's biological mechanisms.

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.

The causal effect of serum amino acids on the risk of prostate cancer: a two-sample mendelian randomization study

Prostate cancer (PCa) is the second most common malignancy affecting men globally. Recent advances in metabolomics have highlighted significant alterations in specific amino acid (AA) metabolism linked to PCa, indicating their potential utility in diagnosis and therapy. However, no direct causal association between serum AA levels and PCa risk has been established. A total of 35 patients with PCa and 30 individuals with benign prostatic hyperplasia (BPH) were recruited for this study. Targeted metabolomic analysis was performed using ultra-high-performance liquid chromatography-tandem mass spectrometry on serum samples. Two-sample Mendelian randomization (MR) was applied to explore potential causal links between serum AA levels and PCa risk, including mediator effects using dual-phase MR and assessing reverse causality through reverse MR. Results Targeted metabolomic profiling identified six amino acids-glutamate (Glu), Ser, histidine (His), arginine (Arg), aspartic acid (Asp), and glycine (Gly)-that showed significant area under the ROC curve in differentiating between BPH and PCa cases. Notably, Glu demonstrated an inverse association with PCa risk, distinct from the other AAs identified. However, definitive evidence supporting a causal relationship between low Glu levels and increased PCa risk was not observed. Our results suggest a protective role of Glu against PCa development, which may have implications for disease prognosis. Increasing dietary Glu intake may present a potential preventive or therapeutic approach for PCa.

A high-fat diet induces changes in mesenteric adipose tissue accelerating early-stage pancreatic carcinogenesis in mice

Increased adiposity is a significant risk factor for pancreatic cancer development. Multiple preclinical studies have documented that high-fat, high calorie diets, rich in omega-6 fatty acids (FA) accelerate pancreatic cancer development. However, the effect of a high-fat, low sucrose diet (HFD), on pancreatic carcinogenesis remains unclear. We evaluated the impact of a HFD on early-stage pancreatic carcinogenesis in the clinically relevant KrasLSL-G12D/+; Ptf1aCre/+ (KC) genetically engineered mouse model, and characterized the role of the mesenteric adipose tissue (MAT). Cohorts of male and female KC mice were randomly assigned to a control diet (CD) or a HFD, matched for FA composition (9:1 of omega-6 FA: omega-3 FA), and fed their diets for 8 weeks. After 8 weeks on a HFD, KC mice had significantly higher body weight, fat mass, and serum leptin compared to CD-fed KC mice. Furthermore, a HFD accelerated pancreatic acinar-to-ductal metaplasia (ADM) and proliferation, associated with increased activation of ERK and STAT3, and macrophage infiltration in the pancreas, compared to CD-fed KC mice. Metabolomics analysis of the MAT revealed sex differences between diet groups. In females, a HFD altered metabolites related to FA (α-linolenic acid and linoleic acid) and amino acid metabolism (alanine, aspartate, glutamate). In males, a HFD significantly affected pathways related to alanine, aspartate, glutamate, linoleic acid, and the citric acid cycle. A HFD accelerates early pancreatic ADM through multifaceted mechanisms, including effects at the tumor and surrounding MAT. The sex-dependent changes in MAT metabolites could explain some of the sex differences in HFD-induced pancreatic ADM.

Pharmacological targets of SGLT2 inhibition on prostate cancer mediated by circulating metabolites: a drug-target Mendelian randomization study

Background

The relationship between sodium-glucose cotransporter 2 (SGLT2) inhibitors and prostate cancer is still unknown. Although these inhibitors can influence tumor glycolysis, the underlying mechanism requires further exploration.

Methods

A two-sample two-step MR was used to determine 1) causal effects of SGLT2 inhibition on prostate cancer; 2) causal effects of 1,400 circulating metabolites or metabolite ratios on prostate cancer; and 3) mediation effects of these circulating metabolites. Genetic proxies for SGLT2 inhibition were identified as variants in the SLC5A2 gene and glycated hemoglobin level (HbA1c). Additionally, positive control analysis on type 2 diabetes mellitus (T2DM) was conducted to test the selection of genetic proxies. Phenome Wide Association Study (PheWAS) and MR-PheWAS analysis were used to explore potential treatable diseases and adverse outcomes of SGLT2 inhibitors.

Results

Genetically predicted SGLT2 inhibition (per 1 SD decrement in HbA1c) was associated with reduced risk of T2DM [odds ratio (OR) = 0.66 (95% CI 0.53, 0.82), P = 1.57 × 10-4]; prostate cancer [0.34 (0.23, 0.49), P = 2.21 × 10-8] and prostate-specific antigen [0.26 (0.08, 0.81), P = 2.07 × 10-2]. The effect of SGLT2 inhibition on prostate cancer was mediated by uridine level, with a mediated proportion of 9.34% of the total effect. In MR-PheWAS, 65 traits were found to be associated with SLGT2 inhibitors (P < 1.78 × 10-5), and among them, 13 were related to diabetes.

Conclusion

Our study suggested that SGLT2 inhibition could lower prostate cancer risk through uridine mediation. More mechanistic and clinical research is necessary to explore how uridine mediates the link between SGLT2 inhibition and prostate cancer.

Risk factors for prostate cancer: An umbrella review of prospective observational studies and mendelian randomization analyses

BACKGROUND

The incidence of prostate cancer is increasing in older males globally. Age, ethnicity, and family history are identified as the well-known risk factors for prostate cancer, but few modifiable factors have been firmly established. The objective of this study was to identify and evaluate various factors modifying the risk of prostate cancer reported in meta-analyses of prospective observational studies and mendelian randomization (MR) analyses.

METHODS AND FINDINGS

We searched PubMed, Embase, and Web of Science from the inception to January 10, 2022, updated on September 9, 2023, to identify meta-analyses and MR studies on prostate cancer. Eligibility criteria for meta-analyses were (1) meta-analyses including prospective observational studies or studies that declared outcome-free at baseline; (2) evaluating the factors of any category associated with prostate cancer incidence; and (3) providing effect estimates for further data synthesis. Similar criteria were applied to MR studies. Meta-analysis was repeated using the random-effects inverse-variance model with DerSimonian-Laird method. Quality assessment was then conducted for included meta-analyses using AMSTAR-2 tool and for MR studies using STROBE-MR and assumption evaluation. Subsequent evidence grading criteria for significant associations in meta-analyses contained sample size, P values and 95% confidence intervals, 95% prediction intervals, heterogeneity, and publication bias, assigning 4 evidence grades (convincing, highly suggestive, suggestive, or weak). Significant associations in MR studies were graded as robust, probable, suggestive, or insufficient considering P values and concordance of effect directions. Finally, 92 selected from 411 meta-analyses and 64 selected from 118 MR studies were included after excluding the overlapping and outdated studies which were published earlier and contained fewer participants or fewer instrument variables for the same exposure. In total, 123 observational associations (45 significant and 78 null) and 145 causal associations (55 significant and 90 null) were categorized into lifestyle; diet and nutrition; anthropometric indices; biomarkers; clinical variables, diseases, and treatments; and environmental factors. Concerning evidence grading on significant associations, there were 5 highly suggestive, 36 suggestive, and 4 weak associations in meta-analyses, and 10 robust, 24 probable, 4 suggestive, and 17 insufficient causal associations in MR studies. Twenty-six overlapping factors between meta-analyses and MR studies were identified, with consistent significant effects found for physical activity (PA) (occupational PA in meta: OR = 0.87, 95% CI: 0.80, 0.94; accelerator-measured PA in MR: OR = 0.49, 95% CI: 0.33, 0.72), height (meta: OR = 1.09, 95% CI: 1.06, 1.12; MR: OR = 1.07, 95% CI: 1.01, 1.15, for aggressive prostate cancer), and smoking (current smoking in meta: OR = 0.74, 95% CI: 0.68, 0.80; smoking initiation in MR: OR = 0.91, 95% CI: 0.86, 0.97). Methodological limitation is that the evidence grading criteria could be expanded by considering more indices.

CONCLUSIONS

In this large-scale study, we summarized the associations of various factors with prostate cancer risk and provided comparisons between observational associations by meta-analysis and genetically estimated causality by MR analyses. In the absence of convincing overlapping evidence based on the existing literature, no robust associations were identified, but some effects were observed for height, physical activity, and smoking.

Biological and clinical significance of radiomics features obtained from magnetic resonance imaging preceding pre-carbon ion radiotherapy in prostate cancer based on radiometabolomics

Introduction

We aimed to investigate the feasibility of metabolomics to explain the underlying biological implications of radiomics features obtained from magnetic resonance imaging (MRI) preceding carbon ion radiotherapy (CIRT) in patients with prostate cancer and to further explore the clinical significance of radiomics features on the prognosis of patients, based on their biochemical recurrence (BCR) status.

Methods

Metabolomic results obtained using high-performance liquid chromatography coupled with tandem mass spectrometry of urine samples, combined with pre-RT radiomic features extracted from MRI images, were evaluated to investigate their biological significance. Receiver operating characteristic (ROC) curve analysis was subsequently conducted to examine the correlation between these biological implications and clinical BCR status. Statistical and metabolic pathway analyses were performed using MetaboAnalyst and R software.

Results

Correlation analysis revealed that methionine alteration extent was significantly related to four radiomic features (Contrast, Difference Variance, Small Dependence High Gray Level Emphasis, and Mean Absolute Deviation), which were significantly correlated with BCR status. The area under the curve (AUC) for BCR prediction of these four radiomic features ranged from 0.704 to 0.769, suggesting that the higher the value of these four radiomic features, the greater the decrease in methionine levels after CIRT and the lower the probability of BCR. Pre-CIRT MRI radiomic features were associated with CIRT-suppressed metabolites.

Discussion

These radiomic features can be used to predict the alteration in the amplitude of methionine after CIRT and the BCR status, which may contribute to the optimization of the CIRT strategy and deepen the understanding of PCa.

A Mendelian randomization-based approach to explore the relationship between leukocyte counts and breast cancer risk in European ethnic groups

Exploring the potential association between peripheral blood leukocyte counts and breast cancer risk by Mendelian randomization (MR) analysis methods. Genetic data related to peripheral blood sorting counts of leukocytes were collected from a genome-wide association study by Blood Cell Consortium (BCX). Single nucleotide polymorphic loci predicting peripheral blood sorting counts of these leukocytes were selected as instrumental variables according to the correlation assumption, independence assumption and exclusivity assumption of MR. The data on breast cancer and its subtypes were obtained from Breast Cancer Association Consortium (BCAC) and FinnGen Consortium. In this study, the Inverse-Variance Weighted (IVW), Weighted Median, MR-Egger, Maximum Likelihood (ML), MR-PRESSO and Constrained Maximum Likelihood and Model Averaging (cML-MA) methods of random effects models were used for MR analysis. Cochran's Q analysis, and MR-Egger intercept analysis were applied for sensitivity analysis. IVW and cML-MA were considered the primary analytical tools, and the results of the other 4 MRs were used as complementary and validation. The results suggest that there is no significant causal relationship between leukocyte count and breast cancer risk (IVW OR = 0.98 [95% CI: 0.93-1.03], p-value = 0.35; CML-MA OR = 1.01 [95% CI: 0.98-1.05], p-value = 0.51). In addition, we analyzed whether there was a potential correlation between the five main types of categorized leukocyte counts and different breast cancer subtypes. We did not find significant evidence to support a significant correlation between leukocyte counts and breast cancer subtypes.

FN1 mediated activation of aspartate metabolism promotes the progression of triple-negative and luminal a breast cancer

BACKGROUND

Breast cancer (BC) is regarded as one of the most common cancers diagnosed among the female population and has an extremely high mortality rate. It is known that Fibronectin 1 (FN1) drives the occurrence and development of a variety of cancers through metabolic reprogramming. Aspartic acid is considered to be an important substrate for nucleotide synthesis. However, the regulatory mechanism between FN1 and aspartate metabolism is currently unclear.

METHODS

We used RNA sequencing (RNA seq) and liquid chromatography-mass spectrometry to analyze the tumor tissues and paracancerous tissues of patients. MCF7 and MDA-MB-231 cells were used to explore the effects of FN1-regulated aspartic acid metabolism on cell survival, invasion, migration and tumor growth. We used PCR, Western blot, immunocytochemistry and immunofluorescence techniques to study it.

RESULTS

We found that FN1 was highly expressed in tumor tissues, especially in Lumina A and TNBC subtypes, and was associated with poor prognosis. In vivo and in vitro experiments showed that silencing FN1 inhibits the activation of the YAP1/Hippo pathway by enhancing YAP1 phosphorylation, down-regulates SLC1A3-mediated aspartate uptake and utilization by tumor cells, inhibits BC cell proliferation, invasion and migration, and promotes apoptosis. In addition, inhibition of FN1 combined with the YAP1 inhibitor or SLC1A3 inhibitor can effectively inhibit tumor growth, of which inhibition of FN1 combined with the YAP1 inhibitor is more effective.

CONCLUSION

Targeting the "FN1/YAP1/SLC1A3/Aspartate metabolism" regulatory axis provides a new target for BC diagnosis and treatment. This study also revealed that intratumoral metabolic heterogeneity plays an important role in the progression of different subtypes of breast cancer.

Changes in the survival of patients with breast cancer: Poland, 2000-2019

PURPOSE

The main aim of this study was to estimate breast cancer survival in Poland over the period from 2000 to 2019 in both sexes.

METHODS

Data were obtained from the Polish National Cancer Registry. The presented metrics included age-standardized 5- and 10-year net survival (NS), median survival times, years of life lost (YLLs), and standardized mortality ratios (SMRs).

RESULTS

Between 2000 and 2019, 315,278 patients (2353 men and 312,925 women; male-to-female ratio 1/100) were diagnosed with breast cancer in Poland. In this period, 721,987 YLLs were linked to breast cancer. Women presented a higher 5- and 10-year age-standardized NS than men (5-year NS: 77.33% for women and 65.47% for men, P < 0.001, common language effect size (CL) 1.00; 10-year NS: 68.75% for women and 49.50% for men, P < 0.001, CL 1.00). Between the earliest and latest studied period, namely 2000-2004 and 2015-2019, there was a statistically significant increase only in female survival (+ 7.32 pp, P < 0.001, CL 1.00). SMRs were significantly higher for women than for men (3.35 vs. 2.89, respectively).

CONCLUSION

Over the last two decades, breast cancer survival in Poland has improved significantly. Nonetheless, special attention should be given to the disparities between sexes and the gap in overall improvement of survival rates compared with other European countries.

Dual Effect of Tryptamine on Prostate Cancer Cell Growth Regulation: A Pilot Study

Abnormal tryptophan metabolism is linked to cancer and neurodegenerative diseases, and tryptophan metabolites have been reported as potential prostate cancer (PCa) biomarkers. However, little is known about the bioactivities of tryptophan metabolites on PCa cell growth. In this study, MTT and transwell assays were used to study the cytotoxicities of 13 major tryptophan metabolites on PCa and normal prostate epithelial cell lines. Ultraperformance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) was used to analyze metabolic changes in cells treated with tryptamine. Flow cytometry, confocal imaging, and Western blot were used to test the apoptosis induced by tryptamine. It was shown that tryptamine had obvious inhibitory effects on PCa cell lines PC-3 and LNCaP, stronger than those on the normal prostate cell line RWPE-1. Tryptamine was further shown to induce apoptosis and inhibit PC-3 cell migration. Metabolic changes including amino acid metabolism related to cell proliferation and metastasis were found in PC-3 cells treated with tryptamine. Furthermore, a PC-3 xenograft mouse model was used to study the effect of tryptamine in vivo. The intratumoral injection of tryptamine was demonstrated to significantly reduce the tumor growth and tumor sizes in vivo; however, intraperitoneal treatment resulted in increased tumor growth. Such dual effects in vivo advanced our understanding of the bioactivity of tryptamine in regulating prostate tumor development, in addition to its major role as a neuromodulator.