Steroid Hormone Biosynthesis Metabolism Is Associated With Fatigue Related to Androgen Deprivation Therapy for Prostate Cancer

Metabolic underpinnings of cancer-related fatigue

Cancer-related fatigue (CRF) is one of the most prevalent and detrimental complications of cancer. Emerging evidence suggests that obesity and insulin resistance are associated with CRF occurrence and severity in cancer patients and survivors. In this narrative review, we analyzed recent studies including both preclinical and clinical research on the relationship between obesity and/or insulin resistance and CRF. We also describe potential mechanisms for these relationships, though with the caveat that because the mechanisms underlying CRF are incompletely understood, the mechanisms mediating the association between obesity/insulin resistance and CRF are similarly incompletely delineated. The data suggest that, in addition to their effects to worsen CRF by directly promoting tumor growth and metastasis, obesity and insulin resistance may also contribute to CRF by inducing chronic inflammation, neuroendocrinological disturbance, and metabolic alterations. Furthermore, studies suggest that patients with obesity and insulin resistance experience more cancer-induced pain and are at more risk of emotional and behavioral disruptions correlated with CRF. However, other studies implied a potentially paradoxical impact of obesity and insulin resistance to reduce CRF symptoms. Despite the need for further investigation utilizing interventions to directly elucidate the mechanisms of cancer-related fatigue, current evidence demonstrates a correlation between obesity and/or insulin resistance and CRF, and suggests potential therapeutics for CRF by targeting obesity and/or obesity-related mediators.

Metabolomics identifies and validates serum androstenedione as novel biomarker for diagnosing primary angle closure glaucoma and predicting the visual field progression

Background

Primary angle closure glaucoma (PACG) is the leading cause of irreversible blindness in Asia, and no reliable, effective diagnostic, and predictive biomarkers are used in clinical routines. A growing body of evidence shows metabolic alterations in patients with glaucoma. We aimed to develop and validate potential metabolite biomarkers to diagnose and predict the visual field progression of PACG.

Methods

Here, we used a five-phase (discovery phase, validation phase 1, validation phase 2, supplementary phase, and cohort phase) multicenter (EENT hospital, Shanghai Xuhui Central Hospital), cross-sectional, prospective cohort study designed to perform widely targeted metabolomics and chemiluminescence immunoassay to determine candidate biomarkers. Five machine learning (random forest, support vector machine, lasso, K-nearest neighbor, and GaussianNaive Bayes [NB]) approaches were used to identify an optimal algorithm. The discrimination ability was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration was assessed by Hosmer-Lemeshow tests and calibration plots.

Results

Studied serum samples were collected from 616 participants, and 1464 metabolites were identified. Machine learning algorithm determines that androstenedione exhibited excellent discrimination and acceptable calibration in discriminating PACG across the discovery phase (discovery set 1, AUCs=1.0 [95% CI, 1.00-1.00]; discovery set 2, AUCs = 0.85 [95% CI, 0.80-0.90]) and validation phases (internal validation, AUCs = 0.86 [95% CI, 0.81-0.91]; external validation, AUCs = 0.87 [95% CI, 0.80-0.95]). Androstenedione also exhibited a higher AUC (0.92-0.98) to discriminate the severity of PACG. In the supplemental phase, serum androstenedione levels were consistent with those in aqueous humor (r=0.82, p=0.038) and significantly (p=0.021) decreased after treatment. Further, cohort phase demonstrates that higher baseline androstenedione levels (hazard ratio = 2.71 [95% CI: 1.199-6.104], p=0.017) were associated with faster visual field progression.

Conclusions

Our study identifies serum androstenedione as a potential biomarker for diagnosing PACG and indicating visual field progression.

Funding

This work was supported by Youth Medical Talents - Clinical Laboratory Practitioner Program (2022-65), the National Natural Science Foundation of China (82302582), Shanghai Municipal Health Commission Project (20224Y0317), and Higher Education Industry-Academic-Research Innovation Fund of China (2023JQ006).

Understanding Sleep Disturbances in Prostate Cancer-A Scientometric Analysis of Sleep Assessment, Aetiology, and Its Impact on Quality of Life

Prostate cancer is the most commonly diagnosed cancer in the United Kingdom. While androgen-deprivation therapy is the most common treatment for prostate cancer, patients undergoing this treatment typically experience side effects in terms of sleep disturbances. However, the relation between prostate cancer and sleep and the way in which sleep interventions may benefit oncological patients is underinvestigated in the literature. The current study aims to review in a data-driven approach the existing literature on the field of prostate cancer and sleep to identify impactful documents and major thematic domains. To do so, a sample of 1547 documents was downloaded from Scopus, and a document co-citation analysis was conducted on CiteSpace software. In the literature, 12 main research domains were identified as well as 26 impactful documents. Research domains were examined regarding the link between prostate cancer and sleep, by taking into account variations in hormonal levels. A major gap in the literature was identified in the lack of use of objective assessment of sleep quality in patients with prostate cancer.

Global metabolomics study on the pathogenesis of pediatric medulloblastoma via UPLC- Q/E-MS/MS

Medulloblastoma is one of the most frequent malignant brain tumors in infancy and childhood. Early diagnosis and treatment are quite crucial for the prognosis. However, the pathogenesis of medulloblastoma is still not completely clarified. High-resolution mass spectrometry has enabled a comprehensive investigation on the mechanism of disease from the perspective of metabolism. Herein, we compared the difference of metabolic profiles of serum between medulloblastoma (n = 33) and healthy control (HC, n = 16) by using UPLC-Q/E-MS/MS. Principal component analysis and orthogonal projections to latent structures discriminant analysis (OPLS-DA) intuitively revealed the significantly distinct metabolic profiles between medulloblastoma and HC (p < 0.01 for permutation test on OPLS-DA model). Total of 25 significantly changed metabolites were identified. ROC analysis reported that six of them (Phosphatidic acid (8:0/15:0), 3'-Sialyllactose, Isocoproporphyrin, Acetylspermidine, Fructoseglycine and 3-Hydroxydodecanedioate) showed high specificity and precision to be potential diagnosis biomarkers (AUC > 0.98). Functional analysis discovered that there are four pathways notably perturbed for medulloblastoma. These pathways are related with the dysfunction of arachidonic acid metabolism, steroid hormone biosynthesis, and folate-related metabolism. The target intervention on these pathways may reduce the mortality of medulloblastoma.

Causality of genetically determined metabolites on anxiety disorders: a two-sample Mendelian randomization study

BACKGROUND

Although anxiety disorders are one of the most prevalent mental disorders, their underlying biological mechanisms have not yet been fully elucidated. In recent years, genetically determined metabolites (GDMs) have been used to reveal the biological mechanisms of mental disorders. However, this strategy has not been applied to anxiety disorders. Herein, we explored the causality of GDMs on anxiety disorders through Mendelian randomization study, with the overarching goal of unraveling the biological mechanisms.

METHODS

A two-sample Mendelian randomization (MR) analysis was implemented to assess the causality of GDMs on anxiety disorders. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, whereas four different GWAS datasets of anxiety disorders were the outcomes. Notably, all datasets were acquired from publicly available databases. A genetic instrumental variable (IV) was used to explore the causality between the metabolite and anxiety disorders for each metabolite. The MR Steiger filtering method was implemented to examine the causality between metabolites and anxiety disorders. The standard inverse variance weighted (IVW) method was first used for the causality analysis, followed by three additional MR methods (the MR-Egger, weighted median, and MR-PRESSO (pleiotropy residual sum and outlier) methods) for sensitivity analyses in MR analysis. MR-Egger intercept, and Cochran's Q statistical analysis were used to evaluate possible heterogeneity and pleiotropy. Bonferroni correction was used to determine the causative association features (P < 1.03 × 10^-4). Furthermore, metabolic pathways analysis was performed using the web-based MetaboAnalyst 5.0 software. All statistical analysis were performed in R software. The STROBE-MR checklist for the reporting of MR studies was used in this study.

RESULTS

In MR analysis, 85 significant causative relationship GDMs were identified. Among them, 11 metabolites were overlapped in the four different datasets of anxiety disorders. Bonferroni correction showing1-linoleoylglycerophosphoethanolamine (OR_{fixed-effect IVW} = 1.04; 95% CI 1.021-1.06; P_{fixed-effect IVW} = 4.3 × 10^-5) was the most reliable causal metabolite. Our results were robust even without a single SNP because of a "leave-one-out" analysis. The MR-Egger intercept test indicated that genetic pleiotropy had no effect on the results (intercept = - 0.0013, SE = 0.0006, P = 0.06). No heterogeneity was detected by Cochran's Q test (MR-Egger. Q = 7.68, P = 0.742; IVW. Q = 12.12, P = 0.436). A directionality test conducted by MR Steiger confirmed our estimation of potential causal direction (P < 0.001). In addition, two significant pathways, the "primary bile acid biosynthesis" pathway (P = 0.008) and the "valine, leucine, and isoleucine biosynthesis" pathway (P = 0.03), were identified through metabolic pathway analysis.

CONCLUSION

This study provides new insights into the causal effects of GDMs on anxiety disorders by integrating genomics and metabolomics. The metabolites that drive anxiety disorders may be suited to serve as biomarkers and also will help to unravel the biological mechanisms of anxiety disorders.

Fatigue have impact on the sexual problems in Chinese females with systemic lupus erythematosus

Background

Systemic lupus erythematosus (SLE) might affect all aspects of life including sexual function; previous study indicated that fatigue was the risk factor of sexual dysfunction. The current study aims to investigate the effects of SLE on Chinese mainland female patients’ sexual problems compared with healthy subjects and to investigate the relationship among fatigue, disease parameters, depression, quality of life and sexual problems in Chinese female patients with SLE.

Methods

A total of 128 female SLE patients (mean age: 43.65 ± 7.13 years) and 121 healthy female controls (mean age 43.59 ± 6.57 years) were included in this cross-sectional study. All data were collected consecutively by face-to-face questionnaires from January 2021 to December 2021. SLE patients completed questionnaires for demographic or clinical variables, the 10-cm Visual Analog Scale for pain, the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) for disease activity, the multidimensional fatigue inventory (MFI) for fatigue, the patient health questionnaire-9 (PHQ-9) for depression, the Female Sexual Function Index (FSFI) for problems, and the Short Form 12 health survey for quality of life. Independent sample t-test, Mann–Whitney U-test, Chi-square test, and forward stepwise binary logistic regression model were used to analyze these data.

Results

Our results showed that the prevalence of female sexual problems was 78.9% in SLE patients, which was significantly higher than the controls (56.7%; p < 0.05). The results found that having child (OR 23.04; p < 0.000), age (OR 1.11; p = 0.002), DMARDs usage (OR 0.04; p = 0.004), MFI total score (OR 1.06; p = 0.006), and disease duration (OR 1.16; p = 0.043) were the potential risk factors of female sexual problems by forward stepwise binary logistic regression.

Conclusion

The present study reported that female sexual problems was more common in Chinese SLE female patients compared to controls. Having child, age, DMARDs usage, fatigue, and disease duration had great impacts on female sexual problems in Chinese SLE patients. Rheumatologists and nurses should pay close attention to SLE female patients’ sexual problems, especially those having no child, older age, not using DMARDs, fatigue, or long disease duration by health education or other methods to improve their sexual problems, and ultimately improve SLE patients’ quality of life.

Comparing metabolic profiles between female endurance athletes and non-athletes reveals differences in androgen and corticosteroid levels

Endurance training is associated with physiological changes in elite athletes, but little is known about female-specific effects of endurance training. Despite the significant rise in female sports participation, findings from studies performed on male athletes are largely extrapolated to females without taking into consideration sex-specific differences in metabolism. Subsequently, this study aimed to investigate the steroid hormone profiles of elite female endurance athletes in comparison with their non-athletic counterparts. Untargeted metabolomics-based mass spectroscopy combined with ultra-high-performance liquid chromatography was performed on serum samples from 51 elite female endurance athletes and 197 non-athletic females. The results showed that, compared to non-athletic females, certain androgen, pregnenolone, and progestin steroid hormones were reduced in elite female endurance athletes, while corticosteroids were elevated. The most significantly altered steroid hormones were 5alpha-androstan-3alpha,17alpha-diol monosulfate (FDR = 1.90 × 10^-05), androstenediol (3alpha, 17alpha) monosulfate (FDR = 2.93 × 10^-04), and cortisol (FDR = 2.93 × 10^-04). Conclusively, the present study suggests that elite female endurance athletes have a unique steroid hormone profile with implications on their general health and performance.

A Molecular Approach to Understanding the Role of Diet in Cancer-Related Fatigue: Challenges and Future Opportunities

Cancer-related fatigue (CRF) is considered one of the most frequent and distressing symptoms for cancer survivors. Despite its high prevalence, factors that predispose, precipitate, and perpetuate CRF are poorly understood. Emerging research focuses on cancer and treatment-related nutritional complications, changes in body composition, and nutritional deficiencies that can compound CRF. Nutritional metabolomics, the novel study of diet-related metabolites in cells, tissues, and biofluids, offers a promising tool to further address these research gaps. In this position paper, we examine CRF risk factors, summarize metabolomics studies of CRF, outline dietary recommendations for the prevention and management of CRF in cancer survivorship, and identify knowledge gaps and challenges in applying nutritional metabolomics to understand dietary contributions to CRF over the cancer survivorship trajectory.

Nandrolone-Induced Tumor Progression in Hormone-Sensitive Prostate Cancer

ABSTRACT

Hormone-sensitive prostate cancer responds favorably to testosterone suppression induced by GnRH analogs or antagonists. This effect may theoretically be countered by anabolic steroids. We describe a patient of a recurrent hormone-sensitive prostate cancer who was on salvage androgen deprivation therapy with degarelix and developed rapid progression after over-the-counter nandrolone injections.