Plasma metabolomic profile associated with fatigue in cancer patients

Prevalence and biopsychosocial indicators of fatigue in cancer patients

INTRODUCTION

Symptoms of cancer-related fatigue (CRF) can have a significant impact on patients' quality of life and treatment adherence. We aimed to investigate the relationship between CRF and multiple psychosocial and somatic indicators within a large mixed cancer sample.

METHODS

In this cross-sectional study, N = 1787 outpatients with cancer were assessed for CRF, pain, anxiety, and depression using validated screening instruments. We further obtained clinical parameters (Hb, CRP, creatinine, leukocytes, ASAT, and ALAT), sociodemographic data (age, gender, income, education level, marital status, parenthood, and living area), and lifestyle factors. Multivariate linear regression models were applied to estimate the impact of each indicator on CRF.

RESULTS

Overall, 90.6% of patients experienced some CRF, with 14.8% experiencing severe CRF. No gender difference was found in the prevalence of CRF. Patients with higher levels of pain, depressive symptoms, and lower Hb levels had significantly higher levels of CRF (ps <0.001). Lower levels of CRF were observed in patients who had children (p = 0.03), had less education (p < 0.001), and were physically active for more than 2 h per week before their oncological diagnosis (p = 0.014). The latter was only a significant indicator in the male subsample.

CONCLUSION

The present results demonstrate a high prevalence of CRF and highlight that not only somatic and psychosocial factors, but also lifestyle factors prior to diagnosis appear to be associated with the etiology and persistence of CRF. To effectively treat CRF, a biopsychosocial, personalized approach is recommended.

Identification of crucial inflammaging related risk factors in multiple sclerosis

Background

Multiple sclerosis (MS) is an immune-mediated disease characterized by inflammatory demyelinating lesions in the central nervous system. Studies have shown that the inflammation is vital to both the onset and progression of MS, where aging plays a key role in it. However, the potential mechanisms on how aging-related inflammation (inflammaging) promotes MS have not been fully understood. Therefore, there is an urgent need to integrate the underlying mechanisms between inflammaging and MS, where meaningful prediction models are needed.

Methods

First, both aging and disease models were developed using machine learning methods, respectively. Then, an integrated inflammaging model was used to identify relative risk factors, by identifying essential "aging-inflammation-disease" triples. Finally, a series of bioinformatics analyses (including network analysis, enrichment analysis, sensitivity analysis, and pan-cancer analysis) were further used to explore the potential mechanisms between inflammaging and MS.

Results

A series of risk factors were identified, such as the protein homeostasis, cellular homeostasis, neurodevelopment and energy metabolism. The inflammaging indices were further validated in different cancer types. Therefore, various risk factors were integrated, and even both the theories of inflammaging and immunosenescence were further confirmed.

Conclusion

In conclusion, our study systematically investigated the potential relationships between inflammaging and MS through a series of computational approaches, and could present a novel thought for other aging-related diseases.

Metabolomic profiling of cancer-related fatigue involved in cachexia and chemotherapy

Patients with advanced cancer are frequently burdened with a severe sensation of fatigue called cancer-related fatigue (CRF). CRF is induced at various stages and treatments, such as cachexia and chemotherapy, and reduces the overall survival of patients. Objective and quantitative assessment of CRF could contribute to the diagnosis and prediction of treatment efficacy. However, such studies have not been intensively performed, particularly regarding metabolic profiles. Here, we conducted plasma metabolomics of 15 patients with urological cancer. The patients with and without fatigue, including those with cachexia or chemotherapy-induced fatigue, were compared. Significantly lower concentrations of valine and tryptophan were observed in fatigued patients than in non-fatigued patients. In addition, significantly higher concentrations of polyamine pathway metabolites were observed in patients with fatigue and cachexia than in those without cachexia. Patients with exacerbated fatigue due to chemotherapy showed significantly decreased cysteine and methionine metabolism before chemotherapy compared with those without fatigue exacerbation. These findings suggest that plasma metabolic profiles could help improve the diagnosis and monitoring of CRF.

Multi-omics analysis of the gut microbiome and metabolites associated with the psychoneurological symptom cluster in children with cancer receiving chemotherapy

BACKGROUND

Children with cancer receiving chemotherapy commonly report a cluster of psychoneurological symptoms (PNS), including pain, fatigue, anxiety, depression, and cognitive dysfunction. The role of the gut microbiome and its functional metabolites in PNS is rarely studied among children with cancer. This study investigated the associations between the gut microbiome-metabolome pathways and PNS in children with cancer across chemotherapy as compared to healthy children.

METHODS

A case-control study was conducted. Cancer cases were recruited from Children's Healthcare of Atlanta and healthy controls were recruited via flyers. Participants reported PNS using the Pediatric Patient-Reported Outcomes Measurement Information System. Data for cases were collected pre-cycle two chemotherapy (T0) and post-chemotherapy (T1), whereas data for healthy controls were collected once. Gut microbiome and its metabolites were measured using fecal specimens. Gut microbiome profiling was performed using 16S rRNA V4 sequencing, and metabolome was performed using an untargeted liquid chromatography-mass spectrometry approach. A multi-omics network integration program analyzed microbiome-metabolome pathways of PNS.

RESULTS

Cases (n = 21) and controls (n = 14) had mean ages of 13.2 and 13.1 years. For cases at T0, PNS were significantly associated with microbial genera (e.g., Ruminococcus, Megasphaera, and Prevotella), which were linked with carnitine shuttle (p = 0.0003), fatty acid metabolism (p = 0.001) and activation (p = 0.001), and tryptophan metabolism (p = 0.008). Megasphaera, clustered with aspartate and asparagine metabolism (p = 0.034), carnitine shuttle (p = 0.002), and tryptophan (p = 0.019), was associated with PNS for cases at T1. Gut bacteria with potential probiotic functions, along with fatty acid metabolism, tryptophan, and carnitine shuttle, were more clustered in cancer cases than the control network and this linkage with PNS needs further studies.

CONCLUSIONS

Using multi-omics approaches, this study indicated specific microbiome-metabolome pathways linked with PNS in children with cancer across chemotherapy. Due to limitations such as antibiotic use in cancer cases, these findings need to be further confirmed in a larger cohort.

Development and validation of nomogram prognostic model for predicting OS in patients with diffuse large B-cell lymphoma: a cohort study in China

This study comprehensively incorporates pathological parameters and novel clinical prognostic factors from the international prognostic index (IPI) to develop a nomogram prognostic model for overall survival in patients with diffuse large B-cell lymphoma (DLBCL). The aim is to facilitate personalized treatment and management strategies. This study enrolled a total of 783 cases for analysis. LASSO regression and stepwise multivariate COX regression were employed to identify significant variables and build a nomogram model. The calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) curve were utilized to assess the model's performance and effectiveness. Additionally, the time-dependent concordance index (C-index) and time-dependent area under the ROC curve (AUC) were computed to validate the model's stability across different time points. The study utilized 8 selected clinical features as predictors to develop a nomogram model for predicting the overall survival of DLBCL patients. The model exhibited robust generalization ability with an AUC exceeding 0.7 at 1, 3, and 5 years. The calibration curve displayed evenly distributed points on both sides of the diagonal, and the slopes of the three calibration curves were close to 1 and statistically significant, indicating high prediction accuracy of the model. Furthermore, the model demonstrated valuable clinical significance and holds the potential for widespread adoption in clinical practice. The novel prognostic model developed for DLBCL patients incorporates readily accessible clinical parameters, resulting in significantly enhanced prediction accuracy and performance. Moreover, the study's use of a continuous general cohort, as opposed to clinical trials, makes it more representative of the broader lymphoma patient population, thus increasing its applicability in routine clinical care.

Significant dysregulation of lipid metabolism in patients with papillary thyroid carcinoma after thyroidectomy

Introduction

Thyroidectomy and thyrotropin suppressive therapy is the widely used surgical treatment for papillary thyroid carcinoma (PTC) patients. However, systematic metabolic changes of post-operative PTC patients were rarely reported.

Methods

Here, untargeted metabolomic detection of cohorts from PTC before (t0) and 1-month-after (t1) thyroidectomy, were performed to characterize circulating metabolic signatures after surgical treatment.

Results

Our results showed PTC patients exhibited lower thyroid stimulating hormone degree, higher total thyroxine, and significant lipid-related metabolic alternations after thyroidectomy, which included 97 upregulations (including 93 lipids) and 5 downregulations (including 2 lipids and 3 nucleotides). Enrichment of metabolic pathways mainly included biosynthesis of fatty acids, purine metabolism, and linoleic acid metabolism. We also demonstrated that differential surgical approaches (hemi- and total thyroidectomy) and post-operative complication phenotypes (insomnia, fatigue), might lead to characteristic metabolic signatures.

Discussion

This study revealed dynamic changes of metabolite characteristics of PTC patients after surgical treatment, which were associated with clinical thyroid function parameters, surgical approaches, and complication occurrence. It enlightened us to pay more attention on the post-operative metabolic dysregulation of PTC patients and their long-term qualities of life, so as to provide cautious clinical decisions on surgical choices, treatments, and follow-up details.

Electroacupuncture treatment of primary dysmenorrhea: A randomized, participant-blinded, sham-controlled clinical trial protocol

BACKGROUND

Primary dysmenorrhea in women is a common and serious public health problem with psychological and physical effects. Painkillers have adverse effects, such as tolerance, addiction, irritation of the digestive tract, and liver and kidney damage. Electroacupuncture has been used as alternative therapy, although with no (non-anecdotal) evidence of effectiveness.

OBJECTIVE

This study aims to provide evidence for the feasibility and efficacy of electroacupuncture in the treatment of primary dysmenorrhea. Moreover, by observing changes in serum and urine metabolites, we will evaluate the putative mechanisms mediating electroacupuncture effects in primary dysmenorrhea.

METHODS

This multicenter, randomized, participant-blinded, sham-controlled clinical trial including 336 women with primary dysmenorrhea is being conducted at three hospital centers in China and consists of a 12-week treatment and a 3-month follow-up. Women will undergo electroacupuncture (n = 168) or sham acupuncture (n = 168), beginning 7 days before their menstruation, once per day, until menstruation. Each menstrual cycle equals one course of treatment, and we will evaluate a total of three courses of treatment. The primary outcome of interest is the change in visual analogue scale scores before and after treatment. The secondary outcomes include changes in the numeric rating scale, Cox Menstrual Symptom Scale, traditional Chinese medicine symptoms, the Self-Rating Anxiety Scale, Self-Rating Depression Scale, and 36-Item Short Form questionnaire scores, and a safety evaluation. Moreover, we will preliminarily investigate the metabolomics mechanism as a potential mediator of the association between electroacupuncture and primary dysmenorrhea symptomology.

DISCUSSION

We aim to find a suitable non-medicinal alternative for primary dysmenorrhea treatment to reduce reliance on non-steroidal anti-inflammatory drugs.

TRIAL REGISTRATION

Chinese Clinical Trial Registry: ChiCTR2100054234; http://www.chictr.org.cn/.

Longitudinal associations of plasma metabolites with persistent fatigue among colorectal cancer survivors up to 2 years after treatment

The underlying biological mechanisms causing persistent fatigue complaints after colorectal cancer treatment need further investigation. We investigated longitudinal associations of circulating concentrations of 138 metabolites with total fatigue and subdomains of fatigue between 6 weeks and 2 years after colorectal cancer treatment. Among stage I-III colorectal cancer survivors (n = 252), blood samples were obtained at 6 weeks, and 6, 12 and 24 months posttreatment. Total fatigue and fatigue subdomains were measured using a validated questionnaire. Tandem mass spectrometry was applied to measure metabolite concentrations (BIOCRATES AbsoluteIDQp180 kit). Confounder-adjusted longitudinal associations were analyzed using linear mixed models, with false discovery rate (FDR) correction. We assessed interindividual (between-participant differences) and intraindividual longitudinal associations (within-participant changes over time). In the overall longitudinal analysis, statistically significant associations were observed for 12, 32, 17 and three metabolites with total fatigue and the subscales "fatigue severity," "reduced motivation" and "reduced activity," respectively. Specifically, higher concentrations of several amino acids, lysophosphatidylcholines, diacylphosphatidylcholines, acyl-alkylphosphatidylcholines and sphingomyelins were associated with less fatigue, while higher concentrations of acylcarnitines were associated with more fatigue. For "fatigue severity," associations appeared mainly driven by intraindividual associations, while for "reduced motivation" stronger interindividual associations were found. We observed longitudinal associations of several metabolites with total fatigue and fatigue subscales, and that intraindividual changes in metabolites over time were associated with fatigue severity. These findings point toward inflammation and an impaired energy metabolism due to mitochondrial dysfunction as underlying mechanisms. Mechanistic studies are necessary to determine whether these metabolites could be targets for intervention.

The prognostic role and metabolic function of GGPS1 in oral squamous cell carcinoma

Background: GGPS1(geranylgeranyl diphosphate synthase 1) is a member of the prenyltransferase family. Abnormal expression of GGPS1 can disrupt the balance between protein farnesylation and geranylgeranylation, thereby affecting a variety of cellular physiologic and pathological processes. However, it is still unknown how this gene could contribute to the prognosis of oral squamous cell carcinoma (OSCC). This study aimed to explore the prognostic role of GGPS1 in OSCC and its relationship with clinical features. Methods: The RNA-seq data and clinical data were obtained from TCGA. The survival analyses, Cox regression analyses, ROC curves, nomograms, calibration curves, and gene function enrichments were established by R software. Results: The results showed that the high expression of GGPS1 in OSCC is related to poor prognosis. At the same time, multivariate Cox regression analyses showed that GGPS1 could be an independent prognostic biomarker, and its gene expression level is closely related to the histological stage of cancer. GGPS1 may promote tumorigenesis because of its metabolic function. Conclusion: This study came to a conclusion that GGPS1, whose high expression has a significantly unfavorable meaning toward the prognosis of OSCC, can act as a novel independent biomarker for OSCC.

Caffeine-Supplemented Diet Prevents Fatigue-Like Behavior in Tumor-Bearing Mice

Caffeine is a widely consumed stimulant, known for its positive effects on physical and mental performance. These effects are potentially beneficial for ameliorating cancer-related fatigue, which affects the quality of life of patients with cancer. This study aimed to determine the anti-fatigue and antitumor effects of caffeine in tumor-bearing mice. BALB/c mice were intravenously injected with C26 colon carcinoma cells and fed with normal or 0.05% caffeine-supplemented diet. Fatigue-like behavior was assessed by running performance using a treadmill test. Lung, blood, liver, muscle, and epididymal adipose tissue samples were collected on day 13 and examined. The antitumor effect of caffeine was assessed using subcutaneous tumor-bearing mice fed with 0.05% caffeine-supplemented diet, and the tumor volume was measured. C26 tumor-bearing mice showed fatigue-like behavior associated with hypoglycemia, depleted liver glycogen and non-esterified fatty acid (NEFA) levels. C26 tumor-bearing mice fed with 0.05% caffeine-supplemented diet showed improved running performance associated with restored NEFA levels. However, exacerbated hypoglycemia and liver glycogen levels after caffeine consumption may be due to tumor-induced catabolic signals, as the tumor volume was not affected. Collectively, caffeine may exert anti-fatigue effects through enhanced lipolysis leading to restored NEFA levels, which can be used as an alternative energy source.

Associative learning contributes to the persistence of fatigue-like behavior in male mice in a model of cancer survivorship

Persistent fatigue is a debilitating side effect that impacts a significant proportion of cancer survivors for which there is not yet an FDA-approved treatment. While certainly a multi-factorial problem, persistent fatigue could be due, in part, to associations learned during treatment. Therefore, we sought to investigate the role of associative learning in the persistence of fatigue using a preclinical model of cancer survivorship. For this purpose, we used a murine model of human papilloma virus-related head and neck cancer paired with a curative regimen of cisplatin-based chemoradiation in male C57BL/6J mice. Fatigue-like behavior was assessed by measuring variations in voluntary wheel running using a longitudinal design. Treatment robustly decreased voluntary wheel running, and this effect persisted for more than a month posttreatment. However, when wheels were removed during treatment, to minimize treatment-related fatigue, mice showed a more rapid return to baseline running levels. We confirmed that the delayed recovery observed in mice with continual wheel access was not due to increased treatment-related toxicity, in fact running attenuated cisplatin-induced kidney toxicity. Finally, we demonstrated that re-exposure to a treatment-related olfactory cue acutely re-instated fatigue. These data provide the first demonstration that associative processes can modulate the persistence of cancer-related fatigue-like behavior.

Transcriptomic and metabolomic insights into the role of the flgK gene in the pathogenicity of Pseudomonas plecoglossicida to orange-spotted grouper (Epinephelus coioides)

Pseudomonas plecoglossicida is the pathogen responsible for visceral white spot disease in large yellow croaker (Larimichthys crocea) and orange-spotted grouper (Epinephelus coioides). Previously, RNA sequencing showed that P. plecoglossicida flgK gene expression was significantly up-regulated in orange-spotted grouper spleens during infection. To explore the role of flgK in P. plecoglossicida pathogenicity, RNA interference (RNAi) was performed to silence the P. plecoglossicida flgK gene, and the mutant (flgK-RNAi strain) with the best silencing efficiency (89.40%) was chosen for further study. Results showed that flgK gene silencing significantly attenuated P. plecoglossicida motility, adhesion, and biofilm formation. Compared to those fish infected with the wild-type strain of P. plecoglossicida, orange-spotted grouper infected with the flgK-RNAi strain showed a 55% increase in the survival rate and a one-day delay in time of first death, with fewer pathogens in the spleen and fewer white spots on the spleen surface. RNAi of flgK significantly affected the transcriptome and metabolome of the spleen in infected orange-spotted grouper. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the C-type lectin receptor signaling pathway was the most significantly changed immune-related pathway and the mitogen-activated protein kinase (MAPK) signaling pathway was related to multiple immune-related pathways. Furthermore, arginine biosynthesis and glycerophospholipid metabolism were the most significantly changed metabolism-related pathways. These findings suggest that flgK is a virulence gene of P. plecoglossicida. Furthermore, flgK appears to be involved in the regulation of motility, adhesion, and biofilm formation in P. plecoglossicida, as well as in the regulation of inflammatory and immune responses of orange-spotted grouper to P. plecoglossicida infection.

Depression and fatigue in active IBD from a microbiome perspective-a Bayesian approach to faecal metagenomics

BACKGROUND

Extraintestinal symptoms are common in inflammatory bowel diseases (IBD) and include depression and fatigue. These are highly prevalent especially in active disease, potentially due to inflammation-mediated changes in the microbiota-gut-brain axis. The aim of this study was to investigate the associations between structural and functional microbiota characteristics and severity of fatigue and depressive symptoms in patients with active IBD.

METHODS

We included clinical data of 62 prospectively enrolled patients with IBD in an active disease state. Patients supplied stool samples and completed the questionnaires regarding depression and fatigue symptoms. Based on taxonomic and functional metagenomic profiles of faecal gut microbiota, we used Bayesian statistics to investigate the associative networks and triangle motifs between bacterial genera, functional modules and symptom severity of self-reported fatigue and depression.

RESULTS

Associations with moderate to strong evidence were found for 3 genera (Odoribacter, Anaerotruncus and Alistipes) and 3 functional modules (pectin, glycosaminoglycan and central carbohydrate metabolism) with regard to depression and for 4 genera (Intestinimonas, Anaerotruncus, Eubacterium and Clostridiales g.i.s) and 2 functional modules implicating amino acid and central carbohydrate metabolism with regard to fatigue.

CONCLUSIONS

This study provides the first evidence of association triplets between microbiota composition, function and extraintestinal symptoms in active IBD. Depression and fatigue were associated with lower abundances of short-chain fatty acid producers and distinct pathways implicating glycan, carbohydrate and amino acid metabolism. Our results suggest that microbiota-directed therapeutic approaches may reduce fatigue and depression in IBD and should be investigated in future research.

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.

Acupuncture ameliorates breast cancer-related fatigue by regulating the gut microbiota-gut-brain axis

Cancer-related fatigue (CRF) is the most common side effect of chemotherapy for breast cancer (BC). Acupuncture treatment has an anti-fatigue effect and can regulate gut microbiota disturbance in fatigue patients. Related studies have shown that the gut microbiota-gut-brain axis is closely related to the occurrence of CRF. In this study, we first investigated the alterations of acupuncture on fatigue-like behavior, gut microbiota, gut inflammation and neuroinflammation response, gut barriers, HPA axis, and serum metabolomics in CRF mice after BC chemotherapy. Then, the correlation analysis of gut microbiota and other indicators was discussed. Our results showed that acupuncture treatment could exert an anti-fatigue effect and ameliorate the gut barrier, gut inflammation, neuroinflammation, and dysfunction of the HPA axis in CRF mice after chemotherapy for BC. 16S rRNA sequencing showed that acupuncture treatment could enhance the abundance of Candidatus Arthromitus, Lactobacillus, and Clostridia_UCG-014_unclassified and decrease the abundances of Escherichia-Shigella, Burkholderia-Caballeronia-Paraburkholderia, and Streptococcus. Serum metabolomics analysis showed that acupuncture treatment could regulate the differential metabolites N-methylnicotinamide, beta-glycerophosphoric acid, geranyl acetoacetate, serotonin and phenylalanine, tyrosine and tryptophan biosynthesis, taurine and hypotaurine, and beta-alanine metabolic pathways. Correlation analysis indicated that there are certain correlations between gut microbiota and gut inflammation, neuroinflammation, gut barrier, HPA axis function and serum metabolites. In conclusion, our findings revealed that the anti-fatigue mechanism of acupuncture treatment may be closely related to the gut microbiota-gut-brain axis. This study also provided a new reference for basic and clinical research on CRF after breast cancer chemotherapy.