Exploratory Investigation of Early Biomarkers for Chronic Fatigue in Prostate Cancer Patients Following Radiation Therapy. Cancer Nurs. 2017;40:184-193. [PMID: 27105468 DOI: 10.1097/ncc.0000000000000381]

Development and validation of machine learning models for predicting cancer-related fatigue in lymphoma survivors

BACKGROUND

New cases of lymphoma are rising, and the symptom burden, like cancer-related fatigue (CRF), severely impacts the quality of life of lymphoma survivors. However, clinical diagnosis and treatment of CRF are inadequate and require enhancement.

OBJECTIVE

The main objective of this study is to construct machine learning-based CRF prediction models for lymphoma survivors to help healthcare professionals accurately identify the CRF population and better personalize treatment and care for patients.

METHODS

A cross-sectional study in China recruited lymphoma patients from June 2023 to March 2024, dividing them into two datasets for model construction and external validation. Six machine learning algorithms were used in this study: Logistic Regression (LR), Random Forest, Single Hidden Layer Neural Network, Support Vector Machine, eXtreme Gradient Boosting, and Light Gradient Boosting Machine (LightGBM). Performance metrics like the area under the receiver operating characteristic (AUROC) and calibration curves were compared. The clinical applicability was assessed by decision curve, and Shapley additive explanations was employed to explain variable significance.

RESULTS

CRF incidence was 40.7 % (dataset I) and 44.8 % (dataset II). LightGBM showed strong performance in training and internal validation. LR excelled in external validation with the highest AUROC and best calibration. Pain, total protein, physical function, and sleep disturbance were important predictors of CRF.

CONCLUSION

The study presents a machine learning-based CRF prediction model for lymphoma patients, offering dynamic, data-driven assessments that could enhance the development of automated CRF screening tools for personalized management in clinical practice.

Mechanistic insights into behavioral clusters associated with cancer-related systemic inflammatory response

PURPOSE OF REVIEW

This focused, narrative review mostly describes our team's investigations into the potential inflammatory mechanisms that contribute to the development of cancer-related gastrointestinal (GI) mucositis and its associated symptoms. This review summarizes details of our clinical and preclinical findings to test the role of inflammation in the development and occurrence of these cancer-related conditions.

RECENT FINDINGS

GI mucositis (GIM) is a common, distressing condition reported by cancer patients. GIM is often clustered with other behaviors including fatigue, pain, anorexia, depression, and diarrhea. It is hypothesized that there is a common biologic mechanism underpinning this symptom cluster. Our multi-platform investigations revealed that GIM and its associated cluster of behaviors may be triggered by local inflammation spreading systemically causing pro-inflammatory-mediated toxicities, leading to alterations in immune, metabolic, and nervous system functions and activities. For example, behavioral toxicities related to local irradiation for non-metastatic cancer may be triggered by mGluR5 activation influencing prolonged T cell as well as NF-κB transcription factor activities. Thus, interventions targeting inflammation and associated pathways may be a reasonable strategy to alleviate GIM and its symptom cluster.

SUMMARY

GIM may be a sign of a broader systemic inflammatory response triggered by cancer or its treatment. Addressing GIM and its associated symptoms primarily involves supportive care strategies focused on relieving symptoms, promoting healing, and preventing complications.

The role of proinflammatory cytokines and CXC chemokines (CXCL1-CXCL16) in the progression of prostate cancer: insights on their therapeutic management

Reproductive cancers are malignancies that develop in the reproductive organs. One of the leading cancers affecting the male reproductive system on a global scale is prostate cancer (PCa). The negative consequences of PCa metastases endure and are severe, significantly affecting mortality and life quality for those who are affected. The association between inflammation and PCa has captured interest for a while. Inflammatory cells, cytokines, CXC chemokines, signaling pathways, and other elements make up the tumor microenvironment (TME), which is characterized by inflammation. Inflammatory cytokines and CXC chemokines are especially crucial for PCa development and prognosis. Cytokines (interleukins) and CXC chemokines such as IL-1, IL-6, IL-7, IL-17, TGF-β, TNF-α, CXCL1-CXCL6, and CXCL8-CXCL16 are thought to be responsible for the pleiotropic effects of PCa, which include inflammation, progression, angiogenesis, leukocyte infiltration in advanced PCa, and therapeutic resistance. The inflammatory cytokine and CXC chemokines systems are also promising candidates for PCa suppression and immunotherapy. Therefore, the purpose of this work is to provide insight on how the spectra of inflammatory cytokines and CXC chemokines evolve as PCa develops and spreads. We also discussed recent developments in our awareness of the diverse molecular signaling pathways of these circulating cytokines and CXC chemokines, as well as their associated receptors, which may one day serve as PCa-targeted therapies. Moreover, the current status and potential of theranostic PCa therapies based on cytokines, CXC chemokines, and CXC receptors (CXCRs) are examined.

Multidimensional Predictors of Cancer-Related Fatigue Based on the Predisposing, Precipitating, and Perpetuating (3P) Model: A Systematic Review

Cancer-related fatigue (CRF) is a widespread symptom with high prevalence in cancer patients, seriously affecting their quality of life. In the context of precision care, constructing machine learning-based prediction models for early screening and assessment of CRF is beneficial to this situation. To further understand the predictors of CRF for model construction, we conducted a comprehensive search in PubMed, Web of Science, Embase, and Scopus databases, combining CRF with predictor-related terms. A total of 27 papers met the inclusion criteria. We evaluated the above studies into three subgroups following the predisposing, precipitating, and perpetuating (3P) factor model. (1) Predisposing factors-baseline fatigue, demographic characteristics, clinical characteristics, psychosocial traits and physical symptoms. (2) Precipitating factors-type and stage of chemotherapy, inflammatory factors, laboratory indicators and metabolic changes. (3) Perpetuating factors-a low level of physical activity and poorer nutritional status. Future research should prioritize large-scale prospective studies with emerging technologies to identify accurate predictors of CRF. The assessment and management of CRF should also focus on the above factors, especially the controllable precipitating factors, to improve the quality of life of cancer survivors.

Effectiveness of Treatments That Alter Metabolomics in Cancer Patients-A Systematic Review

INTRODUCTION

Cancer is the leading cause of death worldwide, with the most frequent being breast cancer in women, prostate cancer in men and colon cancer in both sexes. The use of metabolomics to find new biomarkers can provide knowledge about possible interventions based on the presence of oncometabolites in different cancer types.

OBJECTIVES

The primary purpose of this review is to analyze the characteristic metabolome of three of the most frequent cancer types. We further want to identify the existence and success rate of metabolomics-based intervention in patients suffering from those cancer types. Our conclusions are based on the analysis of the methodological quality of the studies.

METHODS

We searched for studies that investigated the metabolomic characteristics in patients suffering from breast cancer, prostate cancer or colon cancer in clinical trials. The data were analyzed, as well as the effects of specific interventions based on identified metabolomics and one or more oncometabolites. The used databases were PubMed, Virtual Health Library, Web of Science, EBSCO and Cochrane Library. Only nine studies met the selection criteria. Study bias was analyzed using the Cochrane risk of bias tool. This systematic review protocol was registered at the International Prospective Register of Systematic Reviews (PROSPERO: CRD42023401474).

RESULTS

Only nine studies about clinical trials were included in this review and show a moderate quality of evidence. Metabolomics-based interventions related with disease outcome were conflictive with no or small changes in the metabolic characteristics of the different cancer types.

CONCLUSIONS

This systematic review shows some interesting results related with metabolomics-based interventions and their effects on changes in certain cancer oncometabolites. The small number of studies we identified which fulfilled our inclusion criteria in this systematic review does not allow us to draw definitive conclusions. Nevertheless, some results can be considered as promising although further research is needed. That research must focus not only on the presence of possible oncometabolites but also on possible metabolomics-based interventions and their influence on the outcome in patients suffering from breast cancer, prostate cancer or colon cancer.

Positive affect and fatigue as predictors of anti-inflammatory IL-10 concentrations among colorectal cancer patients during adjuvant chemotherapy

OBJECTIVES

(1) To examine the relationships of positive and negative affect and symptoms of depression, anxiety, and fatigue at baseline with the anti-inflammatory cytokine IL-10 concentrations in serum at three points in colorectal cancer patients; and (2) to assess the relationship between these factors and disease recurrence or mortality after a median follow-up of 24 months.

METHODS

In a prospective trial, 92 stage II or III colorectal cancer patients scheduled to receive standard chemotherapy were enrolled. Blood samples were collected prior to start of chemotherapy onset (T0), 3 months later (T1), and upon chemotherapy completion (T2).

RESULTS

IL-10 concentrations were similar across the time points. Linear mixed-effects model analysis showed that controlling for confounders, higher positive affect and lower fatigue pretreatment (T0) predicted IL-10 concentrations across the time points (estimate = 0.18, SE = 0.08, 95% CI = 0.03, 0.34, p < .04 and estimate = -0.25, SE = 0.12, 95% CI = -0.50, 0.01, p < .04, respectively). Depression at T0 significantly predicted higher disease recurrence and mortality (estimate = 0.17, SE = 0.08, adjusted OR = 1.18, 95% CI = 1.02, 1.38, p = .03).

CONCLUSIONS

We report on associations not previously assessed between positive affect and fatigue and the anti-inflammatory cytokine IL-10. Results add to previous findings suggesting that positive affect and fatigue could have a role in anti-inflammatory cytokine dysregulation.

Serum metabolomics reveals the effects of accompanying treatment on fatigue in patients with multiple myeloma

PURPOSE

The renewal and iteration of chemotherapy drugs have resulted in more frequent long-term remissions for patients with multiple myeloma (MM). MM has transformed into a chronic illness for many patients, but the cancer-related fatigue (CRF) of many MM convalescent patients experience is frequently overlooked. We investigated whether the accompanying treatment of family members would affect MM patients' CRF and explore their serum metabolomics, so as to provide clinicians with new ideas for identifying and treating CRF of MM patients.

METHODS

This was a single-center study, and a total of 30 MM patients were included in the study. Patients were divided into two groups based on whether they have close family members accompanying them through the whole hospitalization treatment. These patients received regular chemotherapy by hematology specialists, and long-term follow-up was done by general practitioners. Patients' CRF assessment for several factors used the Chinese version of the Brief Fatigue Inventory (BFI-C). Face-to-face questionnaires were administered at a time jointly determined by the patient and the investigator. All questionnaires were conducted by a general practitioner. The LC-MS-based metabolomics analysis determined whether the patients' serum metabolites were related to their fatigue severity. A correlation analysis investigated the relationship between serum metabolites and clinical laboratory indicators.

RESULTS

The fatigue severity of MM patients whose family members participated in the treatment process (group A) was significantly lower than patients whose family members did not participate in the treatment process (group B). There was a statistically significant difference (fatigue severity composite score: t =  - 2.729, p = 0.011; fatigue interference composite score: t =  - 3.595, p = 0.001). There were no differences between the two groups of patients' gender, age, regarding clinical staging, tumor burden, blood routine, biochemical, or coagulation indexes. There were 11 metabolites, including guanidine acetic acid (GAA), 1-(Methylthio)-1-hexanethiol, isoeucyl-asparagine, L-agaritine, tryptophyl-tyrosine, and betaine, which significantly distinguished the two groups of MM patients. GAA had the strongest correlation with patient fatigue, and the difference was statistically significant (fatigue severity composite score: r = 0.505, p = 0.0044; fatigue interference composite score: r = 0.576, p = 0.0009). The results showed that GAA negatively correlated with albumin (r =  - 0.4151, p = 0.0226) and GGT (r =  - 0.3766, p = 0.0402). Meanwhile, GAA positively correlated with PT (r = 0.385, p = 0.0473), and the difference was statistically significant.

CONCLUSION

The study is the first to report that family presence throughout the whole hospitalization may alleviate CRF in MM patients. Moreover, the study evaluated serum metabolites linked to CRF in MM patients and found that CRF has a significant positive correlation with GAA. GAA may be a more sensitive biomarker than liver enzymes, PT, and serum albumin in predicting patient fatigue. While our sample may not represent all MM patients, it proposes a new entry point to help clinicians better identify and treat CRF in MM patients.

Circulating levels of IL-6 and TGF-β1 in patients with prostate cancer undergoing radiotherapy: associations with acute radiotoxicity and fatigue symptoms

Background

The goal of research was to investigate the possible relations between serum concentrations of IL-6 and TGF-β1, individual and clinical characteristics, and adverse effects of radiotherapy in patients with prostate cancer: acute and late genitourinary and gastrointestinal toxicity, and fatigue.

Methods

Thirty-nine patients with localized or locally advanced prostate cancer who were treated with radiotherapy were enrolled in this study. The acute radiotoxicity grades and fatigue levels were assessed during the radiotherapy and 1 month after the radiotherapy. Estimation of the late radiotoxicity was performed every three months in the first year, every four months in the second year, and then every six months. Serum levels of IL-6 and TGF-β1 were determined before radiotherapy and after the 25th radiotherapy fraction by ELISA.

Results

The significant positive association between diabetes mellitus and changes in acute genitourinary toxicity grades during the radiotherapy was observed in prostate cancer patients. In addition, patients who were smokers had significantly higher maximum fatigue levels in comparison with patients who were non-smokers. The circulating IL-6 levels were significantly higher after the 25th radiotherapy fraction in comparison with levels determined before radiotherapy. The significant positive correlations between pretreatment TGF-β1 levels and maximum genitourinary toxicity grades and between TGF-β1 levels after the 25th fraction and genitourinary toxicity grades after the 25th fraction, were found. The pretreatment IL-6 concentrations and TGF-β1 concentrations after the 25th fraction were positively correlated with maximum genitourinary toxicity grades. The IL-6 levels after the 25th fraction were positively associated with genitourinary toxicity grades after this fraction. The pretreatment IL-6 concentrations were significantly positively correlated with maximum fatigue scores. The significant positive correlation between IL-6 concentrations and fatigue scores after the 25th fraction was determined. The positive correlations between IL-6 and TGF-β1 concentrations measured after the 25th fraction and maximum fatigue scores were observed.

Conclusions

Our results suggest that serum levels of IL-6 and TGF-β1 might influence the severity of acute genitourinary radiotoxicity and fatigue in patients with prostate cancer. Combining clinical parameters and circulating cytokine levels might be useful for the prediction of adverse reactions to radiotherapy.

Differences in Circulating Extracellular Vesicle and Soluble Cytokines in Older Versus Younger Breast Cancer Patients With Distinct Symptom Profiles

Because extracellular vesicle (EV)-associated cytokines, both encapsulated and surface bound, have been associated with symptom severity, and may vary over the lifespan, they may be potential biomarkers to uncover underlying mechanisms of various conditions. This study evaluated the associations of soluble and EV-associated cytokine concentrations with distinct symptom profiles reported by 290 women with breast cancer prior to surgery. Patients were classified into older (≥60 years, n = 93) and younger (< 60 years, n = 197) cohorts within two previously identified distinct symptom severity profiles, that included pain, depressive symptoms, sleep disturbance, and fatigue (i.e., High Fatigue Low Pain and All Low). EVs were extracted using ExoQuick. Cytokine concentrations were determined using Luminex multiplex assay. Mann Whitney U test evaluated the differences in EV and soluble cytokine levels between symptom classes and between and within the older and younger cohorts adjusting for Karnofsky Performance Status (KPS) score, body mass index (BMI), and stage of disease. Partial correlation analyses were run between symptom severity scores and cytokine concentrations. Results of this study suggest that levels of cytokine concentrations differ between EV and soluble fractions. Several EV and soluble pro-inflammatory cytokines had positive associations with depressive symptoms and fatigue within both age cohorts and symptom profiles. In addition, in the older cohort with High Fatigue Low Pain symptom profile, EV GM-CSF concentrations were higher compared to the All Low symptom profile (p < 0.05). Albeit limited by a small sample size, these exploratory analyses provide new information on the association between cytokines and symptom profiles of older and younger cohorts. Of note, unique EV-associated cytokines were found in older patients and in specific symptom classes. These results suggest that EVs may be potential biomarker discovery tools. Understanding the mechanisms that underlie distinct symptom class profiles categorized by age may inform intervention trials and offer precision medicine approaches.

Extracellular vesicle associated and soluble immune marker profiles of psychoneurological symptom clusters in men with prostate cancer: an exploratory study

Psychoneurological symptom clusters are co-occurring and interrelated physiological symptoms that may include cancer-related fatigue, pain, depressive symptoms, cognitive disturbances, and sleep disturbances. These symptoms are hypothesized to share a common systemic proinflammatory etiology. Thus, an investigation of systemic immune biomarkers is an important approach to test this hypothesis. Here, we investigated the associations between extracellular vesicle (EV)-associated and soluble cytokines with immune markers and symptom clusters in men with non-metastatic prostate cancer. This observational study included 40 men with non-metastatic prostate cancer at the start (T1) of external beam radiation therapy (EBRT) and 3 months post treatment (T2), as well as 20 men with non-metastatic prostate cancer on active surveillance (AS) seen at one time point. Collected questionnaires assessed patient-reported fatigue, sleep disturbances, depressive symptoms, and cognitive fatigue. In total, 45 soluble and EV-associated biomarkers in plasma were determined by multiplex assays. Principal component analysis (PCA) was used to identify psychoneurological symptom clusters for each study group and their time points. Bivariate correlation analysis was run for each identified PCA cluster with the concentrations of EV-associated and soluble cytokines and immune markers. Both EV-associated and soluble forms of RANTES significantly correlated with the symptom cluster for EBRT at T1, whereas, at T2, soluble IFNα2, IL-9, and IL-17 correlated with the corresponding symptom cluster. For the AS group, soluble survivin correlated with psychoneurological symptoms. Linking specific inflammatory cytokines with psychoneurological symptom clusters in men receiving prostate cancer treatment can enhance understanding of the underlying mechanisms of this phenomenon and aid in developing targeted interventions.

Possible Bioenergetic Biomarker for Chronic Cancer-Related Fatigue

BACKGROUND

Cancer-related fatigue is a highly prevalent, debilitating, and persistent symptom experienced by patients receiving cancer treatments. Up to 71% of men with prostate cancer receiving radiation therapy experience acute and persistent CRF. There is neither an effective therapy nor a diagnostic biomarker for cancer-related fatigue. This pilot study aimed to discover potential biomarkers associated with chronic cancer-related fatigue in men with prostate cancer receiving radiation therapy.

METHODS

We used a longitudinal repeated-measures research design. Twenty men with prostate cancer undergoing radiation therapy completed all study visits. Cancer-related fatigue was evaluated by a well-established and validated questionnaire, the Patient-Reported Outcomes Measurement Information System-Fatigue (PROMIS-F) Short Form. In addition, peripheral blood mononuclear cells (PBMC) were harvested to quantify ribonucleic acid (RNA) gene expression of mitochondria-related genes. Data were collected before, during, on completion, and 24 months postradiation therapy and analyzed using paired t-tests and repeated measures analysis of variance.

RESULTS

The mean of the PROMIS-F T-score was significantly increased over time in patients with prostate cancer, remaining elevated at 24 months post-radiation therapy compared to baseline. A significant downregulated BC1 ubiquinol-cytochrome c reductase synthesis-like (BCS1L) was observed over time during radiation therapy and at 24 months postradiation therapy. An increased PROMIS-F score was trended with downregulated BCS1L in patients 24 months after completing radiation therapy.

DISCUSSION

This is the first evidence to describe altered messenger RNA for BCS1L in chronic cancer-related fatigue using the PROMIS-F measure with men receiving radiation therapy for prostate cancer.

CONCLUSION

Our results suggest that PBMC messenger RNA for BCS1L is a potential biomarker and therapeutic target for radiation therapy-induced chronic cancer-related fatigue in this clinical population.

Fatigue prevalence in men treated for prostate cancer: A systematic review and meta-analysis

BACKGROUND

The side effects of prostate cancer (PCa) treatment are very prominent, with cancer-related fatigue (CRF) being the most common. Fatigue is a distressing symptom that interferes with daily functioning and seriously affects patient quality of life during, and for many years after, treatment. However, compared with other types of cancer, such as breast cancer, little is known about the prevalence of PCa-related fatigue.

AIM

To determine the prevalence of CRF in patients with PCa.

METHODS

A systematic search of EMBASE, PubMed, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure, WANFANG DATA, Technology Journal Database and the Chinese Biological Medical Database was conducted up to July 28, 2020. Included studies measured the incidence of PCa-related fatigue and differentiated fatigue outcomes (incidence) between treatment modalities and fatigue assessment times. In our meta-analysis, both fixed and random-effects models were used to estimate the pooled prevalence of PCa-related fatigue. Subgroup analyses were performed using treatment modalities and fatigue assessment times. Publication and sensitivity bias analyses were performed to test the robustness of the associations.

RESULTS

Fourteen studies, involving 4736 patients, were eligible for the review. The pooled CRF prevalence was 40% in a total sample of 4736 PCa patients [95% confidence interval (CI): 29-52; P < 0.01; I² = 98%]. The results of the subgroup analyses showed the prevalence of CRF after androgen deprivation therapy treatment, radical prostatectomy and radiotherapy to be 42% (95%CI: 20-67, P < 0.01, I² = 91%), 21% (95%CI: 16-26, P = 0.87, I² = 0%) and 40% (95%CI: 22-58, P < 0.01, I² = 90%), respectively. The prevalence of acute and persistent fatigue was 44% (95%CI: 25-64; P < 0.01; I² = 93%) and 29% (95%CI: 25-32; P = 0.30; I² = 17%), respectively.

CONCLUSION

Our meta-analysis showed that fatigue is a common symptom in men with PCa, especially those using hormone therapy.

Cancer-related fatigue: an overview

A diagnosis of cancer is a major life stressor that can affect the physiological, psychological and physical state of the person concerned. Fatigue is a particularly common and troubling symptom that has a negative impact on quality of life throughout all phases of treatment and stages of the illness. The aim of this review is to provide background information on cancer-related fatigue. This review discusses cancer-related fatigue (CRF) in terms of the definition, prevalence, risk factors, aetiology, and the measurement scales used. The differences between definitions of symptoms and relevant theories will be explored and discussed to help explain the variety of instruments used in its measurement. The prevalence of fatigue will be assessed by looking critically at the evidence of fatigue and the factors that affect it. Potential treatment and management strategies for CRF will also be discussed. Finally, there will be an overview of the instruments used to measure fatigue. This review also provides important evidence for measuring and managing CRF that can help nurses to understand fatigue among patients with cancer. Assessing CRF should be routinely undertaken in clinical settings to help identify the proper interventions, treatments and management to reduce fatigue among cancer patients.

Plasma metabolomic profile associated with fatigue in cancer patients

BACKGROUND

Metabolomics is the newest -omics methodology and allows for a functional snapshot of the biochemical activity and cellular state. The goal of this study is to characterize metabolomic profiles associated with cancer-related fatigue, a debilitating symptom commonly reported by oncology patients.

METHODS

Untargeted ultrahigh performance liquid chromatography/mass spectrometry metabolomics approach was used to identify metabolites in plasma samples collected from a total of 197 participants with or without cancer. Partial least squares-discriminant analysis (PLS-DA) was used to identify discriminant metabolite features, and diagnostic performance of selected classifiers was quantified using area under the receiver operating characteristics (AUROC) curve analysis. Pathway enrichment analysis was performed using Fisher's exact test and the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway database.

FINDINGS

The global metabolomics approach yielded a total of 1120 compounds of known identity. Significant metabolic pathways unique to fatigued cancer versus control groups included sphingolipid metabolism, histidine metabolism, and cysteine and methionine metabolism. Significant pathways unique to non-fatigued cancer versus control groups included inositol phosphate metabolism, primary bile acid biosynthesis, ascorbate and aldarate metabolism, starch and sucrose metabolism, and pentose and glucuronate interconversions. Pathways shared between the two comparisons included caffeine metabolism, tyrosine metabolism, steroid hormone biosynthesis, sulfur metabolism, and phenylalanine metabolism.

CONCLUSIONS

We found significant metabolomic profile differences associated with cancer-related fatigue. By comparing metabolic signatures unique to fatigued cancer patients with metabolites associated with, but not unique to, fatigued cancer individuals (overlap pathways) and metabolites associated with cancer but not fatigue, we provided a broad view of the metabolic phenotype of cancer-related fatigue.

An exploratory analysis of extracellular vesicle-associated and soluble cytokines in cancer-related fatigue in men with prostate cancer

BACKGROUND

Cancer Related Fatigue (CRF) is one of the most prevalent and distressing symptoms associated with cancer treatments. The exact etiology of CRF and its mechanisms are poorly understood. Cytokine dysregulation was hypothesized to be one of these mechanisms. Here, we explored the associations of soluble and extracellular vesicle (EV)-associated markers that include cytokines, heat shock proteins (hsp27, hsp70, hsp90), and neurotrophic factors (BDNF) with CRF.

METHODS

Plasma was collected from men (n ​= ​40) with non-metastatic prostate cancer receiving external beam radiation therapy (EBRT) at the start of the treatment, and three months after EBRT. CRF was assessed using the Functional Assessment of Cancer Therapy - Fatigue (FACT-F) from all participants. EVs were characterized via Nanoparticle Tracking Analysis, electron microscopy, and Western blot. Concentrations of EV-associated and soluble markers were measured with a multiplexed immunoassay system. Bivariate correlation analyses and independent T tests analyzed the relationships of CRF with the markers.

FINDINGS

As CRF worsened, concentrations of EV-associated markers were upregulated. EV-associated fold changes of Eotaxin, hsp27, IP-10, MIP-3α, were significantly higher in fatigued participants compared to non-fatigued EBRT participants three months after treatment. This was not observed in soluble markers. Concentrations of EV-associated CRP and MCP-1, soluble survivin, IFNα2, IL-8, IL-12p70, and MCP-1 significantly correlated with lower (worsening) CRF scores at the start of and three months after treatment.

INTERPRETATION

Concentrations of EV-associated markers increased in fatigued men with prostate cancer three months after EBRT. Both EV-associated and soluble markers correlated with worsening CRF. EV-associated markers, which have not been previously studied in depth, may provide additional insights and serve as potential biomarkers for CRF.

Dietary Oat Bran Reduces Systemic Inflammation in Mice Subjected to Pelvic Irradiation

Patients undergoing radiotherapy to treat pelvic-organ cancer are commonly advised to follow a restricted fiber diet. However, reducing dietary fiber may promote gastrointestinal inflammation, eventually leading to deteriorated intestinal health. The goal of this study was to evaluate the influence of dietary fiber on radiation-induced inflammation. C57BL/6J male mice were fed a High-oat bran diet (15% fiber) or a No-fiber diet (0% fiber) and were either irradiated (32 Gy delivered in four fractions) to the colorectal region or only sedated (controls). The dietary intervention started at 2 weeks before irradiation and lasted for 1, 6, and 18 weeks after irradiation, at which time points mice were sacrificed and their serum samples were assayed for 23 cytokines and chemokines. Our analyses show that irradiation increased the serum cytokine levels at all the time points analyzed. The No-fiber irradiated mice had significantly higher levels of pro-inflammatory cytokines than the High-oat irradiated mice at all time points. The results indicate that a fiber-rich oat bran diet reduces the intensity of radiation-induced inflammation, both at an early and late stage. Based on the results, it seems that the advice to follow a low-fiber diet during radiotherapy may increase the risk of decreased intestinal health in cancer survivors.

Relationships between expression of BCS1L, mitochondrial bioenergetics, and fatigue among patients with prostate cancer

Introduction: Cancer-related fatigue (CRF) is the most debilitating symptom with the greatest adverse side effect on quality of life. The etiology of this symptom is still not understood. The purpose of this study was to examine the relationship between mitochondrial gene expression, mitochondrial oxidative phosphorylation, electron transport chain complex activity, and fatigue in prostate cancer patients undergoing radiotherapy (XRT), compared to patients on active surveillance (AS).

Methods: The study used a matched case–control and repeated-measures research design. Fatigue was measured using the revised Piper Fatigue Scale from 52 patients with prostate cancer. Mitochondrial oxidative phosphorylation, electron-transport chain enzymatic activity, and BCS1L gene expression were determined using patients’ peripheral mononuclear cells. Data were collected at three time points and analyzed using repeated measures ANOVA.

Results: The fatigue score was significantly different over time between patients undergoing XRT and AS (P<0.05). Patients undergoing XRT experienced significantly increased fatigue at day 21 and day 42 of XRT (P<0.01). Downregulated mitochondrial gene (BC1, ubiquinol-cytochrome c reductase, synthesis-like, BCS1L, P<0.05) expression, decreased OXPHOS-complex III oxidation (P<0.05), and reduced activity of complex III were observed over time in patients with XRT. Moreover, increased fatigue was significantly associated with downregulated BCS1L and decreased complex III oxidation in patients undergoing XRT.

Conclusion: Our results suggest that BCS1L and complex III in mitochondrial mononuclear cells are potential biomarkers and feasible therapeutic targets for acute XRT-induced fatigue in this clinical population.

Cognitive and motor aspects of cancer-related fatigue

BACKGROUND

Cancer-related fatigue (CRF) is a debilitating symptom frequently reported by patients during and after treatment for cancer. CRF is a multidimensional experience and is often solely assessed by self-report measures. The goal of the study is to examine the physical and cognitive aspects of self-reported CRF using a cognitive function test and a physical fatigue index in order to provide objective measures that can characterize the CRF phenotype.

METHODS

A total of 59 subjects with nonmetastatic prostate cancer receiving external beam radiation therapy were included in the study. Fatigue was measured using the Functional Assessment of Cancer Therapy-Fatigue (FACT-F) questionnaire. Cognitive characteristics of CRF was measured using the Stroop Color-Word Interference computerized test and the motor aspect of fatigue was measured using the static fatigue test using a handgrip dynamometer.

FINDINGS

Functional Assessment of Cancer Therapy-Fatigue scores significantly correlated with the Stroop Interference score, but not performance accuracy in all test conditions. Fatigued subjects exhibited a more rapid decline to 50% of maximal strength and increased static fatigue index in the handgrip test, whereas maximal grip strength was not affected.

CONCLUSIONS

The results suggest that CRF exhibits both cognitive and physical characteristics. Subjective fatigue was associated with increased time required to overcome cognitive interference, but not cognitive performance accuracy. Fatigued patients exhibited decreased physical endurance and the ability to sustain maximal strength over time. These objective measures may serve as valuable tools for clinicians to detect cognitive and physical impairment associated with CRF.

Cytokines expression levels from tissue, plasma or serum as promising clinical biomarkers in adenocarcinoma of the prostate: a systematic review of recent findings

Prostate cancer (PC) is a common cancer (excluding non-melanoma skin cancer) in men in many parts of the world, although incidence and mortality rates vary significantly by population. In current medical practice, prognostic markers for PC include the presenting serum prostate-specific antigen (PSA) level, tumour Gleason score (GS) and clinical tumour stage. However, existing pre-treatment factors cannot be used to predict acute radiotherapy (RT)-induced toxicity. Therefore, new protein biomarkers are required in RT oncology to improve decision-making, treatment and therapy monitoring for PC patients. The aim of this systematic review is to the update potential research to address the difference in cytokine expression and their association with RT-induced toxicity and clinical outcomes. Studies were collected after searching three electronic databases: PubMed, Medline, and Google Scholar. An additional search was carried out through cross-check on a bibliography of selected articles. After the selection process made by two of the authors, 19 articles met the inclusion criteria and were included in the systematic review. Results from previous studies identified elevated levels of cytokines have been reported in several types of cancers and have sometimes correlated with disease progression or prognosis. Elevated levels of cytokine were noticed after immediate exposure to RT and their association with RT-induced acute/late toxicity of PC patients. Moreover, above studies also identified overexpression of cytokines on tumour biopsies and correlation with shortening cancer-specific survival and biochemical recurrence. Thus, altered levels of cytokine might be predictive biomarkers for RT-induced and clinical outcomes of PC patients.

Co-Occurring Symptoms Contribute to Persistent Fatigue in Prostate Cancer

PURPOSE

Cancer-related fatigue is one of the most debilitating side effects of cancer and cancer therapy. We aimed to investigate co-occurring symptoms associated with persistent fatigue in men receiving external beam radiation therapy (EBRT) for nonmetastatic prostate cancer.

METHODS

A sample of 47 men with prostate cancer scheduled to receive radiotherapy (RT) were followed at baseline and 1 year after RT. Clinical and demographic data were obtained from chart review. Symptom measurements included urinary dysfunction (American Urological Association symptoms score), fatigue (Functional Assessment of Cancer Therapy - Fatigue questionnaire), sleep disturbance (Patient-Reported Outcomes Measurement Information System - Sleep Disturbance form), pain (physical well-being domain pain item of the Functional Assessment of Cancer Therapy - General), and depressive symptoms (Hamilton Depression Rating Scale). Paired t tests, correlations, general linear models, and logistic regressions were used to determine associations between fatigue and other symptom scores.

RESULTS

At 1 year after RT, 34% of subjects continued to experience fatigue. Urinary dysfunction was the best clinical predictor of persistent fatigue. Pain and depressive symptoms further improved the predictive power of the model. A multivariate linear regression model containing all these three clinical variables (urinary dysfunction, pain, and depressive symptoms) explained 74% of total variance associated with persistent fatigue after RT.

CONCLUSIONS

Persistent fatigue at 1 year after EBRT in prostate cancer survivors is likely related to a cluster of symptoms elicited by chronic inflammation. Therapies that target each of these symptoms will likely reduce fatigue in this patient population.

mGluR5 mediates post-radiotherapy fatigue development in cancer patients

Cancer-related fatigue (CRF) is a common burden in cancer patients and little is known about its underlying mechanism. The primary aim of this study was to identify gene signatures predictive of post-radiotherapy fatigue in prostate cancer patients. We employed Fisher Linear Discriminant Analysis (LDA) to identify predictive genes using whole genome microarray data from 36 men with prostate cancer. Ingenuity Pathway Analysis was used to determine functional networks of the predictive genes. Functional validation was performed using a T lymphocyte cell line, Jurkat E6.1. Cells were pretreated with metabotropic glutamate receptor 5 (mGluR5) agonist (DHPG), antagonist (MPEP), or control (PBS) for 20 min before irradiation at 8 Gy in a Mark-1 γ-irradiator. NF-κB activation was assessed using a NF-κB/Jurkat/GFP Transcriptional Reporter Cell Line. LDA achieved 83.3% accuracy in predicting post-radiotherapy fatigue. "Glutamate receptor signaling" was the most significant (p = 0.0002) pathway among the predictive genes. Functional validation using Jurkat cells revealed clustering of mGluR5 receptors as well as increased regulated on activation, normal T cell expressed and secreted (RANTES) production post irradiation in cells pretreated with DHPG, whereas inhibition of mGluR5 activity with MPEP decreased RANTES concentration after irradiation. DHPG pretreatment amplified irradiation-induced NF-κB activation suggesting a role of mGluR5 in modulating T cell activation after irradiation. These results suggest that mGluR5 signaling in T cells may play a key role in the development of chronic inflammation resulting in fatigue and contribute to individual differences in immune responses to radiation. Moreover, modulating mGluR5 provides a novel therapeutic option to treat CRF.

Evaluating the Role of Mitochondrial Function in Cancer-related Fatigue

Fatigue is a common and debilitating condition that affects most cancer patients. To date, fatigue remains poorly characterized with no diagnostic test to objectively measure the severity of this condition. Here we describe an optimized method for assessing mitochondrial function of PBMCs collected from fatigued cancer patients. Using a compact extracellular flux system and sequential injection of respiratory inhibitors, we examined PBMC mitochondrial functional status by measuring basal mitochondrial respiration, spare respiratory capacity, and energy phenotype, which describes the preferred energy pathway to respond to stress. Fresh PBMCs are readily available in the clinical setting using standard phlebotomy. The entire assay described in this protocol can be completed in less than 4 hours without the involvement of complex biochemical techniques. Additionally, we describe a normalization method that is necessary for obtaining reproducible data. The simple procedure and normalization methods presented allow for repeated sample collection from the same patient and generation of reproducible data that can be compared between time points to evaluate potential treatment effects.

Exploring Genetic Attributions Underlying Radiotherapy-Induced Fatigue in Prostate Cancer Patients

CONTEXT

Despite numerous proposed mechanisms, no definitive pathophysiology underlying radiotherapy-induced fatigue (RIF) has been established. However, the dysregulation of a set of 35 genes was recently validated to predict development of fatigue in prostate cancer patients receiving radiotherapy.

OBJECTIVES

To hypothesize novel pathways, and provide genetic targets for currently proposed pathways implicated in RIF development through analysis of the previously validated gene set.

METHODS

The gene set was analyzed for all phenotypic attributions implicated in the phenotype of fatigue. Initially, a "directed" approach was used by querying specific fatigue-related sub-phenotypes against all known phenotypic attributions of the gene set. Then, an "undirected" approach, reviewing the entirety of the literature referencing the 35 genes, was used to increase analysis sensitivity.

RESULTS

The dysregulated genes attribute to neural, immunological, mitochondrial, muscular, and metabolic pathways. In addition, certain genes suggest phenotypes not previously emphasized in the context of RIF, such as ionizing radiation sensitivity, DNA damage, and altered DNA repair frequency. Several genes also associated with prostate cancer depression, possibly emphasizing variable radiosensitivity by RIF-prone patients, which may have palliative care implications. Despite the relevant findings, many of the 35 RIF-predictive genes are poorly characterized, warranting their investigation.

CONCLUSION

The implications of herein presented RIF pathways are purely theoretical until specific end-point driven experiments are conducted in more congruent contexts. Nevertheless, the presented attributions are informative, directing future investigation to definitively elucidate RIF's pathoetiology. This study demonstrates an arguably comprehensive method of approaching known differential expression underlying a complex phenotype, to correlate feasible pathophysiology.

The role of TRAIL in fatigue induced by repeated stress from radiotherapy

Fatigue is one of the most common and debilitating side effects of cancer and cancer treatment, and yet its etiology remains elusive. The goal of this study is to understand the role of chronic inflammation in fatigue following repeated stress from radiotherapy. Fatigue and non-fatigue categories were assessed using ≥ 3-point change in Functional Assessment of Cancer Therapy-Fatigue questionnaire (FACT-F) administered to participants at baseline/before radiotherapy and one year post-radiotherapy. Whole genome microarray and cytokine multiplex panel were used to examine fatigue-related transcriptome and serum cytokine changes, respectively. The study included 86 subjects (discovery phase n = 40, validation phase n = 46). The sample in the discovery phase included men with prostate cancer scheduled to receive external-beam radiotherapy. A panel of 48 cytokines were measured and the significantly changed cytokine found in the discovery phase was validated using sera from a separate cohort of men two years after completing radiotherapy for prostate cancer at a different institution. Effects of the significantly changed cytokine on cell viability was quantified using the MTT assay. During the discovery phase, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and TRAIL decoy receptor, TNFRSF10C (TRAIL-R3), were significantly upregulated in fatigued (≥3-point decrease from baseline to 1yr-post radiotherapy) subjects (n = 15). In the validation phase, TRAIL correlated with fatigue scores 2yrs post-radiotherapy. TRAIL caused selective cytotoxicity in neuronal cells, but not in microglial and muscle cells, in vitro. Late-onset inflammation directed by TRAIL may play a role in fatigue pathogenesis post-repeated stress from irradiation.