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Background: Cancer-related fatigue (CRF) is a prominent cancer-related complication occurring in Prostate cancer (PCa) patients, profoundly affecting prognosis. The lack of diagnostic criteria and biomarkers hampers the management of CRF., Methods: The CRF-related data and PCa single-cell data were retrieved from the GEO database and clinical data was downloaded from the TCGA database. The univariate logistic/Cox regression analysis were used to construct the prediction models. The predictive value of models was analyzed using the ROC curve and Kaplan-Meier survival. The hub genes were screened by an intersection analysis of DEGs. The mice model of PCa and PCa-related fatigue were established, and fatigue-like behaviors of mice were detected. The expression of selected hub genes was validated by RT-PCR and IHC analysis., Results: The diagnosis and risk models showed great predictive value both in the training and validation dataset. Five genes (Baiap2l2, Cacng4, Sytl2, Sec31b and Ms4a1) that enriched the CXCL signaling were identified as hub genes. Among all hub genes, the MS4A1 expression is the most significant in PCa-related fatigue mice., Conclusions: We identified MS4A1 as a promising biomarker for the diagnosis of PCa-related fatigue. Our findings would lay a foundation for revealing the pathogenesis and developing therapies for PCa-related fatigue., Competing Interests: Ethics Approval And Consent To Participate: All animal procedures were performed according to the Guidelines for the Care and Use of Laboratory Animals of the Chinese Animal Welfare Committee and approved by the Institutional Animal Care and Use Committee (IACUC) of Wuhan University of Renmin Hospital. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Genetic factors that influence inflammation and energy production/expenditure in cells may affect patient outcomes following treatment with external beam radiation therapy (EBRT). Sestrins, stress-inducible genes with antioxidant properties, have recently been implicated in several behaviors including fatigue. This proof-of-concept study explored whether the sestrin family of genes ( SESN1, SESN2, and SESN3) were differentially expressed from baseline to the midpoint of EBRT in a sample of 26 Puerto Rican men with nonmetastatic prostate cancer. We also examined whether changes in expression of these genes were associated with changes in fatigue scores during EBRT., Method: Participants completed the 13-item Functional Assessment of Cancer Therapy-Fatigue subscale, Spanish version. Whole blood samples were collected at baseline and at the midpoint of EBRT. Gene expression data were analyzed using the limma package in the R (version R 2.14.0.) statistical software. Linear models and empirical Bayes moderation, adjusted for radiation fraction (total number of days of prescribed radiation treatment), were used to examine potential associations between changes in gene expression and change in fatigue scores., Results: Expression of SESN3 (adjusted p < .01, log fold change -0.649) was significantly downregulated during EBRT, whereas the expressions of SESN1 and SESN2 remained unchanged. After adjustment for radiation fraction, change in SESN3 expression was associated with change in fatigue during EBRT (false discovery rate <.01)., Conclusions: Downregulation of SESN3, a novel pharmacoactive stress response gene, was associated with fatigue intensification during EBRT. SESN3 may serve as an interventional target and a biomarker for the cellular and molecular events associated with EBRT-related fatigue.

Objective: To examine the trajectory of fatigue experienced by 26 Puerto Rican (PR) men over the course of External Beam Radiation Therapy (EBRT) and to assess gene expression changes from baseline to midpoint of EBRT using microarray technology. Design/Research Approach- Prospective exploratory and comparative design study. Setting- RT facility located in San Juan, PR. Sample/Participants-26 PR men with non-metastatic prostate cancer., Methods: Participants completed 2 paper forms: demographics and the Spanish version of the 13-item FACT-fatigue at baseline, midpoint, and end of EBRT. Wholeblood samples were collected at baseline and at midpoint of EBRT. Descriptive data was analyzed using t-test, Wilcoxon, and Friedman test for repeated measures. Gene expression data was analyzed using the LIMMA package in R; the functional network analysis was conducted using Ingenuity Pathway analysis. Main Research Variable-Fatigue scores, gene expression., Results: Subjects were of ages 52-81 with fatigue scores that remained unchanged during EBRT (baseline=42.38, SD=9.34; midpoint=42.11, SD=8.93, endpoint=43.04, SD=8.62). Three hundred seventy-three genes (130-up regulated and 243-down regulated) were differentially expressed from baseline to mid-point of EBRT (FDR<0.01). The top distinct canonical pathways of the differentially expressed probesets (p<0.0001) were: "Phospholipase C Signaling," "Role of NFAT in Regulation of the Immune Response," and "Gαq Signaling.", Conclusion: While fatigue did not worsen over the course of EBRT for this sample as a group, there was variability in fatigue across the sample. It is possible that the over expression of the SESN3 gene, known to suppress oxidative damage, may have contributed to the attenuation of fatigue in this clinical population.

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., (Copyright © 2017 American Academy of Hospice and Palliative Medicine. All rights reserved.)

Context: Cancer-related fatigue (CRF) persists months after treatment completion. Although a CRF biomarker has not yet been identified, validated self-report questionnaires are used to define and phenotype CRF in the discovery of potential biomarkers., Objectives: The purposes of this study are to identify CRF subjects using three well-known CRF phenotyping approaches using validated self-report questionnaires and to compare the biologic profiles that are associated with each CRF phenotype., Methods: Fatigue in men with nonmetastatic prostate cancer receiving external beam radiation therapy was measured at baseline (T1), midpoint (T2), end point (T3), and one-year post-external beam radiation therapy (T4) using the Functional Assessment of Cancer Therapy-Fatigue (FACT-F) and Patient Reported Outcomes Measurement Information System-Fatigue. Chronic fatigue (CF) and nonfatigue subjects were grouped based on three commonly used phenotyping approaches: 1) T4 FACT-F <43; 2) T1-T4 decline in FACT-F score ≥3 points; 3) T4 Patient Reported Outcomes Measurement Information System-Fatigue T-score >50. Differential gene expressions using whole-genome microarray analysis were compared in each of the phenotyping criterion., Results: The study enrolled 43 men, where 34%-38% had CF based on the three phenotyping approaches. Distinct gene expression patterns were observed between CF and nonfatigue subjects in each of the three CRF phenotyping approaches: 1) Approach 1 had the largest number of differentially expressed genes and 2) Approaches 2 and 3 had 40 and 21 differentially expressed genes between the fatigue groups, respectively., Conclusion: The variation in genetic profiles for CRF suggests that phenotypic profiling for CRF should be carefully considered because it directly influences biomarker discovery investigations., (Published by Elsevier Inc.)

Purpose: The purpose of this study was to explore gene expression changes in fatigued men with nonmetastatic prostate cancer receiving localized external beam radiation therapy (EBRT)., Methods: Fatigue was measured in 40 men with prostate cancer (20 receiving EBRT and 20 controls on active surveillance) using the Functional Assessment of Cancer Therapy-Fatigue (FACT-F). EBRT subjects were followed from baseline to midpoint and end point of EBRT, while controls were seen at one time point. EBRT subjects were categorized into high- and low-fatigue groups based on change in FACT-F scores from baseline to EBRT completion. Full genome microarray was performed from peripheral leukocyte RNA to determine gene expression changes related to fatigue phenotypes. Real-time polymerase chain reaction and enzyme-linked immunosorbent assay confirmed the most differentially expressed gene in the microarray experiment., Results: At baseline, mean FACT-F scores were not different between EBRT subjects (44.3 ± 7.16) and controls (46.7 ± 4.32, p = .24). Fatigue scores of EBRT subjects decreased at treatment midpoint (38.6 ± 9.17, p = .01) and completion (37.6 ± 9.9, p = .06), indicating worsening fatigue. Differential expression of 42 genes was observed between fatigue groups when EBRT time points were controlled. Membrane-spanning four domains, subfamily A, member (MS4A1) was the most differentially expressed gene and was associated with fatigue at treatment end point (r = -.46, p = .04)., Conclusion: Fatigue intensification was associated with MS4A1 downregulation, suggesting that fatigue during EBRT may be related to impairment in B-cell immune response. The 42 differentially expressed fatigue-related genes are associated with glutathione biosynthesis, γ-glutamyl cycle, and antigen presentation pathways., (© The Author(s) 2015.)

Background: Androgen deprivation therapy (ADT) often worsens fatigue in patients with prostate cancer, producing symptoms similar to chronic fatigue syndrome (CFS). Comparing expression (mRNA) of many fatigue-related genes in patients with ADT-treated prostate cancer versus with CFS versus healthy controls, and correlating mRNA with fatigue severity may clarify the differing pathways underlying fatigue in these conditions., Methods: Quantitative real-time PCR was performed on leukocytes from 30 fatigued, ADT-treated prostate cancer patients (PCF), 39 patients with CFS and 22 controls aged 40-79, together with ratings of fatigue and pain severity. 46 genes from these pathways were included: (1) adrenergic/monoamine/neuropeptides, (2) immune, (3) metabolite-detecting, (4) mitochondrial/energy, (5) transcription factors., Results: PCF patients showed higher expression than controls or CFS of 2 immune transcription genes (NR3C1 and TLR4), chemokine CXCR4, and mitochondrial gene SOD2. They showed lower expression of 2 vasodilation-related genes (ADRB2 and VIPR2), 2 cytokines (TNF and LTA), and 2 metabolite-detecting receptors (ASIC3 and P2RX7). CFS patients showed higher P2RX7 and lower HSPA2 versus controls and PCF. Correlations with fatigue severity were similar in PCF and CFS for only DBI, the GABA-A receptor modulator (r=-0.50, p<0.005 and r=-0.34, p<0.05). Purinergic P2RY1 was correlated only with PCF fatigue and pain severity (r=+0.43 and +0.59, p=0.025 and p=0.001)., Conclusions: PCF patients differed from controls and CFS in mean expression of 10 genes from all 5 pathways. Correlations with fatigue severity implicated DBI for both patient groups and P2RY1 for PCF only. These pathways may provide new targets for interventions to reduce fatigue., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

The mechanisms behind fatigue intensification during cancer therapy remain elusive. The interferon alpha-inducible protein 27 (IFI27) was the most up-regulated gene based on our previous microarray data in fatigued men with non-metastatic prostate cancer receiving localized external beam radiation therapy (EBRT). The purpose of this study was to confirm the IFI27 up-regulation and determine its association with fatigue intensification during EBRT. Peripheral blood samples and fatigue scores were collected at three time points--prior to EBRT, at midpoint, and at completion of EBRT. Confirmatory quantitative real time polymerase chain reaction (qPCR) and enzyme-linked immunosorbent assay (ELISA) were utilized to verify the microarray results. Subjects were a total of 40 Caucasian men with prostate cancer; 20 scheduled for EBRT (65.6 ± 7.5 years old), and 20 on active surveillance as controls (62.8 ± 6.1 years old). Significant IFI27 expression overtime during EBRT was confirmed by qPCR (p < 0.5), which correlated with fatigue scores during EBRT (R = -0.90, p = 0.006). Alterations in mechanisms associated with immune response and mitochondrial function that explain the up-regulation of IFI27 may provide an understanding of the pathways related to the intensification of fatigue during localized radiation therapy.

In July 2010, at the Muscle Fatigue Meeting, I presented an overview of Chronic Fatigue Syndrome and Cancer Related Fatigue, emphasizing a critical interpretation of the potential association between Chronic Fatigue Syndrome and Cancer Related Fatigue and a newly discovered retrovirus: Xenotropic Murine Related Virus. Since this association was hotly debated at that time, I suggested at the Meeting that it was wrong and most likely due to the identification of the wrong virus culprit. Today, 20 months after the Meeting, the first part of our prediction has turned out to be correct, as Xenotropic Murine Related Virus was shown to be a laboratory-created artefact. Still, the potential association of fatigue-syndromes with an infection (most likely viral) is sustained by a plethora of evidence and this overview will initially summarize data suggesting prior viral infection(s). The principal hypothesized mechanisms for both peripheral and central Chronic Fatigue Syndrome/Cancer Related Fatigue will be then summarized, also indicating plausible associations and triggering factors. All evidence accrued so far suggests that further research work should be performed in this interesting area and in order to identify an infectious agent for Chronic Fatigue Syndrome/Cancer Related Fatigue. One candidate RNA virus, Micro-Foci inducing Virus, will be described in this overview., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Background: Fatigue is a common and distressing side effect of androgen deprivation therapy (ADT) for prostate cancer. The goal of the current study was to examine the relationship between changes in fatigue following initiation of ADT and single nucleotide polymorphisms (SNPs) in three pro-inflammatory cytokine genes: interleukin-1 beta (IL1B), interleukin-6 (IL6), and tumor necrosis factor alpha (TNFA)., Methods: As part of a larger study, men with prostate cancer (n = 53) were recruited prior to initiation of ADT. Fatigue was assessed at recruitment and 6 months after initiation of ADT. DNA was extracted from blood drawn at baseline., Results: Patients with the IL6-174 (rs1800795) G/C or C/C genotype displayed greater increases in fatigue intrusiveness, frequency, and duration than the G/G genotype (p values ≤ 0.05), although inclusion of age, race, and baseline depressive symptomatology in the model attenuated these relationships (p values ≤ 0.09). Patients with the TNFA-308 (rs1800629) G/A genotype showed greater increases in fatigue severity than the G/G genotype (p = 0.02). IL1B-511 (rs16944) genotype did not significantly predict changes in fatigue (p values >0.46). Patients with higher numbers of variants displayed greater increases in fatigue duration and interference (p values ≤ 0.02) than patients with lower numbers of variants., Conclusions: Prostate cancer patients treated with ADT who carry variant alleles of the IL6 and TNFA genes are susceptible to heightened fatigue. These preliminary data lend support for the role of genetic variation in the development of cancer-related fatigue secondary to ADT. Findings are relevant to attempts to develop personalized approaches to cancer treatment., (Copyright © 2012 Elsevier Inc. All rights reserved.)