title: Different Phenotyping Approaches Lead to Dissimilar Biologic Profiles in Men With Chronic Fatigue After Radiation Therapy.
abstract: 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.
  
  
  
  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.
  
  
  
  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.
  
  
  
  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.
  
  
  
  The variation in genetic profiles for CRF suggests that phenotypic profiling for CRF should be carefully considered because it directly influences biomarker discovery investigations.
authors: National Institute of Nursing Research, National Institutes of Health, Bethesda, Maryland, USA.
authors: Li Rebekah
authors: LR
authors: Feng
authors: National Institute of Nursing Research, National Institutes of Health, Bethesda, Maryland, USA.
authors: Kristin
authors: K
authors: Dickinson
authors: Vassar College, Poughkeepsie, New York, USA.
authors: Neila
authors: N
authors: Kline
authors: National Institute of Nursing Research, National Institutes of Health, Bethesda, Maryland, USA. Electronic address: saliganl@mail.nih.gov.
authors: Leorey N
authors: LN
authors: Saligan
mesh_terms: D000368:Aged; D018931:Antineoplastic Agents, Hormonal / Q000627:therapeutic use; D015415:Biomarkers / Q000378:metabolism; D002908:Chronic Disease; D003430:Cross-Sectional Studies; D005221:Fatigue / Q000175:diagnosis* / Q000209:etiology / Q000235:genetics / Q000503:physiopathology*; D005786:Gene Expression Regulation; D006801:Humans; D008297:Male; D046228:Microarray Analysis; D000071066:Patient Reported Outcome Measures; D010641:Phenotype; D025341:Principal Component Analysis; D011471:Prostatic Neoplasms / Q000150:complications / Q000235:genetics / Q000503:physiopathology / Q000532:radiotherapy*; D057566:Self Report; D012720:Severity of Illness Index; D059467:Transcriptome
chemical_list: D018931:Antineoplastic Agents, Hormonal; D015415:Biomarkers
keywords: Cancer-related fatigue; fatigue phenotypes; prostate cancer; radiation therapy; transcriptome profiles