Exploring genetic attributions underlying radiotherapy-induced fatigue in prostate cancer patients

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 (PCP's) receiving radiotherapy.

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

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.

The dysregulated genes attribute to neural, immunological, mitochondrial, muscular, and metabolic pathways. Additionally, 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.

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.

Journal of pain and symptom management. 2017 Aug 07 [Epub ahead of print]

Sepehr Hashemi, Juan Luis Fernandez Martinez, Leorey Saligan, Stephen Sonis

Harvard School of Dental Medicine, Boston, Massachusetts, USA. Electronic address: ., Biomodels LLC, Watertown, Massachusetts, USA; University of Oviedo, Asturias, Spain., National Institutes of Health, National Institute of Nursing Research, Bethesda, Maryland, USA., Harvard School of Dental Medicine, Boston, Massachusetts, USA; Biomodels LLC, Watertown, Massachusetts, USA; Brigham and Women's Hospital, Boston, Massachusetts, USA.