Biological pathways, candidate genes, and molecular markers associated with quality-of-life domains: an update

Sprangers, Mirjam A. G.; Thong, Melissa S. Y.; Bartels, Meike; Barsevick, Andrea; Ordoñana, Juan R.; Shi, Qiuling; Wang, Xin Shelley; Klepstad, Pål; Wierenga, Eddy A.; Singh, Jasvinder A.; Sloan, Jeff A.

doi:10.1007/s11136-014-0656-1

Cited by 67 publications

(67 citation statements)

References 65 publications

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“…In contrast, individuals with two doses of the rare G allele for nuclear factor kappa beta 2 ( NFKB2 ) rs12772374 had a 47.7 fold increase in the odds of belonging to the lower QOL class. These findings add to the growing body of evidence that QOL has a genetic basis [44]. …”

Section: Introductionmentioning

confidence: 53%

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Phenotypic and molecular characteristics associated with various domains of quality of life in oncology patients and their family caregivers

et al. 2016

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Purpose Not all oncology patients and their family caregivers (FCs) experience the same quality of life (QOL). The purposes of this study were to identify latent classes of oncology patients (n=168) and their FCs (n=85) with distinct physical, psychological, social, and spiritual well-being trajectories from prior to through four months after the completion of radiation therapy and to evaluate for demographic, clinical, and genetic characteristics that distinguished between these latent classes. Methods Using growth mixture modelling, two latent classes were found for three (i.e., physical, psychological, and social well-being) of the four QOL domains evaluated. Results Across these three domains, the largest percentage of participants reported relatively high well-being scores across the six months of the study. Across these three QOL domains, patients and FCs who were younger, female, belonged to an ethnic minority group, had children at home, had multiple comorbid conditions, or had a lower functional status were more likely to be classified in the lower QOL class. The social well-being domain was the only domain that had a polymorphism in nuclear factor kappa beta 2 (NFKB2) associated with latent class membership. Carrying one or two doses of the rare allele for rs7897947 was associated with a 52% decrease in the odds of belonging to the lower social well-being class (OR (95% CI) = .46 (.21, .99), p=.049). Conclusions These findings suggest that a number of phenotypic and molecular characteristics contribute to differences in QOL in oncology patients and their FCs.

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Section: Introductionmentioning

confidence: 53%

“…Nonetheless, this study adds to the growing body of evidence of genomic involvement in QOL outcomes [44]. The genetic association identified suggests a relationship between a cytokine gene polymorphism and decrements in social well-being.…”

Section: Discussionmentioning

confidence: 77%

Phenotypic and molecular characteristics associated with various domains of quality of life in oncology patients and their family caregivers

et al. 2016

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“…Studies of genomic encoding for fatigue are now beginning to explore the increased activity of proinflammatory transcription factors as contributors to fatigue [22,23]. A study of breast cancer survivors with persistent fatigue found increased expression of inflammation-related genes, particularly those responsive to the proinflammatory nuclear factor-κB transcription control pathway, together with a decreased expression of glucocorticoid-dependent anti-inflammatory genes [24].…”

Section: What Causes Crf?mentioning

confidence: 99%

Cancer-related and treatment-related fatigue

Wang

Woodruff

2015

Gynecologic Oncology

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Fatigue is a distressing and persistent symptom for patients with gynecological cancer and for survivors. Debilitating cancer-related fatigue (CRF) is produced by both the disease and its treatment. Although awareness and study of CRF have grown in recent years, consistent assessment has not been a priority in routine medical practice. The pathophysiological mechanisms that induce CRF remain unclear, and effective pharmacological interventions have yet to be established. Based on the literature and our own research results, this review focuses on recent progress toward understanding the nature and causes of CRF and on several promising treatment modalities. Given the prevalence and severity of CRF in the gynecological cancer patient population, establishing standardized fatigue measurement and management methods in routine clinical oncology care is of utmost importance. Whether CRF has an underlying inflammatory cause is still hypothetical, however, and no mechanism-driven symptom intervention is currently in clinical use, even though the development of such interventions would provide patients with greater symptom control. Advancing translational and clinical fatigue research will require anatomical pathway studies and well-designed clinical investigations that focus on the development of mechanism-driven interventions based on physiological–behavioral fatigue research, implementation of guidelines for experimental designs, and discovery of biomarkers identifying individuals at high risk for CRF. Validated patient-reported outcomes measures are an essential component of such clinical studies. Because numerous subscales, unidimensional measures, and multidimensional measures exist, clinicians and researchers should consider individual circumstances, good clinical practice, and research goals as guides for choosing the most appropriate fatigue measurement tool. Additionally, education about CRF should be made available to all patients and their caregivers, as accurate and age-appropriate information about conditions like CRF can alleviate much of the stress and anxiety brought on by poor communication about this distressing condition.

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“…Other researchers have reported other biological pathways, candidate genes, and genetic markers for CRF, such as genes related to dopaminergic synapse (COMT, DRD4, and DAT1; Rausch et al, 2010) and cytokine-cytokine receptor interaction (interleukin [IL]-1b, IL-1 receptor antagonist (IL-1RA), IL-6, and tumor necrosis factor [TNF]-a; Aouizerat et al, 2009;Saligan & Kim, 2012;Thornton, Andersen, & Blakely, 2010). However, there are very limited association studies that propose genetic markers for CRF using a wholegenome approach (Sprangers et al, 2014). In the present study, we use whole-genome microarray to explore the association of changes in fatigue with changes in gene expression from RNA of peripheral blood mononuclear cells from fatigued men receiving EBRT for nonmetastatic prostate cancer.…”

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confidence: 99%