Faculty Bibliography

INTRODUCTION: Before and after breast cancer surgery, women have reported varying anxiety levels. Recent evidence has suggested that anxiety has a genetic basis and is associated with inflammation. The purposes of the present study were to identify the subgroups of women with distinct anxiety trajectories; to evaluate for differences in the phenotypic characteristics between these subgroups; and to evaluate for associations between polymorphisms in cytokine genes and subgroup membership. PATIENTS AND METHODS: Patients with breast cancer (n = 398) were recruited before surgery and followed up for 6 months. The patients completed the Spielberger State Anxiety Inventory and provided a blood sample for genomic analyses. Growth mixture modeling was used to identify the subgroups of patients with distinct anxiety trajectories. RESULTS: Two distinct anxiety subgroups were identified. The women in the higher anxiety subgroup were younger and had a lower functional status score. Two single nucleotide polymorphisms in tumor necrosis factor-alpha (rs1799964, rs3093662) were associated with the higher anxiety subgroup. CONCLUSION: The results of the present exploratory study suggest that polymorphisms in cytokine genes could partially explain the interindividual variability in anxiety. The determination of phenotypic and molecular markers associated with greater levels of anxiety can assist clinicians to identify high-risk patients and initiate appropriate interventions.

PURPOSE: The purposes of this study, in a sample of women with breast cancer receiving chemotherapy (CTX), were to identify subgroups of women with distinct experiences with the symptom cluster of pain, fatigue, sleep disturbance, and depressive symptoms and evaluate differences in demographic and clinical characteristics, differences in psychological symptoms, and differences in pain characteristics among these subgroups. METHODS: Patients completed symptom questionnaires in the week following CTX administration. Latent class profile analysis (LCPA) was used to determine the patient subgroups. RESULTS: Three subgroups were identified: 140 patients (35.8 %) in the "low," 189 patients (48.3 %) in the "moderate," and 62 patients (15.9 %) in the "all high" latent class. Patients in the all high class had a lower functional status, a higher comorbidity profile, a higher symptom burden, and a poorer quality of life. CONCLUSIONS: Study findings provide evidence of the utility of LCPA to explain inter-individual variability in the symptom experience of patients undergoing CTX. The ability to characterize subgroups of patients with distinct symptom experiences allows for the identification of high-risk patients and may guide the design of targeted interventions that are tailored to an individual's symptom profile.

BACKGROUND: CA125, a tumor-associated antigen, is primarily used to monitor epithelial ovarian cancer. There is evidence that different species of CA125 exist; however, it is not known if any of these species are present in healthy women during the menstrual cycle and if they are associated with serum concentrations of CA125. The purpose of this study was to determine if the molecular species of CA125 differ across the three phases of the menstrual cycle in healthy women. METHODS: Healthy, Caucasian women between the ages of 18 and 39 were enrolled using strict criteria to exclude factors known to contribute to CA125 fluctuations. Menstrual cycle regularity was determined using calendars maintained by participants for 3 months. After cycle regularity was established, blood was drawn at three time points for Western blot analysis. RESULTS: Western blot analysis yielded 17 distinct profiles (i.e., patterns of species) of CA125, with 80% of the sample exhibiting 5 common profiles. No differences in demographic characteristics and serum CA125 values were found among the various CA125 profiles. CONCLUSIONS: Different molecular species of CA125 exist in healthy women with regular menstrual cycles. These data provide evidence that CA125 is not a homogeneous molecular species. Future research should evaluate the molecular composition and the clinical importance of these species.

PURPOSE/OBJECTIVES: To assess the effects of high blood sugar at the levels of diabetic or prediabetic states during cancer treatment because patients undergoing chemotherapy (CTX) experience multiple symptoms that vary among individuals and may be affected by glucose levels. DESIGN: Descriptive, cross-sectional. SETTING: Two comprehensive cancer centers, one Veterans Affairs hospital, and four community-based oncology programs. SAMPLE: 244 outpatients with breast, gastrointestinal, gynecologic, and lung cancers. METHODS: Patients completed demographic and symptom questionnaires. Glycosylated hemoglobin A1c (HbA1c) was evaluated to determine diabetic state. Descriptive statistics and one-way analyses of variance were used in the analyses. MAIN RESEARCH VARIABLES: HbA1c, symptom severity scores, patient and clinical characteristics (e.g., age, gender, comorbidities, sociodemographic information, body mass index [BMI], lifestyle factors). FINDINGS: HbA1c results showed 9% of the sample in the diabetic and 26% in the prediabetic state. Patients in the diabetic state reported a higher number of comorbid conditions and were more likely to be African American. Patients in the prediabetic state were older aged. Patients in the diabetic and prediabetic states had a higher BMI compared to nondiabetic patients. No differences in symptom severity or quality-of-life (QOL) scores were found among the three diabetic states. CONCLUSIONS: This study is the first to evaluate for associations between diabetic states and symptom severity and QOL scores in patients receiving CTX. This study confirmed that older age, as well as having higher BMI and having multiple comorbidities, were associated with increased mean glycemic levels. IMPLICATIONS FOR NURSING: Clinicians should assess and identify patients with diabetes or prediabetes undergoing treatment for cancer. Patients who are older aged, those with a high BMI, and those with multiple comorbid conditions may be at increased risk for higher glycemic states.

CONTEXT: Little is known about energy levels in oncology patients and their family caregivers (FCs). OBJECTIVES: This study sought to identify latent classes of participants, based on self-reported energy levels and to evaluate for differences in phenotypic and genotypic characteristics between these classes. METHODS: Energy subscale scores from the Lee Fatigue Scale were used to determine latent class membership. Morning and evening energy scores were obtained just prior to, during, and for four months following the completion of radiation therapy. Genetic associations were evaluated for fifteen pro- and anti-inflammatory cytokine genes. RESULTS: Two latent classes with distinct morning energy trajectories were identified. Participants who were younger, female, not married/partnered, Black, and had more comorbidities, and a lower functional status were more likely to be in the Low Morning Energy class. Two polymorphisms (IL2 rs1479923, NFKB1 rs4648110) were associated with morning energy latent class membership. Two latent classes with distinct evening energy trajectories were identified. Participants who were younger and male and who had more comorbidities, decreased body weight, and a lower functional status were more likely to be in the Moderate Evening Energy class. Five different polymorphisms (IL1R2 rs4141134, IL6 rs4719714, IL17A rs8193036, NFKB2 rs1056890, TNFA rs1800683) were associated with evening energy latent class membership. CONCLUSION: This study provides preliminary evidence that decrements in morning and evening energy are associated with different phenotypic risk factors as well as cytokine gene variations.

INTRODUCTION: The aims of this study were to compare microRNA (miR) expression between individuals with and without insulin resistance and to determine whether miRs predict response to thiazolidinedione treatment. MATERIALS AND METHODS: In a sample of 93 healthy adults, insulin resistance was defined as steady state plasma glucose (SSPG)>/=180mg/dL and insulin sensitive as <120mg/dL. Response to thiazolidinedione therapy was defined as >/=10% decrease in SSPG. We selected a panel of microRNAs based on prior evidence for a role in insulin or glucose metabolism. Fold change and Wilcoxon rank sum tests were calculated for the 25 miRs measured. RESULTS: At baseline, 81% (n=75) of participants were insulin resistant. Five miRs were differentially expressed between the insulin resistant and sensitive groups: miR-193b (1.45 fold change (FC)), miR-22-3p (1.15 FC), miR-320a (1.36 FC), miR-375 (0.59 FC), and miR-486 (1.21 FC) (all p<0.05). In the subset who were insulin resistant at baseline and received thiazolidinediones (n=47), 77% (n=36) showed improved insulin sensitivity. Six miRs were differentially expressed between responders compared to non-responders: miR-20b-5p (1.20 FC), miR-21-5p, (0.92 FC), miR-214-3p (1.13 FC), miR-22-3p (1.14 FC), miR-320a (0.98 FC), and miR-486-5p (1.25 FC) (all p<0.05). DISCUSSION: This study is the first to report miRs associated with response to a pharmacologic intervention for insulin resistance. MiR-320a and miR-486-5p identified responders to thiazolidinedione therapy among the insulin resistant group.

CONTEXT: Fatigue is the most common symptom in oncology patients during chemotherapy (CTX). Little is known about the predictors of interindividual variability in initial levels and trajectories of morning fatigue severity in these patients. OBJECTIVES: An evaluation was done to determine which demographic, clinical, and symptom characteristics were associated with initial levels as well as the trajectories of morning fatigue and to compare findings with our companion paper on evening fatigue. METHODS: A sample of outpatients with breast, gastrointestinal, gynecological, and lung cancer (N=586) completed demographic and symptom questionnaires a total of six times over two cycles of CTX. Fatigue severity was evaluated using the Lee Fatigue Scale. Hierarchical linear modeling (HLM) was used to answer the study objectives. RESULTS: A large amount of interindividual variability was found in the morning fatigue trajectories. A piecewise model fit the data best. Patients with higher body mass index (BMI), who did not exercise regularly, with a lower functional status, and who had higher levels of state anxiety, sleep disturbance and depressive symptoms, reported higher levels of morning fatigue at enrollment. Variations in the trajectories of morning fatigue were predicted by the patients' ethnicity and younger age. CONCLUSION: The modifiable risk factors that were associated with only morning fatigue were BMI, exercise, and state anxiety. Modifiable risk factors that were associated with both morning and evening fatigue included functional status, depressive symptoms, and sleep disturbance. Using this information, clinicians can identify patients at higher risk for more severe morning fatigue and evening fatigue, provide individualized patient education, and tailor interventions to address the modifiable risk factors.

CONTEXT: Fatigue is a distressing, persistent sense of physical tiredness that is not proportional to a person's recent activity. Fatigue impacts patients' treatment decisions and can limit their self-care activities. While significant interindividual variability in fatigue severity has been noted, little is known about predictors of interindividual variability in initial levels and trajectories of evening fatigue severity in oncology patients receiving chemotherapy (CTX). OBJECTIVES: To determine whether demographic, clinical, and symptom characteristics were associated with initial levels as well as the trajectories of evening fatigue. METHODS: A sample of outpatients with breast, gastrointestinal, gynecological, and lung cancer (N=586) completed demographic and symptom questionnaires a total of six times over two cycles of CTX. Fatigue severity was evaluated using the Lee Fatigue Scale. Hierarchical linear modeling (HLM) was used to answer the study objectives. RESULTS: A large amount of interindividual variability was found in the evening fatigue trajectories. A piecewise model fit the data best. Patients who were White, diagnosed with breast, gynecological, or lung cancer, and who had more years of education, child care responsibilities, lower functional status, and higher levels of sleep disturbance and depression reported higher levels of evening fatigue at enrollment. CONCLUSION: This study identified both non-modifiable (e.g., ethnicity) and modifiable (e.g., child care responsibilities, depressive symptoms, sleep disturbance) risk factors for more severe evening fatigue. Using this information, clinicians can identify patients at higher risk for more severe evening fatigue, provide individualized patient education, and tailor interventions to address the modifiable risk factors.

CONTEXT: Cancer patients experience a broad range of physical and psychological symptoms as a result of their disease and its treatment. On average, these patients report 10 unrelieved and co-occurring symptoms. OBJECTIVES: The aims were to determine if subgroups of oncology outpatients receiving active treatment (n = 582) could be identified based on their distinct experience with 13 commonly occurring symptoms; to determine whether these subgroups differed on select demographic and clinical characteristics; and to determine if these subgroups differed on quality of life (QOL) outcomes. METHODS: Demographic, clinical, and symptom data from one Australian and two U.S. studies were combined. Latent class analysis was used to identify patient subgroups with distinct symptom experiences based on self-report data on symptom occurrence using the Memorial Symptom Assessment Scale. RESULTS: Four distinct latent classes were identified (i.e., all low [28.0%], moderate physical and lower psych [26.3%], moderate physical and higher psych [25.4%], and all high [20.3%]). Age, gender, education, cancer diagnosis, and presence of metastatic disease differentiated among the latent classes. Patients in the all high class had the worst QOL scores. CONCLUSION: Findings from this study confirm the large amount of interindividual variability in the symptom experience of oncology patients. The identification of demographic and clinical characteristics that place patients at risk for a higher symptom burden can be used to guide more aggressive and individualized symptom management interventions.

Sleep disturbance has been associated with inflammation and cytokine activity, and we previously described genetic associations between cytokine polymorphisms and sleep maintenance and duration among adults with HIV/AIDS. Although sleep onset insomnia (SOI) is also a commonly reported sleep problem, associations between cytokine biomarkers and SOI have not been adequately studied. The purpose of this study was to describe SOI in relation to cytokine plasma concentrations and gene polymorphisms in a convenience sample of 307 adults (212 men, 72 women, and 23 transgender) living with HIV/AIDS. Based on the Pittsburgh Sleep Quality Index item that asks the time it usually took to fall asleep in the past month, participants were categorized as either >30min to fall asleep (n=70, 23%) or 30min or less to fall asleep (n=237). Plasma cytokines were analyzed, and genotyping was conducted for 15 candidate genes involved in cytokine signaling: interferon-gamma (IFNG), IFNG receptor 1 (IFNGR1), interleukins (IL1R2, IL2, IL4, IL6, IL8, IL10, IL13, IL17A), nuclear factor of kappa light polypeptide gene enhancer in B cells (NFKB1 and NFKB2), and tumor necrosis factor alpha (TNFA). Demographic and clinical variables were evaluated as potential covariates. After adjusting for genomic estimates of ancestry, self-reported race/ethnicity and viral load, SOI was associated with higher IL-13 plasma levels and with six single nucleotide polymorphisms (SNPs): IL1B rs1143642 and rs1143623, IL6 rs4719714, IL13 rs1295686, NFKB1 rs4648110, and TNFA rs2857602. In addition, the IL1B rs1143642 polymorphism was associated with plasma levels of IL-1beta in adjusted analyses. This study strengthens the evidence for an association between inflammation and sleep disturbance, particularly self-report of habitual SOI. In this chronic illness population, the cytokine polymorphisms associated with SOI provide direction for future personalized medicine intervention research.