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Many biological pathways involved in regulating substrate metabolism display rhythmic oscillation patterns. In rodents, clock genes regulate circadian rhythms of metabolic genes and substrate metabolism. However, the interrelationships among substrate metabolism, metabolic genes, and clock genes have not been fully explored in people. We tested the hypothesis that the diurnal expression pattern of pyruvate dehydrogenase kinase 4 (PDK4), a key metabolic enzyme involved in fuel switching between glucose and free fatty acids (FFAs), is associated with plasma FFA concentration and clock genes. We analyzed peripheral blood mononuclear cells (PBMCs), subcutaneous adipose tissue, and plasma samples obtained serially during 24 hours from metabolically healthy women (n = 10) and evaluated the interrelationships among PDK4, plasma FFA, and clock genes. We also determined the potential mechanisms responsible for PDK4 transcriptional regulation by using primary human PBMCs and adipocytes. We found that PDK4 diurnal expression patterns were similar in PBMCs and adipose tissue (ρ = 0.84, P < 0.001). The diurnal variation in PBMC PDK4 expression correlated more strongly with plasma FFA and insulin (ρ = 0.86 and 0.63, respectively, both P < 0.001) concentrations than clock genes. Data obtained from primary culture experiments demonstrated that FFAs directly induced PDK4 gene expression, at least in part through activation of peroxisome proliferator-activated receptor α. Our results suggest that plasma FFA availability is an important regulator of diurnal expression patterns of PDK4, and we identify a novel interaction between plasma FFA and cellular diurnal rhythms in regulating substrate metabolism.

Background The recently updated European LeukemiaNet risk stratification guidelines combine cytogenetic abnormalities and genetic mutations to provide the means to triage patients with acute myeloid leukemia for optimal therapies. Despite the identification of many prognostic factors, relatively few have made their way into clinical practice. Methods In order to assess and improve the performance of the European LeukemiaNet guidelines, we developed novel prognostic models using the biomarkers from the guidelines, age, performance status and select transcript biomarkers. The models were developed separately for mononuclear cells and viable leukemic blasts from previously untreated acute myeloid leukemia patients (discovery cohort, N  = 185) who received intensive chemotherapy. Models were validated in an independent set of similarly treated patients (validation cohort, N  = 166). Results Models using European LeukemiaNet guidelines were significantly associated with clinical outcomes and, therefore, utilized as a baseline for comparisons. Models incorporating age and expression of select transcripts with biomarkers from European LeukemiaNet guidelines demonstrated higher area under the curve and C-statistics but did not show a substantial improvement in performance in the validation cohort. Subset analyses demonstrated that models using only the European LeukemiaNet guidelines were a better fit for younger patients (age < 55) than for older patients. Models integrating age and European LeukemiaNet guidelines visually showed more separation between risk groups in older patients. Models excluding results for ASXL1 , CEBPA , RUNX1 and TP53 , demonstrated that these mutations provide a limited overall contribution to risk stratification across the entire population, given the low frequency of mutations and confounding risk factors. Conclusions While European LeukemiaNet guidelines remain a critical tool for triaging patients with acute myeloid leukemia, the findings illustrate the need for additional prognostic factors, including age, to improve risk stratification.

Introduction Acute myeloid leukemia (AML) remains one of the deadliest hematopoietic malignancies. A better understanding of the molecular biology governing AML may lead to improved risk stratification and facilitate the development of novel therapies. Proteins are responsible for much of the biology of cells. Several studies have examined the global proteome in bulk mononuclear cells (MNCs) from AML specimens, which are comprised a heterogenous population of cells at various stages of differentiation. Methods Given the potential impact of the nonleukemic cells on protein expression profiles, we applied an integrative proteogenomic approach utilizing next‐generation sequencing and mass spectrometry‐based proteomics to identify novel protein biomarkers in unsorted MNCs and viable leukemic blasts (VLBs) isolated from blood and bone marrow specimens obtained at the time of AML diagnosis. Results We identified significant differences in protein expression between VLBs and MNCs. Subsequent studies (N = 27) focused on proteomic profiling of VLBs that identified novel candidate biomarkers associated with mutational genotypes and clinical outcome, some of which were recapitulated in an independent cohort of patients. Using mass spectrometry, we also detected mutated protein products, some of which were predicted via in silico analyses to be potential neoantigens amenable to adoptive immunotherapy. As previously described, analyses comparing transcript and protein expression showed an overall modest correlation between mRNA and protein dataset, but enriching for genes associated with mutations significantly improved the protein–RNA correlation. Conclusion Together, the results provide insight into the biology of VLBs and demonstrate the gains derived from examining the proteome in addition to genome and transcriptome.

Background Studies have not systematically compared the ability to verify performance of prognostic transcripts in paired bulk mononuclear cells versus viable CD34-expressing leukemic blasts from patients with acute myeloid leukemia. We hypothesized that examining the homogenous leukemic blasts will yield different biological information and may improve prognostic performance of expression biomarkers. Methods To assess the impact of cellular heterogeneity on expression biomarkers in acute myeloid leukemia, we systematically examined paired mononuclear cells and viable CD34-expressing leukemic blasts from SWOG diagnostic specimens. After enrichment, patients were assigned into discovery and validation cohorts based on availability of extracted RNA. Analyses of RNA sequencing data examined how enrichment impacted differentially expressed genes associated with pre-analytic variables, patient characteristics, and clinical outcomes. Results Blast enrichment yielded significantly different expression profiles and biological pathways associated with clinical characteristics (e.g., cytogenetics). Although numerous differentially expressed genes were associated with clinical outcomes, most lost their prognostic significance in the mononuclear cells and blasts after adjusting for age and ELN risk, with only 11 genes remaining significant for overall survival in both cell populations ( CEP70 , COMMD7 , DNMT3B , ECE1 , LNX2 , NEGR1 , PIK3C2B , SEMA4D , SMAD2 , TAF8 , ZNF444 ). To examine the impact of enrichment on biomarker verification, these 11 candidate biomarkers were examined by quantitative RT/PCR in the validation cohort. After adjusting for ELN risk and age, expression of 4 genes ( CEP70 , DNMT3B , ECE1 , and PIK3CB ) remained significantly associated with overall survival in the blasts, while none met statistical significance in mononuclear cells. Conclusions This study provides insights into biological information gained/lost by examining viable CD34-expressing leukemic blasts versus mononuclear cells from the same patient and shows an improved verification rate for expression biomarkers in blasts.

Endoplasmic reticulum (ER) stress is likely involved in the pathogenesis of metabolic dysfunction in people with obesity and diabetes. Although tissue biopsy is often used to evaluate the presence and severity of ER stress, it is not known whether acute tissue injury‐induced by percutaneous muscle biopsy causes ER stress and its potential downstream effects on markers of inflammation and metabolic function. In this study, we tested the hypothesis that percutaneous biopsy‐induced tissue injury causes ER stress and alters inflammatory and metabolic pathways in skeletal muscle. Vastus lateralis muscle tissue was obtained by percutaneous biopsy at 0600 h and 12 h later from either the contralateral leg (Group 1, n = 6) or at the same site as the initial biopsy (Group 2, n = 6) in women who were overweight. Muscle gene expression of selected markers of ER stress, inflammation, and regulators of glucose and lipid metabolism were determined. Compared with Group 1, muscle gene expression in the second biopsy sample obtained in Group 2 demonstrated marked increases in markers of ER stress (GRP78, XBP1, ATF6) and inflammation (IL6, TNF), and alterations in metabolic regulators (decreased expression of GLUT4 and PPARGC1A and increased expression of FASN). Our results suggest that acute tissue injury induced by percutaneous muscle biopsy causes an integrated local response that involves an induction of ER stress and alterations in markers of inflammation and regulators of glucose and lipid metabolism. This study shows acute tissue injury induced by percutaneous muscle biopsy causes local endoplasmic reticulum (ER) stress in conjunction with transcriptional changes in markers of inflammation and metabolic function. These results suggest ER stress, inflammation, and alterations in cellular metabolic function are components of an integrated acute response to help repair muscle injury induced by percutaneous biopsy.

Background Papulopustular rash is a common class effect of epidermal growth factor receptor inhibitors (EGFRI) that can affect patients’ health-related quality of life and cause disruptions to treatment. SWOG S1013 (NCT01416688) is a multi-center study designed to validate the Functional Assessment of Cancer Therapy EGFRI 18 (FACT-EGFRI 18) using 7-items from the National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events (CTCAE) version 4.0 to assess EGFRI-induced skin-related toxicities and their impact on functional status. Methods Patients with a diagnosis of colorectal or lung cancer to receive EGFRI therapies for at least 6 weeks were enrolled. Patient self-assessments using the FACT-EGFRI 18 were completed prior to undergoing CTCAE assessment by trained clinicians at baseline, weekly × 6, and then monthly × 3. The psychometric properties of the FACT-EGFRI 14 (skin toxicity items only) and 18 (plus 2 nail and 2 hair items) were established based on criterion validity, known groups validity, internal consistency reliability, and responsiveness to change. Results Of the 146 registered patients, 124 were evaluable. High Cronbach’s alpha (> 0.70) for both FACT-EGFRI 14 and FACT-EGFRI 18 scores across assessment times were observed. Although agreement (i.e. criterion validity) between individual and summary scales of the FACT-EGFRI 18 for assessing skin toxicity was good, agreement with the clinician-reported CTCAE was only fair. The minimal important difference was determined to be 3 points. The results also demonstrated responsiveness to symptom change. Discussion Based on the results of this multi-center validation study, the FACT-EGFRI 18 patient-reported outcome instrument provided data from the patient’s perspective yielding unique information as well as complementing clinician-rated CTCAE grades, especially for the symptoms of pain, pruritus, and paronychia. Conclusions Good to excellent psychometric properties for the FACT-EGFRI 18 were demonstrated, supporting further use of this patient-reported outcomes measure. Additional validation with a more diverse group of patients should be conducted.

Studies showing that patients with cancer from rural areas have worse outcomes than their urban counterparts have relied on cancer population data and did not account for differences in access to care. Clinical trial patients receive protocol-directed care by design, so large clinical trial databases are ideal for examining the impact of rural vs urban residency on outcomes. To compare the geographic distribution and survival outcomes for rural vs urban patients with cancer treated in clinical trials. In this comparative effectiveness retrospective cohort analysis, 36 995 patients from all 50 states enrolled in 44 phase 3 and phase 2/3 SWOG (formerly the Southwest Oncology Group) treatment trials from January 1, 1986, to December 31, 2012, were examined. Seventeen different cancer-specific analysis cohorts were constructed. Data through January 30, 2018, were analyzed. Rural vs urban residency was defined using the Rural-Urban Continuum Codes developed by the US Department of Agriculture. Multivariate Cox regression was used to estimate the association of residency with overall survival, progression-free survival, and cancer-specific survival, controlling for major disease-specific prognostic factors and demographic variables and stratifying by study. Different definitions of rurality were examined. The distribution of rural vs urban patients by geographic region was described. Overall, 27.7% of patients were 65 years or older (range across 17 cohort analyses, 7.8%-74.5%), 40.3% were female in the non-sex-specific analyses (range across 17 cohort analyses, 28.1%-45.9%), and 10.8% were black (range across 17 cohort analyses, 1.9%-22.4%). Overall, 19.4% of patients (7184 of 36 995) were from rural locations. Rural patients were more likely to be aged 65 years or older (rural, 30.7% aged ≥65 years vs urban, 27.0% aged ≥65 years; difference, 3.7%; 95% CI, 2.5%-4.9%; P < .001), were less likely to be black (rural, 5.4% vs urban, 12.1%; difference, 6.7%; 95% CI, 6.1%-7.3%; P < .001), were similar with respect to sex (rural, 40.4% female vs urban, 39.7% female; difference, 0.6%; 95% CI, -1.4% to 2.6%; P = .53), and were well represented within major US geographic regions (West, Midwest, South, and Northeast). Clinical prognostic factors were similar. In multivariable regression, rural patients with adjuvant-stage estrogen receptor-negative and progesterone receptor-negative breast cancer had worse overall survival (hazard ratio, 1.27; 95% CI, 1.06-1.51; P = .008) and cancer-specific survival (hazard ratio, 1.26; 95% CI, 1.04-1.52; P = .02). No other statistically significant differences for overall, progression-free, or cancer-specific survival were found. Results were consistent regardless of the definition of rurality. Rural and urban patients with uniform access to cancer care through participation in a SWOG clinical trial had similar outcomes. This finding suggests that improving access to uniform treatment strategies for patients with cancer may help resolve the disparity in cancer outcomes between rural and urban patients.

Prior experience indicated that use of higher doses of cytarabine during induction for acute myeloid leukemia (AML) with a histone deacetylase inhibitor resulted in high response rates. S1203 was a randomized multicenter trial for previously untreated patients aged 18–60 with AML which compared daunorubicin and cytarabine (DA), idarubicin with higher dose cytarabine (IA) and IA with vorinostat (IA + V). The primary endpoint was event free survival (EFS). 738 patients were randomized: 261 to each DA and IA arms and 216 to the IA + V arm. 96, 456, and 150 patients had favorable-, intermediate-, and unfavorable-risk cytogenetics, respectively. 152 were NPM1 and 158 FLT3 mutated. The overall remission rate was 77.5% including 62.5% CR and 15.0% CRi. No differences in remission, EFS, or overall survival were observed among the 3 arms except for the favorable cytogenetics subset who had improved outcomes with DA and postremission high dose cytarabine. A trend towards increased toxicity was observed with the IA and IA + V arms. The use of higher dose cytarabine during induction therapy in younger patients with AML, with or without vorinostat, does not result in improved outcomes. (Funded by the US National Institutes of Health and others, ClinicalTrials.gov number, NCT01802333.)

Background The recently updated European LeukemiaNet risk stratification guidelines combine cytogenetic abnormalities and genetic mutations to provide the means to triage patients with acute myeloid leukemia for optimal therapies. Despite the identification of many prognostic factors, relatively few have made their way into clinical practice. Methods In order to assess and improve the performance of the European LeukemiaNet guidelines, we developed novel prognostic models using the biomarkers from the guidelines, age, performance status and select transcript biomarkers. The models were developed separately for mononuclear cells and viable leukemic blasts from previously untreated acute myeloid leukemia patients (discovery cohort, N = 185) who received intensive chemotherapy. Models were validated in an independent set of similarly treated patients (validation cohort, N = 166). Results Models using European LeukemiaNet guidelines were significantly associated with clinical outcomes and, therefore, utilized as a baseline for comparisons. Models incorporating age and expression of select transcripts with biomarkers from European LeukemiaNet guidelines demonstrated higher area under the curve and C-statistics but did not show a substantial improvement in performance in the validation cohort. Subset analyses demonstrated that models using only the European LeukemiaNet guidelines were a better fit for younger patients (age < 55). Models integrating age and European LeukemiaNet guidelines visually showed more separation between risk groups in older patients. Models, which excluded results for ASXL1, CEBPA, RUNX1 and TP53, demonstrated a limited overall contribution to risk stratification across the entire population, given the low frequency of mutations and confounding risk factors. Conclusions While European LeukemiaNet guidelines remain a critical tool for triaging patients with acute myeloid leukemia, the findings illustrate the need for additional prognostic factors, including age, to improve risk stratification.

JENNIE GRAY was a dull scholar; but she was loved by all who knew her.