Decker, Paul A.

Abstract Abstract 2807 CCDC26 is a retinoic acid-dependent modulator of myeloid cell differentiation and death (Yin W et al. Oncogene 2006 :25 :3735). CCDC26 maps to chromosome 8q24.21 and germline polymorphisms in the gene have been associated with low-grade gliomas (Jenkins RB et al. Cancer Genetics 2011;204 :13), which in turn have recently been shown to frequently express IDH1 mutations (Parsons D et al, Science 2008;321 :1807). More recently, we have discovered that CCDC26 SNP associations in gliomas are primarily restricted to patients with IDH1 mutations (Jenkins et al. unpublished observations). We therefore hypothesized that germline CCDC26 SNPS might be associated with patients with myeloid malignancies that harbor IDH1 mutations (Mardis et al. NEJM 2009;361 :1058). Seventy-two IDH -mutated patients with chronic or blast phase myeloproliferative neoplasms (MPN), myelodysplastic syndromes or acute myeloid leukemia (most constituting post-MPN events) were identified: 18 IDH1 R132, one IDH2 R172 and 53 IDH2 R140. These 72 patients and a control group of 153 IDH unmutated cases with myeloproliferative or myelodysplastic neoplasms (total n =225) were genotyped for CCDC26 risk alleles associated with IDH -mutated gliomas: rs10464870, rs891835 and rs4295627. The respective minor allele frequencies (MAF) were significantly different between IDH1 (11%, 8% and 6%) and IDH2 (30%, 27% and 24%) mutated cases (p=0.037, 0.040 and 0.021; OR 3.4, 3.7 and 6.1 with 95% CI of 1.1–10.5, 1.1–13.0 and 1.3–28.9) as well as between IDH- wild type (24%, 24% and 21%) and IDH1 -mutated (11%, 8% and 6%) cases (p=0.10, 0.043 and 0.035; OR 0.42, 0.29 and 0.21 with 95% CI of 0.15–1.19, 0.09–0.96 and 0.05–0.90). The MAF values in our IDH -unmutated cases were similar to that of population-based controls. However, the direction of SNP associations in IDH1 -mutated myeloid malignancies were opposite of those seen in IDH1 -mutated gliomas. Our observations suggest a differential effect of CCDC26 genetic polymorphisms in IDH1 -mutated myeloid malignancies compared to either their IDH2 R140-mutated or IDH1 -mutated gliomas. Such differences in genomic context might contribute to hitherto seen differences in prognostic impact between IDH2 R140 vs. IDH1 R132 vs. IDH2 R172, in AML (Green CL et al. Blood Published online before print May 19, 2011, doi: 10.1182/blood-2010-12-322479). Disclosures: No relevant conflicts of interest to declare.

Abstract Introduction In general population samples, higher levels of stress and depression have been associated with increased prevalence of smoking in pregnancy. Little is known about the association of prenatal tobacco use, stress, and depression among American Indian or Alaska Native (AI/AN) women. Methods The Healthy Pregnancies Project is a cluster-randomized controlled trial, evaluating a community-level intervention compared with usual care, for reducing tobacco use during pregnancy and postpartum among AN women in 16 villages in western Alaska. This cross-sectional study analyzed baseline data from enrolled pregnant women. Baseline measures included the self-reported, 7-day, point-prevalence current use of any tobacco, Perceived Stress Scale (PSS), and the Center for Epidemiological Studies-Depression (CES-D). Generalized estimating equations (GEE) analyses adjusted for village, participant age, and gestational age. Results Participants (N = 352) were on average (SD) 25.8 (5.0) years of age and at 26.8 (9.8) weeks gestation. 66.5% were current tobacco users, of which 77% used Iqmik, a homemade form of smokeless tobacco. Compared with nonusers, tobacco users reported lower PSS score (p = .020) and less clinical levels of depression (CES-D ≥ 16) (18.1% vs. 9.3%, p = .21). Findings were not accounted for by nicotine dependence severity or self-reported tobacco use before pregnancy. Conclusions In this sample of pregnant AN women, tobacco users report less stress and clinical levels of depression than nonusers. A potential challenge with tobacco treatment for pregnant AN women is to provide alternative ways of deescalating stress and affect management instead of using tobacco. Implications This study contributes novel information on the association of tobacco use, perceived stress, and depression among Alaska Native women enrolled in a clinical trial to promote healthy pregnancies. Most prior studies addressing this topic were conducted among general population samples of pregnant women who smoked cigarettes. Little is known about these associations with prenatal smokeless tobacco, or among American Indian or Alaska Native women. The results are contrary to findings reported previously, because current tobacco use was associated with less stress and depression than nonuse. The study findings have implications for cessation treatment for this tobacco-use disparity group.

Prior research explored reasons for tobacco use among pregnant Alaska Native (AN) women but did not address the postpartum period. This study followed up with AN women one to three years postpartum who had participated in a prenatal smoking cessation intervention study (Motivate Alaska Women (MAW) Phase 3) and had consented to be re-contacted for future studies. Of 47 eligible women, 32 (68%) participated. A semi-structured phone interview was conducted a mean of 2.0 years after delivery (range 1.6–2.8). Measures assessed self-reported tobacco use status in the 12 months after delivery, at 12 months postpartum, and at the time of the interview; reasons for maintaining abstinence, continued use, or relapse; and included the Perceived Stress Scale (PSS) and Negative Affect (NA) scale. Content analysis was used to generate themes from open-ended response items. Tobacco use was reported by 23 women (72%) at delivery, 30 (94%) within the 12 months after delivery, 27 (84%) at 12 months postpartum, and 29 (91%) at the time of the interview. Among nine women not using tobacco at delivery, seven (78%) relapsed during the 12 months after delivery. Of the 29 current tobacco users, 28 (97%) smoked cigarettes. Twenty-seven participants (84%) reported stress and 15 (52%) indicated addiction as reasons for continuing, starting, or resuming tobacco use. Types of stressors were related to parenting and traumatic experiences. Among current tobacco users, mean NA score (18.7) was significantly higher (p = 0.01) than the normative mean (14.8), but no differences were detected for PSS score. In this sample of AN women, postpartum tobacco use was highly prevalent, and stress was a primary reason that women endorsed for using tobacco. These preliminary results have several practice and research implications for exploring ways to support non-tobacco use among postpartum AN women.

AbstractBackgroundGlioblastoma (GBM) represents an aggressive cancer type with a median survival of only 14 months. With fewer than 5% of patients surviving 5 years, comprehensive profiling of these rare patients could elucidate prognostic biomarkers that may confer better patient outcomes. We utilized multiple molecular approaches to characterize the largest patient cohort of isocitrate dehydrogenase (IDH)–wildtype GBM long-term survivors (LTS) to date.MethodsRetrospective analysis was performed on 49 archived formalin-fixed paraffin embedded tumor specimens from patients diagnosed with GBM at the Mayo Clinic between December 1995 and September 2013. These patient samples were subdivided into 2 groups based on survival (12 LTS, 37 short-term survivors [STS]) and subsequently examined by mutation sequencing, copy number analysis, methylation profiling, and gene expression.ResultsOf the 49 patients analyzed in this study, LTS were younger at diagnosis (P = 0.016), more likely to be female (P = 0.048), and MGMT promoter methylated (UniD, P = 0.01). IDH-wildtype STS and LTS demonstrated classic GBM mutations and copy number changes. Pathway analysis of differentially expressed genes showed LTS enrichment for sphingomyelin metabolism, which has been linked to decreased GBM growth, invasion, and angiogenesis. STS were enriched for DNA repair and cell cycle control networks.ConclusionsWhile our findings largely report remarkable similarity between these LTS and more typical STS, unique attributes were observed in regard to altered gene expression and pathway enrichment. These attributes may be valuable prognostic markers and are worth further examination. Importantly, this study also underscores the limitations of existing biomarkers and classification methods in predicting patient prognosis.

Background: Accurate identification of stroke cases from electronic health record (EHR) is needed for efficient and valid clinical and epidemiology research. A number of studies have evaluated the validity of using ICD-9 and ICD-10 codes for stroke identification. Previous research results show that sensitivity and positive predictive value (PPV) for stroke identification is the lowest among all other cerebrovascular diseases, with notable differences observed by stroke pathological subtypes. While most prevalent cerebrovascular disease cases can be detected using 430-438/I60-I69 collectively, more accurate and comprehensive stroke phenotyping algorithm is needed to identify incident stroke cases from EHR. In our work, we compared case identification results using ICD-codes exclusively with ICD plus a natural language processing (NLP) algorithm. Methods: We developed the NLP part of our stroke algorithm using a list of expert provided stroke-related keywords, which covers transient ischemic attack (TIA), ischemic stroke, and hemorrhagic stroke. We validated the hybrid (ICD+NLP) algorithm and compared it with ICD-exclusive algorithm in a previously established atrial fibrillation cohort (n=5,062). Clinical notes and ICD codes of all patients after the incident AF event were reviewed by two nurse abstracters to confirm new stroke incidences. All past clinical notes and ICD codes of a subset of patients (n=402) were reviewed to confirm lifetime (prior and current) stroke cases. Manual abstraction results were considered the gold standard for evaluation of ICD only and ICD+NLP automatic extraction. Sensitivity and positive predictive values (PPV) of both algorithms were calculated. Results: Among 5,062 patients, 593 patients were confirmed to have suffered a stroke after atrial fibrillation while 4,469 patients were confirmed with no EHR evidence of stroke after AF. The ICD-exclusive algorithm had a sensitivity of 47.2% and a PPV of 47.8% for detecting new stroke incidences. The hybrid stroke algorithm achieved a sensitivity of 92.4% and a PPV of 60.6% for extraction of incident stroke. For extraction of lifetime stroke cases, the hybrid approach achieved a sensitivity of 93.9% and a PPV of 88.7%. Performance of new stroke incidence extraction is limited because past/current stroke mentions in clinical notes are difficult to distinguish by our NLP algorithm (may be a future direction). Conclusions: We developed and validated a stroke algorithm that performed well for identifying incident and lifetime stroke cases. The addition of NLP into the stroke algorithm improved the sensitivity and PPV of compared to an ICD-exclusive algorithm.