Citations

Abstract BACKGROUND: Glioma accounts for ~27% of all primary brain tumors and is responsible for ~13,000 cancer-related deaths in the US each year. Glioma tumors can be broadly classified into glioblastoma (GBM) and lower-grade non-GBM. Typically gliomas have a poor prognosis irrespective of medical care, with the most common form, GBM, having a five-year survival rate of only 5%. While genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, individual studies have had limited power to identify risk loci. METHODS: We performed the largest glioma GWAS to date, comprising a meta-analysis of six existing GWAS (6,405 cases, 14,100 controls) as well as new GWAS from the Glioma International Case Control Consortium (GICC; 4,572 cases and 3,286 controls) and University of California, San Francisco (UCSF)-Mayo (1,519 cases, 804 controls), totaling 12,496 cases (6,191 classified as GBM, 5,819 as non-GBM) and 18,190 controls. RESULTS: We identified five new risk loci for GBM at 1p31.3 (rs12752552; near JAK1, P=2.04×10-9, odds ratio (OR)=1.22), 11q14.1 (rs11233250; P=9.95×10-10, OR=1.24), 16p13.3 (rs2562152; near MPG, P=1.93x10-8, OR=1.21), 16q12.1 (rs10852606; HEATR3, P=1.29×10-11, OR=1.18), 22q13.1 (rs2235573; P=1.76×10-10, OR=1.15) and eight for non-GBM at 1q32.1 (rs4252707; MDM4, P=3.34×10-9, OR=1.19), 1q44 (rs12076373; AKT3, P=2.63×10-10, OR=1.23), 2q33.3 (rs7572263; near IDH1, P=2.18×10-10, OR=1.20), 3p14.1 (rs11706832; LRIG1, P=7.66×10-9, OR=1.15), 10q24.33 (rs11598018; OBFC1, P=3.39×10-8, OR=1.14), 11q21 (rs7107785; P=3.87×10-10, OR=1.16), 14q12 (rs10131032; P=5.07x10-11, OR=1.33) and 16p13.3 (rs3751667; P=2.61×10-9, OR=1.18). Case-only analyses confirmed the specificity of 11q14.1, 16p13.3 and 22q13.1 associations for GBM and 1q44, 2q33.3, 3p14.1, 11q21 and 14q12 for non-GBM tumors. In the combined meta-analysis, among previously published glioma risk SNPs, those for all glioma at 17p13.1 (TP53), GBM at 5p15.33 (TERT), 7p11.2 (EGFR), 9p21.3 (CDKN2B-AS1) and 20q13.33 (RTEL1) and for non-GBM at 8q24.21 (CCDC26), 11q23.2, 11q23.3 (PHLDB1) and 15q24.2 (ETFA) showed even greater evidence for association. SNPs at 10q25.2 and 12q12.1 for non-GBM tumors retained genome-wide significance (i.e. P<5.0x10-8). Associations at the previously reported loci for GBM at 3q26.2 (near TERC) and 12q23.33 (POLR3B) did not retain statistical significance. CONCLUSIONS: Our findings substantiate genetic susceptibility to GBM and non-GBM glioma being highly distinct, consistent with their distinctive molecular profiles presumably resulting from different etiological pathways. Functional analyses should lead to further insights into the biological basis of the different glioma histologies. Such information can inform gene discovery initiatives and therefore have a measurable impact on the successful development of new therapeutic agents. Citation Format: Ben Kinnersley, Beatrice S. Melin, Jill S. Barnholtz-Sloan, Margaret R. Wrensch, Christoffer Johansen, Dora Il’yasova, Quinn Ostrom, and members of GICC, Karim Labreche, Jeanette E. Eckel-Passow, Paul A. Decker, Marianne Labussière, Ahmed Idbaih, Khe Hoang-Xuan, Anna-Luisa Di Stefano, Karima Mokhtari, Jean-Yves Delattre, Pilar Galan, Konstantinos Gousias, Johannes Schramm, Minouk J. Schoemaker, Sarah J. Fleming, Stefan Herms, Stefanie Heilmann, Marcus M. Nöthen, Heinz-Erich Wichmann, Stefan Schreiber, Anthony Swerdlow, Mark Lathrop, Matthias Simon, Marc Sanson, Preetha Rajaraman, Stephen Chanock, Martha Linet, Zhaoming Wang, Meredith Yeager, Rose K. Lai, Elizabeth B. Claus, Sara H. Olson, Robert B. Jenkins, Richard S. Houlston, Melissa L. Bondy. Genome-wide association study of glioma reveals specific differences in genetic susceptibility to glioblastoma and non-glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1302. doi:10.1158/1538-7445.AM2017-1302

ObjectiveTo confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder.MethodData were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth‐cohort, family history, polarity of first episode and country physician density.ResultsThere was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth‐cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth‐cohort (all estimated coefficientsP< 0.001).ConclusionA large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure (LEDlighting, mobile devices backlit withLEDs) may influence adaptability to a springtime circadian challenge.

AbstractEpigenomics, the study of modifications to genetic material that do not alter the underlying DNA sequence, is generating increasing interest as a means to help clarify disease pathogenesis and outcomes. Although genome-wide association studies have identified several potential candidate genes that may be implicated in primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC), it is estimated that these genes explain less than 20% of the heritability of these diseases. Thus, to date, the origins of “missing heritability” for PBC and PSC remain elusive. The epigenome may provide a potentially elegant solution to this phenomenon, as it can be modified by both internal and external exposures (coined the “exposome”). This may explain differences in disease presentation, treatment response, and rates of progression between individuals. Epigenetic changes may also provide a framework for discovering potential biomarkers for diagnosis and screening of PBC and PSC. Importantly, because the epigenome is modifiable, it may also highlight novel pathways for therapeutic discovery and interventions of these diseases.

AbstractBackgroundWe characterized the pharmacogenomics (PGx) results received by diagnostic odyssey patients as secondary findings during clinical whole exome sequencing (WES) testing as a part of their care in Mayo Clinic's Individualized Medicine Clinic to determine the potential benefits and limitations to this cohort.MethodsWES results on 94 patients included a subset of PGx variants in CYP2C19, CYP2C9, and VKORC1 if identified in the patient. Demographic, phenotypic, and medication usage information was abstracted from patient medical data. A pharmacist interpreted the PGx results in the context of the patients’ current medication use and made therapeutic recommendations.ResultsThe majority was young with a median age of 10 years old, had neurological involvement in the disease presentation (71%), and was currently taking medications (90%). Of the 94 PGx‐evaluated patients, 91% had at least one variant allele reported and 20% had potential immediate implications on current medication use.ConclusionDue to the disease complexity and medication needs of diagnostic odyssey patients, there may be immediate benefit obtained from early life PGx testing for many and most will likely find benefit in the future. These results require conscientious interpretation and management to be actionable for all prescribing physicians throughout the lifetime of the patient.

AbstractBackground and AimPrimary sclerosing cholangitis (PSC) typically develops in middle‐age adults. Little is known about phenotypic differences when PSC is diagnosed at various ages. Therefore, we sought to compare the clinical characteristics of a large PSC cohort based on the age when PSC was diagnosed.MethodsWe performed a multicenter retrospective review to compare the features of PSC among those diagnosed between 1–19 (n = 95), 20–59 (n = 662), and 60–79 years (n = 102).ResultsThose with an early diagnosis (ED) of PSC were more likely to have small‐duct PSC (13%) than those with a middle‐age diagnosis (MD) (5%) and late diagnosis (LD) groups (2%), P < 0.01, and appeared to have a decrease risk of hepatobiliary malignancies: ED versus MD: hazard ratio (HR), 0.25; 95% confidence interval (CI) 0.06–1.03, and ED versus LD: HR, 0.07; 95% CI 0.01–0.62. Cholangiocarcinoma was diagnosed in 78 subjects (ED n = 0, MD n = 66, and LD n = 12) and was more likely to be diagnosed within a year after the PSC diagnosis among those found to have PSC late in life: ED 0% (0/95), MD 2% (14/662), and LD 6% (6/102), P = 0.02. Similarly, hepatic decompensation was more common among those with LD‐PSC versus younger individuals: LD versus MD: HR, 1.64; 95% CI 0.98–2.70, and LD versus ED: HR, 2.26; 95% CI 1.02–5.05.ConclusionsThose diagnosed with PSC early in life are more likely to have small‐duct PSC and less likely to have disease‐related complications. Clinicians should be vigilant for underlying cholangiocarcinoma among those with PSC diagnosed late in life.

Abstract Over the recent years significant knowledge has been accumulated on which drugs can be therapeutically beneficial for a given patient based on mutational profiling of their tumors using selected gene panels. Much less, however, is known under which conditions targeting of genes which are amplified could be beneficial. Apart from successfully targeting HER2-positive cancers, many of which frequently carry amplified ERBB2 gene, no other targeted therapy based on DNA amplifications or gains of the genes is offered to the patients due to lack of clinical response data. Using mate pair sequencing we have profiled 60 high grade serous ovarian tumors to compare genomic rearrangements and copy number changes. The analyses revealed that these tumors carry highly rearranged genome. Copy number changes amplifications, gains and losses were very common and included genes potentially therapeutically targetable. In contrast, only a few of targetable fusion genes were identified in a set of 60 cases. The tumors were propagated in immunocompromised mice (mouse avatars), sequenced and showed identical to original patient tumor landscape of rearrangements. Using these mouse avatar models we tested whether a therapy inhibiting selected based on genomic amplification targets provided a benefit compared to standard chemotherapy. Mice which harbored tumors showing amplifications of CDKs (CDK2, 4 and 9) and ERBB3 were treated with flavopiridol and pertuzumab respectively, and response was compared to that of standard for ovarian cancer chemotherapy (carboplatin and paclitaxel combination). We observed that application of either agent, significantly inhibited tumor growth in treated mice as compared to untreated. However, neither drug alone caused tumor regression. The treatment regimen then was modified to administer chemotherapy and targeted therapy together. A mouse avatars in which genomic analyses revealed amplification at loci involving AKT3 and RICTOR genes was treated with chemotherapy alone and in combination with MK2206 (AKT inhibitor) or MK8669 (mTOR inhibitor). The high level of both target proteins was confirmed by immunoblotting. Significant regression of tumor was observed after 6 weeks of treatment. Addition of either targeted drug provided an extra benefit in killing tumor cells compared to chemotherapy alone. The mice are followed to study tumor recurrence. These data indicated that genomic information obtained using next generation sequencing can aid therapy decisions by tailoring treatments to individual tumor makeup. Avatar models in conjunction with genomic analyses of the original tumors are invaluable for testing specific targeted therapies selected based on amplification/gains of putative genes-targets and for studying mechanisms of tumor recurrence and therapy resistance. Citation Format: Faye R. Harris, Lin Yang, Xiaonan Hou, Konstantinos Leventakos, Saravut J. Weroha, George Vasmatzis, Irina V. Kovtun. Targeting genes which are amplified in ovarian cancer. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Targeting the Vulnerabilities of Cancer; May 16-19, 2016; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(1_Suppl):Abstract nr A34.