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BackgroundNational Malaria Control Programmes (NMCPs) currently make limited use of parasite genetic data. We have developed GenRe-Mekong, a platform for genetic surveillance of malaria in the Greater Mekong Subregion (GMS) that enables NMCPs to implement large-scale surveillance projects by integrating simple sample collection procedures in routine public health procedures.MethodsSamples from symptomatic patients are processed by SpotMalaria, a high-throughput system that produces a comprehensive set of genotypes comprising several drug resistance markers, species markers and a genomic barcode. GenRe-Mekong delivers Genetic Report Cards, a compendium of genotypes and phenotype predictions used to map prevalence of resistance to multiple drugs.ResultsGenRe-Mekong has worked with NMCPs and research projects in eight countries, processing 9623 samples from clinical cases. Monitoring resistance markers has been valuable for tracking the rapid spread of parasites resistant to the dihydroartemisinin-piperaquine combination therapy. In Vietnam and Laos, GenRe-Mekong data have provided novel knowledge about the spread of these resistant strains into previously unaffected provinces, informing decision-making by NMCPs.ConclusionsGenRe-Mekong provides detailed knowledge about drug resistance at a local level, and facilitates data sharing at a regional level, enabling cross-border resistance monitoring and providing the public health community with valuable insights. The project provides a rich open data resource to benefit the entire malaria community.FundingThe GenRe-Mekong project is funded by the Bill and Melinda Gates Foundation (OPP11188166, OPP1204268). Genotyping and sequencing were funded by the Wellcome Trust (098051, 206194, 203141, 090770, 204911, 106698/B/14/Z) and Medical Research Council (G0600718). A proportion of samples were collected with the support of the UK Department for International Development (201900, M006212), and Intramural Research Program of the National Institute of Allergy and Infectious Diseases.

Background: Neurofibromatosis type 1 (NF1) is a cancer syndrome associated with many different cancer types. There are limited studies examining melanoma risk in this population. Objective: To identify melanoma cases in NF1 patients and compare melanoma incidence rates relative to a general population sample. Methods: A retrospective single institution case review of 857 NF1 patients (seen from 7/1997 to 7/2017) was conducted. We calculated age- and calendar period-adjusted standardized incidence ratios (SIRs) for white patients >20 years old overall (N=282) and for females (N=156) at their last visit date. We obtained general population melanoma reference rates from the Surveillance, Epidemiology, and End Results (SEER) 9 database. Results: Among 857 patients, 52.2% were female, 54% were 20 (40.4±14.9) years old at their last visit date. One white female patient had a malignant melanoma diagnosed at 47 years old. The adjusted SIR was 0.97 (95% CI 0.05-4.78) overall (N=282) and 1.62 (95% CI 0.08-7.98) for females (N=156). Conclusions: We did not find statistical evidence for an increased melanoma risk in adults with NF1. However, additional large studies are warranted to clarify whether melanoma risk is increased in NF1 patients.

The Brain Tumor Epidemiology Consortium (BTEC) is an international consortium that aims to foster multicenter and inter-disciplinary collaborations that focus on research related to the etiology, outcomes, and prevention of brain tumors. The 19th annual BTEC meeting was held in Copenhagen, Denmark, on June 19 - 21, 2018. The meeting focused on forming international collaborations and integrating multiple data types for the next generation of studies in brain tumor epidemiology. The next BTEC meeting will be held in Southern California in June 2019.
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We conducted the largest investigation of predisposition variants in cancer to date, discovering 853 pathogenic or likely pathogenic variants in 8% of 10,389 cases from 33 cancer types. Twenty-one genes showed single or cross-cancer associations, including novel associations of SDHA in melanoma and PALB2 in stomach adenocarcinoma. The 659 predisposition variants and 18 additional large deletions in tumor suppressors, including ATM, BRCA1, and NF1, showed low gene expression and frequent (43%) loss of heterozygosity or biallelic two-hit events. We also discovered 33 such variants in oncogenes, including missenses in MET, RET, and PTPN11 associated with high gene expression. We nominated 47 additional predisposition variants from prioritized VUSs supported by multiple evidences involving case-control frequency, loss of heterozygosity, expression effect, and co-localization with mutations and modified residues. Our integrative approach links rare predisposition variants to functional consequences, informing future guidelines of variant classification and germline genetic testing in cancer.

The Brain Tumor Epidemiology Consortium (BTEC) is an international consortium that aims to advance the development of multicenter and interdisciplinary collaborations that focus on research related to the etiology, outcomes, and prevention of brain tumors. The 18th annual BTEC meeting was held in Banff, AB, Canada, on June 27 - 29, 2017. The meeting focused on the intersection between epidemiology and precision medicine, that is, the use of molecular indicators of risk, early disease and prognosis or precision epidemiology. While traditional epidemiologic approaches group large numbers of participants for statistical power, precision epidemiology is founded on the uniqueness and biology of individual disease characteristics. With this in mind, plenary speakers described the molecular heterogeneity of adult and pediatric brain tumors and how those characteristics are currently being used to guide therapy and etiologic research. Rare subtypes and novel mechanisms for recruitment of individuals for research on brain tumors were discussed along with concepts and methodology related to biological and etiologic heterogeneity. The incorporation of relevant molecular classifiers into population registries was emphasized for its role in future research endeavors, ensuring the accessibility of such tools for researchers and clinicians seeking to improve the lives of individuals with brain tumors and those at risk. The next BTEC meeting will be held in Copenhagen, Denmark, in June 2018.
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The Brain Tumor Epidemiology Consortium (BTEC) is an international consortium that aims to advance development of multicenter and interdisciplinary collaborations that focus on research related to the etiology, outcomes, and prevention of brain tumors. The 17th annual BTEC meeting was held in Barcelona, Spain on June 21 - 23, 2016. The meeting focused on immune and viral factors that influence brain tumor development. Fundamentals of innate and adaptive immunity were reviewed, the role of immune checkpoint inhibitors in primary and secondary brain tumors was addressed, vaccination strategies for glioma treatment were presented, and the potential contribution of immune dysfunction and viruses tropic for glial cells in gliomagenesis was discussed. Further contributions addressed the risk of non-ionizing radiation, molecular and birth characteristics on brain tumor induction/outcomes, and patterns of care and effects of different treatments on brain tumor survival in the real world setting. The next BTEC meeting will be held in June 2017 in Banff, Canada, and will focus on brain tumor epidemiology in the era of precision medicine.
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Background: Access to breast screening mammogram services decreased during the COVID-19 pandemic. Our objectives were to estimate: 1) the COVID-19 affected period, 2) the proportion of pandemic-associated missed or delayed screening encounters, and 3) pandemic-associated patient attrition in screening encounters overall and by sociodemographic subgroup. Methods: We included screening mammogram encounter EPIC data from 1-1-2019 to 12-31-2022 for females ≥40 years old. We used Bayesian State Space models to describe weekly screening mammogram counts, modeling an interruption that phased in and out between 3-1-2020 and 9-1-2020. We used the posterior predictive distribution to model differences between a predicted, uninterrupted process and the observed screening mammogram counts. We estimated associations between race/ethnicity and age group and return screening mammogram encounters during the pandemic among those with 2019 encounters using logistic regression. Results: Our analysis modeling weekly screening mammogram counts included 231,385 encounters (n = 127,621 women). Model-estimated screening mammograms dropped by >98% between 03-15-2020 and 05-24-2020 followed by a return to pre-pandemic levels or higher with similar results by race/ethnicity and age group. Among 79,257 women, non-Hispanic (NH) Asians, NH Blacks, and Hispanics had significantly (p <.05) lower odds of screening encounter returns during 2020–2022 vs. NH Whites with odds ratios (ORs) from 0.70 to 0.91. Among 79,983 women, those 60–69 had significantly higher odds of any return screening encounter during 2020–2022 (OR = 1.28), while those ≥80 and 40–49 had significantly lower odds (ORs 0.77, 0.45) than those 50–59 years old. A sensitivity analysis suggested a possible pre-existing pattern. Conclusions: These data suggest a short-term pandemic effect on screening mammograms of ~2 months with no evidence of disparities. However, we observed racial/ethnic disparities in screening mammogram returns during the pandemic that may be at least partially pre-existing. These results may inform future pandemic planning and continued efforts to eliminate mammogram screening disparities. [ABSTRACT FROM AUTHOR]

BackgroundHepatoblastoma is a rare pediatric liver tumor that has significantly increased in incidence over the last several decades. The International Agency for Research on Cancer (IARC) recently classified hepatoblastoma as a tobacco-related cancer. Parental alcohol use has shown no association. We examined associations between parental tobacco and alcohol use around the time of pregnancy and hepatoblastoma in a large case-control study.MethodsMaternal interviews were completed for 383 cases diagnosed in the United States during 2000-2008. Controls (n = 387) were identified through U.S. birth registries and frequency-matched to cases on birth weight, birth year, and region of residence. We used unconditional logistic regression to calculate ORs and 95% confidence intervals (CI) for associations between parental smoking and maternal drinking and offspring hepatoblastoma.ResultsWe found no association between hepatoblastoma and maternal smoking at any time (OR, 1.0; 95% CI, 0.7-1.4), within the year before pregnancy (OR, 1.1; 95% CI, 0.8-1.6), early in pregnancy (OR, 1.0; 95% CI, 0.7-1.6), or throughout pregnancy (OR, 0.9; 95% CI, 0.5-1.6). We observed marginally positive associations between hepatoblastoma and paternal smoking in the year before pregnancy (OR, 1.4; 95% CI, 1.0-2.0) and during pregnancy (OR, 1.4; 95% CI, 0.9-2.0). Maternal alcohol use was not associated with hepatoblastoma.ConclusionOur results do not provide evidence for an etiologic relationship between maternal smoking or drinking and hepatoblastoma, and only weak evidence for an association for paternal smoking in the year before pregnancy.ImpactOur study provides limited support for hepatoblastoma as a tobacco-related cancer; however, it remains wise to counsel prospective parents on the merits of smoking cessation.

Complex insertions and deletions (indels) are formed by simultaneously deleting and inserting DNA fragments of different sizes at a common genomic location. Here we present a systematic analysis of somatic complex indels in the coding sequences of samples from over 8,000 cancer cases using Pindel-C. We discovered 285 complex indels in cancer-associated genes (such as PIK3R1, TP53, ARID1A, GATA3 and KMT2D) in approximately 3.5% of cases analyzed; nearly all instances of complex indels were overlooked (81.1%) or misannotated (17.6%) in previous reports of 2,199 samples. In-frame complex indels are enriched in PIK3R1 and EGFR, whereas frameshifts are prevalent in VHL, GATA3, TP53, ARID1A, PTEN and ATRX. Furthermore, complex indels display strong tissue specificity (such as VHL in kidney cancer samples and GATA3 in breast cancer samples). Finally, structural analyses support findings of previously missed, but potentially druggable, mutations in the EGFR, MET and KIT oncogenes. This study indicates the critical importance of improving complex indel discovery and interpretation in medical research., Next-generation sequencing (NGS) technologies have fueled genetic research and provided unprecedented means of building an increasingly comprehensive catalog of single-nucleotide variants (SNVs), small indels and structural variants. Although cataloging these [...]