Geospatial Distribution of Age-Adjusted Incidence of the Three Major Types of Pediatric Cancers and Waterborne Agrichemicals in Nebraska.
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ABSTRACT:
SUBMITTER: Ouattara BS
PROVIDER: S-EPMC8859510 | biostudies-literature | 2022 Feb
REPOSITORIES: biostudies-literature
Publications
Geospatial Distribution of Age-Adjusted Incidence of the Three Major Types of Pediatric Cancers and Waterborne Agrichemicals in Nebraska.
Ouattara Balkissa S BS Puvvula Jagadeesh J Abadi Azar A Munde Siddhi S Kolok Alan S AS Bartelt-Hunt Shannon S Bell Jesse E JE Wichman Christopher S CS Rogan Eleanor E
GeoHealth 20220201 2
This study was conducted to examine, at the county level, the relationship between pediatric cancer incidence rate and atrazine and nitrate mean concentrations in surface and groundwater. A negative binomial regression analysis was performed to investigate the association between central nervous system (CNS) tumors, leukemia, lymphoma, and atrazine and nitrate mean concentrations in groundwater. The age-adjusted brain and other CNS cancer incidence was higher than the national average in 63% of ...[more]
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Project description:PurposeTo report the incidence, prevalent subtypes, and clinical characteristics of pediatric nystagmus diagnosed over a 30-year period.DesignRetrospective, population-based study.MethodsUsing the Rochester Epidemiology Project, we reviewed the medical records of all children (<19 years) diagnosed as residents in Olmsted County, Minnesota, with any form of nystagmus from January 1, 1976, through December 31, 2005.ResultsSeventy-one children were diagnosed during the 30-year period, yielding an annual incidence of 6.72 per 100,000 younger than 19 years (95% confidence interval [CI], 5.15-8.28) Infantile nystagmus, onset by 6 months, comprised 62 (87.3%) of the study patients, corresponding to a birth prevalence of 1 in 821. The median age at diagnosis for the cohort was 12.7 months (range, 0 days to 18.6 years) and 42 subjects (59.2%) were male. The main types of nystagmus, in declining order, were nystagmus associated with retinal/optic nerve disease in 23 (32.4%), idiopathic or congenital motor nystagmus in 22 (31.0%), manifest latent nystagmus or latent nystagmus in 17 (24.0%), and 2 (2.8%) each associated with Chiari malformation, medication use, tumor of the central nervous system, and no diagnosis. Developmental delay was diagnosed in 31 (43.6%), strabismus in 25 (35.2%), and amblyopia in 10 (14.1%). Eighty percent had 20/40 (or equivalent) or better vision at presentation in at least 1 eye.ConclusionsThis study provides population-based data on incidence and clinical characteristics of childhood nystagmus in North America. Idiopathic and nystagmus associated with retinal/optic nerve disease were the most common presentations, with most patients having good vision. Developmental delay, strabismus, and amblyopia were common in this cohort.
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Project description:Introduction: Though cancer research has traditionally centered on individual-level exposures, there is growing interest in the geography of both cancer and its risk factors. This geographic and epidemiological research has consistently shown that cancer outcomes and their known causal exposures exhibit geographic variation that coincide with area-level socioeconomic status and the composition of neighborhoods. A retrospective study was conducted to evaluate geospatial variation for female breast, cervical, and colorectal cancer incidence in Baltimore City. Materials and Methods: Using a Maryland Cancer Registry dataset of incident breast, cervical, and colorectal cancers (N = 4,966) among Baltimore City female residents diagnosed from 2000 to 2010, spatial and epidemiological analyses were conducted through choropleth maps, spatial cluster identification, and local Moran's I. Ordinary least squares regression models identified characteristics associated with the geospatial clusters. Results: Each cancer type exhibited geographic variation across Baltimore City with the neighborhoods showing high incidence differing by cancer type. Specifically, breast cancer had significant low incidence in downtown Baltimore while cervical cancer had high incidence. The neighborhood covariates associated with the geographic variation also differed by cancer type while local Moran's I identified discordant clusters. Discussion: Cancer incidence varied geographically by cancer type within a single city (county). Small area estimates are needed to detect local patterns of disease when developing health and preventative programs. Given the observed variability of community-level characteristics associated with each cancer type incidence, local information is essential for developing place-, social-, and outcome-specific interventions.
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Project description:We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.
| S-EPMC8143193 | biostudies-literature
Project description:BackgroundIt is widely believed that cancers develop upon acquiring a particular number of (epi) mutations in driver genes, but the law governing the kinetics of this process is not known. We have previously shown that the age distribution of incidence for the 20 most prevalent cancers of old age is best approximated by the Erlang probability distribution. The Erlang distribution describes the probability of several successive random events occurring by the given time according to the Poisson process, which allows an estimate for the number of critical driver events.MethodsHere we employ a computational grid search method to find global parameter optima for five probability distributions on the CDC WONDER dataset of the age distribution of childhood and young adulthood cancer incidence.ResultsWe show that the Erlang distribution is the only classical probability distribution we found that can adequately model the age distribution of incidence for all studied childhood and young adulthood cancers, in addition to cancers of old age.ConclusionsThis suggests that the Poisson process governs driver accumulation at any age and that the Erlang distribution can be used to determine the number of driver events for any cancer type. The Poisson process implies the fundamentally random timing of driver events and their constant average rate. As waiting times for the occurrence of the required number of driver events are counted in decades, and most cells do not live this long, it suggests that driver mutations accumulate silently in the longest-living dividing cells in the body-the stem cells.
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Project description:ImportanceThe population of infants, children, and adolescents cared for at pediatric long-term care facilities is increasing in complexity and size and thus consumes substantial health care resources. Infections are a significant cause of morbidity and mortality in this population, but few recent data describe their incidence and effects.ObjectivesTo describe the types of infections diagnosed in residents of pediatric long-term care facilities, calculate infection rates, and identify risk factors for respiratory tract infections (RTIs).Design, setting, and participantsThis prospective cohort study, which was part of a larger trial called Keep It Clean for Kids, was conducted from September 1, 2012, to December 31, 2015, at 3 pediatric long-term care facilities in New York. Residents of the facilities who were 21 years or younger and either residents or admitted during the study period (n = 717) were enrolled in the study. Medical records were reviewed to identify infections diagnosed by site clinicians.Main outcomes and measuresIncidence of infections, such as RTIs; skin and soft-tissue infections; chronic comorbid conditions, including neurologic and respiratory disorders; and device use, including gastrostomy tubes and tracheostomies, was determined. Risk factors for RTIs were assessed by generalized linear mixed method regression modeling.ResultsThe 717 residents had a median (interquartile range) age at enrollment of 2.6 (0.4-9.1) years; 358 (49.9%) were male. Four hundred twenty-eight residents (59.7%) had feeding tubes and 215 (30.0%) had tracheostomies. Most chronic comorbid conditions were musculoskeletal or ambulation (532 residents [74.2%]), neurologic (505 [70.4%]), respiratory (361 [50.3%]), and gastrointestinal (230 [32.1%]) disorders, and 460 residents (64.2%) had 4 or more chronic comorbid conditions. Site clinicians diagnosed 2052 infections during the 3-year study period. Respiratory tract infections were most common and were diagnosed in 1291 residents (62.9%). The overall infection rate was 5.3 infections per 1000 resident-days, and RTI rates were 3.3 infections per 1000 resident-days. Overall infection rates and rates of RTI, skin and soft-tissue infection, urinary tract infection, and bloodstream infection varied among the 3 sites. In the multivariable model, younger age (incidence rate ratio [IRR], 1.05; 95% CI, 1.03-1.06), increased number of chronic comorbid conditions (IRR, 1.12; 95% CI, 1.06-1.19), and the use of feeding tubes (IRR, 1.34; 95% CI, 1.03-1.64) and tracheostomies (IRR, 1.40; 95% CI, 1.17-1.69) were associated with RTIs.Conclusions and relevanceIn this study, RTIs were the most common infections diagnosed, but modifiable risk factors for RTIs were not identified. Future work should focus on optimizing infection prevention and control strategies to reduce infections, particularly RTIs, in the pediatric long-term care population.
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Project description:<p>Francesca Petralia,Nicole Tignor,Boris Reva, et al., (2020) <a href="https://www.cell.com/cell/fulltext/S0092-8674(20)31451-3" target="_blank">Cell 183, 1962-1985</a></p><p>We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.</p><p>The Children's Brain Tumor Network (CBTN) and the Pacific Pediatric Neuro-Oncology Consortia (PNOC) are collaborative research consortia focused on identifying therapies for children with brain tumors (<a href="https://cbttc.org" target="_blank">https://cbttc.org</a>). The consortia have contributed a <a href="https://kidsfirstdrc.org/support/studies-and-access/#SD_BHJXBDQK" target="_blank">Pediatric Brain Tumor Atlas (PBTA) dataset</a>, a cohort of 991 brain tumor subject clinical data, with associated whole genome sequencing and RNAseq hosted by the Gabriella Miller Kids First Data Resource (<a href="https://kidsfirstdrc.org/" target="_blank">kidsfirstdrc.org</a>) as part of the Gabriella Miller Kids First Pediatric Research Program (Kids First). Kids First is a Pan NIH Common Fund program dedicated to the development of large-scale data resources to help researchers uncover new insights into the biology of childhood cancer and structural birth defects (<a href="https://commonfund.nih.gov/KidsFirst" target="_blank">https://commonfund.nih.gov/KidsFirst</a>).</p><p>Mass Spectrometry raw data generation along with preliminary analyses were performed at the <a href="https://tcmp.hms.harvard.edu/" target="_blank">Thermo Fisher Scientific Center for Multiplexed Proteomics (TCMP)</a>, Harvard Medical School (HMS) under the direction of <a href="https://cellbio.med.harvard.edu/people/faculty/gygi" target="_blank">Prof. Steven Gygi</a>. Samples were prepared using the streamline (SL)-TMT protocol (<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5994137/" target="_blank">Navarrete-Perea et al., 2018</a>) and MS analysis was performed using the SPS-MS3 strategy (<a href="https://www.nature.com/articles/nmeth.1714" target="_blank">Ting et al., 2011</a>) developed in the <a href="https://gygi.med.harvard.edu/" target="_blank">Gygi lab</a>. Additional data analyses from the CPTAC Common Data Analysis Pipeline (<a href="https://www.ncbi.nlm.nih.gov/pubmed/26860878" target="_blank">Rudnick et al., 2016</a>) and from the University of Michigan Proteomics and Integrative Bioinformatics Laboratory (<a href="https://github.com/Nesvilab" target="_blank">https://github.com/Nesvilab</a>) are also provided. All raw and processed genomic data, as well as pathology reports, radiology reports, MRIs, histology slide images are accessible via the <a href="https://portal.kidsfirstdrc.org/dashboard" target="_blank">Kids First DRC (Data Resource Center)</a>.</p>
2021-02-04 | MSV000086810 | MassIVE
Project description:Gathering vast data sets of cancer genomes requires more efficient and autonomous procedures to classify cancer types and to discover a few essential genes to distinguish different cancers. Because protein expression is more stable than gene expression, we chose reverse phase protein array (RPPA) data, a powerful and robust antibody-based high-throughput approach for targeted proteomics, to perform our research. In this study, we proposed a computational framework to classify the patient samples into ten major cancer types based on the RPPA data using the SMO (Sequential minimal optimization) method. A careful feature selection procedure was employed to select 23 important proteins from the total of 187 proteins by mRMR (minimum Redundancy Maximum Relevance Feature Selection) and IFS (Incremental Feature Selection) on the training set. By using the 23 proteins, we successfully classified the ten cancer types with an MCC (Matthews Correlation Coefficient) of 0.904 on the training set, evaluated by 10-fold cross-validation, and an MCC of 0.936 on an independent test set. Further analysis of these 23 proteins was performed. Most of these proteins can present the hallmarks of cancer; Chk2, for example, plays an important role in the proliferation of cancer cells. Our analysis of these 23 proteins lends credence to the importance of these genes as indicators of cancer classification. We also believe our methods and findings may shed light on the discoveries of specific biomarkers of different types of cancers.
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Project description:BackgroundDay-of-surgery cancellation (DoSC) represents a substantial wastage of hospital resources and can cause significant inconvenience to patients and families. Cancellation is reported to impact between 2% and 20% of the 50 million procedures performed annually in American hospitals. Up to 85% of cancellations may be amenable to the modification of patients' and families' behaviors. However, the factors underlying DoSC and the barriers experienced by families are not well understood.ObjectiveThis study aims to conduct a geospatial analysis of patient-specific variables from electronic health records (EHRs) of Cincinnati Children's Hospital Medical Center (CCHMC) and of Texas Children's Hospital (TCH), as well as linked socioeconomic factors measured at the census tract level, to understand potential underlying contributors to disparities in DoSC rates across neighborhoods.MethodsThe study population included pediatric patients who underwent scheduled surgeries at CCHMC and TCH. A 5-year data set was extracted from the CCHMC EHR, and addresses were geocoded. An equivalent set of data >5.7 years was extracted from the TCH EHR. Case-based data related to patients' health care use were aggregated at the census tract level. Community-level variables were extracted from the American Community Survey as surrogates for patients' socioeconomic and minority status as well as markers of the surrounding context. Leveraging the selected variables, we built spatial models to understand the variation in DoSC rates across census tracts. The findings were compared to those of the nonspatial regression and deep learning models. Model performance was evaluated from the root mean squared error (RMSE) using nested 10-fold cross-validation. Feature importance was evaluated by computing the increment of the RMSE when a single variable was shuffled within the data set.ResultsData collection yielded sets of 463 census tracts at CCHMC (DoSC rates 1.2%-12.5%) and 1024 census tracts at TCH (DoSC rates 3%-12.2%). For CCHMC, an L2-normalized generalized linear regression model achieved the best performance in predicting all-cause DoSC rate (RMSE 1.299%, 95% CI 1.21%-1.387%); however, its improvement over others was marginal. For TCH, an L2-normalized generalized linear regression model also performed best (RMSE 1.305%, 95% CI 1.257%-1.352%). All-cause DoSC rate at CCHMC was predicted most strongly by previous no show. As for community-level data, the proportion of African American inhabitants per census tract was consistently an important predictor. In the Texas area, the proportion of overcrowded households was salient to DoSC rate.ConclusionsOur findings suggest that geospatial analysis offers potential for use in targeting interventions for census tracts at a higher risk of cancellation. Our study also demonstrates the importance of home location, socioeconomic disadvantage, and racial minority status on the DoSC of children's surgery. The success of future efforts to reduce cancellation may benefit from taking social, economic, and cultural issues into account.
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Project description:PurposeTo compare the incidence profile of four major cancers in Australia by place of birth.MethodsIn this retrospective population-based cohort study, the analysis included 548,851 residents diagnosed with primary colorectum, lung, female breast, or prostate cancer during 2005-2014. Incidence rate ratio (IRR) and 95% confidence intervals (CI) were calculated for migrant groups relative to Australian-born.ResultsCompared with Australian-born residents, most migrant groups had significantly lower incidence rates for cancers of the colorectum, breast and prostate. The lowest rates of colorectal cancer were among males born in Central America (IRR = 0.46, 95% CI 0.29-0.74) and females born in Central Asia (IRR = 0.38, 95% CI 0.23-0.64). Males born in North-East Asia had the lowest rates of prostate cancer (IRR = 0.40, 95% CI 0.38-0.43) and females born in Central Asia had the lowest rates of breast cancer (IRR = 0.55, 95% CI 0.43-0.70). For lung cancer, several migrant groups had higher rates than Australian-born residents, with the highest rates among those from Melanesia (males IRR = 1.39, 95% CI 1.10-1.76; females IRR = 1.40, 95% CI 1.10-1.78).ConclusionsThis study describes cancer patterns among Australian migrants, which are potentially helpful in understanding the etiology of these cancers and guiding the implementation of culturally sensitive and safe prevention measures. The lower incidence rates observed for most migrant groups may be maintained with continued emphasis on supporting communities to minimize modifiable risk factors such as smoking and alcohol consumption and participation in organized cancer screening programmes. Additionally, culturally sensitive tobacco control measures should be targeted to migrant communities with high lung cancer incidence rates.
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Project description:β-Site APP-cleaving enzyme 1 (BACE1) inhibition is considered one of the most promising therapeutic strategies for Alzheimer's disease, but current BACE1 inhibitors also block BACE2. As the localization and function of BACE2 in the brain remain unknown, it is difficult to predict whether relevant side effects can be caused by off-target inhibition of BACE2 and whether it is important to generate BACE1-specific inhibitors. Here, we show that BACE2 is expressed in discrete subsets of neurons and glia throughout the adult mouse brain. We uncover four new substrates processed by BACE2 in cultured glia: vascular cell adhesion molecule 1, delta and notch-like epidermal growth factor-related receptor, fibroblast growth factor receptor 1, and plexin domain containing 2. Although these substrates were not prominently cleaved by BACE2 in healthy adult mice, proinflammatory TNF induced a drastic increase in BACE2-mediated shedding of vascular cell adhesion molecule 1 in CSF. Thus, although under steady-state conditions the effect of BACE2 cross-inhibition by BACE1-directed inhibitors is rather subtle, it is important to consider that side effects might become apparent under physiopathological conditions that induce TNF expression.
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