Functional screening of amplification outlier oncogenes in organoid models of early tumorigenesis

Genomics; Organoid; Squamous cancerGenómica funcional; Organoide; Cáncer escamosoGenòmica funcional; Organoide; Càncer escamósSomatic copy number gains are pervasive across cancer types, yet their roles in oncogenesis are insufficiently evaluated. This inadequacy is partly due to copy gains spanning large chromosomal regions, obscuring causal loci. Here, we employed organoid modeling to evaluate candidate oncogenic loci identified via integrative computational analysis of extreme copy gains overlapping with extreme expression dysregulation in The Cancer Genome Atlas. Subsets of “outlier” candidates were contextually screened as tissue-specific cDNA lentiviral libraries within cognate esophagus, oral cavity, colon, stomach, pancreas, and lung organoids bearing initial oncogenic mutations. Iterative analysis nominated the kinase DYRK2 at 12q15 as an amplified head and neck squamous carcinoma oncogene in p53−/− oral mucosal organoids. Similarly, FGF3, amplified at 11q13 in 41% of esophageal squamous carcinomas, promoted p53−/− esophageal organoid growth reversible by small molecule and soluble receptor antagonism of FGFRs. Our studies establish organoid-based contextual screening of candidate genomic drivers, enabling functional evaluation during early tumorigenesis.This work was supported by the NCI Cancer Target Discovery and Development (CTD∧2) Network (U01CA217851, C.J.K and C.C.; U01CA176058, W.C.H.). Support was also provided by NIH K08DE027730 and D.R. discretionary funds to A.A.S., AEI RYC2019- 026576-I, “LaCaixa” Foundation LCF/PR/PR17/51120011 to J.A.S., and NIH U54CA224081, NIH U01CA199241, Emerson Collective, Ludwig Cancer Research, and Stand Up To Cancer to C.J.K. This manuscript is dedicated to the memories of Dr. Daniela Gerhard and Dr. Kenneth Scott

Global, regional, and national burden of osteoarthritis, 1990–2020 and projections to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Background Osteoarthritis is the most common form of arthritis in adults, characterised by chronic pain and loss of mobility. Osteoarthritis most frequently occurs after age 40 years and prevalence increases steeply with age. WHO has designated 2021–30 the decade of healthy ageing, which highlights the need to address diseases such as osteoarthritis, which strongly affect functional ability and quality of life. Osteoarthritis can coexist with, and negatively effect, other chronic conditions. Here we estimate the burden of hand, hip, knee, and other sites of osteoarthritis across geographies, age, sex, and time, with forecasts of prevalence to 2050. Methods In this systematic analysis for the Global Burden of Disease Study, osteoarthritis prevalence in 204 countries and territories from 1990 to 2020 was estimated using data from population-based surveys from 26 countries for knee osteoarthritis, 23 countries for hip osteoarthritis, 42 countries for hand osteoarthritis, and US insurance claims for all of the osteoarthritis sites, including the other types of osteoarthritis category. The reference case definition was symptomatic, radiographically confirmed osteoarthritis. Studies using alternative definitions from the reference case definition (for example self-reported osteoarthritis) were adjusted to reference using regression models. Osteoarthritis severity distribution was obtained from a pooled meta-analysis of sources using the Western Ontario and McMaster Universities Arthritis Index. Final prevalence estimates were multiplied by disability weights to calculate years lived with disability (YLDs). Prevalence was forecast to 2050 using a mixed-effects model. Findings Globally, 595 million (95% uncertainty interval 535–656) people had osteoarthritis in 2020, equal to 7·6% (95% UI 6·8–8·4) of the global population, and an increase of 132·2% (130·3–134·1) in total cases since 1990. Compared with 2020, cases of osteoarthritis are projected to increase 74·9% (59·4–89·9) for knee, 48·6% (35·9–67·1) for hand, 78·6% (57·7–105·3) for hip, and 95·1% (68·1–135·0) for other types of osteoarthritis by 2050. The global age-standardised rate of YLDs for total osteoarthritis was 255·0 YLDs (119·7–557·2) per 100 000 in 2020, a 9·5% (8·6–10·1) increase from 1990 (233·0 YLDs per 100 000, 109·3–510·8). For adults aged 70 years and older, osteoarthritis was the seventh ranked cause of YLDs. Age-standardised prevalence in 2020 was more than 5·5% in all world regions, ranging from 5677·4 (5029·8–6318·1) per 100 000 in southeast Asia to 8632·7 (7852·0–9469·1) per 100 000 in high-income Asia Pacific. Knee was the most common site for osteoarthritis. High BMI contributed to 20·4% (95% UI –1·7 to 36·6) of osteoarthritis. Potentially modifiable risk factors for osteoarthritis such as recreational injury prevention and occupational hazards have not yet been explored in GBD modelling. Interpretation Age-standardised YLDs attributable to osteoarthritis are continuing to rise and will lead to substantial increases in case numbers because of population growth and ageing, and because there is no effective cure for osteoarthritis. The demand on health systems for care of patients with osteoarthritis, including joint replacements, which are highly effective for late stage osteoarthritis in hips and knees, will rise in all regions, but might be out of reach and lead to further health inequity for individuals and countries unable to afford them. Much more can and should be done to prevent people getting to that late stage

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Molecular Mechanics of Filamin's Rod Domain☆

Rearrangement of the actin cytoskeleton is integral to cell shape and function. Actin-binding proteins, e.g., filamin, can naturally contribute to the mechanics and function of the actin cytoskeleton. The molecular mechanical bases for filamin's function in actin cytoskeletal reorganization are examined here using molecular dynamics simulations. Simulations are performed by applying forces ranging from 25 pN to 125 pN for 2.5 ns to the rod domain of filamin. Applying small loads (∼25 pN) to filamin's rod domain supplies sufficient energy to alter the conformation of the N-terminal regions of the rod. These forces break local hydrogen bond coordination often enough to allow side chains to find new coordination partners, in turn leading to drastic changes in the conformation of filamin, for example, increasing the hydrophobic character of the N-terminal rod region and, alternatively, activating the C-terminal region to become increasingly stiff. These changes in conformation can lead to changes in the affinity of filamin for its binding partners. Therefore, filamin can function to transduce mechanical signals as well as preserve topology of the actin cytoskeleton throughout the rod domain

Real-Time Tracking of BODIPY-C12 Long-Chain Fatty Acid in Human Term Placenta Reveals Unique Lipid Dynamics in Cytotrophoblast Cells

Figures from PONE-D-16-00993R

BODIPY-C₁₂ fatty acid uptake in human term placental explants (30 min exposure).

<p>Dashed line represents the syncytiotrophoblast-cytotrophoblast interface. Co-localized BODIPY-C₁₂ and LipidTOX forms yellow LD, indicating esterified BODIPY-C_12. (A) BODIPY-C₁₂ (green) is localized to punctate structures (arrow heads) and diffuse areas in syncytiotrophoblasts (SCT) and cytotrophoblasts (CTB). Dark “holes” are unstained nuclei. (B) Pre-existing neutral lipids (LipidTOX, red) are found in punctate structures which are lipid droplets (LD) (arrow head); (C) LipidTOX co-localizes with BODIPY-C₁₂ (double arrowhead) predominantly in CTB, providing evidence that BODIPY-C₁₂ is esterified and localized within LD. Conversely, in SCT, LD (arrowhead) contains little BODIPY-C12 (corresponding region 2A open circle). (D-F) images of explants after fixation showing BODIPY-C₁₂ (green) and LipidTOX (red). (D) LD are present in both SCT and CTB, but BODIPY-C₁₂ seen in (A) has mostly washed out in processing but some remain in sequestered organelles. (E) Hoechst (blue) marks nuclei and HAI-1 (magenta) marks CTB, (F) BODIPY-C₁₂ (green) is found primarily in CTB (magenta) but not in SCT (see double arrow head). (G) BODIPY-C₁₂ containing lipid droplets (arrow heads) are found extensively in the CTB layer (e-cadherin, red) but are sparse in the SCT layer. (H) phloretin (a blocker of protein mediated transport), and (I) triacsin C (a blocker of long-chain fatty acyl-CoA synthetases) reduces the population of lipid droplet containing BODIPY-C₁₂ in CTB. These experiments suggest that transporters and acyl-CoA synthetases are required for production of LD. (J) Quantification of lipid droplets synthesized in explants illustrating the effects of chemical inhibitors and shows under control conditions BODIPY-C₁₂ LD accumulation is higher in 30 min in the CTB vs. SCT; (I): Data are mean ± SEM; n = 6 control, n = 5 phloretin, and n = 4 triacsin C. 2-way ANOVA, *** = p<0.001 vs CTB vehicle; VS, villous stroma; FET CAP, fetal capillary; Scale Bar: 5μm.</p

mRNA expression of key lipid processing genes before and after cytotrophoblast syncytialization.

<p>(A) In 72hr syncytia, the expression of <i>BHCG</i> is significantly higher compared to cytotrophoblast at 4hrs, indicating differentiation. (B-I) By 72 hours, there are significant changes in expression of several fatty acid uptake and processing genes. (B) <i>SLC27A2</i> (FATP2, the most highly expressed fatty acid transport protein in placenta). (C) <i>FABP4</i> (fatty acid binding protein). (D) <i>GPAT3</i> (glycerol-3-phosphate acyltransferase). (E) <i>ACSL5</i> (Acyl-CoA synthetase, long-chain). (F) <i>LPCAT3</i> (lysophosphatidylcholine acyl transferase). (G) <i>SLC27A4</i> (FATP4, fatty acid transport protein). (H) <i>CD36</i> (FAT, fatty acid translocase). (I) <i>SLC27A1</i> (FATP1, fatty acid transport protein). Data are mean ± SEM, n = 6 for all groups. Expression is relative to GAPDH, which is not significantly different between groups. Paired t-test * = p<0.05, ** = p<0.01, *** = p<0.001. (J) Immunofluorescence of FATP2 (green), nuclei are blue (Hoechst). (K) Merged immunofluorescence illustrating cytotrophoblast (E-cadherin, red), syncytiotrophoblast (BHCG, magenta) with FATP2/SLC27A2 (green). FATP2 can be found in both cytotrophoblast and syncytiotrophoblast, but appears to be more strongly expressed in cytotrophoblast which fits gene expression data in panel (B). Dashed line represents the syncytiotrophoblast-cytotrophoblast interface. Scale Bar: 5μm.</p