Molecular analysis of the role of E2F proteins in the pRB pathway

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Biology, 1998.Includes bibliographical references.The E2F family of transcription factors appear to represent the primary cellular target of the tumor suppressive properties of the retinoblastoma protein. E2F therefore functions in a pathway which is a frequent target in human cancer, and the tumorigenicity of these mutations may be mediated at the transcriptional level by E2F. E2F is also regulated by cell cycle-dependent interactions with the pRB-related proteins p107 and p130. Unlike pRB, mutations in p107 or p130 are not associated with cancer. The different properties of the pRB family may result from the manner in which each protein regulates E2F. To determine how individual E2Fs contribute to the cell cycle regulatory properties of pRB, p107 and p1 30, we have examined the regulation of individual members of the E2F family. Our data suggest that the induction of E2F responsive genes is primarily due to the loss of nuclear repressor complexes at G1/S. This loss correlates with the disappearance of nuclear forms of E2F-4 protein, which represents the majority of pRBbound nuclear E2F during G1. These data suggests that E2F-4, the most abundant E2F in vivo, acts primarily as the DNA-binding component of a G1 transcriptional repressor complex. In contrast, we find that E2F-1, -2 and -3 are present at low levels in vivo and localize to the nucleus by virtue of a nuclear localization signal sequence in the N-terminal domain of these proteins. Their constitutive nuclear localization suggests that these E2F family members will contribute to the activation of responsive gene transcription during S-phase. Together, these data suggest that induction of E2F-responsive genes at G1/S is triggered both by the loss of an abundant transcriptional repressor, E2F-4*pRB, and by the presence of nuclear forms of E2F capable of transcriptional activation. These functional differences among E2Fs may underlie the oncogenic consequences specifically associated with pRB loss. Inactivation of pRB is predicted to both abrogate repression of E2F-responsive genes, and relieve inhibition of nuclear, activatory E2Fs. The combined effect of these forms of transcriptional deregulation of the E2F pathway may be sufficient to promote transformation in vivo.by Kenneth H. Moberg, Jr.Ph.D

Functional Interactions between the erupted/tsg101 Growth Suppressor Gene and the DaPKC and rbf1 Genes in Drosophila Imaginal Disc Tumors

BACKGROUND: The Drosophila gene erupted (ept) encodes the fly homolog of human Tumor Susceptibility Gene-101 (TSG101), which functions as part of the conserved ESCRT-1 complex to facilitate the movement of cargoes through the endolysosomal pathway. Loss of ept or other genes that encode components of the endocytic machinery (e.g. synatxin7/avalanche, rab5, and vps25) produces disorganized overgrowth of imaginal disc tissue. Excess cell division is postulated to be a primary cause of these 'neoplastic' phenotypes, but the autonomous effect of these mutations on cell cycle control has not been examined. PRINCIPAL FINDINGS: Here we show that disc cells lacking ept function display an altered cell cycle profile indicative of deregulated progression through the G1-to-S phase transition and express reduced levels of the tumor suppressor ortholog and G1/S inhibitor Rbf1. Genetic reductions of the Drosophila aPKC kinase (DaPKC), which has been shown to promote tumor growth in other fly tumor models, prevent both the ept neoplastic phenotype and the reduction in Rbf1 levels that otherwise occurs in clones of ept mutant cells; this effect is coincident with changes in localization of Notch and Crumbs, two proteins whose sorting is altered in ept mutant cells. The effect on Rbf1 can also be blocked by removal of the gamma-secretase component presenilin, suggesting that cleavage of a gamma-secretase target influences Rbf1 levels in ept mutant cells. Expression of exogenous rbf1 completely ablates ept mutant eye tissues but only mildly affects the development of discs composed of cells with wild type ept. CONCLUSIONS: Together, these data show that loss of ept alters nuclear cell cycle control in developing imaginal discs and identify the DaPKC, presenilin, and rbf1 genes as modifiers of molecular and cellular phenotypes that result from loss of ept

Genetic Interactions between the Drosophila Tumor Suppressor Gene ept and the stat92E Transcription Factor

Tumor Susceptibility Gene-101 (TSG101) promotes the endocytic degradation of transmembrane proteins and is implicated as a mutational target in cancer, yet the effect of TSG101 loss on cell proliferation in vertebrates is uncertain. By contrast, Drosophila epithelial tissues lacking the TSG101 ortholog erupted (ept) develop as enlarged undifferentiated tumors, indicating that the gene can have anti-growth properties in a simple metazoan. A full understanding of pathways deregulated by loss of Drosophila ept will aid in understanding potential links between mammalian TSG101 and growth control.We have taken a genetic approach to the identification of pathways required for excess growth of Drosophila eye-antennal imaginal discs lacking ept. We find that this phenotype is very sensitive to the genetic dose of stat92E, the transcriptional effector of the Jak-Stat signaling pathway, and that this pathway undergoes strong activation in ept mutant cells. Genetic evidence indicates that stat92E contributes to cell cycle deregulation and excess cell size phenotypes that are observed among ept mutant cells. In addition, autonomous Stat92E hyper-activation is associated with altered tissue architecture in ept tumors and an effect on expression of the apical polarity determinant crumbs.These findings identify ept as a cell-autonomous inhibitor of the Jak-Stat pathway and suggest that excess Jak-Stat signaling makes a significant contribution to proliferative and tissue architectural phenotypes that occur in ept mutant tissues

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

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

The Drosophila F-box protein Archipelago controls levels of the Trachealess transcription factor in the embryonic tracheal system

AbstractThe archipelago gene (ago) encodes the F-box specificity subunit of an SCF(skp-cullin-f box) ubiquitin ligase that inhibits cell proliferation in Drosophila melanogaster and suppresses tumorigenesis in mammals. ago limits mitotic activity by targeting cell cycle and cell growth proteins for ubiquitin-dependent degradation, but the diverse developmental roles of other F-box proteins suggests that it is likely to have additional protein targets. Here we show that ago is required for the post-mitotic shaping of the Drosophila embryonic tracheal system, and that it acts in this tissue by targeting the Trachealess (Trh) protein, a conserved bHLH-PAS transcription factor. ago restricts Trh levels in vivo and antagonizes transcription of the breathless FGF receptor, a known target of Trh in the tracheal system. At a molecular level, the Ago protein binds Trh and is required for proteasome-dependent elimination of Trh in response to expression of the Dysfusion protein. ago mutations that elevate Trh levels in vivo are defective in binding forms of Trh found in Dysfusion-positive cells. These data identify a novel function for the ago ubiquitin-ligase in tracheal morphogenesis via Trh and its target breathless, and suggest that ago has distinct functions in mitotic and post-mitotic cells that influence its role in development and disease

The <em>Archipelago</em> Ubiquitin Ligase Subunit Acts in Target Tissue to Restrict Tracheal Terminal Cell Branching and Hypoxic-Induced Gene Expression

<div><p>The <em>Drosophila melanogaster</em> gene <em>archipelago</em> (<em>ago</em>) encodes the F-box/WD-repeat protein substrate specificity factor for an SCF (Skp/Cullin/F-box)-type polyubiquitin ligase that inhibits tumor-like growth by targeting proteins for degradation by the proteasome. The Ago protein is expressed widely in the fly embryo and larva and promotes degradation of pro-proliferative proteins in mitotically active cells. However the requirement for Ago in post-mitotic developmental processes remains largely unexplored. Here we show that Ago is an antagonist of the physiologic response to low oxygen (hypoxia). Reducing Ago activity in larval muscle cells elicits enhanced branching of nearby tracheal terminal cells in normoxia. This tracheogenic phenotype shows a genetic dependence on <em>sima</em>, which encodes the HIF-1α subunit of the hypoxia-inducible transcription factor dHIF and its target the FGF ligand <em>branchless (bnl)</em>, and is enhanced by depletion of the <em>Drosophila</em> Von Hippel Lindau (<em>dVHL</em>) factor, which is a subunit of an oxygen-dependent ubiquitin ligase that degrades Sima/HIF-1α protein in metazoan cells. Genetic reduction of <em>ago</em> results in constitutive expression of some hypoxia-inducible genes in normoxia, increases the sensitivity of others to mild hypoxic stimulus, and enhances the ability of adult flies to recover from hypoxic stupor. As a molecular correlate to these genetic data, we find that Ago physically associates with Sima and restricts Sima levels <em>in vivo</em>. Collectively, these findings identify Ago as a required element of a circuit that suppresses the tracheogenic activity of larval muscle cells by antagonizing the Sima-mediated transcriptional response to hypoxia.</p> </div

<i>ago</i>^{Δ<i>3–7/1</i>} larvae display a wide range of tracheal terminal branch phenotypes.

<p>(A,B) Schematic (left) and representative photomicrograph showing branching of LH lateral terminal cells in control (A) and <i>ago</i>^{Δ<i>3–7/1</i>} (B) larvae. Branch termini are indicated with asterisks. (C) Quantification of branch number per LH (left) and LG (right) terminal cell in the indicated genotypes (*p<0.001 relative to control). (D) <i>ago</i>^{Δ<i>3–7/1</i>} larva displaying terminal branch tangling. (E,F) Ganglionic tracheal branches in control (E) and <i>ago</i>^{Δ<i>3–7/1</i>} (F) larvae. Ringlet-shaped branches and tangles occur in approximately 25% of <i>ago</i>^{Δ<i>3–7/1</i>} larvae.</p

<i>ago</i> acts non-tracheal cell autonomously to regulate terminal branching.

<p>(A,B) Schematic (left) and representative photomicrograph depiction of LH and LF lateral terminal cell branch termini on VLM12 in <i>5053A-Gal4:UAS-nlsGFP</i> control (A) and <i>5053A-Gal4:UAS-nlsGFP,UAS-agoΔF</i> (B) larvae. Terminal branches terminating on VLM12 are indicated by asterisks. Arrowheads mark terminal branches with termini on other body wall muscles. (C,D) Immunofluorescence with anti-Ago antisera shows that Ago is expressed in nuclei of VLM12 (C) as marked by expression of nlsGFP (D) in <i>5053A-Gal4:UAS-nlsGFP</i> larvae.</p

Effects of <i>ago</i> and <i>dMyc</i> on VLM12 size.^a

a<p>size calculated by pixel counts using Photoshop</p>b<p>p<1.0×10⁻⁴ relative to <i>5053A-Gal4:UAS-nlsGFP</i>.</p