Developing a National-Scale Exposure Index for Combined Environmental Hazards and Social Stressors and Applications to the Environmental Influences on Child Health Outcomes (ECHO) Cohort.

Tools for assessing multiple exposures across several domains (e.g., physical, chemical, and social) are of growing importance in social and environmental epidemiology because of their value in uncovering disparities and their impact on health outcomes. Here we describe work done within the Environmental influences on Child Health Outcomes (ECHO)-wide Cohort Study to build a combined exposure index. Our index considered both environmental hazards and social stressors simultaneously with national coverage for a 10-year period. Our goal was to build this index and demonstrate its utility for assessing differences in exposure for pregnancies enrolled in the ECHO-wide Cohort Study. Our unitless combined exposure index, which collapses census-tract level data into a single relative measure of exposure ranging from 0-1 (where higher values indicate higher exposure to hazards), includes indicators for major air pollutants and air toxics, features of the built environment, traffic exposures, and social determinants of health (e.g., lower educational attainment) drawn from existing data sources. We observed temporal and geographic variations in index values, with exposures being highest among participants living in the West and Northeast regions. Pregnant people who identified as Black or Hispanic (of any race) were at higher risk of living in a "high" exposure census tract (defined as an index value above 0.5) relative to those who identified as White or non-Hispanic. Index values were also higher for pregnant people with lower educational attainment. Several recommendations follow from our work, including that environmental and social stressor datasets with higher spatial and temporal resolutions are needed to ensure index-based tools fully capture the total environmental context.

Associations between combined exposure to environmental hazards and social stressors at the neighborhood level and individual perinatal outcomes in the ECHO-wide cohort.

Limited studies examine how prenatal environmental and social exposures jointly impact perinatal health. Here we investigated relationships between a neighborhood-level combined exposure (CE) index assessed during pregnancy and perinatal outcomes, including birthweight, gestational age, and preterm birth. Across all participants, higher CE index scores were associated with small decreases in birthweight and gestational age. We also observed effect modification by race; infants born to Black pregnant people had a greater risk of preterm birth for higher CE values compared to White infants. Overall, our results suggest that neighborhood social and environmental exposures have a small but measurable joint effect on neonatal indicators of health.

Correction: Racial and geographic variation in effects of maternal education and neighborhood-level measures of socioeconomic status on gestational age at birth: Findings from the ECHO cohorts.

[This corrects the article DOI: 10.1371/journal.pone.0245064.].

Racial and geographic variation in effects of maternal education and neighborhood-level measures of socioeconomic status on gestational age at birth: Findings from the ECHO cohorts.

Preterm birth occurs at excessively high and disparate rates in the United States. In 2016, the National Institutes of Health (NIH) launched the Environmental influences on Child Health Outcomes (ECHO) program to investigate the influence of early life exposures on child health. Extant data from the ECHO cohorts provides the opportunity to examine racial and geographic variation in effects of individual- and neighborhood-level markers of socioeconomic status (SES) on gestational age at birth. The objective of this study was to examine the association between individual-level (maternal education) and neighborhood-level markers of SES and gestational age at birth, stratifying by maternal race/ethnicity, and whether any such associations are modified by US geographic region. Twenty-six ECHO cohorts representing 25,526 mother-infant pairs contributed to this disseminated meta-analysis that investigated the effect of maternal prenatal level of education (high school diploma, GED, or less; some college, associate's degree, vocational or technical training [reference category]; bachelor's degree, graduate school, or professional degree) and neighborhood-level markers of SES (census tract [CT] urbanicity, percentage of black population in CT, percentage of population below the federal poverty level in CT) on gestational age at birth (categorized as preterm, early term, full term [the reference category], late, and post term) according to maternal race/ethnicity and US region. Multinomial logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CIs). Cohort-specific results were meta-analyzed using a random effects model. For women overall, a bachelor's degree or above, compared with some college, was associated with a significantly decreased odds of preterm birth (aOR 0.72; 95% CI: 0.61-0.86), whereas a high school education or less was associated with an increased odds of early term birth (aOR 1.10, 95% CI: 1.00-1.21). When stratifying by maternal race/ethnicity, there were no significant associations between maternal education and gestational age at birth among women of racial/ethnic groups other than non-Hispanic white. Among non-Hispanic white women, a bachelor's degree or above was likewise associated with a significantly decreased odds of preterm birth (aOR 0.74 (95% CI: 0.58, 0.94) as well as a decreased odds of early term birth (aOR 0.84 (95% CI: 0.74, 0.95). The association between maternal education and gestational age at birth varied according to US region, with higher levels of maternal education associated with a significantly decreased odds of preterm birth in the Midwest and South but not in the Northeast and West. Non-Hispanic white women residing in rural compared to urban CTs had an increased odds of preterm birth; the ability to detect associations between neighborhood-level measures of SES and gestational age for other race/ethnic groups was limited due to small sample sizes within select strata. Interventions that promote higher educational attainment among women of reproductive age could contribute to a reduction in preterm birth, particularly in the US South and Midwest. Further individual-level analyses engaging a diverse set of cohorts are needed to disentangle the complex interrelationships among maternal education, neighborhood-level factors, exposures across the life course, and gestational age at birth outcomes by maternal race/ethnicity and US geography.

The role of vaccination coverage, individual behaviors, and the public health response in the control of measles epidemics: an agent-based simulation for California.

BACKGROUND: Measles cases continue to occur among susceptible individuals despite the elimination of endemic measles transmission in the United States. Clustering of disease susceptibility can threaten herd immunity and impact the likelihood of disease outbreaks in a highly vaccinated population. Previous studies have examined the role of contact tracing to control infectious diseases among clustered populations, but have not explicitly modeled the public health response using an agent-based model. METHODS: We developed an agent-based simulation model of measles transmission using the Framework for Reconstructing Epidemiological Dynamics (FRED) and the Synthetic Population Database maintained by RTI International. The simulation of measles transmission was based on interactions among individuals in different places: households, schools, daycares, workplaces, and neighborhoods. The model simulated different levels of immunity clustering, vaccination coverage, and contact investigations with delays caused by individuals' behaviors and/or the delay in a health department's response. We examined the effects of these characteristics on the probability of uncontrolled measles outbreaks and the outbreak size in 365 days after the introduction of one index case into a synthetic population. RESULTS: We found that large measles outbreaks can be prevented with contact investigations and moderate contact rates by having (1) a very high vaccination coverage (≥ 95%) with a moderate to low level of immunity clustering (≤ 0.5) for individuals aged less than or equal to 18 years, or (2) a moderate vaccination coverage (85% or 90%) with no immunity clustering for individuals (≤ 18 years of age), a short intervention delay, and a high probability that a contact can be traced. Without contact investigations, measles outbreaks may be prevented by the highest vaccination coverage with no immunity clustering for individuals (≤ 18 years of age) with moderate contact rates; but for the highest contact rates, even the highest coverage with no immunity clustering for individuals (≤ 18 years of age) cannot completely prevent measles outbreaks. CONCLUSIONS: The simulation results demonstrated the importance of vaccination coverage, clustering of immunity, and contact investigations in preventing uncontrolled measles outbreaks.

Quantifying the economic value and quality of life impact of earlier influenza vaccination.

BACKGROUND: Influenza vaccination is administered throughout the influenza disease season, even as late as March. Given such timing, what is the value of vaccinating the population earlier than currently being practiced? METHODS: We used real data on when individuals were vaccinated in Allegheny County, Pennsylvania, and the following 2 models to determine the value of vaccinating individuals earlier (by the end of September, October, and November): Framework for Reconstructing Epidemiological Dynamics (FRED), an agent-based model (ABM), and FluEcon, our influenza economic model that translates cases from the ABM to outcomes and costs [health care and lost productivity costs and quality-adjusted life-years (QALYs)]. We varied the reproductive number (R0) from 1.2 to 1.6. RESULTS: Applying the current timing of vaccinations averted 223,761 influenza cases, $16.3 million in direct health care costs, $50.0 million in productivity losses, and 804 in QALYs, compared with no vaccination (February peak, R0 1.2). When the population does not have preexisting immunity and the influenza season peaks in February (R0 1.2-1.6), moving individuals who currently received the vaccine after September to the end of September could avert an additional 9634-17,794 influenza cases, $0.6-$1.4 million in direct costs, $2.1-$4.0 million in productivity losses, and 35-64 QALYs. Moving the vaccination of just children to September (R0 1.2-1.6) averted 11,366-1660 influenza cases, $0.6-$0.03 million in direct costs, $2.3-$0.2 million in productivity losses, and 42-8 QALYs. Moving the season peak to December increased these benefits, whereas increasing preexisting immunity reduced these benefits. CONCLUSION: Even though many people are vaccinated well after September/October, they likely are still vaccinated early enough to provide substantial cost-savings.

Metformin inhibits mitochondrial complex I of cancer cells to reduce tumorigenesis.

Recent epidemiological and laboratory-based studies suggest that the anti-diabetic drug metformin prevents cancer progression. How metformin diminishes tumor growth is not fully understood. In this study, we report that in human cancer cells, metformin inhibits mitochondrial complex I (NADH dehydrogenase) activity and cellular respiration. Metformin inhibited cellular proliferation in the presence of glucose, but induced cell death upon glucose deprivation, indicating that cancer cells rely exclusively on glycolysis for survival in the presence of metformin. Metformin also reduced hypoxic activation of hypoxia-inducible factor 1 (HIF-1). All of these effects of metformin were reversed when the metformin-resistant Saccharomyces cerevisiae NADH dehydrogenase NDI1 was overexpressed. In vivo, the administration of metformin to mice inhibited the growth of control human cancer cells but not those expressing NDI1. Thus, we have demonstrated that metformin's inhibitory effects on cancer progression are cancer cell autonomous and depend on its ability to inhibit mitochondrial complex I.DOI: http://dx.doi.org/10.7554/eLife.02242.001.

FRED (a Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations.

BACKGROUND: Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels. RESULTS: FRED (a Framework for Reconstructing Epidemic Dynamics) is a freely available open-source agent-based modeling system based closely on models used in previously published studies of pandemic influenza. This version of FRED uses open-access census-based synthetic populations that capture the demographic and geographic heterogeneities of the population, including realistic household, school, and workplace social networks. FRED epidemic models are currently available for every state and county in the United States, and for selected international locations. CONCLUSIONS: State and county public health planners can use FRED to explore the effects of possible influenza epidemics in specific geographic regions of interest and to help evaluate the effect of interventions such as vaccination programs and school closure policies. FRED is available under a free open source license in order to contribute to the development of better modeling tools and to encourage open discussion of modeling tools being used to evaluate public health policies. We also welcome participation by other researchers in the further development of FRED.

Geospatial analytics to evaluate point-of-dispensing sites for mass immunizations in Allegheny County, Pennsylvania.

CONTEXT: Public health agencies use mass immunization locations to quickly administer vaccines to protect a population against an epidemic. The selection of such locations is frequently determined by available staffing levels and in some places, not all potential sites can be opened, often because of a lack of resources. Public health agencies need assistance in determining which n sites are the prime ones to open given available staff to minimize travel time and travel distance for those in the population who need to get to a site to receive treatment. OBJECTIVE: Employ geospatial analytical methods to identify the prime n locations from a predetermined set of potential locations (eg, schools) and determine which locations may not be able to achieve the throughput necessary to reach the herd immunity threshold based on varying R0 values. DESIGN: Spatial location-allocation algorithms were used to select the ideal n mass vaccination locations. SETTING: Allegheny County, Pennsylvania, served as the study area. MAIN OUTCOME MEASURES: The most favorable sites were selected and the number of individuals required to be vaccinated to achieve the herd immunity threshold for a given R0, ranging from 1.5 to 7, was determined. Locations that did not meet the Centers for Disease Control and Prevention throughput recommendation for smallpox were identified. RESULTS: At R0 = 1.5, all mass immunization locations met the required throughput to achieve the herd immunity threshold within 5 days. As R0s increased from 2 to 7, an increasing number of sites were inadequate to meet throughput requirements. CONCLUSIONS: Identifying the top n sites and categorizing those with throughput challenges allows health departments to adjust staffing, shift length, or the number of sites. This method has the potential to be expanded to select immunization locations under a number of additional scenarios.

Synthesized Population Databases: A Geospatial Database of US Poultry Farms.

The pervasive and potentially severe economic, social, and public health consequences of infectious disease in farmed animals require that plans be in place for a rapid response. Increasingly, agent-based models are being used to analyze the spread of animal-borne infectious disease outbreaks and derive policy alternatives to control future outbreaks. Although the locations, types, and sizes of animal farms are essential model inputs, no public domain nationwide geospatial database of actual farm locations and characteristics currently exists in the United States. This report describes a novel method to develop a synthetic dataset that replicates the spatial distribution of poultry farms, as well as the type and number of birds raised on them. It combines county-aggregated poultry farm counts, land use/land cover, transportation, business, and topographic data to generate locations in the conterminous United States where poultry farms are likely to be found. Simulation approaches used to evaluate the accuracy of this method when compared to that of a random placement alternative found this method to be superior. The results suggest the viability of adapting this method to simulate other livestock farms of interest to infectious disease researchers.

Reductive carboxylation supports growth in tumour cells with defective mitochondria.

Mitochondrial metabolism provides precursors to build macromolecules in growing cancer cells. In normally functioning tumour cell mitochondria, oxidative metabolism of glucose- and glutamine-derived carbon produces citrate and acetyl-coenzyme A for lipid synthesis, which is required for tumorigenesis. Yet some tumours harbour mutations in the citric acid cycle (CAC) or electron transport chain (ETC) that disable normal oxidative mitochondrial function, and it is unknown how cells from such tumours generate precursors for macromolecular synthesis. Here we show that tumour cells with defective mitochondria use glutamine-dependent reductive carboxylation rather than oxidative metabolism as the major pathway of citrate formation. This pathway uses mitochondrial and cytosolic isoforms of NADP(+)/NADPH-dependent isocitrate dehydrogenase, and subsequent metabolism of glutamine-derived citrate provides both the acetyl-coenzyme A for lipid synthesis and the four-carbon intermediates needed to produce the remaining CAC metabolites and related macromolecular precursors. This reductive, glutamine-dependent pathway is the dominant mode of metabolism in rapidly growing malignant cells containing mutations in complex I or complex III of the ETC, in patient-derived renal carcinoma cells with mutations in fumarate hydratase, and in cells with normal mitochondria subjected to acute pharmacological ETC inhibition. Our findings reveal the novel induction of a versatile glutamine-dependent pathway that reverses many of the reactions of the canonical CAC, supports tumour cell growth, and explains how cells generate pools of CAC intermediates in the face of impaired mitochondrial metabolism.

Including the Group Quarters Population in the US Synthesized Population Database.

In 2005, RTI International researchers developed methods to generate synthesized population data on US households for the US Synthesized Population Database. These data are used in agent-based modeling, which simulates large-scale social networks to test how changes in the behaviors of individuals affect the overall network. Group quarters are residences where individuals live in close proximity and interact frequently. Although the Synthesized Population Database represents the population living in households, data for the nation's group quarters residents are not easily quantified because of US Census Bureau reporting methods designed to protect individuals' privacy.Including group quarters population data can be an important factor in agent-based modeling because the number of residents and the frequency of their interactions are variables that directly affect modeling results. Particularly with infectious disease modeling, the increased frequency of agent interaction may increase the probability of infectious disease transmission between individuals and the probability of disease outbreaks.This report reviews our methods to synthesize data on group quarters residents to match US Census Bureau data. Our goal in developing the Group Quarters Population Database was to enable its use with RTI's US Synthesized Population Database in the Modeling of Infectious Diseases Agent Study.

The role of subway travel in an influenza epidemic: a New York City simulation.

The interactions of people using public transportation in large metropolitan areas may help spread an influenza epidemic. An agent-based model computer simulation of New York City's (NYC's) five boroughs was developed that incorporated subway ridership into a Susceptible-Exposed-Infected-Recovered disease model framework. The model contains a total of 7,847,465 virtual people. Each person resides in one of the five boroughs of NYC and has a set of socio-demographic characteristics and daily behaviors that include age, sex, employment status, income, occupation, and household location and membership. The model simulates the interactions of subway riders with their workplaces, schools, households, and community activities. It was calibrated using historical data from the 1957-1958 influenza pandemics and from NYC travel surveys. The surveys were necessary to enable inclusion of subway riders into the model. The model results estimate that if influenza did occur in NYC with the characteristics of the 1957-1958 pandemic, 4% of transmissions would occur on the subway. This suggests that interventions targeted at subway riders would be relatively ineffective in containing the epidemic. A number of hypothetical examples demonstrate this feature. This information could prove useful to public health officials planning responses to epidemics.

The benefits to all of ensuring equal and timely access to influenza vaccines in poor communities.

When influenza vaccines are in short supply, allocating vaccines equitably among different jurisdictions can be challenging. But justice is not the only reason to ensure that poorer counties have the same access to influenza vaccines as do wealthier ones. Using a detailed computer simulation model of the Washington, D.C., metropolitan region, we found that limiting or delaying vaccination of residents of poorer counties could raise the total number of influenza infections and the number of new infections per day at the peak of an epidemic throughout the region-even in the wealthier counties that had received more timely and abundant vaccine access. Among other underlying reasons, poorer counties tend to have high-density populations and more children and other higher-risk people per household, resulting in more interactions and both increased transmission of influenza and greater risk for worse influenza outcomes. Thus, policy makers across the country, in poor and wealthy areas alike, have an incentive to ensure that poorer residents have equal access to vaccines.

Would school closure for the 2009 H1N1 influenza epidemic have been worth the cost?: a computational simulation of Pennsylvania.

BACKGROUND: During the 2009 H1N1 influenza epidemic, policy makers debated over whether, when, and how long to close schools. While closing schools could have reduced influenza transmission thereby preventing cases, deaths, and health care costs, it may also have incurred substantial costs from increased childcare needs and lost productivity by teachers and other school employees. METHODS: A combination of agent-based and Monte Carlo economic simulation modeling was used to determine the cost-benefit of closing schools (vs. not closing schools) for different durations (range: 1 to 8 weeks) and symptomatic case incidence triggers (range: 1 to 30) for the state of Pennsylvania during the 2009 H1N1 epidemic. Different scenarios varied the basic reproductive rate (R(0)) from 1.2, 1.6, to 2.0 and used case-hospitalization and case-fatality rates from the 2009 epidemic. Additional analyses determined the cost per influenza case averted of implementing school closure. RESULTS: For all scenarios explored, closing schools resulted in substantially higher net costs than not closing schools. For R(0) = 1.2, 1.6, and 2.0 epidemics, closing schools for 8 weeks would have resulted in median net costs of $21.0 billion (95% Range: $8.0 - $45.3 billion). The median cost per influenza case averted would have been $14,185 ($5,423 - $30,565) for R(0) = 1.2, $25,253 ($9,501 - $53,461) for R(0) = 1.6, and $23,483 ($8,870 - $50,926) for R(0) = 2.0. CONCLUSIONS: Our study suggests that closing schools during the 2009 H1N1 epidemic could have resulted in substantial costs to society as the potential costs of lost productivity and childcare could have far outweighed the cost savings in preventing influenza cases.

Hypoxia. 2. Hypoxia regulates cellular metabolism.

Adaptation to lowering oxygen levels (hypoxia) requires coordinated downregulation of metabolic demand and supply to prevent a mismatch in ATP utilization and production that might culminate in a bioenergetic collapse. Hypoxia diminishes ATP utilization by downregulating protein translation and the activity of the Na-K-ATPase. Hypoxia diminishes ATP production in part by lowering the activity of the electron transport chain through activation of the transcription factor hypoxia-inducible factor-1. The decrease in electron transport limits the overproduction of reactove oxygen species during hypoxia and slows the rate of oxygen depletion to prevent anoxia. In this review, we discuss these mechanisms that diminish metabolic supply and demand for adaptation to hypoxia.

Vaccination deep into a pandemic wave potential mechanisms for a "third wave" and the impact of vaccination.

BACKGROUND: In December 2009, when the H1N1 influenza pandemic appeared to be subsiding, public health officials and unvaccinated individuals faced the question of whether continued H1N1 immunization was still worthwhile. PURPOSE: To delineate what combinations of possible mechanisms could generate a third pandemic wave and then explore whether vaccinating the population at different rates and times would mitigate the wave. METHODS: As part of ongoing work with the Office of the Assistant Secretary for Preparedness and Response at the USDHHS during the H1N1 influenza pandemic, the University of Pittsburgh Models of Infectious Disease Agent Study team employed an agent-based computer simulation model of the Washington DC metropolitan region to delineate what mechanisms could generate a "third pandemic wave" and explored whether vaccinating the population at different rates and times would mitigate the wave. This model included explicit representations of the region's individuals, school systems, workplaces/commutes, households, and communities. RESULTS: Three mechanisms were identified that could cause a third pandemic wave; substantially increased viral transmissibility from seasonal forcing (changing influenza transmission with changing environmental conditions, i.e., seasons) and progressive viral adaptation; an immune escape variant; and changes in social mixing from holiday school closures. Implementing vaccination for these mechanisms, even during the down-slope of the fall epidemic wave, significantly mitigated the third wave. Scenarios showed the gains from initiating vaccination earlier, increasing the speed of vaccination, and prioritizing population subgroups based on Advisory Committee on Immunization Practices recommendations. CONCLUSIONS: Additional waves in an epidemic can be mitigated by vaccination even when an epidemic appears to be waning.

Quantifying interhospital patient sharing as a mechanism for infectious disease spread.

BACKGROUND: Assessments of infectious disease spread in hospitals seldom account for interfacility patient sharing. This is particularly important for pathogens with prolonged incubation periods or carrier states. METHODS: We quantified patient sharing among all 32 hospitals in Orange County (OC), California, using hospital discharge data. Same-day transfers between hospitals were considered "direct" transfers, and events in which patients were shared between hospitals after an intervening stay at home or elsewhere were considered "indirect" patient-sharing events. We assessed the frequency of readmissions to another OC hospital within various time points from discharge and examined interhospital sharing of patients with Clostridium difficile infection. RESULTS: In 2005, OC hospitals had 319,918 admissions. Twenty-nine percent of patients were admitted at least twice, with a median interval between discharge and readmission of 53 days. Of the patients with 2 or more admissions, 75% were admitted to more than 1 hospital. Ninety-four percent of interhospital patient sharing occurred indirectly. When we used 10 shared patients as a measure of potential interhospital exposure, 6 (19%) of 32 hospitals "exposed" more than 50% of all OC hospitals within 6 months, and 17 (53%) exposed more than 50% within 12 months. Hospitals shared 1 or more patient with a median of 28 other hospitals. When we evaluated patients with C. difficile infection, 25% were readmitted within 12 weeks; 41% were readmitted to different hospitals, and less than 30% of these readmissions were direct transfers. CONCLUSIONS: In a large metropolitan county, interhospital patient sharing was a potential avenue for transmission of infectious agents. Indirect sharing with an intervening stay at home or elsewhere composed the bulk of potential exposures and occurred unbeknownst to hospitals.

A computer simulation of vaccine prioritization, allocation, and rationing during the 2009 H1N1 influenza pandemic.

In the fall 2009, the University of Pittsburgh Models of Infectious Disease Agent Study (MIDAS) team employed an agent-based computer simulation model (ABM) of the greater Washington, DC, metropolitan region to assist the Office of the Assistant Secretary of Public Preparedness and Response, Department of Health and Human Services, to address several key questions regarding vaccine allocation during the 2009 H1N1 influenza pandemic, including comparing a vaccinating children (i.e., highest transmitters)-first policy versus the Advisory Committee on Immunization Practices (ACIP)-recommended vaccinating at-risk individuals-first policy. Our study supported adherence to the ACIP (instead of a children-first policy) prioritization recommendations for the H1N1 influenza vaccine when vaccine is in limited supply and that within the ACIP groups, children should receive highest priority.

Mitochondrial metabolism and ROS generation are essential for Kras-mediated tumorigenicity.

Otto Warburg's theory on the origins of cancer postulates that tumor cells have defects in mitochondrial oxidative phosphorylation and therefore rely on high levels of aerobic glycolysis as the major source of ATP to fuel cellular proliferation (the Warburg effect). This is in contrast to normal cells, which primarily utilize oxidative phosphorylation for growth and survival. Here we report that the major function of glucose metabolism for Kras-induced anchorage-independent growth, a hallmark of transformed cells, is to support the pentose phosphate pathway. The major function of glycolytic ATP is to support growth under hypoxic conditions. Glutamine conversion into the tricarboxylic acid cycle intermediate alpha-ketoglutarate through glutaminase and alanine aminotransferase is essential for Kras-induced anchorage-independent growth. Mitochondrial metabolism allows for the generation of reactive oxygen species (ROS) which are required for Kras-induced anchorage-independent growth through regulation of the ERK MAPK signaling pathway. We show that the major source of ROS generation required for anchorage-independent growth is the Q(o) site of mitochondrial complex III. Furthermore, disruption of mitochondrial function by loss of the mitochondrial transcription factor A (TFAM) gene reduced tumorigenesis in an oncogenic Kras-driven mouse model of lung cancer. These results demonstrate that mitochondrial metabolism and mitochondrial ROS generation are essential for Kras-induced cell proliferation and tumorigenesis.