Background: Maternal nutritional status is a key determinant of small for gestational age (SGA), but some knowledge gaps remain, particularly regarding the role of the energy balance entering pregnancy.Objective: We investigated how preconceptional and gestational weight trajectories  are associated with SGA risk in rural Gambia.Design: The sample comprised 670 women in a trial with serial weight data (7310 observations) that were available before and during pregnancy. Individual trajectories from 6 mo before conception to 30 wk of gestation were produced with the use of multilevel modeling. Summary traits were expressed as weight z scores  and were related to SGA risk with the use of Poisson regression with confounder adjustment; linear splines were used to account for nonlinearity.Results: Maternal weight at each time point had a consistent nonlinear relation with SGA risk. For example, the zwt−3 mo estimate was stronger in women with values ≤0.5  than in women with values >0.5 . The former group had the highest observed SGA prevalence. Focusing on weight change, only conditional zwt+7 mo was associated with SGA and only in women with values >−0.5 .Conclusions: Protection against delivering an SGA neonate offered by greater preconceptional or gestational weight may be most pronounced in more undernourished and vulnerable women. Independent of this possibility, greater second- and third-trimester weight gain beyond a threshold may be protective. This trial was registered at http://www.isrctn.com/ as ISRCTN49285450. TheLancet, Black et al. k et al.  estimateMaternal nutrition is a key determinant of fetal growth and, therefore, an important target for SGA prevention . Part ofDespite growing evidence that nutritional status in the preconceptional period can have an effect on SGA risk, there remain some limitations and knowledge gaps. Prepregnancy weight is normally assessed retrospectively and is a single static measurement that does not capture the extent to which a women may be losing or gaining weight  as she enters pregnancy . Similar1) iron and folic acid, 2) multiple micronutrients (MMNs), 3) protein energy (PE), and 4) PE plus MMNs and were supplemented from entry into the trial until delivery. The first women started to receive supplementation in January 2010, and the final infant was born in February 2014.The ENID (Early Nutrition and Immune Development) trial is a randomized trial to assess whether nutritional supplementation to pregnant women (from <20 wk of gestation to term) and their infants (from 6 to 12 mo of age) can enhance immune development . Within http://www.isrctn.com/ as ISRCTN49285450.The trial was approved by the joint Gambia Government/MRC Unit, The Gambia Ethics Committee (project SCC1126v2). Written informed consent was obtained from all women before enrollment in the trial. The trial observed Good Clinical Practice Standards and the current version of the Helsinki Declaration. The trial was registered at n = 875) . The first sample comprised participants with data that were necessary to model maternal weight trajectories (n = 670), and the second sample comprised participants with data that were necessary to relate trajectory traits to SGA risk (n = 519); defining characteristics were not different between included and excluded participants (data not shown). The third sample comprised a subsample of the second, which was selected on the basis of maternal preconception weight, and was used in a subset analysis  (n = 400).Three samples were selected from the total ENID cohort , gestational age was ascertained on the basis of fetal biometry with the use of a Siemens ACUSON Antares Ultrasound Imaging System .Maternal weight was measured at the monthly surveillance visits, and maternal weight and height were measured at the clinic visits, with the use of standard techniques and equipment [Tanita DH305 scales (Tanita Corp.) and Leicester height measure ]. The maternal date of birth and, thus, age were ascertained from the West Kiang Demographic Surveillance System . MaternaBirth weight, length, and head circumference were measured in the infant’s home by the study midwife and within 72 h of delivery. Weight was measured with the use of digital infant scales  with the infant in minimal clothing and to the nearest 10 g. Length was measured on a portable infant rollameter  to the nearest 0.1 cm. Head circumference was measured with the use of standard circumference tapes (Seca). All measures were made with the use of standard protocols, and the equipment was regularly validated.A 2-stage approach was applied, whereby we modeled trajectories before relating summary traits to SGA risk.The maternal weight data from the monthly surveillance visits and clinic visits at booking and 20 and 30 wk of gestation were pooled, the time scale was expressed as decimal years from conception, and the limited data that occurred before 6 mo preconception or after 9 mo postconception were dropped. This left 7310 observations with a mean of 10.9 observations/participant (range: 4–15 observations/participant) over a mean of 0.98 y (range: 0.44–1.19 y). All women had ≥1 preconception observation and 2 postconception observations.Individual trajectories were modeled in a multilevel regression framework  , 34. The1) conceived at the end of the dry/harvest season and 2) conceived at the end of the rainy/hungry season. The individual trajectories were summarized by estimated weight at 1) 3 mo preconception, 2) conception, 3) 3 mo postconception , and 4) 7 mo postconception . Weight at 6 mo preconception was not estimated because it was unlikely to provide any further information (in terms of SGA risk) over that obtained with the use of weight at 3 mo preconception. A correlation matrix of the 4 traits and additional traits capturing weight changes was produced. Values (of the same traits) of the sample-average trajectory, according to the month of conception, were also estimated.Fit was assessed via diagnostic plots of the level-1 residuals. To show the relation of seasonality with maternal weight, the sample-average trajectory from 6 mo preconception to 30 wk of gestation was plotted for the following 2 circumstances: z score . In addition, a model that incorporated conditional measures , which were computed as the standardized residuals from regressing weight at one time point on weight at all previous time points, was built to investigate the associations of weight changes between consecutive time points with SGA  with SGA risk that was captured by the first 4 sets of Fourier terms.Poisson regression models with robust error variance  were usewith SGA , 39. SGAwith SGA , and appz score outcomes according to the INTERGROWTH-21st standards  with SGA risk was clearly nonlinear  with an inflection point at 0.5 z scores . As such, in the Poisson regression models, zwt−3 mo was included with the use of 2 linear spline terms, the first of which explained the association of zwt−3 mo with SGA risk if zwt−3 mo was ≤0.5 and the second of which explained the association of zwt−3 mo with SGA risk if zwt−3 mo was >0.5. Supplemental Figure 3B shows an approximately linear association, and in this scenario, the maternal weight trait  would have been entered into the Poisson regression model as a normal, single term.Before building the Poisson and general linear regression models previously outlined, the shape of the association between each maternal weight trait and each outcome was explored with the use of restricted cubic splines. Any nonlinearity was subsequently approximated with the use of linear splines. For example, as shown in zwt−3 mo ≤0.5 in whom we showed a protective association of zwt−3 mo with SGA risk. This approach quantified mediation, whereas the previously described regression models answer different questions . Before building the path model, maternal weight z scores were recalculated with the use of only data on the subset. Paths between maternal weight variables were estimated as general linear regression coefficients, and paths to SGA were estimated as Poisson regression coefficients. Adjustment was made for the season of birth, sex, parity, maternal age at booking, maternal height at booking, and intervention (as in the Poisson regression models). Total, total indirect, and direct effects of each maternal weight trait on SGA were computed as RRs with robust error variances.To understand the extent to which preconceptional weight was associated with SGA independently of weight during pregnancy, a path model was applied to a subset of participants with All procedures were performed in Stata 14 software (StataCorp LP) with the exception that the path model was performed in MPlus 7.4 software . The Staz score was −0.82, indicating that our sample was lighter than the 25th percentile of the INTERGROWTH-21st standard, and 33% of the infants were SGA  further showed how seasonality was associated with a diverse range of maternal weight-change patterns.The relation of seasonality with the sample-average maternal weight trajectory is illustrated in Supplemental Table 3. Briefly, the mean weight at conception was 55.5 kg, and the mean weight gain between conception and 7 mo of gestation was 5.5 kg, which fell between the 10th and 25th percentiles of the INTERGROWTH-21st gestational weight-gain standard . Nonlinearity was also observed in the models that investigated the starting weight at 3 mo preconception and the subsequent weight change  reduced risk of SGA in women with values ≤0.5 but only 8%  reduced risk in women with values >0.5. The former group with values ≤0.5 had the highest observed SGA rates. Subsequently, a 1-unit increase in the conditional zwt+7 mo was not related to SGA risk in women with values ≤−0.5  but was associated with ∼42%  reduced risk in women with values >−0.5. This threshold of −0.5 approximated a change of 4.5 kg in maternal weight between 3 and 7 mo of gestation. Also, note that the preconceptional weight change that was captured by the conditional zwt0 mo was not associated with SGA risk .In unadjusted and adjusted Poisson regression models, a higher zwt−3 mo with SGA risk) is shown in zwt0 mo and zwt+3 mo had total indirect effects on SGA risk  operating through subsequent weight, but only the zwt+7 mo had a direct effect  . Note that associations of conditional zwt+3 mo and conditional zwt+7 mo with infant head-circumference-for-gestational-age z score were linear, whereas those with infant weight and length-for-gestational-age z-scores were nonlinear and favored women with higher weight gain (in line with the SGA findings). Also, zwt−3 mo was associated with infant weight-for-gestational-age z score  and head-circumference-for-gestational-age z score , but the conditional zwt0 mo was not strongly related to any outcome.Secondary analyses with continuous outcomes are presented in This study investigated how preconceptional and gestational weight trajectories  are associated with SGA risk in a population of rural African women and in a setting with high risk of SGA. The first key finding was that greater weight at 3 mo preconception  was related to lower SGA risk but only in the more-underweight women who had the highest observed SGA rates. In a path analysis that focused only on this subgroup, only weight at 7 mo of gestation had a direct effect on SGA risk. Although this result suggests that any association of preconceptional weight with SGA risk is likely to operate indirectly via weight during pregnancy, it does not suggest that intervening in pregnancy could offset the impact of poor nutritional status before conception. Instead, preconceptional weight is an important determinant of SGA risk because it is highly correlated with maternal weight throughout pregnancy. The second key finding was that greater weight gain between 3 and 7 mo of gestation was related to lower SGA risk but only in women who surpassed a threshold (∼4.5 kg) which was presumably the point at which the nutritional environment can support both the mother and fetus , 45. ThiInformed by previous research, we expected seasonally driven nutrition- and health-related factors in The Gambia to produce a diverse range of maternal weight trajectories –30. For Outside of The Gambia, observational studies have reported positive relations of prepregnancy weight with birth weight –24, but 1) a robust multilevel model was developed to produce individual-level maternal weight trajectories  with the use of data from the full sample; 2) the shapes of the associations of maternal weight traits  with SGA were properly captured with the use of linear splines within an appropriate regression framework  to obtain estimates as RRs; and 3) a path analysis was used (in a subsample) to correctly estimate the extent to which maternal weight at different time points influenced SGA risk directly or indirectly via maternal weight at subsequent time points. To our knowledge, no other study has been able to look at preconceptional weight and weight change in such detail. In terms of limitations, no weight measure at the end of pregnancy was available, and thus, we could not capture weight change to the end of the third trimester, and it was not prudent to test for an effect modification  because of our sample size and model complexity. In support of this decision, other studies have shown no evidence of an interaction between prepregnancy weight and gestational weight gain on birth weight , these 2 recommendations are not mutually exclusive. Finally, maternal obesity and excessive gestational weight gain are known to be related to large-for-gestational-age and various cardiometabolic risk factors (With acknowledgment of the limitations of observational data, our results may inform nutritional intervention programs to reduce SGA risk in LMIC settings. First, the results suggest a need to target the most undernourished and vulnerable women, perhaps <3 mo preconception because preconceptional and early gestational weight changes were not strongly related to SGA risk, and to maintain any improvement in nutritional status throughout pregnancy. In agreement, previous prenatal trials in The Gambia have been shown to improve gestational weight gain and birth weight more so in the nutritionally debilitating rainy/hungry season than in the dry/harvest season , 58. Sec factors –63, and In conclusion, our results suggest that, in resource-poor settings such as The Gambia, any association of greater preconceptional or gestational weight with lower SGA risk may be most pronounced in more undernourished and vulnerable women. Independent of this proposition, greater second- and third-trimester weight gains beyond a threshold may be protective.


The aim of this study was to survey refugees and asylum-seekers attending a Refugee Health Service in Melbourne, Australia to estimate the prevalence of psychiatric disorders based on screening measures and with post-traumatic stress disorder (PTSD) specifically highlighted. A secondary aim was to compare the prevalence findings with Australian-born matched comparators from the 2007 National Survey of Mental Health and Well-Being.We conducted a cross-sectional survey of 135 refugees and asylum-seeker participants using instruments including Kessler-10 (K10) and PTSD-8 to obtain estimates of the prevalence of mental disorders. We also performed a comparative analysis using matched sets of one participant and four Australian-born residents, comparing prevalence results with conditional Poisson regression estimated risk ratios (RR).The prevalence of mental illness as measured by K10 was 50.4%, while 22.9% and 31.3% of participants screened positive for PTSD symptoms in the previous month and lifetime, respectively. The matched analysis yielded a risk ratio of 3.16  for abnormal K10, 2.25  for PTSD-lifetime and 4.44  for PTSD-month.This information on high absolute and relative risk of mental illness substantiate the increased need for mental health screening and care in this and potentially other refugee clinics and should be considered in relation to service planning. While the results cannot be generalised outside this setting, the method may be more broadly applicable, enabling the rapid collection of key information to support service planning for new waves of refugees and asylum-seekers. Matching data with existing national surveys is a useful way to estimate differences between groups at no additional cost, especially when the target group is comparatively small within a population. The year 2014, globally, saw 59.5 million people forcibly displaced, the highest level on record. By the end of 2014, the Syrian Arab Republic became the largest source country of refugees, overtaking Afghanistan, which had held this position for over 30 years. The scale of forced global displacement of people is both unprecedented and accelerating, growing 40% over just 3 years from 42.4 million in 2011 [Placing large numbers of refugees and asylum-seekers in the community over a short period of time can create particular challenges for services in high settlement areas. Physical and psychological stresses that many refugees and asylum-seekers undergo in their countries of origin, during transition and on arrival in the host country, can increase risks of mental health problems , with vaFrom 2008 to 2013, Australia experienced another period where the numbers of people seeking asylum rapidly increased. Asylum-seekers arriving by boat added to already growing numbers of international students seeking protection . In 2012The work reported herein took place in a government-funded Refugee Health Service (RHS) located in a high settlement area for refugees and asylum seekers at the peak of this last major influx of new arrivals. Established in 2007 in an urban area of Victoria, Australia, the service had an initial focus on meeting the physical health needs of its clients. In the context of specific concerns raised in clinical work and overstretched local services, the service expanded its brief to address mental health needs. However, despite having an awareness that many refugees and asylum seeker groups may be vulnerable to mental health issues, systematic information about the nature of these problems locally was lacking . With liThis paper reports prevalence estimates for mental health problems amongst RHS clients, derived from screening instruments. Findings regarding refugee mental health can be biased both by the demographic profiles of refugee and asylum-seeker samples, which are untypical of the Australian population , and by Report estimates of overall prevalence of mental disorders including PTSD among RHS clients.Establish matched risk ratios by comparing RHS clientele prevalence findings with a matched Australian-born comparator group from the 2007 NSMHWB.Comment on the acceptability of the set of measures used in the survey for RHS clients as a pilot for use in screening for mental illness in this service and elsewhere .The aims of this paper are to:The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines .As previously published , there aThe setting is the catchment of Monash Health, the largest public health care provider in the state of Victoria, Australia, providing services to a core population of over 950,000 in the south-eastern suburbs of Melbourne and to a greater population of 1.344 million . The catThe site for recruitment was the RHS. The RHS comprises two sites: a weekly hospital-based outpatient clinic and a clinic based in a community health centre. Recruitment took place in the community health site during 2013 with interviews conducted between April and November. The study was approved by the local governing university and hospital ethics committees .Eligible participants could be aged 18–85 years  and were refugees or asylum-seekers who were attending the RHS community health site for any reason . Because measures were translated in advance to support consistency of interpreting in the research interviews, participants were required to be fluent in either English or at least one of the major languages from the regions of Afghanistan, Sri Lanka or Iran, including Dari/Dari-Hazaragi, Pashto, Persian/Farsi and Tamil. Written informed consent was obtained from all participants.Control participant data from the Australian-born sample in the NSMHWB Confidentialised Unit Record File (CURF)  involvedthe Kessler Psychological Distress Scale (K10)  is a 10-Diagnostic and Statistical Manual of Mental Disorders  [Participants read or had read to them a list of traumatic events and asked to answer yes or no as to whether they, or someone close to them such as a family member, had ever experienced or witnessed any of these events, as per criteria from the M-IV-TR) . The lisM-IV-TR) ), with tM-IV-TR) ; as therParticipants who indicated that they had been exposed to a traumatic event were then administered the PTSD-8 , an 8-itGeneral health service utilisation was recorded for matching purposes by refugee participant answers (Yes/No) to questions condensed from the 2007 NSMHWB assessment: 1) In the past 12 months, have you seen a general practitioner for your own physical or mental health? 2) In the past 12 months, have you been admitted overnight or longer in any hospital for a physical health problem? 3) In the past 12 months, have you seen any kind of specialist health care provider such as a specialist doctor, psychiatrist, psychologist, social worker or anyone else?totally unacceptable to 7 = perfectly acceptable. Measures were interview-administered by trained research assistants using interpreters as required [Relevant demographic and healthcare use data were also collected . At the required .The K10 was also used for the NSMHWB sample along with more detailed but parallel service utilisation questions. PTSD was identified using the World Mental Health Survey Initiative version of the Composite International Diagnostic Interview  .The K10 is the primary outcome measure, given that the same measure was used in both samples: refugees at the RHS and Australian-born health service users in the community sample . PTSD isThe sample size required was calculated to be 130 refugee participants. This is adequate to detect a difference in proportion affected by a mental health condition of 0.125, assuming the proportion affected in the Australian-born NSMHWB sample is 0.25, with power of 0.8, alpha of 0.05 and four matched Australian-born residents per refugee.To support administration in interview and work towards standardisation of translation by interpreters, all measures were translated into Dari, Pashto, Farsi and Tamil then back-translated into English. The translations were reviewed by cultural advisors appointed to the project then field tested. Cultural advisors were two medical doctors, both refugees themselves, with one being Afghan in nationality  and the other Sri Lankan (fluent in Tamil). The field testing process was conducted over 14 weeks by cultural advisors who trialled the measures with three members of each of the non-English speaking groups. Field testing indicated that the questionnaire items were understood by informants with the use of elaborations and additional explanatory statements. Participant Information and Consent Forms were translated into the nominated languages then reviewed by the cultural advisors see .Gender: male/femaleGeneral practice visit/consultation in last twelve months:o Australian-born group: yes/no.o Refugees and asylum-seekers: most of the clinic participants in this study had been referred here from a routine health triage assessment for newly arrived asylum-seekers that occurred in the last twelve months. On the assumption that the vast majority of refugee and asylum-seeker participants would have had at least two primary care level service consultations , RHS participants reporting ‘No’ in the survey to consulting a GP in the previous twelve months were matched to Australian-born comparators reporting 2 GP consultations in the previous twelve months. Refugees and asylum-seekers reporting ‘Yes’ to this question were matched to Australian-born comparators reporting 3 or more GP consultations in the previous twelve months.Specialist visit/consultation in last twelve months: yes/no.Hospitalisation in in last twelve months: yes/no.Each refugee or asylum-seeker participant was matched by random selection without replacement to four Australian-born comparators from the NSMHWB data set; varying the age criterion to plus/minus 5, 7 or 10 years was investigated to find the best matching strategy that could identify four comparators per participant. In addition to age, the matching criteria were:Demographic characteristics of the sample were compared to the Monash Health catchment population and to the asylum-seeker population nationally. As a check for possible selection bias, chi-square tests were used to examine whether there were demographic differences between the participants and potentially eligible clients who declined or were not interviewed before the close of recruitment. Cronbach’s alpha was calculated to assess the internal reliability of the K10 and PTSD-8. The occurrence of any missing data is reported and examined further. In this study, missing data was minimal and handled in the analyses using casewise deletion based on availability of complete data for individual variables.Based on the survey data collected from refugee and asylum-seeker participants, the overall frequency of K10 scores at or above the clinical cut-off was determined then broken down using the K10 clinical and NSMHWB cut-off scores. The overall frequency of PTSD-8 scores at or above the clinical cut-off indicating a likelihood of having PTSD was first calculated, then broken down using the K10 sub-groups.Matched comparative analysis , 33 withAll eligible clients, including all new referrals during the recruitment period, were approached by RHS bicultural staff either by phone or during a scheduled appointment and invited to speak to the researchers about participating in the study. In total, 267 clients were invited to take part; of these, 207 accepted the invitation, 55 declined and 5 did not meet eligibility criteria. Of the 207 clients who accepted the invitation, 7 did not meet eligibility criteria, 6 participants declined participation and 59 did not proceed to meet with the researchers before the planned closure of recruitment once power considerations were satisfied . The resDemographic characteristics are detailed in Table All 135 participants completed the K10. Four participants did not complete the PTSD-8 due to concerns by the interviewer or participant about participant distress levels, making complete PTSD case data for 131/135 (97.0%). Those participants who did not complete the PTSD-8 had K10 scores of 26–46 . Only one person who screened positive for current PTSD had a normal K10. Notwithstanding the very small sample size for some languages, the K10 and PTSD-8 demonstrated acceptable to excellent internal consistency across language groups , with the exception of PTSD-lifetime for Tamil which was 0.68.Interview acceptability ratings were available from 129 participants (including 3 of the 4 people with missing data for the PTSD-8). From the available data, 96% of participants rated the interview as acceptable or perfectly acceptable (median rating: 7); no one rated the interview as unacceptable.Based on K10 clinical cut-off scores, mental illness prevalence in the clinic population was 50.4% 68/135). Most participants 92.5%) reported having experienced a traumatic event with 22.9% (30/131) screening positive for PTSD-month and 31.3% (41/131) for PTSD-lifetime (PTSD-8). The combined prevalence rate of mental illness over the past month was 51.1%. Almost all those screening positive on PTSD-month had abnormal K10 scores (29/30) and 22/30 were in the severe range (30–50). In those with PTSD-lifetime, 33/41 had abnormal K10 and 26/41 were in the severe range. The breakdown of K10 scores by PTSD is shown in Table .5% repor5. Most pyes to hospitalisation but no GP or specialist consultation in previous 12 months had no matched comparators so was excluded from the matched analyses reducing the sample size to 134. This matched 134 refugees and asylum-seeker participants with 535 Australian-born residents, including four Australian-born residents for 133/135 participants and three for 1/135.Of all participants in the NSMHWB, 13.25% scored above clinical cut-off on the K10 (1171/8841). Contrasting this with the above finding of a 50.4% rate in the study group gives an unadjusted RR 3.83  but this comparison, unadjusted for sample demographics (Table p < 0.02) showing higher risks in refugees and asylum-seekers compared to Australian-born comparators.Table From Table The aims of this study were to survey clients attending the RHS in order to determine an overall estimate of the prevalence of mental health disorders then to establish matched risk ratios through comparison with a matched Australian-born comparator group drawn from the 2007 NSMHWB. All participants had arrived in Australia from source countries where human rights violations are common. Results showed that around half the surveyed RHS clients screened positive for a mental health condition over the previous month, while nearly a quarter screened positive for PTSD. With adjustment for demographics and, in part, for service use, this studied population had a RR for an elevated K10 of 3.16 compared to the Australian-born comparison group. Tentatively, given difference in instrumentation, we note that findings support the expectation of elevated risk ratios for PTSD in our refugee and asylum-seeker sample, with refugees and asylum-seekers over four times as likely to have PTSD-month and twice as likely to have PTSD-lifetime. Cases of PTSD as a proportion of K10 positive participants was considerably higher in the refugee and asylum-seeker group compared to the Australian sample.Use of brief screening questionnaires as here employed might result in misclassification that could inflate prevalence estimates, however it was preferred as it very likely assisted response rates while serving to pilot practical measures for regular use. Study enrollment closure when the intended sample size was achieved left some willing participants not interviewed however the comparison of demographics between non-respondents does not suggest any substantial selection bias.Considering adjustment by matching, while this has a strong pragmatic rationale, some limitations arise from differences in sampling used for acquiring the two groups used in this study: the refugee group were sampled from a service setting and the reference group were acquired from users of health services within a community sample survey. We had filtered the community sample to participants who were users of health services to an approximately comparable degree to the RHS clients (based on the same assessment measure) and over a similar 12 month time frame. We did this in order to help reduce bias that could be introduced by comparing a clinic sample with a community sample. While there are precedents for this methodology , 39, andIt might be expected that most individuals with current PTSD would also score in the abnormal range on the K10. However, in the Australian-born sample, 40.7% of the 27 people testing positive for PTSD-month had a normal K10. This seemingly high percentage might be the product of limitations in sensitivity of the K10 , as wellThe results of this study support the importance of specific planning for mental health service provision in areas of high refugee settlement, which may also be areas of socioeconomic disadvantage. Recent examination of national surveys has shown socio-economically disadvantaged areas to have significant effects on prevalence of elevated K10 scores . The RR In clinic populations attended by refugees and asylum-seekers, health care assessments should be completed with a high index of suspicion for the presence of co-morbid mental health disorders. It seems important, therefore, that adequate mental health training is provided to primary care providers when delivering care to this group, including training in use of tools such as the K10 and PTSD-8. Our experience suggests that the co-location of mental health services within a broader health setting, and particularly within a specialist refugee health clinic which is skilled at providing culturally-responsive services, is likely to go some way to lowering barriers to early mental health assessment and treatment . Such a Although it is possible to find some consistencies in prevalence rates across selected studies, such comparisons are of limited utility in this highly localised study due to differences in factors such as visa status, recruitment setting, time in host country, ethnicity and measures; large differences in rates of PTSD and depression reported in the literature for refugee populations have been noted previously , 5, 49. Building a New Life in Australia project: The Longitudinal Study of Humanitarian Migrants is an excellent example of representative sampling in the refugee population [The substantial heterogeneity in prevalence rates in refugee populations underscores the need for both representational community surveying methods as well as local methods when considering need for mental health care. Representational community sampling is important to support policy and service planning at state and national level . It requpulation : reportiMethods of assessing local need are also important, as this may be very different to what is found in large-scale surveys. Thus, while the findings reported here cannot be generalised to the community, even amongst identical cultural groups, they have been important for informing the response of the RHS to the mental health needs of attendees and have contributed to decisions to maintain or extend co-located mental health service provision for instance. The streamlined measures used in this study were administered in a relatively brief interview and acceptability ratings for the interview were high so, with proper validation, there is potential for such measures to be used on a regular basis as part of regular health surveillance to detect need for care and changing patterns over time. The authors can be contacted directly in regards to sharing the translated versions of the instruments with other interested services or researchers.Building a New Life in Australia project [Although the K10 was not validated in this study it did appear to be a useful screening measure and possibly more useful than the PTSD-8. Similar to Sulaiman-Hill and Thompson , who use project  offeringThe data-matching process, though imperfect, does represent an advance over simply presenting raw prevalence rates and was completed at no additional data-collection cost. Matching a relatively small target sample with over 500 multiply-matched comparators from the NSMHWB enabled some useful comparisons. Some variance in the data were accounted for by matching with age, gender and service use that is associated with different rates of mental illness-for example, people who visit the doctor are more likely to be ill so the results are more likely to accurately reflect sample differences in rates of mental illness. Thus, in relation to the K10, our matching strategy reduced the risk from 3.83 based on all NSMHWB data to 3.16 with matching. This means that we extracted a subset from the NSMHWB that have more mental illness than the overall NHMHWB sample and it excludes the possibility that the higher rate of mental illness in the RHS clinic sample is simply a product of demographics of this population and gives some, more modest, level of correction for service use patterns. Epidemiological studies commonly use matching to control for effects of confounders that are known to influence the outcome of interest , in our The need for rapid mental health service planning at the local level will continue to be a pressing need globally. Since this study was conducted, Afghanistan has been supplanted by Syria as the lead country of origin for refugees and high levels of mental illness have been observed amongst this population in neighbouring countries. The present large numbers of refugees fleeing war zones puts a demand on mental health services in the receiving countries. The information presented in this study on high absolute and relative risk of mental illness substantiates the increased need for mental health screening and care in this and potentially other refugee clinics and should be considered in relation to local service planning. Providing complex psychotherapy to refugee and asylum-seeker populations in an array of foreign languages is a challenging task requiring a considerable investment in terms of staff training and ongoing service provision. In order to justify such an investment, for example to government or other funding bodies, a first step is having a clear demonstration of need which surveys such as this one described in this paper can provide. This study methodology can be potentially adjusted to accommodate new waves of refugees and changes in dominant languages to enable a rapid method of collecting key information to support service planning. Matching is a useful way to estimate differences between groups, especially when the target group is comparatively small. While there is no intent to generalize the findings, this methodology may be helpful in determining the need for mental health care in other local services in order to assist service planning and to be able to give some indication of the extent of that need relative to a comparison group at no additional cost. Future researchers are encouraged to use the potential numerous comparator groups such as is available in large population surveys. For practical purposes, the K10 has potential as an initial screen for PTSD in this population, though this may not apply outside this setting where the PTSD rate is very high. There is a pressing need to properly validate such instruments for use in both local and large-scale screening of newly arrived refugees in order to both carry out early intervention when needed and to try to prevent worsening of mental health problems.


Akt activation in human cancers exerts chemoresistance, but pan-Akt inhibition elicits adverse consequences. We exploited the consequences of Akt-mediated mitochondrial and glucose metabolism to selectively eradicate and evade chemoresistance of prostate cancer displaying hyperactive Akt. PTEN-deficient prostate cancer cells that display hyperactivated Akt have high intracellular reactive oxygen species (ROS) levels, in part, because of Akt-dependent increase of oxidative phosphorylation. High intracellular ROS levels selectively sensitize cells displaying hyperactive Akt to ROS-induced cell death enabling a therapeutic strategy combining a ROS inducer and rapamycin in PTEN-deficient prostate tumors in mouse models. This strategy elicited tumor regression, and markedly increased survival even after the treatment was stopped. By contrast, exposure to antioxidant increased prostate tumor progression. To increase glucose metabolism, Akt activation phosphorylated HK2 and induced its expression. Indeed, HK2 deficiency in mouse models of Pten-deficient prostate cancer elicited a marked inhibition of tumor development and extended lifespan. While Akt1 is ubiquitously expressed, Akt2 is expressed at the highest level in insulin-responsive tissues, and Akt3 is expressed at the highest level in the brain. Different mouse phenotypes with individual Akt isoform germ line deletions can be explained by their relative expression in the organs that determine the phenotype , which generates the phosphatidylinositol-3,4,5-trisphophate  . Sesn3 iTaken together, these results show that PTEN-deficient prostate cancer cells display high OXPHO and ROS levels in an Akt-dependent manner.We previously reported that cells that display high Akt activity could be selectivity killed by increasing the intracellular level of ROS . This seSesn3 increased PEITC-induced cell death in DU145 cells, and overexpression of SESN3in PC3 cells decreased their sensitivity to PEITC . Mice that are deficient for PTEN in the prostate display progressive forms of prostatic cancer that histologically resemble human prostate cancer, ranging from mild prostatic intraepithelial neoplasia (PIN) at 10 weeks of age to large multinodular malignant adenocarcinoma with metastasis within 8 months  protein adducts , which is not expressed in most mammalian tissues, is markedly induced in cancer cells by different mechanisms . PreviouHK2 knockdown in PC3 and LNCaP cells markedly affected the proliferation of the cells, as measured by the cell numbers and BrdU incorporation, whereas the proliferation of the DU145 cells was not significantly affected . The knof/fPbsn-Cre4;Pten mice with f/fHk2 mice to generate f/f;Hk2f/fPbsn-Cre4;Pten mice. As shown in f/fPbsn-Cre4;Pten mice compared with that of the control mice. The deletion of HK2 in the f/f;Hk2f/fPbsn-Cre4;Pten mice markedly decreased the prostate weights  cells in the absence of doxycycline, and doxycycline induction was at 900 ng/ml for the inducible DU145, PC3, and LNCaP HK2 knockdown cell lines.The DU145, PC3, LNCaP, 293FT, and phoenix cells were purchased from ATCC . The DU145, PC3, and LNCaP cells were maintained in RPMI-1640/10% FBS/1% pen-strep media. The 293FT and phoenix-amphotropic cells were maintained in DMEM/10% FBS/1% pen-strep media. All cells were maintained in the exponential phase of growth at 37°C in a humidified 5% COAll cells were confirmed to be mycoplasma negative, using the Sigma LookOut Mycoplasma PCR Detection Kit .et al.  cells were plated in six-well plates in DMEM supplemented with 10% FBS. The next day, cells were transfected with 50 nM control-siRNA or sestrin3-siRNA using DharmaFECT reagent (Dharmacon) according to the manufacturer's instructions. Cells were split for ROS measurement or treatment with PEITC, followed by assessment of cell death 72 hr after transfection. The knockdown efficiency was analyzed by either immunoblotting or real-time PCR.SMARTpool ON-TARGET plus SESN3 and control non-targeting siRNA were purchased from Dharmacon . DU145 ]. For the tissue extracts, frozen tissues collected by liquid nitrogen snap freezing were thawed and homogenized in the same buffer. The extracts were run on 6% to 12% SDS-PAGE gels, transferred to PVDF membranes, and probed with the following antibodies: anti-phospho-Akt Ser473, anti-panAkt, anti-cleaved caspase-3, anti-HK1, anti-HK2 anti-PTEN , anti-HA , anti-4HNE , anti-catalase, anti-CuZnSOD and anti-MnSOD , anti-SESN3 , and anti-ß-actin (Sigma). Immunoblots were quantified using the NIH ImageJ software program by densitometric signal and normalized as described in figure legends.For western blot analysis, 2 × 103/well) were plated in a 48‐well plates. Upon treatment to induce cell death, NucView-conjugated Caspase‐three substrate (Nexcelom ViaStain Live Caspase 3/7 Detection) was also added at a final concentration of 4 μM. During apoptosis, caspase 3/7 proteins cleave its substrate complex and thereby release the high-affinity DNA dye (NucView), which translocates to the nucleus and binds to the DNA, producing a bright green fluorescent signal. Thirty minutes before the end of the incubation, Hoechst 33342 was added to each well (4 μg/ml) and fluorescence was measured with the Celigo Image Cytometer . The percentage of Green (apoptotic) to Total (Blue-Hoechst) is calculated.Cells were treated as described in the figure legends, and apoptosis and cell death was quantified by DAPI staining as previously described  or by PIIntracellular ROS generation was assessed using 2',7’-dichlorofluorescein diacetate or dihydroethidium (Thermo Fisher scientific) as described by Nogueira et al. .+) were measured with previously described enzymatic cycling methods, as described Jeon et al. . For the Clark-type oxygen electrode method, 2 × 104 cells/well, trypsinized and resuspended in JC-1 solution (10 μg/ml) in RPMI, and incubated in CO2 incubator at 37°C for 30 min. Before measurements, the cells were centrifuged and then washed twice with the PBS and immediately analyzed by flow cytometry. Each experiment included a positive control; 10 μM of the FCCP was added to the cells as an uncoupler. Results are shown as a ratio of fluorescence measured with red to green filters (aggregates to monomer fluorescence). Each sample was run three times in triplicate.MMP was determined with JC-1 dye (Thermofisher) using a FACScan flow cytometer. JC-1 dye accumulates in the mitochondrial membrane in a potential-dependent manner. The high potential of the inner mitochondrial membrane facilitates formation of the dye aggregates with both excitation and emission shifted towards red light when compared with that for JC-1 monomers (green light). Cells were seeded into a 12-well black plate at a density of 10 × 104 cells per well. The cells were incubated for 24 hr in a humidified 37°C incubator with 5% CO2 in RMPI-1640 medium (10% FBS). One hour prior to performing an assay, the growth medium in the wells of an XF cell plate was replaced by XF assay medium , and the plate was transferred to a 37°C CO2-free incubator. For OCR measurement, successive injection of compounds measured ATP-coupled respiration (1 µM oligomycin), maximal respiration (0.5 µM FCCP), and non-mitochondrial respiration (0.5 µM rotenone/antimycin A). Basal respiration, proton leakage, and spare respiratory capacity were then calculated using these parameters. For ECAR measurement, successive injection of compounds measured glycolysis (10 mM glucose), glycolytic capacity (1 µM oligomycin), and non-glycolytic acidification (50 mM 2-deoxyglucose). The glycolytic reserve was then calculated using these parameters. In a typical experiment, three baseline measurements were taken prior to the addition of any compound, and three response measurements were taken after the addition of each compound. The OCR and ECAR are reported as being normalized against cell counts (pmoles/min/106 cells for OCR and mpH/min/106 cells for ECAR). The baseline OCR or ECAR refers to the starting rates prior to the addition of a compound. Each experiment was performed at least three times in triplicate.OCR and ECAR measurements were performed using the XF96e Extracellular Flux analyzer . Cells were plated on XF96 cell culture plates (Agilent Technologies) at 3 × 10Whole-cell HK activity was measured as described previously .4) were plated on 6 cm dishes in triplicate and counted every day for 6 days. Media was changed on the third day to ensure continuous natural growth. For BrdU incorporation, on the third day of proliferation, a subset of cells was pulsed with 3 μg/ml BrdU for 2 hr and fixed with 70% ethanol. In addition, immunostaining was performed with primary anti-BrdU monoclonal antibodies (Dako - Agilent) followed by a FITC-conjugated secondary antibody.Cells (4 × 103) were re-suspended in a single cell suspension in 10% FBS in RPMI medium containing 0.35% agarose and plated onto a layer of 0.7% low-melt agarose-containing medium in a six-well dish. Cells were grown for 3 weeks in media, and doxycycline was replaced every 3 days. Soft-agar colonies from the entire well were counted after 3 weeks. The experiments were performed three times in triplicate.In brief, cells , and first strand cDNA was produced with SuperScript III reverse transcriptase (Invitrogen) following the standard protocol. Quantitative PCR was performed with BIO-RAD iQ-SYBR green super-mix and the related system. Samples were assayed in triplicate, and data were normalized to the actin mRNA levels. The primer sequences for hSesn3 were 5’- ATG CTT TGG CAA GCT TTG TT −3’ and 5’- GCA AGA TCA CAA ACG CAG AA −3’, and the primer sequences for hActin were 5’-CCA TCA TGA AGT GTG ACG TGG −3’ and 5’-GTC CGC CTA GAA GCA TTT GCG −3’.f/fPbsn-Cre4;Pten mice have been described previously. f/+Pbsn-Cre4;Pten mice were intercrossed to generate the following genotypes for experiments: f/f, Pbsn-Cre4, Ptenf/fPtenand f/f; Hk2f/f/Pbsn-Cre4;Pten were described in  were injected subcutaneously into both the left and right flanks of each mouse. The mice were equally randomized into different treatment groups (see the figure legend). When the tumors reached a size of 10 to 15 mm3, the animals were treated with the indicated drugs ) from Monday through Friday by intraperitoneal injection. All the drugs were dissolved in solvent containing ethanol, cremophor-EL (Sigma), and PBS (1:1:8 vol ratio). Control mice were injected with an equal volume of solvent as a control. The body weights and tumor sizes of the mice were measured and recorded twice per week for the duration of the experiment. When the tumor sizes reached the end-point criterion , the mice were euthanized, and xenograft tumors were collected. Tumor tissues from representative mice from each group were sectioned, embedded in paraffin, and stained.Male athymic mice (6 to 8 weeks old) were purchased from Charles River Laboratories and maintained in accordance with the NIH Guide for the Care and Use of Laboratory Animals. Cells  expressing doxycycline-inducible shRNA constructs were subcutaneously injected into male nude mice. Once tumors were palpable, the mice were randomly assigned into different groups and fed regular chow (control) or doxycycline chow ), and they received an IP injection of the vehicle solvent etoposide (10 mg/kg) as described above.For the doxycycline-inducible experiments, PC3 Tet-ON HK2sh cells  or histopathology .Control and f/fPbsn-Cre4;Pten mice received a daily (5 days a week) intraperitoneal injection of N-acetyl-cysteine  or PBS for 12 consecutive weeks. At the end of the study, tissues will be collected for immunoblot analysis (snap-freezing in liquid nitrogen) or histopathology . For the survival curve experiments, the mice were monitored until their death or until humane end-point criteria was attained .For the NAC study, a subset of 4-month-old control and Xenograft tumors (nude mice) and prostate tissues were collected at the indicated time points, rinsed in PBS, and quickly fixed in 10% formalin overnight before being subsequently preserved with 70% ethanol. The fixed tissues were then processed and embedded in paraffin. The paraffin-embedded tissues were processed, and 5 μM slides were prepared for hematoxylin and eosin (H and E) staining or immunostaining. For antigen retrieval, tissue sections were incubated at 95°C in 10 mM citric acid (pH 6.0) for 30 min. Detection was achieved using ABC-DAB kits , an anti-BrdU mouse monoclonal antibody (Dako# M0744), and an anti-cleaved caspase-3 (Asp175) antibody . For quantification, cells were counted from four section fields at a 40x magnification using four mice per condition.For the BrdU labeling experiments, mice were injected intraperitoneally with BrdU (Sigma) in PBS (0.5 mg BrdU/10 g of body weight) 2 hr prior to sacrifice and tissue collection. Tumors were collected and processed as described above. After dewaxing and rehydration, paraffin sections were digested by pepsin followed by EcoRI and Exonuclease III. The slides were then incubated with anti-BrdU and processed for immunohistochemistry as described above.Statistical analysis was performed using unpaired Student’s t-tests. Survival curves were analyzed by log-rank tests, and the data are expressed as the mean ± SEM as indicated in the figure legends. Unless otherwise indicated, all the experiments were performed at least three times in triplicate. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by four peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your work entitled "Selective and dramatic eradication of cancer by exploiting the metabolic consequences of Akt activation" for consideration by eLife. The editors and referees judge that the manuscript will require additional experiments beyond those that you propose to provide in response to the reviewer comments. There was a sense among the reviewers that in your response you were largely proposing to address the concerns by text edits rather than by providing new data, and that this would not adequately address the issues or extend the work beyond what has previously been published. We should also note that eLife tends to reject papers if it would take more than 2 months to address the reviewer comments, and throughout this process there has been uncertainty whether you would be able to provide enough data in such a time period to satisfy most of the reviewers. We are returning your submission to you now in case you wish to submit elsewhere for speedy publication. If you are able to address the reviewer comments points in a way that includes new experiments and wish to resubmit your work to eLife, we would still be willing to consider a revised paper. Please note that it would be treated as a new submission with no guarantees of acceptance.Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in Reviewer #1:Nogueira et al. extend findings from their 2008 publication to further support the model that activation of Akt downstream of Pten loss in prostate cancer causes high ROS. The current paper suggests some therapeutic strategies to take advantage of this, and provide some impressive data for PEITC and rapamycin causing tumor regression in a xenograft model of prostate cancer. They also present some data from a Pten-null mouse model in support of this combination, and include two figures at the end to build on their past work around HK2, and suggest HK2 is another target in prostate cancer.The most novel and exciting data surround PEITC and rapamycin in the prostate xenograft models. Their remain some questions around how to interpret the data in the Pten-null model, and the final two figures on HK2 feel like a bit of a departure from the rest of the paper. I wonder if those data might be better served in a separate publication.Specific comments1) The authors use PEITC, which can deplete intracellular glutathione. This may have consequences beyond increasing ROS, although some data to confirm that it acts through glutathione depletion in their system would add to the paper. Alternatively, they might try an alternative glutathione reducing agent such as BSO, which has been in clinical trials in patients.1/2 hairpins.2) A cDNA rescue experiment to control fro shRNA off target effects should be included for key data using the Akt3) Some experiments are shown with Akt knockdown and Akt expression to confirm dependence on some phenotypes, but extending the Akt gain of function studies in the Pten wild-type cells to confirm key claims would also enhance the paper. Most importantly, showing that Akt expression in DU145 could sensitize the cells to PEITC and rapamycin would go along way toward supporting the model that active Akt is the determinant of this phenotype.4) I am somewhat confused by the data in the Pten-null model. First, they start treating mice at 2 months and 4 months. The timing of PIN versus cancer in their hands should be confirmed, but based on the literature only invasive cancer is not expected at either time point. Thus, this is really more of a cancer prevention study. Second, how was the schedule and timing of treatment determined? They treat the animals for a very long time, and while differences are noted, they clearly have not prevented the cancer even with very long treatment since some proliferation is still observed even in the treated prostates at this late time point. This is at odds with the regressions observed in the xenografts, and perhaps indicates the combination is less effective in early stage lesions. Could treatment be initiated in older mice with invasive cancers to better match the xenograft experiment?5) More detail is needed on the age of the mice and length of treatment when they show NAC increases prostate cancer progression. Perhaps I missed it, but it is unclear whether this timing paralleled the treatments as implied in the text.6) The argument that finding isoform selective inhibitors for Akt would be challenging is noted. One might expect a similar challenge to generate isoform selective inhibitors of HK2, yet the conclusion of the second story in the paper is that selective targeting of HK2 might be an alternative strategy to treat Akt active prostate cancer. While the data showing HK2 is required are fine, they are less impressive than the PEITC/Rapamycin data and feel very much like a separate story. This might be better served as a short communication elsewhere.Reviewer #2:In the present manuscript Hay and colleagues propose to exploit the vulnerability generated by Akt-mediated ROS production as a therapeutic target in prostate cancer.This mechanism of sensitization to oxidative stress is not new in cancer and the authors themselves contributed to elucidate it in their previous work . However, the link proposed in the present manuscript between Akt-induced ROS production and PTEN loss, an acknowledged driver in prostate cancer, is intriguing and potentially relevant for the clinics.Unfortunately the manuscript lacks coherence, as it proposes two distinct parts (ROS inducer + rapamycin treatment and HK2 deficiency) that are barely integrated in the text.Specific Comments:1) The method used in Figure 2A-D for detection of apoptosis does not allow for the discrimination between apoptosis and other means of cell death. The authors correctly make use of caspase-3 cleavage as an apoptotic marker in vivo throughout the manuscript, but in order to make the same claim in their in vitro model they should resort to more specific methods for apoptosis detection (e.g. Annexin V staining). A brief overview of the method should be given instead along with the reference.2) Experiments shown in Figures S1F-G, 1F and 2C are conducted only in PC3 cells. As they are key to prove the authors' point, they should be reproduced also in LnCAP cells.3) When rapamycin treatment is introduced, the rationale for the use of this drug is not explained and is only very briefly mentioned only in the Discussion section. This might make the comprehension of the given results difficult for non-expert readers. The mechanism by which rapamycin induces an increase in ROS production by removing mTOR inhibition over Akt should be more clearly stated up front.4) In DU145 cells, rapamycin does not substantially increase ROS production, whereas it does in cells with PTEN loss. This would suggest that PTEN control over Akt activity is epistatic over mTOR control. To better clarify this relationship, and to which extent mTOR inhibition is actually able to activate Akt in the different conditions, the authors should check the basal mTOR activity in the three cell lines, as well Akt activation upon rapamycin treatment both in vitro and in their mouse model. To further prove the proposed mechanism, they could also try to sensitize DU145 cells to rapamycin by knocking down PTEN.5) The authors state "Interestingly, basal oxygen consumption in DU145 cells reached the maximum capacity of the respiratory chain, while PC3 and LNCaP cells have a larger spare capacity." However, the graphs show that for all cell lines basal respiration matches spare respiration.6) As already mentioned, the findings on HK2 role in the induction of Akt-mediated ROS production, although interesting, seem more preliminary and do not integrate well with the previous part of the manuscript.Reviewer #3:This paper shows that hyper activation of AKT causes a ROS vulnerability in prostate cancer cells. Impressively, they demonstrate that rapamycin plus a ROS inducer markedly reduce tumor growth in PTEN-deficient prostate tumors in mouse models. Additionally the authors demonstrate that loss of PTEN in prostate cancer cells induces hexokinase 2 (HK2) expression to increase glucose metabolism. Furthermore, HK2 deficiency in mouse models of Pten-deficient prostate cancer elicited a marked inhibition of tumor development.eLife.The paper is interesting and suitable for I have a few comments that should be addressed.Does the hyper activation of AKT lead to increase in mitochondrial membrane potential (MPP)? ROS generation is very sensitive to slight changes in MPP.Any increase in MPP would increase ROS generation.Does hyper activation of AKT lead to pentose phosphate pathway (PPP) dependent NADPH production or do AKT dependent cells use non-oxidative PPP? You could imagine that AKT hyper activation could lead to massive up regulation of PPP in certain cells resulting in better redox balance (the opposite of the findings in this paper). Also AKT is likely increasing lipogenesis thus decreasing NADPH levels. They might consider strategies to increase NADPH levels including AMPK activation, overexpression of IDH1 or malic enzymes see if it rescues from the detrimental effects of PIETC.In Figure 5G the resensitization to etoposide due to HK2 deficiency. Does NAC rescue this? Is HK2 deficiency leading to decrease PPP flux and diminished antioxidant capacity? Are cells resensitized to etoposide in galactose media?It is beyond the scope of the current study but it would be interesting to see if NAC would decrease the survival of PTEN-HK2 DKO to levels similar to PTEN single KO with NAC. This would formally demonstrate that the effects HK2 deficiency are due to redox imbalance.Reviewer #4:This manuscript is the follow up of previous work published by the authors in 2008 and 2012. It provides a low incremental gain of knowledge to the previous studies and is mostly based on correlative associations between AKT signaling, ROS production, metabolism and cytotoxicity.1) It is my impression that the title is an overstatement that confuses the reader: Selective and dramatic eradication of cancer by exploiting the metabolic consequences of Akt activation. The evidence for a selective action on AKT hyperactive tumors is minimal, being this assumption based on the study of 3 established cell lines . The use of "dramatic" in the title is by itself an overstatement. The demonstration of exploitation of metabolic consequences downstream AKT is minor, and ROS production is attributed by the authors correlatively to OXPHOS and based on previous studies to Sestrin3 regulation.2) The authors mention the concept chemoresistance several times in the manuscript, but there is no data supporting this notion. The closer thing to chemotherapy they attempt to use is rapamycin, which would be far from that.3) I perceive that, despite the fact that they do extensive pre-clinical assays in the PTEN KO model with ROS-inducers + Rapa, the study adds very little conceptual novelty to the field.4) The authors present evidence on the interest of targeting HK2 in these tumor cells, but this notion is poorly connected to the rest of the study. Again, this evidence is based on previous reports. There is no causal connection of HK2 to ROS production. In addition, in the experiments with etoposide no selectiveness towards AKT activated tumors is presented. The outcome of the genetic cross of PTEN and HK2 KO could be intrinsically metabolic, and disconnected from ROS production.[Editors’ note: what now follows is the decision letter after the authors submitted for further consideration.]eLife. Your revised article has been favorably evaluated by Sean Morrison (Senior editor), a Reviewing editor and three reviewers. There are a few remaining issues that need to be addressed before acceptance, as outlined below:Thank you for resubmitting your work entitled "Selective eradication of cancer displaying hyperactive Akt by exploiting the metabolic consequences of Akt activation" for further consideration at The manuscript is much improved. However, there are some minor points that should be addressed:1) Results section. The rationale for using Rapa is the release of the negative-feedback on AKT. Yet, the fact that Rapa increases pAKT in this system is not shown.2) Figure 4J/6G. How do the authors measure tumour-free survival? The Pten model does have full incidence of pre/tumoural masses by 6 months, as reported by them.3) The statement "Next, we wanted to know whether the efficacy of such a treatment was greater if the mice were treated at a younger age, reflecting early detection in adult human males. Therefore, the mice were treated at 2 months according to the protocol depicted in Figure 4A" is incorrect. Treating these mice at 8 weeks has no resemblance with early detection, since these mice do not have cancer (barely PIN) and patients would have early or intermediate grade tumours.4) What is the explanation for a decrease in pAKT upon treatment and release with Rapa+PEITC (S10C).5) The quality of the IHC images should be improved .6) There are some typos in the Abstract, most notably "Akt" is missing from: "…the display hyperactivated have high…". [Editors’ note: the author responses to the first round of peer review follow.]Reviewer #1:Nogueira et al. extend findings from their 2008 publication to further support the model that activation of Akt downstream of Pten loss in prostate cancer causes high ROS. The current paper suggests some therapeutic strategies to take advantage of this, and provide some impressive data for PEITC and rapamycin causing tumor regression in a xenograft model of prostate cancer. They also present some data from a Pten-null mouse model in support of this combination, and include two figures at the end to build on their past work around HK2, and suggest HK2 is another target in prostate cancer.The most novel and exciting data surround PEITC and rapamycin in the prostate xenograft models. Their remain some questions around how to interpret the data in the Pten-null model, and the final two figures on HK2 feel like a bit of a departure from the rest of the paper. I wonder if those data might be better served in a separate publication.We thank the reviewer for these comments. We used the Pten-null model because only in this model, which recapitulates human prostate cancer, we could treat the mice at different stages, and most importantly to determine tumor free survival. As shown in Figure 3 and Figure 4 we markedly increased the tumor free survival . The effect was cytotoxic and not only cytostatic indicating that the tumors are eradicated. This is also manifested by the sustained effect even 6 months after the treatment was stopped . As for the HK2 experiments we strongly believe that they should be part of the paper. Elevation of glycolysis in Pten-deficient prostate cancer cells is dependent of Akt, which elevates HK2 expression and activity. Therefore, it represents another metabolic vulnerability of Akt activation.Specific comments1) The authors use PEITC, which can deplete intracellular glutathione. This may have consequences beyond increasing ROS, although some data to confirm that it acts through glutathione depletion in their system would add to the paper. Alternatively, they might try an alternative glutathione reducing agent such as BSO, which has been in clinical trials in patients.In the revised manuscript we showed that PEITC reduced GSH levels and reduced GSH/GSSG ratio . BSO like PEITC preferentially killed the cancer cells that display hyperactive Akt .1/2 hairpins.2) A cDNA rescue experiment to control fro shRNA off target effects should be included for key data using the AktThe hairpins used here are verified and established, and others and we previously used them. In the revised manuscript we show that the knockdown of Akt1 and Akt2 reduced ROS levels and cell death and these are restored when activated Akt is re-expressed .3) Some experiments are shown with Akt knockdown and Akt expression to confirm dependence on some phenotypes, but extending the Akt gain of function studies in the Pten wild-type cells to confirm key claims would also enhance the paper. Most importantly, showing that Akt expression in DU145 could sensitize the cells to PEITC and rapamycin would go along way toward supporting the model that active Akt is the determinant of this phenotype.First, in the revised manuscript we show that either the knockdown of PTEN or the expression of activated Akt in DU145 cells increased ROS level and rendered them more sensitive to PEITC and rapamycin , and like in PC3 cells the knockdown of Akt1 and Akt2 in LNCaP cells rendered them more resistant to PEITC .4) I am somewhat confused by the data in the Pten-null model. First, they start treating mice at 2 months and 4 months. The timing of PIN versus cancer in their hands should be confirmed, but based on the literature only invasive cancer is not expected at either time point. Thus, this is really more of a cancer prevention study. Second, how was the schedule and timing of treatment determined? They treat the animals for a very long time, and while differences are noted, they clearly have not prevented the cancer even with very long treatment since some proliferation is still observed even in the treated prostates at this late time point. This is at odds with the regressions observed in the xenografts, and perhaps indicates the combination is less effective in early stage lesions. Could treatment be initiated in older mice with invasive cancers to better match the xenograft experiment?We chose these two time points, because the onset of PIN and the enlargement of prostate is observed at 8-10 weeks, and because high grade PINs and the transition to carcinoma occurs at 4 months, and invasive carcinoma at 6-8 months. Therefore, we do not think that this could be considered cancer prevention. As for regression we observed a dramatic reduction in BrdU incorporation (10 fold decrease) when the mice were treated with rapamycin and PEITC , which is almost the same as basal level of BrdU incorporation . Notably, the same as with human, prostate enlargement is naturally occurring in aged mice . Moreover apoptosis was massively increased after treatment with rapamycin and PEITC . Furthermore when mice treated between 2-6 months and were left without treatment for another six month we observed that the effect of PEITC and rapamycin and PEITC persists and BrdU incorporation was diminished and cell death continued to occur, and eventually the mice lived substantially longer than control untreated mice .5) More detail is needed on the age of the mice and length of treatment when they show NAC increases prostate cancer progression. Perhaps I missed it, but it is unclear whether this timing paralleled the treatments as implied in the text.For NAC, mice were injected at 4 months of age for 12 weeks and prostates were analyzed for IHC and weight at the end of treatment (about 8½ months). Manuscript was corrected accordingly.6) The argument that finding isoform selective inhibitors for Akt would be challenging is noted. One might expect a similar challenge to generate isoform selective inhibitors of HK2, yet the conclusion of the second story in the paper is that selective targeting of HK2 might be an alternative strategy to treat Akt active prostate cancer. While the data showing HK2 is required are fine, they are less impressive than the PEITC/Rapamycin data and feel very much like a separate story. This might be better served as a short communication elsewhere.We would like to clarify that the purpose of the paper is to exploit metabolic vulnerabilities as a consequence of Akt activation to identify therapeutic approaches that selectively target cancer cells possessing active Akt. We found two metabolic vulnerabilities, which are Akt dependent. One is related to elevated OXOPHO and ROS levels and the other is related to increased glycolysis and hexokinase expression and activity. We found that in prostate cancer in which PTEN is lost HK2 expression is high and is dependent on Akt activity. This is also true in mice deficient for PTEN in the prostate. Furthermore, Akt directly phosphorylates HK2 increasing its activity and its ability to promote cell survival. Therefore we strongly believe that the HK2 data should be included in the manuscript, because this is also the first time demonstrating that HK2 deletion in a mouse model of prostate cancer markedly decreases tumor development and extends lifespan. As for isoform specificity it was recently published that it is feasible to selectivity target HK2 and not HK1 . This is discussed in the revised manuscript.Reviewer #2:In the present manuscript Hay and colleagues propose to exploit the vulnerability generated by Akt-mediated ROS production as a therapeutic target in prostate cancer.This mechanism of sensitization to oxidative stress is not new in cancer and the authors themselves contributed to elucidate it in their previous work . However, the link proposed in the present manuscript between Akt-induced ROS production and PTEN loss, an acknowledged driver in prostate cancer, is intriguing and potentially relevant for the clinics.Unfortunately the manuscript lacks coherence, as it proposes two distinct parts (ROS inducer + rapamycin treatment and HK2 deficiency) that are barely integrated in the text.In the revised a manuscript we show additional mechanisms such as increased NADP/NADPH and mitochondrial potential, which contribute to Akt– induced ROS. We also showed that ROS is an impediment to tumor progression as treatment with NAC increased tumor progression .The objectives of the paper are to exploit metabolic vulnerabilities of Akt in order to circumvent the use of Akt inhibitors and to selectively target prostate cancer cells displaying Akt. Therefore, we identified two metabolic vulnerabilities that we targeted. One is the increased OXPHO and ROS and the other is the increase in HK2 expression and activity. Please also see response to point 6 of reviewer 1.Specific Comments:1) The method used in Figure 2A-D for detection of apoptosis does not allow for the discrimination between apoptosis and other means of cell death. The authors correctly make use of caspase-3 cleavage as an apoptotic marker in vivo throughout the manuscript, but in order to make the same claim in their in vitro model they should resort to more specific methods for apoptosis detection (e.g. Annexin V staining). A brief overview of the method should be given instead along with the reference.As indicated by the reviewer we used cleaved caspase 3 to show apoptosis. The method that we used to quantify cell death (PI staining) is commonly used. In the tumor samples we quantified apoptosis by cleaved caspase 3. In the revised manuscript we changed the Y axis from apoptosis to cell death when π staining only was used. In some of the experiments we corroborated the data by apoptosis assays such as DAPI staining and quantification of caspases3/7 cleavage . In the revised manuscript we provided a brief overview of the methods.2) Experiments shown in Figures S1F-G, 1F and 2C are conducted only in PC3 cells. As they are key to prove the authors' point, they should be reproduced also in LnCAP cells.In the revised manuscript the NAC experiments were repeated in LNCaP cells . We also knocked down Akt1 and Akt2 in LNCaP cells and showed that it decreased ROS and sensitivity to PEITC .3) When rapamycin treatment is introduced, the rationale for the use of this drug is not explained and is only very briefly mentioned only in the Discussion section. This might make the comprehension of the given results difficult for non-expert readers. The mechanism by which rapamycin induces an increase in ROS production by removing mTOR inhibition over Akt should be more clearly stated up front.This was clearly stated in the revised manuscript.in vitro and in their mouse model. To further prove the proposed mechanism, they could also try to sensitize DU145 cells to rapamycin by knocking down PTEN.4) In DU145 cells, rapamycin does not substantially increase ROS production, whereas it does in cells with PTEN loss. This would suggest that PTEN control over Akt activity is epistatic over mTOR control. To better clarify this relationship, and to which extent mTOR inhibition is actually able to activate Akt in the different conditions, the authors should check the basal mTOR activity in the three cell lines, as well Akt activation upon rapamycin treatment both We would like to point out that rapamycin alone did not substantially increased ROS in all the cell lines tested and not just in DU145 . mTORC1 appears to be a downstream effector of Akt-mediated OXPHO. However, the effect of mTORC1 on OXPHO is mediated by eIF4E and not by S6K1, and rapamycin is not sufficient to inhibit eIF4E by 4EBP and therefore does not inhibit mTORC1-mediated OXPHO. Indeed, we showed in the manuscript that rapamycin does not inhibit OCR and OCR is only inhibited by mTOR kinase inhibitor . Thus the addition of PEITC converts rapamycin from being cytostatic to being cytotoxic. We will determine if Akt was activated by rapamycin .5) The authors state "Interestingly, basal oxygen consumption in DU145 cells reached the maximum capacity of the respiratory chain, while PC3 and LNCaP cells have a larger spare capacity." However, the graphs show that for all cell lines basal respiration matches spare respiration.The graph presented in Figure 1B, shows that baseline respiration match maximal respiration. However, when analyzing OCR data, basal respiration is calculated by subtracting non-mitochondrial respiration to baseline. In this case, we obtain the graph in So when we calculate the spare capacity , DU145 cells do not have a spare capacity compared to PC3 and LNCaP cells.6) As already mentioned, the findings on HK2 role in the induction of Akt-mediated ROS production, although interesting, seem more preliminary and do not integrate well with the previous part of the manuscript.We did not claim that HK2 has a role in Akt-mediated ROS production. We found that the suppression of HK2 further increased ROS and further sensitizes to PEITC. However, because HK2 expression is induced in Akt-dependent manner in prostate cancer cells, and since it is directly phosphorylated by Akt, it is a metabolic vulnerability of Akt activation. Please also see response to comment 6 of reviewer 1.Reviewer #3:This paper shows that hyper activation of AKT causes a ROS vulnerability in prostate cancer cells. Impressively, they demonstrate that rapamycin plus a ROS inducer markedly reduce tumor growth in PTEN-deficient prostate tumors in mouse models. Additionally the authors demonstrate that loss of PTEN in prostate cancer cells induces hexokinase 2 (HK2) expression to increase glucose metabolism. Furthermore, HK2 deficiency in mouse models of Pten-deficient prostate cancer elicited a marked inhibition of tumor development.The paper is interesting and suitable for eLife.I have a few comments that should be addressed.Does the hyper activation of AKT lead to increase in mitochondrial membrane potential (MPP)? ROS generation is very sensitive to slight changes in MPP.Any increase in MPP would increase ROS generation.We thank the reviewer for the positive comments. In Figure 1—figure supplement 1 of the revised manuscript we show that MPP is higher in PC3 and LNCaP in comparison to DU145 cells.Does hyper activation of AKT lead to pentose phosphate pathway (PPP) dependent NADPH production or do AKT dependent cells use non-oxidative PPP? You could imagine that AKT hyper activation could lead to massive up regulation of PPP in certain cells resulting in better redox balance (the opposite of the findings in this paper). Also AKT is likely increasing lipogenesis thus decreasing NADPH levels. They might consider strategies to increase NADPH levels including AMPK activation, overexpression of IDH1 or malic enzymes see if it rescues from the detrimental effects of PIETC.We do not know if the oxidative PPP is elevated in cells with hyperactive Akt. In the original manuscript we showed two mechanisms by which Akt activation elevates intracellular ROS levels. In the revised manuscript we measured NADP/NADPH ratio and found that it is elevated in the PTEN-deficient cells . The elevated NADP/NADPH could be either contributing to the high level of ROS or a consequence of high level of ROS as the cells’ attempt to combat high ROS level and therefore consume NADPH. Alternatively, high NADPH consumption for fatty acid synthesis in the PTEN-deficient cells contributes to the higher NADP/NADPH ratio.In Figure 5G the resensitization to etoposide due to HK2 deficiency. Does NAC rescue this? Is HK2 deficiency leading to decrease PPP flux and diminished antioxidant capacity? Are cells resensitized to etoposide in galactose media?We conducted the proposed experiments and found that replacement of glucose with galactose modestly resensitizes PC3 and LNCaP cells to etoposide see . We did Reviewer #4:This manuscript is the follow up of previous work published by the authors in 2008 and 2012. It provides a low incremental gain of knowledge to the previous studies and is mostly based on correlative associations between AKT signaling, ROS production, metabolism and cytotoxicity.1) It is my impression that the title is an overstatement that confuses the reader: Selective and dramatic eradication of cancer by exploiting the metabolic consequences of Akt activation. The evidence for a selective action on AKT hyperactive tumors is minimal, being this assumption based on the study of 3 established cell lines . The use of "dramatic" in the title is by itself an overstatement. The demonstration of exploitation of metabolic consequences downstream AKT is minor, and ROS production is attributed by the authors correlatively to OXPHOS and based on previous studies to Sestrin3 regulation.In our current manuscript we provided additional mechanisms to by which Akt could increase ROS in Pten-deficient prostate cancer cells. We identified two metabolic consequences of Akt activation. First, Akt elevates OXPHO, increases NADP/NADPH ratio and therefore increased ROS. Second, Akt elevates the expression and activity of HK2 in Pten-deficient prostate cancer to increase glycolysis. To determine the efficacy of the therapeutic strategies we employed two genetically engineered mice that we followed for two years. To complement these studies we also employed xenografts of human cancer cells.We have modified the title of the manuscript. We clearly showed in the manuscript that OXPHO, high ROS, and cell death are Akt dependent . We also showed that expression of high HK2 levels is Akt dependent . Furthermore, Akt directly phosphorylates HK2 and increased its binding to mitochondria . As we recently showed binding of HK2 to mitochondria is important for glycolysis .2) The authors mention the concept chemoresistance several times in the manuscript, but there is no data supporting this notion. The closer thing to chemotherapy they attempt to use is rapamycin, which would be far from that.It is well established that hyperactivation of Akt exerts chemoresistance. As an example we showed that Pten-deficient cells are relatively resistant to etoposide in Akt-dependent manner, and we could overcome this resistance by ablating HK2 . In the revised manuscript we showed that expressing activated Akt in the DU145 cells renders them more resistant to etoposide, whereas the knockdown of Akt1 and Akt2 in LNCaP and PC3 cells render them more sensitive to etoposide .3) I perceive that, despite the fact that they do extensive pre-clinical assays in the PTEN KO model with ROS-inducers + Rapa, the study adds very little conceptual novelty to the field.4) The authors present evidence on the interest of targeting HK2 in these tumor cells, but this notion is poorly connected to the rest of the study. Again, this evidence is based on previous reports. There is no causal connection of HK2 to ROS production. In addition, in the experiments with etoposide no selectiveness towards AKT activated tumors is presented. The outcome of the genetic cross of PTEN and HK2 KO could be intrinsically metabolic, and disconnected from ROS production.We would like to clarify that the purpose of the paper is to exploit metabolic vulnerabilities as a consequence of Akt activation to identify therapeutic approaches that selectively target cancer cells possessing active Akt. We found that in prostate cancer in which PTEN is lost HK2 expression is high and is dependent on Akt activity. This is also true in mice deficient for PTEN in the prostate. Furthermore, Akt directly phosphorylates HK2 increasing its activity and its ability to promote cell survival. Finally we showed that HK2 KD increased ROS levels . Therefore we strongly believe that the HK2 data should be included in the manuscript, because this is also the first time demonstrating that HK2 deletion in a mouse model of prostate cancer markedly decreases tumor development and extends lifespan.[Editors’ note: the author responses to the re-review follow.]The manuscript is much improved. However, there are some minor points that should be addressed:1) Results section. The rationale for using Rapa is the release of the negative-feedback on AKT. Yet, the fact that Rapa increases pAKT in this system is not shown.We added a new sup Figure 6 to show the increase in pAkt by rapamycin.2) Figure 4J/6G. How do the authors measure tumour-free survival? The Pten model does have full incidence of pre/tumoural masses by 6 months, as reported by them.We had to sacrifice mice because tumor mass reached to end-point in which we could no longer keep the mice. It might be correct that a better definition is survival and this was corrected in the revised manuscript.3) The statement "Next, we wanted to know whether the efficacy of such a treatment was greater if the mice were treated at a younger age, reflecting early detection in adult human males. Therefore, the mice were treated at 2 months according to the protocol depicted in Figure 4A" is incorrect. Treating these mice at 8 weeks has no resemblance with early detection, since these mice do not have cancer (barely PIN) and patients would have early or intermediate grade tumours.We agree with this assessment and corrected the text to “at early time point”.4) What is the explanation for a decrease in pAKT upon treatment and release with Rapa+PEITC (S10C).There is no Figure S10C in the original manuscript and in fact there is no immunoblot showing pAkt after Rapa+PEITC. The question stems from a statement in the text that was erroneously introduced. These statements were deleted in the revised manuscript.5) The quality of the IHC images should be improved .This was improved in the revised manuscript.6) There are some typos in the Abstract, most notably "Akt" is missing from: "…the display hyperactivated have high…".This was corrected in the revised manuscript.