High-throughput sequencing of small RNA transcriptomes reveals critical biological features targeted by microRNAs in cell models used for squamous cell cancer research

Abstract Background The implication of post-transcriptional regulation by microRNAs in molecular mechanisms underlying cancer disease is well documented. However, their interference at the cellular level is not fully explored. Functional in vitro studies are fundamental for the comprehension of their role; nevertheless results are highly dependable on the adopted cellular model. Next generation small RNA transcriptomic sequencing data of a tumor cell line and keratinocytes derived from primary culture was generated in order to characterize the microRNA content of these systems, thus helping in their understanding. Both constitute cell models for functional studies of microRNAs in head and neck squamous cell carcinoma (HNSCC), a smoking-related cancer. Known microRNAs were quantified and analyzed in the context of gene regulation. New microRNAs were investigated using similarity and structural search, ab initio classification, and prediction of the location of mature microRNAs within would-be precursor sequences. Results were compared with small RNA transcriptomic sequences from HNSCC samples in order to access the applicability of these cell models for cancer phenotype comprehension and for novel molecule discovery. Results Ten miRNAs represented over 70% of the mature molecules present in each of the cell types. The most expressed molecules were miR-21, miR-24 and miR-205, Accordingly; miR-21 and miR-205 have been previously shown to play a role in epithelial cell biology. Although miR-21 has been implicated in cancer development, and evaluated as a biomarker in HNSCC progression, no significant expression differences were seen between cell types. We demonstrate that differentially expressed mature miRNAs target cell differentiation and apoptosis related biological processes, indicating that they might represent, with acceptable accuracy, the genetic context from which they derive. Most miRNAs identified in the cancer cell line and in keratinocytes were present in tumor samples and cancer-free samples, respectively, with miR-21, miR-24 and miR-205 still among the most prevalent molecules at all instances. Thirteen miRNA-like structures, containing reads identified by the deep sequencing, were predicted from putative miRNA precursor sequences. Strong evidences suggest that one of them could be a new miRNA. This molecule was mostly expressed in the tumor cell line and HNSCC samples indicating a possible biological function in cancer. Conclusions Critical biological features of cells must be fully understood before they can be chosen as models for functional studies. Expression levels of miRNAs relate to cell type and tissue context. This study provides insights on miRNA content of two cell models used for cancer research. Pathways commonly deregulated in HNSCC might be targeted by most expressed and also by differentially expressed miRNAs. Results indicate that the use of cell models for cancer research demands careful assessment of underlying molecular characteristics for proper data interpretation. Additionally, one new miRNA-like molecule with a potential role in cancer was identified in the cell lines and clinical samples.

MVP expression in the prediction of clinical outcome of locally advanced oral squamous cell carcinoma patients treated with radiotherapy

[EN] Objective: To explore the role of Major Vault Protein (MVP) in oral cavity squamous cell carcinoma patients. Subjects and Methods: 131 consecutive patients suffering from oral cavity squamous cell carcinoma were included in the study. In the whole series, the mean follow-up for survivors was 123.11 ± 40.36 months. Patients in tumour stages I and II were referred to surgery; patients in stage III-IV to postoperative radiotherapy (mean dose = 62.13 ± 7.74 Gy in 1.8–2 Gy/fraction). MVP expression was studied by immunohistochemistry in paraffin-embedded tumour tissue. Results: MVP expression was positive in 112 patients (85.5%) and no relation was found with clinic pathological variables. MVP overexpression (those tumours with moderate or strong expression of the protein) was related to insulin-like growth factor receptor-1 (IGF-1R) expression (P = 0.014). Tumour stage of the disease was the most important prognostic factor related to survival. Tumours overexpressing MVP and IGF-1R were strongly related to poor disease-free survival (P = 0.008, Exp(B) = 2.730, CI95% (1.302-5.724)) and cause-specific survival (P = 0.014, Exp(B) = 2.570, CI95% (1.215-5.437)) in patients achieving tumour stages III-IV, in multivariate analysis. Conclusions: MVP and IGF-1R expression were related in oral squamous cell carcinoma and conferred reduced long-term survival in patients suffering from advanced stages of the disease.

Prediction of clinical toxicity in locally advanced head and neck cancer patients by radio-induced apoptosis in peripheral blood lymphocytes (PBLs)

[EN] Head and neck cancer is treated mainly by surgery and radiotherapy. Normal tissue toxicity due to x-ray exposure is a limiting factor for treatment success. Many efforts have been employed to develop predictive tests applied to clinical practice. Determination of lymphocyte radio-sensitivity by radio-induced apoptosis arises as a possible method to predict tissue toxicity due to radiotherapy. The aim of the present study was to analyze radio-induced apoptosis of peripheral blood lymphocytes in head and neck cancer patients and to explore their role in predicting radiation induced toxicity. Seventy nine consecutive patients suffering from head and neck cancer, diagnosed and treated in our institution, were included in the study. Toxicity was evaluated using the Radiation Therapy Oncology Group scale. Peripheral blood lymphocytes were isolated and irradiated at 0, 1, 2 and 8 Gy during 24 hours. Apoptosis was measured by flow cytometry using annexin V/propidium iodide. Lymphocytes were marked with CD45 APC-conjugated monoclonal antibody. Radiation-induced apoptosis increased in order to radiation dose and fitted to a semi logarithmic model defined by two constants: α and β. α, as the origin of the curve in the Y axis determining the percentage of spontaneous cell death, and β, as the slope of the curve determining the percentage of cell death induced at a determined radiation dose, were obtained. β value was statistically associated to normal tissue toxicity in terms of severe xerostomia, as higher levels of apoptosis were observed in patients with low toxicity (p = 0.035; Exp(B) 0.224, I.C.95% (0.060-0.904)). These data agree with our previous results and suggest that it is possible to estimate the radiosensitivity of peripheral blood lymphocytes from patients determining the radiation induced apoptosis with annexin V/propidium iodide staining. β values observed define an individual radiosensitivity profile that could predict late toxicity due to radiotherapy in locally advanced head and neck cancer patients. Anyhow, prospective studies with different cancer types and higher number of patients are needed to validate these results.

Prediction of clinical toxicity in localized cervical carcinoma by radio-induced apoptosis study in peripheral blood lymphocytes (PBLs)

[EN] Background: Cervical cancer is treated mainly by surgery and radiotherapy. Toxicity due to radiation is a limiting factor for treatment success. Determination of lymphocyte radiosensitivity by radio-induced apoptosis arises as a possible method for predictive test development. The aim of this study was to analyze radio-induced apoptosis of peripheral blood lymphocytes. Methods: Ninety four consecutive patients suffering from cervical carcinoma, diagnosed and treated in our institution, and four healthy controls were included in the study. Toxicity was evaluated using the Lent-Soma scale. Peripheral blood lymphocytes were isolated and irradiated at 0, 1, 2 and 8 Gy during 24, 48 and 72 hours. Apoptosis was measured by flow cytometry using annexin V/propidium iodide to determine early and late apoptosis. Lymphocytes were marked with CD45 APC-conjugated monoclonal antibody. Results: Radiation-induced apoptosis (RIA) increased with radiation dose and time of incubation. Data strongly fitted to a semi logarithmic model as follows: RIA = βln(Gy) + α. This mathematical model was defined by two constants: α, is the origin of the curve in the Y axis and determines the percentage of spontaneous cell death and β, is the slope of the curve and determines the percentage of cell death induced at a determined radiation dose (β = ΔRIA/Δln(Gy)). Higher β values (increased rate of RIA at given radiation doses) were observed in patients with low sexual toxicity (Exp(B) = 0.83, C.I. 95% (0.73-0.95), p = 0.007; Exp(B) = 0.88, C.I. 95% (0.82-0.94), p = 0.001; Exp(B) = 0.93, C.I. 95% (0.88-0.99), p = 0.026 for 24, 48 and 72 hours respectively). This relation was also found with rectal (Exp(B) = 0.89, C.I. 95% (0.81-0.98), p = 0.026; Exp(B) = 0.95, C.I. 95% (0.91-0.98), p = 0.013 for 48 and 72 hours respectively) and urinary (Exp(B) = 0.83, C.I. 95% (0.71-0.97), p = 0.021 for 24 hours) toxicity. Conclusion: Radiation induced apoptosis at different time points and radiation doses fitted to a semi logarithmic model defined by a mathematical equation that gives an individual value of radiosensitivity and could predict late toxicity due to radiotherapy. Other prospective studies with higher number of patients are needed to validate these results.

Studio dei profili di espressione dei microRNA nell'epatocarcinoma umano

Il carcinoma epatocellulare (HCC) è il più frequente tumore maligno del fegato e rappresenta il sesto tipo di tumore più comune nel mondo. Spesso i pazienti con HCC vengono diagnosticati a stadi piuttosto avanzati, quando le uniche opzioni terapeutiche in grado di migliorarne la sopravvivenza sono la chemoembolizzazione dell'arteria epatica ed il trattamento con l'inibitore multi-cinasico, Sorafenib. In questo contesto, la scoperta del ruolo centrale dei microRNA (miRNA) nella tumorigenesi umana risulta di fondamentale importanza per lo sviluppo di nuovi marcatori diagnostici e bersagli terapeutici. I microRNA (miRNA) sono delle piccole molecole di RNA non codificante, della lunghezza di 19-22 nucleotidi, filogeneticamente molto conservati, ed esercitano un ruolo cruciale nella regolazione di importanti processi fisiologici, quali sviluppo, proliferazione, differenziamento, apoptosi e risposta a numerosi segnali extracellulari e di stress. I miRNA sono inoltre responsabile della fine regolazione dell'espressione di centinaia di geni bersaglio attraverso il blocco della traduzione o la degradazione dell'mRNA target. Studi di profiling hanno evidenziato l'espressione aberrante di specifici miRNA in numerosi tipi di tumore umano. Lo scopo del presente lavoro è stato quello di individuare un pannello di miRNA deregolati nell'epatocarcinoma umano e di caratterizzare il ruolo biologico di tre miRNA deregolati nell'HCC, al fine di individuare alcuni dei meccanismi molecolari alla base della trasformazione maligna miRNA-associata. La nostra ricerca è stata inoltre focalizzata nell'individuazione di nuovi bersagli e strumenti terapeutici, quali i microRNA, per il trattamento combinato di HCC in stadio intermedio-avanzato.

Antinociceptive effects, metabolism and disposition of ketamine in ponies under target-controlled drug infusion

Ketamine is widely used as an anesthetic in a variety of drug combinations in human and veterinary medicine. Recently, it gained new interest for use in long-term pain therapy administered in sub-anesthetic doses in humans and animals. The purpose of this study was to develop a physiologically based pharmacokinetic (PBPk) model for ketamine in ponies and to investigate the effect of low-dose ketamine infusion on the amplitude and the duration of the nociceptive withdrawal reflex (NWR). A target-controlled infusion (TCI) of ketamine with a target plasma level of 1 microg/ml S-ketamine over 120 min under isoflurane anesthesia was performed in Shetland ponies. A quantitative electromyographic assessment of the NWR was done before, during and after the TCI. Plasma levels of R-/S-ketamine and R-/S-norketamine were determined by enantioselective capillary electrophoresis. These data and two additional data sets from bolus studies were used to build a PBPk model for ketamine in ponies. The peak-to-peak amplitude and the duration of the NWR decreased significantly during TCI and returned slowly toward baseline values after the end of TCI. The PBPk model provides reliable prediction of plasma and tissue levels of R- and S-ketamine and R- and S-norketamine. Furthermore, biotransformation of ketamine takes place in the liver and in the lung via first-pass metabolism. Plasma concentrations of S-norketamine were higher compared to R-norketamine during TCI at all time points. Analysis of the data suggested identical biotransformation rates from the parent compounds to the principle metabolites (R- and S-norketamine) but different downstream metabolism to further metabolites. The PBPk model can provide predictions of R- and S-ketamine and norketamine concentrations in other clinical settings (e.g. horses).

Effectively Selecting a Target Population for a Future Comparative Study

When comparing a new treatment with a control in a randomized clinical study, the treatment effect is generally assessed by evaluating a summary measure over a specific study population. The success of the trial heavily depends on the choice of such a population. In this paper, we show a systematic, effective way to identify a promising population, for which the new treatment is expected to have a desired benefit, using the data from a current study involving similar comparator treatments. Specifically, with the existing data we first create a parametric scoring system using multiple covariates to estimate subject-specific treatment differences. Using this system, we specify a desired level of treatment difference and create a subgroup of patients, defined as those whose estimated scores exceed this threshold. An empirically calibrated group-specific treatment difference curve across a range of threshold values is constructed. The population of patients with any desired level of treatment benefit can then be identified accordingly. To avoid any ``self-serving'' bias, we utilize a cross-training-evaluation method for implementing the above two-step procedure. Lastly, we show how to select the best scoring system among all competing models. The proposals are illustrated with the data from two clinical trials in treating AIDS and cardiovascular diseases. Note that if we are not interested in designing a new study for comparing similar treatments, the new procedure can also be quite useful for the management of future patients who would receive nontrivial benefits to compensate for the risk or cost of the new treatment.

Population pharmacokinetics of sevoflurane in conjunction with the AnaConDa: toward target-controlled infusion of volatiles into the breathing system

BACKGROUND: The Anesthetic Conserving Device (AnaConDa) uncouples delivery of a volatile anesthetic (VA) from fresh gas flow (FGF) using a continuous infusion of liquid volatile into a modified heat-moisture exchanger capable of adsorbing VA during expiration and releasing adsorbed VA during inspiration. It combines the simplicity and responsiveness of high FGF with low agent expenditures. We performed in vitro characterization of the device before developing a population pharmacokinetic model for sevoflurane administration with the AnaConDa, and retrospectively testing its performance (internal validation). MATERIALS AND METHODS: Eighteen females and 20 males, aged 31-87, BMI 20-38, were included. The end-tidal concentrations were varied and recorded together with the VA infusion rates into the device, ventilation and demographic data. The concentration-time course of sevoflurane was described using linear differential equations, and the most suitable structural model and typical parameter values were identified. The individual pharmacokinetic parameters were obtained and tested for covariate relationships. Prediction errors were calculated. RESULTS: In vitro studies assessed the contribution of the device to the pharmacokinetic model. In vivo, the sevoflurane concentration-time courses on the patient side of the AnaConDa were adequately described with a two-compartment model. The population median absolute prediction error was 27% (interquartile range 13-45%). CONCLUSION: The predictive performance of the two-compartment model was similar to that of models accepted for TCI administration of intravenous anesthetics, supporting open-loop administration of sevoflurane with the AnaConDa. Further studies will focus on prospective testing and external validation of the model implemented in a target-controlled infusion device.

A pancreatic islet-specific microRNA regulates insulin secretion

MicroRNAs (miRNAs) constitute a growing class of non-coding RNAs that are thought to regulate gene expression by translational repression. Several miRNAs in animals exhibit tissue-specific or developmental-stage-specific expression, indicating that they could play important roles in many biological processes. To study the role of miRNAs in pancreatic endocrine cells we cloned and identified a novel, evolutionarily conserved and islet-specific miRNA (miR-375). Here we show that overexpression of miR-375 suppressed glucose-induced insulin secretion, and conversely, inhibition of endogenous miR-375 function enhanced insulin secretion. The mechanism by which secretion is modified by miR-375 is independent of changes in glucose metabolism or intracellular Ca2+-signalling but correlated with a direct effect on insulin exocytosis. Myotrophin (Mtpn) was predicted to be and validated as a target of miR-375. Inhibition of Mtpn by small interfering (si)RNA mimicked the effects of miR-375 on glucose-stimulated insulin secretion and exocytosis. Thus, miR-375 is a regulator of insulin secretion and may thereby constitute a novel pharmacological target for the treatment of diabetes.

ROLE OF MICRORNA LET-7 IN PANCREATIC BETA CELLS

MicroRNAs (miRNAs) are small non-coding RNAs that inhibit gene expression at transcriptional or post-transcriptional level. Let-7 family is among the first identified human miRNAs and regulates multiple cellular processes including glucose metabolism in multiple organs. It has been reported that overexpression of let-7 resulted in insulin resistance and impaired glucose tolerance through repressing insulin signaling pathway in both muscle and liver. However, the role and mechanism underlying let-7 function in pancreatic beta-cells have yet to be elucidated. Let-7 family contains nine members, which poses a significant challenge in complete deletion of this miRNA family. To study the function of let-7 and to overcome the functional redundancies of various let-7 members in pancreatic beta-cells, the highly expressed let-7a and let-7b were blocked simultaneously using short tandem target mimic (STTM) approach developed in our laboratory. Introducing STTM-let7 into beta-cells markedly increased the expression of Caspase 3, a direct target of let-7, confirming a sufficient functional knockdown of let-7a/b by STTM-let7. STTM-let7 enhanced apoptotic cell death induced by cytokine, indicating that let-7a/b is able to protect from apoptosis through attenuating Caspase 3 expression in pancreatic beta-cells. In contrast to the previous observation that let-7 silencing increases insulin signaling in muscle and liver, inhibition of let-7 with STTM-let7 significantly repressed glucose-stimulated insulin signaling in pancreatic beta-cells, leading to impaired insulin secretion and reduced beta-cell proliferation. Taken together, an appropriate level of let-7 is essential in maintaining beta-cell function and viability. Dysregulation of let-7 may contribute to the pathogenesis of type 2 diabetes.

In silico target fishing for rationalized ligand discovery exemplified on constituents of Ruta graveolens

The identification of targets whose interaction is likely to result in the successful treatment of a disease is of growing interest for natural product scientists. In the current study we performed an exemplary application of a virtual parallel screening approach to identify potential targets for 16 secondary metabolites isolated and identified from the aerial parts of the medicinal plant RUTA GRAVEOLENS L. Low energy conformers of the isolated constituents were simultaneously screened against a set of 2208 pharmacophore models generated in-house for the IN SILICO prediction of putative biological targets, i. e., target fishing. Based on the predicted ligand-target interactions, we focused on three biological targets, namely acetylcholinesterase (AChE), the human rhinovirus (HRV) coat protein and the cannabinoid receptor type-2 (CB (2)). For a critical evaluation of the applied parallel screening approach, virtual hits and non-hits were assayed on the respective targets. For AChE the highest scoring virtual hit, arborinine, showed the best inhibitory IN VITRO activity on AChE (IC (50) 34.7 muM). Determination of the anti-HRV-2 effect revealed 6,7,8-trimethoxycoumarin and arborinine to be the most active antiviral constituents with IC (50) values of 11.98 muM and 3.19 muM, respectively. Of these, arborinine was predicted virtually. Of all the molecules subjected to parallel screening, one virtual CB (2) ligand was obtained, i. e., rutamarin. Interestingly, in experimental studies only this compound showed a selective activity to the CB (2) receptor ( Ki of 7.4 muM) by using a radioligand displacement assay. The applied parallel screening paradigm with constituents of R. GRAVEOLENS on three different proteins has shown promise as an IN SILICO tool for rational target fishing and pharmacological profiling of extracts and single chemical entities in natural product research.

Distinct microRNA Expression Profile in Prostate Cancer Patients with Early Clinical Failure and the Impact of let-7 as Prognostic Marker in High-Risk Prostate Cancer

Background The identification of additional prognostic markers to improve risk stratification and to avoid overtreatment is one of the most urgent clinical needs in prostate cancer (PCa). MicroRNAs, being important regulators of gene expression, are promising biomarkers in various cancer entities, though the impact as prognostic predictors in PCa is poorly understood. The aim of this study was to identify specific miRNAs as potential prognostic markers in high-risk PCa and to validate their clinical impact. Methodology and Principal Findings We performed miRNA-microarray analysis in a high-risk PCa study group selected by their clinical outcome (clinical progression free survival (CPFS) vs. clinical failure (CF)). We identified seven candidate miRNAs (let-7a/b/c, miR-515-3p/5p, -181b, -146b, and -361) that showed differential expression between both groups. Further qRT-PCR analysis revealed down-regulation of members of the let-7 family in the majority of a large, well-characterized high-risk PCa cohort (n = 98). Expression of let-7a/b/and -c was correlated to clinical outcome parameters of this group. While let-7a showed no association or correlation with clinical relevant data, let-7b and let-7c were associated with CF in PCa patients and functioned partially as independent prognostic marker. Validation of the data using an independent high-risk study cohort revealed that let-7b, but not let-7c, has impact as an independent prognostic marker for BCR and CF. Furthermore, we identified HMGA1, a non-histone protein, as a new target of let-7b and found correlation of let-7b down-regulation with HMGA1 over-expression in primary PCa samples. Conclusion Our findings define a distinct miRNA expression profile in PCa cases with early CF and identified let-7b as prognostic biomarker in high-risk PCa. This study highlights the importance of let-7b as tumor suppressor miRNA in high-risk PCa and presents a basis to improve individual therapy for high-risk PCa patients.

Potentially avoidable 30-day hospital readmissions in medical patients: derivation and validation of a prediction model

IMPORTANCE Because effective interventions to reduce hospital readmissions are often expensive to implement, a score to predict potentially avoidable readmissions may help target the patients most likely to benefit. OBJECTIVE To derive and internally validate a prediction model for potentially avoidable 30-day hospital readmissions in medical patients using administrative and clinical data readily available prior to discharge. DESIGN Retrospective cohort study. SETTING Academic medical center in Boston, Massachusetts. PARTICIPANTS All patient discharges from any medical services between July 1, 2009, and June 30, 2010. MAIN OUTCOME MEASURES Potentially avoidable 30-day readmissions to 3 hospitals of the Partners HealthCare network were identified using a validated computerized algorithm based on administrative data (SQLape). A simple score was developed using multivariable logistic regression, with two-thirds of the sample randomly selected as the derivation cohort and one-third as the validation cohort. RESULTS Among 10 731 eligible discharges, 2398 discharges (22.3%) were followed by a 30-day readmission, of which 879 (8.5% of all discharges) were identified as potentially avoidable. The prediction score identified 7 independent factors, referred to as the HOSPITAL score: h emoglobin at discharge, discharge from an o ncology service, s odium level at discharge, p rocedure during the index admission, i ndex t ype of admission, number of a dmissions during the last 12 months, and l ength of stay. In the validation set, 26.7% of the patients were classified as high risk, with an estimated potentially avoidable readmission risk of 18.0% (observed, 18.2%). The HOSPITAL score had fair discriminatory power (C statistic, 0.71) and had good calibration. CONCLUSIONS AND RELEVANCE This simple prediction model identifies before discharge the risk of potentially avoidable 30-day readmission in medical patients. This score has potential to easily identify patients who may need more intensive transitional care interventions.

Unravelling the impact of microRNA on Amyotrophic Lateral Sclerosis (ALS) pathogenesis

ALS is the most common adult neurodegenerative disease that specifically affects upper and lower neurons leading to progressive paralysis and death. There is currently no effective treatment. Thus, identification of the signaling pathways and cellular mediators of ALS remains a major challenge in the search for novel therapeutics. Recent studies have shown that noncoding RNA molecules have a significant impact on normal CNS development and on causes and progression of human neurological disorders. To investigate the hypothesis that expression of the mutant SOD1 protein, which is one of the genetic causes of ALS, may alter expression of miRNAs thereby contributing to the pathogenesis of familial ALS, we compared miRNA expression in SH-SY5Y expressing either the wild type or the SOD1 protein using small RNA deep-sequencing followed by RT-PCR validation. This strategy allowed us to find a group of up and down regulated miRNAs, which are predicted to play a role in the motorneurons physiology and pathology. The aim of my work is to understand if these modulators of gene expression may play a causative role in disease onset or progression. To this end I have checked the expression level of these misregulated miRNAs derived from RNA-deep sequencing by qPCR on cDNA derived from ALS mice models at early onset of the disease. Thus, I’m looking for the most up-regulated one even in Periferal Blood Mononuclear Cell (PBMC) of sporadic ALS patients. Furthermore I’m functionally characterizing the most up-regulated miRNAs through the validation of bioinformatic-predicted targets by analyzing endogenous targets levels after microRNA transfection and by UTR-report luciferase assays. Thereafter I’ll analyze the effect of misregulated targets on pathogenesis or progression of ALS by loss of functions or gain of functions experiments, based on the identified up/down-regulation of the specific target by miRNAs. In the end I would define the mechanisms responsible for the miRNAs level misregulation, by silencing or stimulating the signal transduction pathways putatively involved in miRNA regulation.

Prediction and prevention of psychosis: current progress and future tasks

Prevention of psychoses has been intensively investigated within the past two decades, and particularly, prediction has been much advanced. Depending on the applied risk indicators, current criteria are associated with average, yet significantly heterogeneous transition rates of ≥30 % within 3 years, further increasing with longer follow-up periods. Risk stratification offers a promising approach to advance current prediction as it can help to reduce heterogeneity of transition rates and to identify subgroups with specific needs and response patterns, enabling a targeted intervention. It may also be suitable to improve risk enrichment. Current results suggest the future implementation of multi-step risk algorithms combining sensitive risk detection by cognitive basic symptoms (COGDIS) and ultra-high-risk (UHR) criteria with additional individual risk estimation by a prognostic index that relies on further predictors such as additional clinical indicators, functional impairment, neurocognitive deficits, and EEG and structural MRI abnormalities, but also considers resilience factors. Simply combining COGDIS and UHR criteria in a second step of risk stratification produced already a 4-year hazard rate of 0.66. With regard to prevention, two recent meta-analyses demonstrated that preventive measures enable a reduction in 12-month transition rates by 54-56 % with most favorable numbers needed to treat of 9-10. Unfortunately, psychosocial functioning, another important target of preventive efforts, did not improve. However, these results are based on a relatively small number of trials; and more methodologically sound studies and a stronger consideration of individual profiles of clinical needs by modular intervention programs are required