Translational precision medicine: an industry perspective.

In the era of precision medicine, digital technologies and artificial intelligence, drug discovery and development face unprecedented opportunities for product and business model innovation, fundamentally changing the traditional approach of how drugs are discovered, developed and marketed. Critical to this transformation is the adoption of new technologies in the drug development process, catalyzing the transition from serendipity-driven to data-driven medicine. This paradigm shift comes with a need for both translation and precision, leading to a modern Translational Precision Medicine approach to drug discovery and development. Key components of Translational Precision Medicine are multi-omics profiling, digital biomarkers, model-based data integration, artificial intelligence, biomarker-guided trial designs and patient-centric companion diagnostics. In this review, we summarize and critically discuss the potential and challenges of Translational Precision Medicine from a cross-industry perspective.

Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees.

A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant cis-expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.

MYD88 L265P somatic mutation in Waldenström's macroglobulinemia.

BACKGROUND: Waldenström's macroglobulinemia is an incurable, IgM-secreting lymphoplasmacytic lymphoma (LPL). The underlying mutation in this disorder has not been delineated. METHODS: We performed whole-genome sequencing of bone marrow LPL cells in 30 patients with Waldenström's macroglobulinemia, with paired normal-tissue and tumor-tissue sequencing in 10 patients. Sanger sequencing was used to validate the findings in samples from an expanded cohort of patients with LPL, those with other B-cell disorders that have some of the same features as LPL, and healthy donors. RESULTS: Among the patients with Waldenström's macroglobulinemia, a somatic variant (T→C) in LPL cells was identified at position 38182641 at 3p22.2 in the samples from all 10 patients with paired tissue samples and in 17 of 20 samples from patients with unpaired samples. This variant predicted an amino acid change (L265P) in MYD88, a mutation that triggers IRAK-mediated NF-κB signaling. Sanger sequencing identified MYD88 L265P in tumor samples from 49 of 54 patients with Waldenström's macroglobulinemia and in 3 of 3 patients with non-IgM-secreting LPL (91% of all patients with LPL). MYD88 L265P was absent in paired normal tissue samples from patients with Waldenström's macroglobulinemia or non-IgM LPL and in B cells from healthy donors and was absent or rarely expressed in samples from patients with multiple myeloma, marginal-zone lymphoma, or IgM monoclonal gammopathy of unknown significance. Inhibition of MYD88 signaling reduced IκBα and NF-κB p65 phosphorylation, as well as NF-κB nuclear staining, in Waldenström's macroglobulinemia cells expressing MYD88 L265P. Somatic variants in ARID1A in 5 of 30 patients (17%), leading to a premature stop or frameshift, were also identified and were associated with an increased disease burden. In addition, 2 of 3 patients with Waldenström's macroglobulinemia who had wild-type MYD88 had somatic variants in MLL2. CONCLUSIONS: MYD88 L265P is a commonly recurring mutation in patients with Waldenström's macroglobulinemia that can be useful in differentiating Waldenström's macroglobulinemia and non-IgM LPL from B-cell disorders that have some of the same features. (Funded by the Peter and Helen Bing Foundation and others.).

Power in the phenotypic extremes: a simulation study of power in discovery and replication of rare variants.

Next-generation sequencing technologies are making it possible to study the role of rare variants in human disease. Many studies balance statistical power with cost-effectiveness by (a) sampling from phenotypic extremes and (b) utilizing a two-stage design. Two-stage designs include a broad-based discovery phase and selection of a subset of potential causal genes/variants to be further examined in independent samples. We evaluate three parameters: first, the gain in statistical power due to extreme sampling to discover causal variants; second, the informativeness of initial (Phase I) association statistics to select genes/variants for follow-up; third, the impact of extreme and random sampling in (Phase 2) replication. We present a quantitative method to select individuals from the phenotypic extremes of a binary trait, and simulate disease association studies under a variety of sample sizes and sampling schemes. First, we find that while studies sampling from extremes have excellent power to discover rare variants, they have limited power to associate them to phenotype­suggesting high false-negative rates for upcoming studies. Second, consistent with previous studies, we find that the effect sizes estimated in these studies are expected to be systematically larger compared with the overall population effect size; in a well-cited lipids study, we estimate the reported effect to be twofold larger. Third, replication studies require large samples from the general population to have sufficient power; extreme sampling could reduce the required sample size as much as fourfold. Our observations offer practical guidance for the design and interpretation of studies that utilize extreme sampling.

Democratizing data at Novartis through clinical trial data access.

Enabling broad access and usage of clinical trial data within biopharmaceutical companies has historically been impeded by technical, cultural, and policy hurdles. Novartis has attempted to address this comprehensively through a program called data42; here, we explore how a diverse set of enterprise-wide stakeholders formulated a risk-based data access approach to streamline access to anonymized clinical trial data and vastly improved its use by authorized research and development (R&D) associates within the company. The result is that most Novartis clinical trial data requests, from internal associates, can now be automatically approved. The process of developing this framework and its impact on Novartis and the broader industry are explored and discussed.

Artificial intelligence and machine learning in clinical development: a translational perspective.

Future of clinical development is on the verge of a major transformation due to convergence of large new digital data sources, computing power to identify clinically meaningful patterns in the data using efficient artificial intelligence and machine-learning algorithms, and regulators embracing this change through new collaborations. This perspective summarizes insights, recent developments, and recommendations for infusing actionable computational evidence into clinical development and health care from academy, biotechnology industry, nonprofit foundations, regulators, and technology corporations. Analysis and learning from publically available biomedical and clinical trial data sets, real-world evidence from sensors, and health records by machine-learning architectures are discussed. Strategies for modernizing the clinical development process by integration of AI- and ML-based digital methods and secure computing technologies through recently announced regulatory pathways at the United States Food and Drug Administration are outlined. We conclude by discussing applications and impact of digital algorithmic evidence to improve medical care for patients.

The Gly2019Ser mutation in LRRK2 is not fully penetrant in familial Parkinson's disease: the GenePD study.

BACKGROUND: We report age-dependent penetrance estimates for leucine-rich repeat kinase 2 (LRRK2)-related Parkinson's disease (PD) in a large sample of familial PD. The most frequently seen LRRK2 mutation, Gly2019Ser (G2019S), is associated with approximately 5 to 6% of familial PD cases and 1 to 2% of idiopathic cases, making it the most common known genetic cause of PD. Studies of the penetrance of LRRK2 mutations have produced a wide range of estimates, possibly due to differences in study design and recruitment, including in particular differences between samples of familial PD versus sporadic PD. METHODS: A sample, including 903 affected and 58 unaffected members from 509 families ascertained for having two or more PD-affected members, 126 randomly ascertained PD patients and 197 controls, was screened for five different LRRK2 mutations. Penetrance was estimated in families of LRRK2 carriers with consideration of the inherent bias towards increased penetrance in a familial sample. RESULTS: Thirty-one out of 509 families with multiple cases of PD (6.1%) were found to have 58 LRRK2 mutation carriers (6.4%). Twenty-nine of the 31 families had G2019S mutations while two had R1441C mutations. No mutations were identified among controls or unaffected relatives of PD cases. Nine PD-affected relatives of G2019S carriers did not carry the LRRK2 mutation themselves. At the maximum observed age range of 90 to 94 years, the unbiased estimated penetrance was 67% for G2019S families, compared with a baseline PD risk of 17% seen in the non-LRRK2-related PD families. CONCLUSION: Lifetime penetrance of LRRK2 estimated in the unascertained relatives of multiplex PD families is greater than that reported in studies of sporadically ascertained LRRK2 cases, suggesting that inherited susceptibility factors may modify the penetrance of LRRK2 mutations. In addition, the presence of nine PD phenocopies in the LRRK2 families suggests that these susceptibility factors may also increase the risk of non-LRRK2-related PD. No differences in penetrance were found between men and women, suggesting that the factors that influence penetrance for LRRK2 carriers are independent of the factors which increase PD prevalence in men.

HaploBuild: an algorithm to construct non-contiguous associated haplotypes in family based genetic studies.

UNLABELLED: We have created a program that searches densely genotyped regions for associated non-contiguous haplotypes using a standard family based haplotype association test. This program was designed to expand upon the 'sliding window' methodologies commonly used for haplotype construction by allowing the association of subsets of single nucleotide polymorphisms (SNPs) to drive the construction of the haplotype. This strategy permits HaploBuild to construct more biologically relevant haplotypes that are not constrained by arbitrary length and contiguous orientation. AVAILABILITY: http://snp.bumc.bu.edu.

Polymorphisms near EXOC4 and LRGUK on chromosome 7q32 are associated with Type 2 Diabetes and fasting glucose; the NHLBI Family Heart Study.

BACKGROUND: The chromosome 7q32 region is linked to metabolic syndrome and obesity related traits in the Family Heart Study. As part of a fine mapping study of the region, we evaluated the relationship of polymorphisms to fasting glucose levels and Type 2 diabetes. METHODS: Thirty-nine HapMap defined tag SNPs in a 1.08 Mb region and a novel deletion polymorphism were genotyped in 2,603 participants of the NHLBI Family Heart Study (FHS). Regression modeling, adjusting for BMI, age, sex, smoking and the TCF7L2 polymorphism, was used to evaluate the association of these polymorphisms with T2D and fasting glucoses levels. RESULTS: The deletion polymorphism confers a protective effect for T2D, with homozygous deletion carriers having a 53% reduced risk compared to non-deleted carriers. Among non-diabetics, the deletion was significantly associated with lower fasting glucose levels in men (p = 0.038) but not women (p = 0.118). In addition, seven SNPs near the deletion were significantly associated (p < 0.01) to diabetes. CONCLUSION: Chromosome 7q32 contains both SNPs and a deletion that were associated to T2D. Although the deletion region contains several islands of strongly conserved sequence, it is not known to contain a transcribed gene. The closest nearby gene, EXOC4, is involved in insulin-stimulated glucose transport and may be a candidate for this association. Further work is needed to determine if the deletion represents a functional variant or may be in linkage disequilibrium with a functional mutation influencing EXOC4 or another nearby gene.

Transcriptional profiles of human epithelial cells in response to heat: computational evidence for novel heat shock proteins.

We hypothesized that broad-scale expression profiling would provide insight into the regulatory pathways that control gene expression in response to stress and potentially identify novel heat-responsive genes. HEp2 cells, a human malignant epithelial cell line, were heated at 37 degrees C to 43 degrees C for 60 min to gauge the heat shock response, using as a proxy inducible Hsp70 quantified by Western blot analysis. Based on these results, microarray experiments were conducted at 37 degrees C, 40 degrees C, 41 degrees C, 42 degrees C, and 43 degrees C. Using linear modeling, we compared the sets of microarrays at 40 degrees C, 41 degrees C, 42 degrees C, and 43 degrees C with the 37 degrees C baseline temperature and took the union of the genes exhibiting differential gene expression signal to create two sets of "heat shock response" genes, each set reflecting either increased or decreased RNA abundance. Leveraging human and mouse orthologous alignments, we used the two lists of coexpressed genes to predict transcription factor binding sites in silico, including those for heat shock factor (HSF) 1 and HSF2 transcription factors. We discovered HSF1 and HSF2 binding sites in 15 genes not previously associated with the heat shock response. We conclude that microarray experiments coupled with upstream promoter analysis can be used to identify novel genes that respond to heat shock. Additional experiments are required to validate these putative heat shock proteins and facilitate a deeper understanding of the mechanisms involved during the stress response.

Framingham Heart Study genome-wide association: results for pulmonary function measures.

BACKGROUND: Pulmonary function measures obtained by spirometry are used to diagnose chronic obstructive pulmonary disease (COPD) and are highly heritable. We conducted genome-wide association (GWA) analyses (Affymetrix 100K SNP GeneChip) for measures of lung function in the Framingham Heart Study. METHODS: Ten spirometry phenotypes including percent of predicted measures, mean spirometry measures over two examinations, and rates of change based on forced expiratory volume in one second (FEV1), forced vital capacity (FVC), forced expiratory flow from the 25th to 75th percentile (FEF25-75), the FEV1/FVC ratio, and the FEF25-75/FVC ratio were examined. Percent predicted phenotypes were created using each participant's latest exam with spirometry. Predicted lung function was estimated using models defined in the set of healthy never-smokers, and standardized residuals of percent predicted measures were created adjusting for smoking status, pack-years, and body mass index (BMI). All modeling was performed stratified by sex and cohort. Mean spirometry phenotypes were created using data from two examinations and adjusting for age, BMI, height, smoking and pack-years. Change in pulmonary function over time was studied using two to four examinations with spirometry to calculate slopes, which were then adjusted for age, height, smoking and pack-years. RESULTS: Analyses were restricted to 70,987 autosomal SNPs with minor allele frequency > or = 10%, genotype call rate > or = 80%, and Hardy-Weinberg equilibrium p-value > or = 0.001. A SNP in the interleukin 6 receptor (IL6R) on chromosome 1 was among the best results for percent predicted FEF25-75. A non-synonymous coding SNP in glutathione S-transferase omega 2 (GSTO2) on chromosome 10 had top-ranked results studying the mean FEV1 and FVC measurements from two examinations. SNPs nearby the SOD3 and vitamin D binding protein genes, candidate genes for COPD, exhibited association to percent predicted phenotypes. CONCLUSION: GSTO2 and IL6R are credible candidate genes for association to pulmonary function identified by GWA. These and other observed associations warrant replication studies. This resource of GWA results for pulmonary function measures is publicly available at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite.

The Framingham Heart Study 100K SNP genome-wide association study resource: overview of 17 phenotype working group reports.

BACKGROUND: The Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies. METHODS: Adult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests. RESULTS: The participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 +/- 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency > or + 10%, genotype call rate > or = 80%, Hardy-Weinberg equilibrium p-value > or = 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite. CONCLUSION: We have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.

Sepiapterin reductase expression is increased in Parkinson's disease brain tissue.

The PARK3 locus on chromosome 2p13 has shown linkage to both the development and age of onset of Parkinson's disease (PD). One candidate gene at this locus is sepiapterin reductase (SPR). Sepiapterin reductase catalyzes the final step in the biosynthetic pathway of tetrahydrobiopterin (BH(4)), an essential cofactor for aromatic amino acid hydrolases including tyrosine hydroxylase, the rate-limiting enzyme in dopamine synthesis. The expression of SPR was assayed using semiquantitative real-time RT-PCR in human post-mortem cerebellar tissue from neuropathologically confirmed PD cases and neurologically normal controls. The expression of other enzymes involved in BH(4) biosynthesis, including aldose reductase (AKR1B1), carbonyl reductase (CBR1 and CBR3), GTP-cyclohydrolase I (GCH1), and 6-pyruvoyltetrahydrobiopterin (PTS), was also examined. Single-nucleotide polymorphisms around the SPR gene that have been previously reported to show association to PD affection and onset age were genotyped in these samples. Expression of SPR showed a significant 4-fold increase in PD cases relative to controls, while the expression of AKR1B1 and PTS was significantly decreased in PD cases. No difference in expression was detected for CBR1, CBR3, and GCH1. Genetic variants did not show a significant effect on SPR expression, however, this is likely due to the low frequency of rare genotypes in the sample. While the association of SPR to PD is not strong enough to support that this is the PARK3 gene, this study further implicates a role for SPR in idiopathic PD.

A Bayesian mathematical model of motor and cognitive outcomes in Parkinson's disease.

BACKGROUND: There are few established predictors of the clinical course of PD. Prognostic markers would be useful for clinical care and research. OBJECTIVE: To identify predictors of long-term motor and cognitive outcomes and rate of progression in PD. METHODS: Newly diagnosed PD participants were followed for 7 years in a prospective study, conducted at 55 centers in the United States and Canada. Analyses were conducted in 244 participants with complete demographic, clinical, genetic, and dopamine transporter imaging data. Machine learning dynamic Bayesian graphical models were used to identify and simulate predictors and outcomes. The outcomes rate of cognition changes are assessed by the Montreal Cognitive Assessment scores, and rate of motor changes are assessed by UPDRS part-III. RESULTS: The most robust and consistent longitudinal predictors of cognitive function included older age, baseline Unified Parkinson's Disease Rating Scale (UPDRS) parts I and II, Schwab and England activities of daily living scale, striatal dopamine transporter binding, and SNP rs11724635 in the gene BST1. The most consistent predictor of UPDRS part III was baseline level of activities of daily living (part II). Key findings were replicated using long-term data from an independent cohort study. CONCLUSIONS: Baseline function near the time of Parkinson's disease diagnosis, as measured by activities of daily living, is a consistent predictor of long-term motor and cognitive outcomes. Additional predictors identified may further characterize the expected course of Parkinson's disease and suggest mechanisms underlying disease progression. The prognostic model developed in this study can be used to simulate the effects of the prognostic variables on motor and cognitive outcomes, and can be replicated and refined with data from independent longitudinal studies.

Evidence for a gene influencing heart rate on chromosome 5p13-14 in a meta-analysis of genome-wide scans from the NHLBI Family Blood Pressure Program.

BACKGROUND: Elevated resting heart rate has been shown in multiple studies to be a strong predictor of cardiovascular disease. Previous family studies have shown a significant heritable component to heart rate with several groups conducting genomic linkage scans to identify quantitative trait loci. METHODS: We performed a genome-wide linkage scan to identify quantitative trait loci influencing resting heart rate among 3,282 Caucasians and 3,989 African-Americans in three independent networks comprising the Family Blood Pressure Program (FBPP) using 368 microsatellite markers. Mean heart rate measurements were used in a regression model including covariates for age, body mass index, pack-years, currently drinking alcohol (yes/no), hypertension status and medication usage to create a standardized residual for each gender/ethnic group within each study network. This residual was used in a nonparametric variance component model to generate a LOD score and a corresponding P value for each ethnic group within each study network. P values from each ethnic group and study network were merged using an adjusted Fisher's combining P values method and the resulting P values were converted to LOD scores. The entire analysis was redone after individuals currently taking beta-blocker medication were removed. RESULTS: We identified significant evidence of linkage (LOD = 4.62) to chromosome 10 near 142.78 cM in the Caucasian group of HyperGEN. Between race and network groups we identified a LOD score of 1.86 on chromosome 5 (between 39.99 and 45.34 cM) in African-Americans in the GENOA network and the same region produced a LOD score of 1.12 among Caucasians within a different network (HyperGEN). Combining all network and race groups we identified a LOD score of 1.92 (P = 0.0013) on chromosome 5p13-14. We assessed heterogeneity for this locus between networks and ethnic groups and found significant evidence for low heterogeneity (P < or = 0.05). CONCLUSION: We found replication (LOD > 1) between ethnic groups and between study networks with low heterogeneity on chromosome 5p13-14 suggesting that a gene in this region influences resting heart rate.

Molecular diagnostics in sepsis: from bedside to bench.

BACKGROUND: Based on recent in vitro data, we tested the hypothesis that microarray expression profiles can be used to diagnose sepsis, distinguishing in vivo between sterile and infectious causes of systemic inflammation. STUDY DESIGN: Exploratory studies were conducted using spleens from septic patients and from mice with abdominal sepsis. Seven patients with sepsis after injury were identified retrospectively and compared with six injured patients. C57BL/6 male mice were subjected to cecal ligation and puncture, or to IP lipopolysaccharide. Control mice had sham laparotomy or injection of IP saline, respectively. A sepsis classification model was created and tested on blood samples from septic mice. RESULTS: Accuracy of sepsis prediction was obtained using cross-validation of gene expression data from 12 human spleen samples and from 16 mouse spleen samples. For blood studies, classifiers were constructed using data from a training data set of 26 microarrays. The error rate of the classifiers was estimated on seven de-identified microarrays, and then on a subsequent cross-validation for all 33 blood microarrays. Estimates of classification accuracy of sepsis in human spleen were 67.1%; in mouse spleen, 96%; and in mouse blood, 94.4% (all estimates were based on nested cross-validation). Lists of genes with substantial changes in expression between study and control groups were used to identify nine mouse common inflammatory response genes, six of which were mapped into a single pathway using contemporary pathway analysis tools. CONCLUSIONS: Sepsis induces changes in mouse leukocyte gene expression that can be used to diagnose sepsis apart from systemic inflammation.

Global gene expression in neuroendocrine tumors from patients with the MEN1 syndrome.

BACKGROUND: Multiple Endocrine Neoplasia type 1 (MEN1, OMIM 131100) is an autosomal dominant disorder characterized by endocrine tumors of the parathyroids, pancreatic islets and pituitary. The disease is caused by the functional loss of the tumor suppressor protein menin, coded by the MEN1 gene. The protein sequence has no significant homology to known consensus motifs. In vitro studies have shown menin binding to JunD, Pem, Smad3, NF-kappaB, nm23H1, and RPA2 proteins. However, none of these binding studies have led to a convincing theory of how loss-of-menin leads to neoplasia. RESULTS: Global gene expression studies on eight neuroendocrine tumors from MEN1 patients and 4 normal islet controls was performed utilizing Affymetrix U95Av2 chips. Overall hierarchical clustering placed all tumors in one group separate from the group of normal islets. Within the group of tumors, those of the same type were mostly clustered together. The clustering analysis also revealed 19 apoptosis-related genes that were under-expressed in the group of tumors. There were 193 genes that were increased/decreased by at least 2-fold in the tumors relative to the normal islets and that had a t-test significance value of p < or = 0.005. Forty-five of these genes were increased and 148 were decreased in the tumors relative to the controls. One hundred and four of the genes could be classified as being involved in cell growth, cell death, or signal transduction. The results from 11 genes were selected for validation by quantitative RT-PCR. The average correlation coefficient was 0.655 (range 0.235-0.964). CONCLUSION: This is the first analysis of global gene expression in MEN1-associated neuroendocrine tumors. Many genes were identified which were differentially expressed in neuroendocrine tumors arising in patients with the MEN1 syndrome, as compared with normal human islet cells. The expression of a group of apoptosis-related genes was significantly suppressed, suggesting that these genes may play crucial roles in tumorigenesis in this syndrome. We identified a number of genes which are attractive candidates for further investigation into the mechanisms by which menin loss causes tumors in pancreatic islets. Of particular interest are: FGF9 which may stimulate the growth of prostate cancer, brain cancer and endometrium; and IER3 (IEX-1), PHLDA2 (TSS3), IAPP (amylin), and SST, all of which may play roles in apoptosis.