Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients.

PURPOSE: The purpose of our study was to assess whether a model combining clinical factors, MR imaging features, and genomics would better predict overall survival of patients with glioblastoma (GBM) than either individual data type. METHODS: The study was conducted leveraging The Cancer Genome Atlas (TCGA) effort supported by the National Institutes of Health. Six neuroradiologists reviewed MRI images from The Cancer Imaging Archive (http://cancerimagingarchive.net) of 102 GBM patients using the VASARI scoring system. The patients' clinical and genetic data were obtained from the TCGA website (http://www.cancergenome.nih.gov/). Patient outcome was measured in terms of overall survival time. The association between different categories of biomarkers and survival was evaluated using Cox analysis. RESULTS: The features that were significantly associated with survival were: (1) clinical factors: chemotherapy; (2) imaging: proportion of tumor contrast enhancement on MRI; and (3) genomics: HRAS copy number variation. The combination of these three biomarkers resulted in an incremental increase in the strength of prediction of survival, with the model that included clinical, imaging, and genetic variables having the highest predictive accuracy (area under the curve 0.679±0.068, Akaike's information criterion 566.7, P<0.001). CONCLUSION: A combination of clinical factors, imaging features, and HRAS copy number variation best predicts survival of patients with GBM.

Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features.

Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.

#22 TCGA

Combined media monoprints on photographic paper. 16" x 20", DNA/Transformation Series. Private Collection

Distal and proximal colon cancers differ in terms of molecular, pathological, and clinical features.

BACKGROUND: Differences exist between the proximal and distal colon in terms of developmental origin, exposure to patterning genes, environmental mutagens, and gut flora. Little is known on how these differences may affect mechanisms of tumorigenesis, side-specific therapy response or prognosis. We explored systematic differences in pathway activation and their clinical implications. MATERIALS AND METHODS: Detailed clinicopathological data for 3045 colon carcinoma patients enrolled in the PETACC3 adjuvant chemotherapy trial were available for analysis. A subset of 1404 samples had molecular data, including gene expression and DNA copy number profiles for 589 and 199 samples, respectively. In addition, 413 colon adenocarcinoma from TCGA collection were also analyzed. Tumor side-effect on anti-epidermal growth factor receptor (EGFR) therapy was assessed in a cohort of 325 metastatic patients. Outcome variables considered were relapse-free survival and survival after relapse (SAR). RESULTS: Proximal carcinomas were more often mucinous, microsatellite instable (MSI)-high, mutated in key tumorigenic pathways, expressed a B-Raf proto-oncogene, serine/threonine kinase (BRAF)-like and a serrated pathway signature, regardless of histological type. Distal carcinomas were more often chromosome instable and EGFR or human epidermal growth factor receptor 2 (HER2) amplified, and more frequently overexpressed epiregulin. While risk of relapse was not different per side, SAR was much poorer for proximal than for distal stage III carcinomas in a multivariable model including BRAF mutation status [N = 285; HR 1.95, 95% CI (1.6-2.4), P < 0.001]. Only patients with metastases from a distal carcinoma responded to anti-EGFR therapy, in line with the predictions of our pathway enrichment analysis. CONCLUSIONS: Colorectal carcinoma side is associated with differences in key molecular features, some immediately druggable, with important prognostic effects which are maintained in metastatic lesions. Although within side significant molecular heterogeneity remains, our findings justify stratification of patients by side for retrospective and prospective analyses of drug efficacy and prognosis.

A Novel Volume-Age-KPS (VAK) Glioblastoma Classification Identifies a Prognostic Cognate microRNA-Gene Signature.

BACKGROUND: Several studies have established Glioblastoma Multiforme (GBM) prognostic and predictive models based on age and Karnofsky Performance Status (KPS), while very few studies evaluated the prognostic and predictive significance of preoperative MR-imaging. However, to date, there is no simple preoperative GBM classification that also correlates with a highly prognostic genomic signature. Thus, we present for the first time a biologically relevant, and clinically applicable tumor Volume, patient Age, and KPS (VAK) GBM classification that can easily and non-invasively be determined upon patient admission. METHODS: We quantitatively analyzed the volumes of 78 GBM patient MRIs present in The Cancer Imaging Archive (TCIA) corresponding to patients in The Cancer Genome Atlas (TCGA) with VAK annotation. The variables were then combined using a simple 3-point scoring system to form the VAK classification. A validation set (N = 64) from both the TCGA and Rembrandt databases was used to confirm the classification. Transcription factor and genomic correlations were performed using the gene pattern suite and Ingenuity Pathway Analysis. RESULTS: VAK-A and VAK-B classes showed significant median survival differences in discovery (P = 0.007) and validation sets (P = 0.008). VAK-A is significantly associated with P53 activation, while VAK-B shows significant P53 inhibition. Furthermore, a molecular gene signature comprised of a total of 25 genes and microRNAs was significantly associated with the classes and predicted survival in an independent validation set (P = 0.001). A favorable MGMT promoter methylation status resulted in a 10.5 months additional survival benefit for VAK-A compared to VAK-B patients. CONCLUSIONS: The non-invasively determined VAK classification with its implication of VAK-specific molecular regulatory networks, can serve as a very robust initial prognostic tool, clinical trial selection criteria, and important step toward the refinement of genomics-based personalized therapy for GBM patients.

Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer.

Invasive lobular carcinoma (ILC) is the second most prevalent histologic subtype of invasive breast cancer. Here, we comprehensively profiled 817 breast tumors, including 127 ILC, 490 ductal (IDC), and 88 mixed IDC/ILC. Besides E-cadherin loss, the best known ILC genetic hallmark, we identified mutations targeting PTEN, TBX3, and FOXA1 as ILC enriched features. PTEN loss associated with increased AKT phosphorylation, which was highest in ILC among all breast cancer subtypes. Spatially clustered FOXA1 mutations correlated with increased FOXA1 expression and activity. Conversely, GATA3 mutations and high expression characterized luminal A IDC, suggesting differential modulation of ER activity in ILC and IDC. Proliferation and immune-related signatures determined three ILC transcriptional subtypes associated with survival differences. Mixed IDC/ILC cases were molecularly classified as ILC-like and IDC-like revealing no true hybrid features. This multidimensional molecular atlas sheds new light on the genetic bases of ILC and provides potential clinical options.

Mir-21-Sox2 Axis Delineates Glioblastoma Subtypes with Prognostic Impact.

UNLABELLED: Glioblastoma (GBM) is the most aggressive human brain tumor. Although several molecular subtypes of GBM are recognized, a robust molecular prognostic marker has yet to be identified. Here, we report that the stemness regulator Sox2 is a new, clinically important target of microRNA-21 (miR-21) in GBM, with implications for prognosis. Using the MiR-21-Sox2 regulatory axis, approximately half of all GBM tumors present in the Cancer Genome Atlas (TCGA) and in-house patient databases can be mathematically classified into high miR-21/low Sox2 (Class A) or low miR-21/high Sox2 (Class B) subtypes. This classification reflects phenotypically and molecularly distinct characteristics and is not captured by existing classifications. Supporting the distinct nature of the subtypes, gene set enrichment analysis of the TCGA dataset predicted that Class A and Class B tumors were significantly involved in immune/inflammatory response and in chromosome organization and nervous system development, respectively. Patients with Class B tumors had longer overall survival than those with Class A tumors. Analysis of both databases indicated that the Class A/Class B classification is a better predictor of patient survival than currently used parameters. Further, manipulation of MiR-21-Sox2 levels in orthotopic mouse models supported the longer survival of the Class B subtype. The MiR-21-Sox2 association was also found in mouse neural stem cells and in the mouse brain at different developmental stages, suggesting a role in normal development. Therefore, this mechanism-based classification suggests the presence of two distinct populations of GBM patients with distinguishable phenotypic characteristics and clinical outcomes. SIGNIFICANCE STATEMENT: Molecular profiling-based classification of glioblastoma (GBM) into four subtypes has substantially increased our understanding of the biology of the disease and has pointed to the heterogeneous nature of GBM. However, this classification is not mechanism based and its prognostic value is limited. Here, we identify a new mechanism in GBM (the miR-21-Sox2 axis) that can classify ∼50% of patients into two subtypes with distinct molecular, radiological, and pathological characteristics. Importantly, this classification can predict patient survival better than the currently used parameters. Further, analysis of the miR-21-Sox2 relationship in mouse neural stem cells and in the mouse brain at different developmental stages indicates that miR-21 and Sox2 are predominantly expressed in mutually exclusive patterns, suggesting a role in normal neural development.

Targeting oncogenic signaling proteins : new insights using a FRET-based chemical biology approach

Cancer affects more than 20 million people each year and this rate is increasing globally. The Ras/MAPK-pathway is one of the best-studied cancer signaling pathways. Ras proteins are mutated in almost 20% of all human cancers and despite numerous efforts, no effective therapy that specifically targets Ras is available to date. It is now well established that Ras proteins laterally segregate on the plasma membrane into transient nanoscale signaling complexes called nanoclusters. These Ras nanoclusters are essential for the high-fidelity signal transmission. Disruption of nanoclustering leads to reduction in Ras activity and signaling, therefore targeting nanoclusters opens up important new therapeutic possibilities in cancer. This work describes three different studies exploring the idea of membrane protein nanoclusters as novel anti-cancer drug targets. It is focused on the design and implementation of a simple, cell-based Förster Resonance Energy Transfer (FRET)-biosensor screening platform to identify compounds that affect Ras membrane organization and nanoclustering. Chemical libraries from different sources were tested and a number of potential hit molecules were validated on full-length oncogenic proteins using a combination of imaging, biochemical and transformation assays. In the first study, a small chemical library was screened using H-ras derived FRET-biosensors. Surprisingly from this screen, commonly used protein synthesis inhibitors (PSIs) were found to specifically increase H-ras nanoclustering and downstream signalling in a H-ras dependent manner. Using a representative PSI, increase in H-ras activity was shown to induce cancer stem cell (CSC)-enriched mammosphere formation and tumor growth of breast cancer cells. Moreover, PSIs do not increase K-ras nanoclustering, making this screening approach suitable for identifying Ras isoform-specific inhibitors. In the second study, a nanoncluster-directed screen using both H- and K-ras derived FRET biosensors identified CSC inhibitor salinomycin to specifically inhibit K-ras nanocluster organization and downstream signaling. A K-ras nanoclusteringassociated gene signature was established that predicts the drug sensitivity of cancer cells to CSC inhibitors. Interestingly, almost 8% of patient tumor samples in the The Cancer Genome Atlas (TCGA) database had the above gene signature and were associated with a significantly higher mortality. From this mechanistic insight, an additional microbial metabolite screen on H- and K-ras biosensors identified ophiobolin A and conglobatin A to specifically affect K-ras nanoclustering and to act as potential breast CSC inhibitors. In the third study, the Ras FRET-biosensor principle was used to investigate membrane anchorage and nanoclustering of myristoylated proteins such as heterotrimeric G-proteins, Yes- and Src-kinases. Furthermore, Yes-biosensor was validated to be a suitable platform for performing chemical and genetic screens to identify myristoylation inhibitors. The results of this thesis demonstrate the potential of the Ras-derived FRETbiosensor platform to differentiate and identify Ras-isoform specfic inhibitors. The results also highlight that most of the inhibitors identified predominantly perturb Ras subcellular distribution and membrane organization through some novel and yet unknown mechanisms. The results give new insights into the role of Ras nanoclusters as promising new molecular targets in cancer and in stem cells.

Understanding the transcriptional control of EIF4E and its dysregulation in acute myeloid leukemia: role of NF-κB

EIF4E, le facteur d’initiation de la traduction chez les eucaryotes est un oncogène puissant et qui se trouve induit dans plusieurs types de cancers, parmi lesquels les sous-types M4 et M5 de la leucémie aiguë myéloblastique (LAM). EIF4E est régulé à plusieurs niveaux cependant, la régulation transcriptionnelle de ce gène est peu connue. Mes résultats montrent que EIF4E est une cible transcriptionnelle directe du facteur nucléaire « kappa-light- chain- enhancer of activated B cells » (NF-κB).Dans les cellules hématopoïétiques primaires et les lignées cellulaires, les niveaux de EIF4E sont induits par des inducteurs de NF-κB. En effet, l’inactivation pharmaceutique ou génétique de NF-κB réprime l’activation de EIF4E. En effet, suite à l’activation de NF-κB chez l’humain, le promoteur endogène de EIF4E recrute p65 (RelA) et c-Rel aux sites évolutionnaires conservés κB in vitro et in vivo en même temps que p300 ainsi que la forme phosphorylée de Pol II. De plus, p65 est sélectivement associé au promoteur de EIF4E dans les sous-types LAM M4/M5 mais non pas dans les autres sous-types LAM ou dans les cellules hématopoïétiques primaires normales. Ceci indique que ce processus représente un facteur essentiel qui détermine l’expression différentielle de EIF4E dans la LAM. Les analyses de données d’expressions par séquençage de l’ARN provenant du « Cancer Genome Atlas » (TCGA) suggèrent que les niveaux d’ARNm de EIF4E et RELA se trouvent augmentés dans les cas LAM à pronostic intermédiaire ou faible mais non pas dans les groupes cytogénétiquement favorables. De plus, des niveaux élevés d’ARNm de EIF4E et RELA sont significativement associés avec un taux de survie relativement bas chez les patients. En effet, les sites uniques κB se trouvant dans le promoteur de EIF4E recrutent le régulateur de transcription NF-κB p65 dans 47 nouvelles cibles prévues. Finalement, 6 nouveaux facteurs de transcription potentiellement impliqués dans la régulation du gène EIF4E ont été prédits par des analyses de données ChIP-Seq provenant de l’encyclopédie des éléments d’ADN (ENCODE). Collectivement, ces résultats fournissent de nouveaux aperçus sur le control transcriptionnel de EIF4E et offrent une nouvelle base moléculaire pour sa dérégulation dans au moins un sous-groupe de spécimens de LAM. L’étude et la compréhension de ce niveau de régulation dans le contexte de spécimens de patients s’avère important pour le développement de nouvelles stratégies thérapeutiques ciblant l’expression du gène EIF4E moyennant des inhibiteurs de NF-κB en combinaison avec la ribavirine.

Detrimental effects of exuberant and restrained immune responses against the central nervous system in the context of multiple sclerosis and glioblastoma multiforme

Glioblastoma multiforme (GBM) is the most common and most aggressive astrocytic tumor of the central nervous system (CNS) in adults. The standard treatment consisting of surgery, followed by a combinatorial radio- and chemotherapy, is only palliative and prolongs patient median survival to 12 to 15 months. The tumor subpopulation of stem cell-like glioma-initiating cells (GICs) shows resistance against radiation as well as chemotherapy, and has been suggested to be responsible for relapses of more aggressive tumors after therapy. The efficacy of immunotherapies, which exploit the immune system to specifically recognize and eliminate malignant cells, is limited due to strong immunosuppressive activities of the GICs and the generation of a specialized protective microenvironment. The molecular mechanisms underlying the therapy resistance of GICs are largely unknown. rnThe first aim of this study was to identify immune evasion mechanisms in GICs triggered by radiation. A model was used in which patient-derived GICs were treated in vitro with fractionated ionizing radiation (2.5 Gy in 7 consecutive passages) to select for a more radio-resistant phenotype. In the model cell line 1080, this selection process resulted in increased proliferative but diminished migratory capacities in comparison to untreated control GICs. Furthermore, radio-selected GICs downregulated various proteins involved in antigen processing and presentation, resulting in decreased expression of MHC class I molecules on the cellular surface and diminished recognition potential by cytotoxic CD8+ T cells. Thus, sub-lethal fractionated radiation can promote immune evasion and hamper the success of adjuvant immunotherapy. Among several immune-associated proteins, interferon-induced transmembrane protein 3 (IFITM3) was found to be upregulated in radio-selected GICs. While high expression of IFITM3 was associated with a worse overall survival of GBM patients (TCGA database) and increased proliferation and migration of differentiated glioma cell lines, a strong contribution of IFITM3 to proliferation in vitro as well as tumor growth and invasiveness in a xenograft model could not be observed. rnMultiple sclerosis (MS) is the most common autoimmune disease of the CNS in young adults of the Western World, which leads to progressive disability in genetically susceptible individuals, possibly triggered by environmental factors. It is assumed that self-reactive, myelin-specific T helper cell 1 (Th1) and Th17 cells, which have escaped the control mechanisms of the immune system, are critical in the pathogenesis of the human disease and its animal model experimental autoimmune encephalomyelitis (EAE). It was observed that in vitro differentiated interleukin 17 (IL-17) producing Th17 cells co-expressed the Th1-phenotypic cytokine Interferon-gamma (IFN-γ) in combination with the two respective lineage-associated transcription factors RORγt and T-bet after re-isolation from the CNS of diseased mice. Pathogenic molecular mechanisms that render a CD4+ T cell encephalitogenic have scarcely been investigated up to date. rnIn the second part of the thesis, whole transcriptional changes occurring in in vitro differentiated Th17 cells in the course of EAE were analyzed. Evaluation of signaling networks revealed an overrepresentation of genes involved in communication between the innate and adaptive immune system and metabolic alterations including cholesterol biosynthesis. The transcription factors Cebpa, Fos, Klf4, Nfatc1 and Spi1, associated with thymocyte development and naïve T cells were upregulated in encephalitogenic CNS-isolated CD4+ T cells, proposing a contribution to T cell plasticity. Correlation of the murine T-cell gene expression dataset to putative MS risk genes, which were selected based on their proximity (± 500 kb; ensembl database, release 75) to the MS risk single nucleotide polymorphisms (SNPs) proposed by the most recent multiple sclerosis GWAS in 2011, revealed that 67.3% of the MS risk genes were differentially expressed in EAE. Expression patterns of Bach2, Il2ra, Irf8, Mertk, Odf3b, Plek, Rgs1, Slc30a7, and Thada were confirmed in independent experiments, suggesting a contribution to T cell pathogenicity. Functional analysis of Nfatc1 revealed that Nfatc1-deficient CD4+ T cells were restrained in their ability to induce clinical signs of EAE. Nfatc1-deficiency allowed proper T cell activation, but diminished their potential to fully differentiate into Th17 cells and to express high amounts of lineage cytokines. As the inducible Nfatc1/αA transcript is distinct from the other family members, it could represent an interesting target for therapeutic intervention in MS.rn

TBX3-Mutationsanalysen und Konstruktion einer Zelllinie für TBX2-Inhibitorscreenings

Die nahe verwandten T-box Transkriptionsfaktoren TBX2 und TBX3 werden in zahlreichen humanen Krebsarten überexprimiert, insbesondere in Brustkrebs und Melanomen. Die Überexpression von TBX2 und TBX3 hat verschiedene zelluläre Effekte, darunter die Unterdrückung der Seneszenz, die Förderung der Epithelialen-Mesenchymalen Transition sowie invasive Zellmotilität. Im Gegensatz dazu führt ein Funktionsverlust von TBX3 und der meisten anderen humanen T-box-Gene zu haploinsuffizienten Entwicklungsdefekten. Durch Sequenzierung des Exoms von Brustkrebsproben identifizierten Stephens et al. fünf verschiedene Mutationen in TBX3, welche allesamt die DNA-bindende T-box-Domäne betrafen. Die In-Frame-Deletion N212delN wurde zweimal gefunden. Aus der Anhäufung der Mutationen innerhalb der T-box-Domäne wurde geschlossen, dass TBX3 bei Brustkrebs ein Treibergen ist. Da Mutationen innerhalb der T-box-Domäne im Allgemeinen zu einem Funktionsverlust führen, aber die onkogene Aktivität von TBX3 meist auf eine Überexpression zurückzuführen ist, wurden die potentiellen Treibermutationen hinsichtlich einer verminderten oder gesteigerten TBX3-Funktion geprüft. Getestet wurden zwei In-Frame Deletionen, eine Missense- sowie eine Frameshift-Mutante bezüglich der DNA-Bindung in vitro und der Zielgen-Repression in Zellkultur. Zusätzlich wurde eine in silico Analyse der im The Cancer Genome Atlas (TCGA) gelisteten somatischen TBX-Brustkrebsmutationen durchgeführt. Sowohl die experimentelle als auch die in silico Analyse zeigten, dass die untersuchten Mutationen vorwiegend zum Verlust der TBX3-Funktion führen. Um den Mechanismus der Genrepression durch TBX3 besser zu verstehen, wurden weitere TBX3-Mutanten bezüglich ihrer Wirkung auf die p21-Promotoraktivität (p21-Luc-Reporter und endogene p21-Expression) analysiert. Wildtypische p21-Luc-Repression zeigten die zwei Mutationen S674A (Phosphorylierung) und D275K (SUMOylierung), welche posttranslationale Modifikationen verhindern, sowie die Interaktion mit dem Tumorsuppressor Rb1 unterbindende M302A/V304A-Mutation. Erstaunlicherweise war die endogene p21-Repression dieser Mutanten stärker als die des wildtypischen TBX3-Proteins. Alle drei Mutationen führten zu einer Stabilisierung des TBX3-Proteins. Die ursprünglich in Patienten mit Ulna-Mamma Syndrom identifizierte, DNA-bindungsdefekte Y149S-Mutante konnte weder p21-Luc noch endogenes p21 reprimieren. Mutationen in potentiellen Interaktionsdomänen für die Bindung der Co-Repressoren Groucho und C-terminalem Bindeprotein zeigten sowohl auf p21-Luc als auch auf endogenes p21-Gen wildtypische Repressoraktivität, so dass diese Co-Repressoren in COS-7-Zellen wahrscheinlich nicht an der Repression dieses Gens beteiligt sind. Da TBX2 und TBX3 interessante Ziele zur direkten Krebsbekämpfung darstellen, sollte ein zelluläres Reportersystem zur Identifikation TBX2-inhibierender, pharmakologisch aktiver Substanzen etabliert werden. Dazu sollte eine stabile Zelllinie mit vom p21-Promotor reguliertem d2EGFP-Reporter und Doxyzyklin-induzierbarem TBX2-Protein erzeugt werden, da ektopische Expression von TBX2 genetische Instabilität und Toxizität induzieren kann. In dieser Zelllinie sollte die TBX2-Expression zur Reduktion der d2EGFP-Fluoreszenz führen. Zur Erzeugung der Zelllinie wurden die folgenden drei Konstrukte Schritt-für-Schritt stabil in das Genom der Zielzelllinie COS-7 integriert: pEF1alpha-Tet3G, pTRE3G-TBX2 und p21-d2EGFP. Während die Herstellung der doppelt stabilen COS-7-Zelllinie gelang, scheiterte die Herstellung der dreifach stabilen Zelllinie.

Contribution of Ectodomain Mutations in Epidermal Growth Factor Receptor to Signaling in Glioblastoma Multiforme

CONTRIBUTION OF ECTODOMAIN MUTATIONS IN EPIDERMAL GROWTH FACTOR RECEPTOR TO SIGNALING IN GLIOBLASTOMA MULTIFORME Publication No._________ Marta Rojas, M.S. Supervisory Professor: Oliver Bögler, Ph.D. The Cancer Genome Atlas (TCGA) has conducted a comprehensive analysis of a large tumor cohort and has cataloged genetic alterations involving primary sequence variations and copy number aberrations of genes involved in key signaling pathways in glioblastoma (GBM). This dataset revealed missense ectodomain point mutations in epidermal growth factor receptor (EGFR), but the biological and clinical significance of these mutations is not well defined in the context of gliomas. In our study, we focused on understanding and defining the molecular mechanisms underlying the functions of EGFR ectodomain mutants. Using proteomic approaches to broadly analyze cell signaling, including antibody array and mass spectrometry-based methods, we found a differential spectrum of tyrosine phosphorylation across the EGFR ectodomain mutations that enabled us to stratify them into three main groups that correlate with either wild type EGFR (EGFR) or the long-studied mutant, EGFRvIII. Interestingly, one mutant shared characteristics of both groups suggesting a continuum of behaviors along which different mutants fall. Surprisingly, no substantial differences were seen in activation of classical downstream signaling pathways such as Akt and S6 pathways between these classes of mutants. Importantly, we demonstrated that ectodomain mutations lead to differential tumor growth capabilities in both in vitro (anchorage independent colony formation) and in vivo conditions (xenografts). Our data from the biological characterization allowed us to categorize the mutants into three main groups: the first group typified by EGFRvIII are mutations with a more aggressive phenotype including R108K and A289T; a second group characterized by a less aggressive phenotype exemplified by EGFR and the T263P mutation; and a third group which shared characteristics from both groups and is exemplified by the mutation A289D. In addition, we treated cells overexpressing the mutants with various agents employed in the clinic including temozolomide, cisplatin and tarceva. We found that cells overexpressing the mutants in general displayed resistance to the treatments. Our findings yield insights that help with the molecular characterization of these mutants. In addition, our results from the drug studies might be valuable in explaining differential responses to specific treatments in GBM patients.

Identification of micro-RNAs targeting genes of PI3K/AKT pathway in ovarian cancer

Ovarian cancer is the leading cause of cancer-related death for females due to lack of specific early detection method. It is of great interest to find molecular-based biomarkers which are sensitive and specific to ovarian cancer for early diagnosis, prognosis and therapeutics. miRNAs have been proposed to be potential biomarkers that could be used in cancer prevention and therapeutics. The current study analyzed the miRNA and mRNA expression data extracted from the Cancer Genome Atlas (TCGA) database. Using simple linear regression and multiple regression models, we found 71 miRNA-mRNA pairs which were negatively associated between 56 miRNAs and 24 genes of PI3K/AKT pathway. Among these miRNA and mRNA target pairs, 9 of them were in agreement with the predictions from the most commonly used target prediction programs including miRGen, miRDB, miRTarbase and miR2Disease. These shared miRNA-mRNA pairs were considered to be the most potential genes that were involved in ovarian cancer. Furthermore, 4 of the 9 target genes encode cell cycle or apoptosis related proteins including Cyclin D1, p21, FOXO1 and Bcl2, suggesting that their regulator miRNAs including miR-16, miR-96 and miR-21 most likely played important roles in promoting tumor growth through dysregulated cell cycle or apoptosis. miR-96 was also found to directly target IRS-1. In addition, the results showed that miR-17 and miR-9 may be involved in ovarian cancer through targeting JAK1. This study might provide evidence for using miRNA or miRNA profile as biomarker.^

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.

Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus

BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk