Age-Specific Signatures of Glioblastoma at the Genomic, Genetic, and Epigenetic Levels

Age is a powerful predictor of survival in glioblastoma multiforme (GBM) yet the biological basis for the difference in clinical outcome is mostly unknown. Discovering genes and pathways that would explain age-specific survival difference could generate opportunities for novel therapeutics for GBM. Here we have integrated gene expression, exon expression, microRNA expression, copy number alteration, SNP, whole exome sequence, and DNA methylation data sets of a cohort of GBM patients in The Cancer Genome Atlas (TCGA) project to discover age-specific signatures at the transcriptional, genetic, and epigenetic levels and validated our findings on the REMBRANDT data set. We found major age-specific signatures at all levels including age-specific hypermethylation in polycomb group protein target genes and the upregulation of angiogenesis-related genes in older GBMs. These age-specific differences in GBM, which are independent of molecular subtypes, may in part explain the preferential effects of anti-angiogenic agents in older GBM and pave the way to a better understanding of the unique biology and clinical behavior of older versus younger GBMs

INTEGRATIVE ANALYSIS OF OMICS DATA IN ADULT GLIOMA AND OTHER TCGA CANCERS TO GUIDE PRECISION MEDICINE

Transcriptomic profiling and gene expression signatures have been widely applied as effective approaches for enhancing the molecular classification, diagnosis, prognosis or prediction of therapeutic response towards personalized therapy for cancer patients. Thanks to modern genome-wide profiling technology, scientists are able to build engines leveraging massive genomic variations and integrating with clinical data to identify “at risk” individuals for the sake of prevention, diagnosis and therapeutic interventions. In my graduate work for my Ph.D. thesis, I have investigated genomic sequencing data mining to comprehensively characterise molecular classifications and aberrant genomic events associated with clinical prognosis and treatment response, through applying high-dimensional omics genomic data to promote the understanding of gene signatures and somatic molecular alterations contributing to cancer progression and clinical outcomes. Following this motivation, my dissertation has been focused on the following three topics in translational genomics. 1) Characterization of transcriptomic plasticity and its association with the tumor microenvironment in glioblastoma (GBM). I have integrated transcriptomic, genomic, protein and clinical data to increase the accuracy of GBM classification, and identify the association between the GBM mesenchymal subtype and reduced tumorpurity, accompanied with increased presence of tumor-associated microglia. Then I have tackled the sole source of microglial as intrinsic tumor bulk but not their corresponding neurosphere cells through both transcriptional and protein level analysis using a panel of sphere-forming glioma cultures and their parent GBM samples.FurthermoreI have demonstrated my hypothesis through longitudinal analysis of paired primary and recurrent GBM samples that the phenotypic alterations of GBM subtypes are not due to intrinsic proneural-to-mesenchymal transition in tumor cells, rather it is intertwined with increased level of microglia upon disease recurrence. Collectively I have elucidated the critical role of tumor microenvironment (Microglia and macrophages from central nervous system) contributing to the intra-tumor heterogeneity and accurate classification of GBM patients based on transcriptomic profiling, which will not only significantly impact on clinical perspective but also pave the way for preclinical cancer research. 2) Identification of prognostic gene signatures that stratify adult diffuse glioma patientsharboring1p/19q co-deletions. I have compared multiple statistical methods and derived a gene signature significantly associated with survival by applying a machine learning algorithm. Then I have identified inflammatory response and acetylation activity that associated with malignant progression of 1p/19q co-deleted glioma. In addition, I showed this signature translates to other types of adult diffuse glioma, suggesting its universality in the pathobiology of other subset gliomas. My efforts on integrative data analysis of this highly curated data set usingoptimizedstatistical models will reflect the pending update to WHO classification system oftumorsin the central nervous system (CNS). 3) Comprehensive characterization of somatic fusion transcripts in Pan-Cancers. I have identified a panel of novel fusion transcripts across all of TCGA cancer types through transcriptomic profiling. Then I have predicted fusion proteins with kinase activity and hub function of pathway network based on the annotation of genetically mobile domains and functional domain architectures. I have evaluated a panel of in -frame gene fusions as potential driver mutations based on network fusion centrality hypothesis. I have also characterised the emerging complexity of genetic architecture in fusion transcripts through integrating genomic structure and somatic variants and delineating the distinct genomic patterns of fusion events across different cancer types. Overall my exploration of the pathogenetic impact and clinical relevance of candidate gene fusions have provided fundamental insights into the management of a subset of cancer patients by predicting the oncogenic signalling and specific drug targets encoded by these fusion genes. Taken together, the translational genomic research I have conducted during my Ph.D. study will shed new light on precision medicine and contribute to the cancer research community. The novel classification concept, gene signature and fusion transcripts I have identified will address several hotly debated issues in translational genomics, such as complex interactions between tumor bulks and their adjacent microenvironments, prognostic markers for clinical diagnostics and personalized therapy, distinct patterns of genomic structure alterations and oncogenic events in different cancer types, therefore facilitating our understanding of genomic alterations and moving us towards the development of precision medicine

Molecular and Genetic Determinants of Glioma Cell Invasion.

A diffusely invasive nature is a major obstacle in treating a malignant brain tumor, "diffuse glioma", which prevents neurooncologists from surgically removing the tumor cells even in combination with chemotherapy and radiation. Recently updated classification of diffuse gliomas based on distinct genetic and epigenetic features has culminated in a multilayered diagnostic approach to combine histologic phenotypes and molecular genotypes in an integrated diagnosis. However, it is still a work in progress to decipher how the genetic aberrations contribute to the aggressive nature of gliomas including their highly invasive capacity. Here we depict a set of recent discoveries involving molecular genetic determinants of the infiltrating nature of glioma cells, especially focusing on genetic mutations in receptor tyrosine kinase pathways and metabolic reprogramming downstream of common cancer mutations. The specific biology of glioma cell invasion provides an opportunity to explore the genotype-phenotype correlation in cancer and develop novel glioma-specific therapeutic strategies for this devastating disease

Molecular hallmarks of gliomas

Gliomas are a heterogeneous group of neoplasias that account for the majority of primary tumors of the central nervous system, of which glioblastoma multiforme is by far the most common and malignant subtype. These are particularly dramatic diseases, as they rank first among all human tumor types for the tumor‐related average years of life lost, and for which curative therapies are not yet available. Their etiology remains mostly undetermined: so far, only exposure to high‐dose therapeutic radiation has been firmly established as a risk factor, but other plausible causes include genetic syndromes, familial aggregation, and genetic polymorphisms. Equally mysterious are truly clinically‐relevant prognostic factors of glioma patients; patient age at diagnosis and clinical performance status are classic features associated with patient outcome, but recent evidences suggest that tumor’s molecular traits are also major determinants of prognosis. The outcome of glioblastoma patients is remarkably variable and unpredictable. Regardless, all patients are equally treated with a standardized therapeutic approach. It is widely acknowledged that a set of molecular (genetic and epigenetic) markers predictive of patient outcome, and/or tumor response to specific therapies, will be the basis of a molecular stratification of subgroups of glioblastoma and may prove crucial in rationalizing treatment decisions. However, well-established and clinically relevant biomarkers of prognosis of glioblastoma patients are still lacking. The methylation status of the promoter region of MGMT is currently the most promising, but has not reached clinical applicability. In this context, one of the most important research fields in neuro-oncology today is the identification of molecular determinants of survival and therapy response in glioma patients. This is very relevant because if patients with poor prognosis could be identified at the time of surgery, they would be followed more closely and would be promptly directed to potentially effective experimental therapies, rather than suffering the effects of ineffective and expensive treatments. Identifying new molecular markers and understanding their functional mechanisms in these aggressive therapy-insensitive gliomas may also be the first step in designing novel therapies. The general aim of this chapter is to review some of the most relevant genetic and epigenetic hallmarks of glial tumors, with a particular emphasis on those molecular alterations that have been suggested to affect the prognosis of glioma patients. Naturally, a special focus will be given to glioblastoma, one of the highest devastating human tumors. The chapter is organized in individual subsections, which are more interrelated than autonomous, starting with a brief summary of the classification, epidemiology, and treatment of gliomas. Subsequently, the different types of molecular alterations are defined and discussed in the context of brain gliomas, as well as the interaction between these different features. The molecular alterations are specific to tumor subtype and grade, and may be genetic, including deletion, gain, amplification, mutation, and translocation, or epigenetic, such as DNA CpG island hypermethylation, gene-specific and global genome-wide hypomethylation, and aberrant post-translational histone modifications. Together, these molecular aberrations result in altered gene expression profiles, including oncogene activation, tumor suppressor gene inactivation, loss of imprinting, and chromosomal instability, which ultimately culminate in uncontrolled cell division, deregulation of programmed cell death mechanisms, and limitless replication potential, favoring tumor expansion, angiogenesis, and infiltration into surrounding normal brain tissue. Although epigenetic alterations are usually studied independently of genetic alterations, there is interaction on specific genes, signaling pathways and within chromosomal domains. For example, we recently found that a chromosomal domain of transcriptional aberrant activation encompassing the HOXA genes is present in a subgroup of glioblastoma, and demonstrated that a PI3K‐associated epigenetic mechanism reversibly regulates this domain via histone modifications. In addition, we showed that reactivation of HOXA9 expression, one of the genes within this domain, is a novel, independent, and negative prognostic factor in glioblastoma patients, highlighting the clinical relevance of concurrent genetic and epigenetic events in brain tumors. A particular emphasis will be given to some of the currently most promising biomarkers of glioma prognosis (e.g., MGMT promoter methylation, IDH genes mutations, HOXA genes activation), and some of the challenges for future studies in the field of glioma biomarkers will be discussed

High-Resolution Cartography of the Transcriptome and Methylome Landscapes of Diffuse Gliomas

Molecular mechanisms of lower-grade (II–III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendroglioma-like (IDH-O) tumors both carrying mutations(s) at the isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma resemblance. We generated detailed maps of the transcriptomes and DNA methylomes, revealing that cell functions divided into three major archetypic hallmarks: (i) increased proliferation in IDH-wt and, to a lesser degree, IDH-O; (ii) increased inflammation in IDH-A and IDH-wt; and (iii) the loss of synaptic transmission in all subtypes. Immunogenic properties of IDH-A are diverse, partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We analyzed details of coregulation between gene expression and DNA methylation and of the immunogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby, molecular cartography provides a graphical coordinate system that links gene-level information with glioma subtypes, their phenotypes, and clinical context

Molecular Neuropathology of Gliomas

Gliomas are the most common primary human brain tumors. They comprise a heterogeneous group of benign and malignant neoplasms that are histologically classified according to the World Health Organization (WHO) classification of tumors of the nervous system. Over the past 20 years the cytogenetic and molecular genetic alterations associated with glioma formation and progression have been intensely studied and genetic profiles as additional aids to the definition of brain tumors have been incorporated in the WHO classification. In fact, first steps have been undertaken in supplementing classical histopathological diagnosis by the use of molecular tests, such as MGMT promoter hypermethylation in glioblastomas or detection of losses of chromosome arms 1p and 19q in oligodendroglial tumors. The tremendous progress that has been made in the use of array-based profiling techniques will likely contribute to a further molecular refinement of glioma classification and lead to the identification of glioma core pathways that can be specifically targeted by more individualized glioma therapies

A Distinct DNA Methylation Shift in a Subset of Glioma CpG Island Methylator Phenotypes during Tumor Recurrence

Glioma diagnosis is based on histomorphology and grading; however, such classification does not have predictive clinical outcome after glioblastomas have developed. To date, no bona fide biomarkers that significantly translate into a survival benefit to glioblastoma patients have been identified. We previously reported that the IDH mutant G-CIMP-high subtype would be a predecessor to the G-CIMP-low subtype. Here, we performed a comprehensive DNA methylation longitudinal analysis of diffuse gliomas from 77 patients (200 tumors) to enlighten the epigenome-based malignant transformation of initially lower-grade gliomas. Intra-subtype heterogeneity among G-CIMP-high primary tumors allowed us to identify predictive biomarkers for assessing the risk of malignant recurrence at early stages of disease. G-CIMP-low recurrence appeared in 9.5% of all gliomas, and these resembled IDH-wild-type primary glioblastoma. G-CIMP-low recurrence can be characterized by distinct epigenetic changes at candidate functional tissue enhancers with AP-1/SOX binding elements, mesenchymal stem cell-like epigenomic phenotype, and genomic instability. Molecular abnormalities of longitudinal G-CIMP offer possibilities to defy glioblastoma progression

Novel Oncogenic Drivers in Pediatric Gliomagenesis

Pediatric high-grade gliomas (pHGGs), with a two-year survival rate of less than 20%, are some of the most aggressive human cancers. This dissertation begins with our analysis of 127 pHGGs, including brainstem (BS) and non-brainstem (NBS) tumors, from 118 patients using next-generation sequencing technologies. Nearly one-third of BS-HGGs, also known as diffuse intrinsic pontine gliomas (DIPGs), harbored somatic heterozygous missense mutations in ACVR1, coding for a receptor serine-threonine kinase involved in bone morphogenetic protein (BMP) signaling. These alterations led to gain-of-function as evidenced by increased phosphorylation of downstream targets in primary astrocytes and zebrafish embryo ventralization. Whole-genome sequencing and RNASeq revealed that nearly half of our cohort contained structural variants. We identified recurrent gene fusions preserving the kinase domain of the neurotrophin family of receptor tyrosine kinases (NTRK) including three novel fusions and two fusions previously described in other tumor types. NTRK fusion genes were identified in 40% of infant (\u3c3 years of age) NBS-HGGs, and 7% of pHGG overall. We also found that infants have significantly reduced mutation burdens when compared to pHGGs in older children, suggesting a small number of oncogenic mutations are required in infant tumors. These findings, coupled with the observation that infants have a better prognosis than non-infants, make infant NBS tumors a distinct subgroup of pHGG. NTRK gene fusions also occur in pediatric low-grade glioma (pLGG) and adult glioblastoma but are not as enriched as they are in infant NBS-HGG, and adult glioblastoma and non-infant pHGGs exhibit higher mutation rates than infant tumors. NTRK fusion genes are therefore gliomagenic drivers throughout various development settings; yet it appears as if gliomas driven by the same oncogenic lesion can vary in tumor phenotype as a function of contextual differences. With this in mind, we used genetically engineered mice with a NTRK gene fusion knock-in allele to generate HGG in vivo. Given that tumor is evident by early postnatal life (P5), this is, to our knowledge, the first report of a bona fide spontaneous pHGG model. The second part of this dissertation is the characterization of these tumors

Specific Preferences in Lineage Choice and Phenotypic Plasticity of Glioma Stem Cells Under BMP4 and Noggin Influence

Although BMP4-induced differentiation of glioma stem cells (GSCs) is well recognized, details of the cellular responses triggered by this morphogen are still poorly defined. In this study, we established several GSC-enriched cell lines (GSC-ECLs) from high-grade gliomas. The expansion of these cells as adherent monolayers, and not as floating neurospheres, enabled a thorough study of the phenotypic changes that occurred during their differentiation. Herein, we evaluated GSC-ECLs' behavior toward differentiating conditions by depriving them of growth factors and/or by adding BMP4 at different concentrations. After analyzing cellular morphology, proliferation and lineage marker expression, we determined that GSC-ECLs have distinct preferences in lineage choice, where some of them showed an astrocyte fate commitment and others a neuronal one. We found that this election seems to be dictated by the expression pattern of BMP signaling components present in each GSC-ECL. Additionally, treatment of GSC-ECLs with the BMP antagonist, Noggin, also led to evident phenotypic changes. Interestingly, under certain conditions, some GSC-ECLs adopted an unexpected smooth muscle-like phenotype. As a whole, our findings illustrate the wide differentiation potential of GSCs, highlighting their molecular complexity and paving a way to facilitate personalized differentiating therapies.Fil: Videla Richardson, Guillermo Agustín. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Garcia, Carolina Paola. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Roisman, Alejandro. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; ArgentinaFil: Slavutsky, Irma Rosa. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; ArgentinaFil: Fernandez Espinosa, Damian Dario. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Romorini, Leonardo. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; ArgentinaFil: Miriuka, Santiago Gabriel. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; ArgentinaFil: Arakaki, Naomi. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Martinetto, Horacio Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Scassa, Maria Elida. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Sevlever, Gustavo Emilio. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentin