Longitudinal recordings of visual cortical activity during local glioma progression in a mouse model

UNIVERSITA’ DEGLI STUDI DI PISA

Facoltà di Scienze, Matematiche, Fisiche e Naturali Corso di laurea magistrale in Biologia Molecolare e Cellulare

Longitudinal recordings of cortical

visual activity in a mouse model

during glioma progression.

RELATORE Prof. Matteo Caleo

CORELATORI Prof. Michela Ori

Prof. Maurizio Cammalleri

Candidato Tommaso TOSATO

INDEX

INTRODUCTION ………... Page 1

1.1 Glioma 1.2 Therapies 1.3 Glioma models

1.4 Reciprocal interaction between glioma and neurons 1.5 Epilepsy

1.6 Exploiting visual cortex to mesure glioma induced network disfunction and hyperexcitability

1.7 The visual system

AIM OF THE THESIS ………... Page 20

1.8 Aim of the thesis

MATERIALS AND METHODS ……… Page 21

2.1 Mice 2.2 GL26 cells

2.3 Glioma cells injection

2.4 Chronic recordings apparatus implantation 2.5 The visual system

2.6 Methods for awake recordings 2.7 Signal processing

2.8 Freely moving EEG recordings 2.9 Statistical analysis

RESULTS ……….. Page 26

3.1 Feature of the LFP signal 3.2 Feature of vep waveforms

3.3 Longitudinal evolution of vep in normal animal 3.4 Longitudinal evolution of vep in glioma animal 3.5 Acuity, contrast threshold, temporal resolution 3.6 Epileptiform alteration

DISCUSSION……… Page 43

4.1 Sustained Theta oscillation in the LFP

4.2 Temporal resolution is increased in awake animal 4.3 Perceptual learning

4.4 Decrease of VEP responses in the context of hyperexcitable networks 4.5 Visual Acuity is the first affected parameter by glioma progression. 4.6 Epileptiform alteration

BIBLIOGRAPHY……… Page 47

1

1 - INTRODUCTION

1.1 GLIOMA

Gliomas are the most common primary central nervous system tumours and, although they represent only 2% of cancers, their treatment is one of the greatest challenges to oncologists. The incidence of primary brain tumours worldwide is approximately 7 per 100.000 individuals per year, accounting for almost 2% of primary tumours. Despite advances in therapy, these tumours remain associated with high morbidity and mortality (Burnet et al., 2007). The common gliomas which affect the cerebral hemispheres of adults are termed “diffuse” due to their propensity to infiltrate, early and extensively, throughout the brain parenchyma. The most used tumour classifications nowadays is that of the World Health Organization (WHO) (Louis et al., 2007). It’s based on histological features including cellularity, mitotic activity, nuclear atypia, vascularity and necrosis. It also recognizes 4 prognostic grades and a variety of histological subtypes, of which astrocytomas (60-70%), oligodendrocytomas (10-30%) and ependymomas

(<10%) are the most common (Walker, 2011). Tumours are graded on a WHO

consensus-derived scale of I to IV according to their degree of malignancy as judged by various histological features accompanied by genetic alterations (Louis et al., 2007). Grade I tumours are biologically benign and can be cured if they can be surgically resected; grade II tumours are low-grade malignancies that may follow long clinical courses, but early diffuse infiltration of the surrounding brain renders them incurable by surgery; grade III tumours exhibit increased anaplasia and proliferation over grade II tumours and are more rapidly fatal; grade IV tumours exhibit more advanced features of malignancy, including vascular proliferation and necrosis, and as they are recalcitrant to radio/chemotherapy. They are generally lethal within 12 months (Furnari et al., 2007). Currently, the most clinically useful and specific markers for classification of gliomas are GFAP and OLIG2. GFAP is universally expressed in astrocytic and ependymal tumours and only rarely in oligodendroglial lineage tumours, while OLIG2, a more recently discovered stem/progenitor and oligodendroglial marker, is CNS specific and is universally and abundantly expressed in all diffuse gliomas but is rarely

2 expressed at such high levels in other types of glioma and CNS malignancies (Ligon et al., 2004; Rousseau et al., 2006). Thus, these markers serve as effective tools for

unequivocal identification of gliomas and their distinction from non-CNS tumours, while aiding the pathologist in distinction of different glioma classes (Furnari et al., 2007). Glioma cell invasion results promoted via the overexpression of receptor such as MET or EGFR, as well as downstream signaling through PI3K and MAPK pathways, and the Rho family of GTPases among others (Kwiatkowska and Symons, 2013). Gliomas preferentially invade along white-matter tracts of the cerebrum, sometimes crossing the corpus callosum. Other patterns of cell spreading include perivascular growth, subpial spread or perineuronal satellitosis (Louis, 2006). The most malignant form of glioma is represented by glioblastoma multiforme (GBM or WHO grade IV). GBM is uniformly fatal and largely unresponsive to all available treatments. Median survival with currently available therapies remains less than 1 years from the time of first diagnosis (Khasraw and Lassman, 2010). GBM presents with significant intratumoural heterogeneity at cytopathological, transcriptional and genomic levels. This complexity has conspired to make this cancer one of the most difficult to understand and to treat (Furnari et al., 2007). Glioblastoma tumours arise in two scenarios: primary GBM with new onset disease, or secondary GBM with a previous history of lower grade astrocytoma. They rarely metastasize outside the CNS, but can be highly invasive within the brain parenchyma (Fortin Ensign et al., 2013). GBM accounts for 60-75% of astrocytic tumours (Stupp et al., 2006), affecting predominantly adults with a peak incidence between 45 and 75 years of age and occurring most

commonly in the subcortical white matter of the cerebral hemispheres. It is an

anaplastic cellular glioma with pleomorphic astrocytic cells with marked nuclear atypia and high mitotic rates and has a rapid evolution, typically with neoplastic infiltration of adjacent normal brain tissue and solid proliferating tumour at the periphery. The rapid tumour growth results in spontaneous necrosis with pseudopalisading of tumour cells, quickly developing a necroting tumour core. The essential diagnostic features that distinguish glioblastomas from lower grade gliomas are: prominent endothelial proliferation, forming multilayered vessels and/or necrosis. In addition, although primary and secondary glioblastomas are morphologically identical, primary

3 evidence of an earlier precursor lesion. However, they can be distinguished looking at the genetic alterations; the most common one is the amplificated, mutated or

overexpressed EGFR. In this kind of tumours we can also have mutations of Rb1, PTEN, TP53, loss of p14 and/or p16 and the amplification or mutation of MDM2 and PI3K (Walker, 2011). However, the cellular origin of gliomas remains a topic to debate. One hypothesis is that gliomas arise from neoplastic transformation and

dedifferentiation of mature glial cells, astrocytes, oligodendrocytes, ependymal cells or their precursors (Martin-Villalba et al., 2008). But there are limited evidences that support this mechanism of gliomagenesis, which does not account for mixed gliomas. Alternatively, the cancer stem cell hypothesis suggests that tumour cells with stem-cell like properties are present within tumours and are responsible for their initiation and continued repopulation (Walker, 2011).

1.2 THERAPIES

Strategies actually used to fight gliomas are represented by surgical excision, chemotherapy and radiotherapy. Unfortunately, none of them is of real efficacy. Conventional surgical excision, generally limited to the main tumour mass, does not remove the microscopic foci of neoplastic cells that invade the surrounding normal brain substance beyond the main tumour mass and that is responsible for the inevitable tumour recurrence. At the same time, radiotherapy and chemotherapy, often associated to surgery, cannot ablate completely these tumours, since this would require

unacceptably high radiation or chemotherapic doses that result in severe brain-neuron damage (Colman et al., 2006; Furnari et al., 2007). Concerning chemotherapy, alkylating agents such as temozolomide (TMZ) are widely used in the treatment of brain tumours (Stupp et al., 2005a). As a cytotoxic alkylating agent, TMZ is converted at physiologic pH to the short-lived active compound, monomethyl triazeno imidazole carboxamide (MTIC). The cytotoxicity of MTIC is primarily due to the methylation of DNA at the O6 and N7 positions of guanine, inhibiting DNA replication. A sub-analysis in an international randomized trial by the European Organization for Research and

Treatment of Cancer/National Cancer Institute of Canada (EORTC/NCIC) compared the results of radiotherapy (RT) alone with those of concomitant RT and

4 temozolomide (TMZ) and found that the addition of TMZ to radiotherapy for newly diagnosed GBM resulted in a significant survival benefit (Stupp et al., 2005b);

additionally, the subgroup analysis of the 5-year survival data of the EORTC/NCIC trial also revealed its benefit (Stupp et al., 2009). Since then, TMZ has been the current firstline chemotherapeutic agent for GBM therapy, but chemotherapics have substantial side effects and limited efficacy.

Despite aggressive treatments already mentioned, GBM is still lacking a cure. The causes of treatment failure, disease progression and recurrence arise from the

fundamental biology of gliomas, challenging the biologist to advance the understanding of the genetic aberrations and cellular mechanisms that dictate tumour behavior and provide better diagnostic tools and new targeted therapies. Thus, it is necessary to find innovative approaches for glioma treatment. For these reasons, many studies are now aimed to overcome several determinants of resistance to conventional therapy. In particular, using various approaches to improve the dismal prognosis of GBM (such as modifying TMZ administration and combining TMZ with other agents) or developing novel moleculartargeting agents and novel strategies targeting GSCs (Colman et al., 2006; Furnari et al., 2007; Stupp et al., 2009).

1.3 GLIOMA MODELS

Animal models represents an important tool in the study of tumourigenesis. As a matter of fact, researchers have exploited the role of molecular pathways in brain tumour development to induce gliomas and study them. Thus, genetic engineering of mouse genes or intracranial delivery of oncogenic transgenes in adult mice and rats have been attempted in order to trigger the development of endogenous brain tumour in rodents (Reilly, 2009). The cellular signalling pathways important for the genesis of brain tumour are multiple, with feedback mechanisms that can dramatically affect the efficacy of molecularly targeted therapeutic strategies; in addition, the heterogeneous composition of human high grade gliomas, which consist of tumour stem cells and differentiated tumour cells with varying characteristics, further complicates their susceptibility to treatment. Brain tumours can also evolve within their

5 microenvironment, adapting to changes that produce epigenetic effects altering their biology but concomitantly providing additional targets for the therapeutic intervention. There is a general consensus that valid brain tumour models should fulfil the following criteria: 1) they should be derived from glial cells; 2) it should be possible to grow and clone them in vitro as continuous cell lines and propagate them in vivo by serial

transplantation; 3) tumour growth rates should be predictable and reproducible; 4) the tumours should have glioma-like growth characteristics within the brain; 5) host survival time following tumour implantation should be of sufficient duration to permit therapy and determination of efficacy; 6) for therapy studies, the tumours should be either non orweakly immunogenic in syngenic hosts; 7) they should not grow into the epidural space orextend beyond the brain; 8) their response or lack thereof to

conventional treatments hould be predictive of the response in human brain tumours (Sun et al., 2011). Here I principally report murine models, with their advantages and disadvantages. The ideal brain tumour model should exhibit predictable and

reproducible intracranial growth patterns, histopathological and biochemical

resemblance to human GBMs and be unimmunogenic. The laboratory mouse shares extensive molecular and physiological similarities to humans, such as angiogenesis and metastasis processes, so they represent a powerful tool for studying cancer. More importantly, mouse tumour models provide temporally and genetically controlled systems for studying the tumourigenic process as well as response to treatment (Reilly and Jacks, 2001). Three main categories of murine models are currently used for the study of GBM: transplantation of murine glioma cells into syngeneic mice,

transplantation of human glioma cells into immunocompromised mice and transgenic models. In transplant models tumoural growth is predictable, reproducible and in a known location (the site of injection); syngeneic models are considered particularly valuable for the in vivo studies because, unlike the human xenograft models, they do not require a deficient immune system and may mimic more closely the interaction between tumour and immune system, which takes place in human GBM patients (Elizabeth W. Newcomb, 2009). In addition, tissue specific overexpression of putative oncogenes of interest (using methods which link the gene of interest to a glial specific promoter such as GFAP, S100beta, or Nestin) provides an appealing approach towards the creation of spontaneously occurring brain tumours in animals, seen in many germline knockout.

6 Indeed, overexpression of the transcription factor E2F1 under the transcriptional control of the GFAP promoter led to the formation of astrocytomas in p53 KO mice; this fact suggests a role for E2F1 as an oncogene in the formation of brain tumours (Olson et al., 2007).

1.3.1 Genetic glioma models

Catalyzed by the profusion of genetic information arising from a number of genome-wide studies that revealed mutations present in human gliomas, as well as the advances in molecular biology tools, dozens of genetic mouse glioma models have been

generated over the last two decades. In particular, genetic mouse models have been widely used to investigate the cell of origin of malignant glioma (Alcantara Llaguno et al., 2009; Liu et al., 2011; Uhrbom et al., 2005). It was subsequently found that the core signalling pathways are crucial for gliomas; for example, genetically engineered mice that activate RTK pathways in the brain, along with simultaneous loss of genes involved in cell-cycle control, develop glioma with high penetrance. Also, like human gliomas, additional loss of the tumour suppressor PTEN causes higher-grade

malignancy and reduced survival in mouse glioma models (Kwon et al., 2008).

Suzanne Baker’s group has recently reported the first comprehensive genomic study of a mouse model of high-grade astrocytoma (HGA) generated by manipulating tumour suppressors commonly mutated in human HGAs: Pten, P53, and Rb (Chow et al., 2011). Their studies revealed an astonishing similarity in gene copy number and alteration between mouse HGAs and human GBMs, demonstrating that mouse tumours show similar molecular subtypes as those found in human malignant gliomas (Chow et al., 2011). Thus, this study testified the physiological relevance and value of mouse glioma models for future preclinical studies.

Transgenic technology has allowed scientists to alter the function of specific genes of interest, exploiting defined genetic lesions to produce more biologically correct models of CNS cancer resulting from activation and/or inactivation of endogenous genes in rodent genomes. Among them there are: p53, INK4a/ARF, Phosphatase and Tensin Homolog (PTEN), Epidermal Growth Factor Receptor (EGFR), Platelet Derived Growth Factor (PDGF). For instance, loss of both p53 and PTEN functions seems to be important in the development of astrocytomas; instead, in a somatic gene-transfer

7 model the constitutive activation of Ras and Akt gives rise to the formation of high-grade gliomas morphologically similar to humans (Holland et al., 2000). Moreover, in a high percentage of human GBM tumours were found evidences of the downregulation of tumour suppressor genes such as p53 and PTEN as well as elevated expression of growth factors and their cognate tyrosine kinase receptors, like PDGF and EGFR (Schwartzbaum et al., 2006).

Conditional knockout models represent a promising new attempt to eliminate tumour suppressor function in a cell specific manner. These techniques have recently been used to create a variety of transgenic brain tumour models using targeted conditional

knockouts of p53, PTEN, Ptc, and Rb. Frequently, conditional knockouts used in combination with oncogenes (overexpressed on tissue specific promoters or introduced using viral vectors) can create a localized tumour which is genetically similar to human cancer in an immune competent animal.

Transgenic mice that display cell type-specific overexpression of oncogenes have been employed to study genetic abnormalities in astrocytes and neural progenitors. This turns out to be useful to establish the role of oncogenes in the tumourigenesis and progression of GBM. Considering that cell type specific expression of certain genes is lethal during early development, oncogene overexpression has also been approached by delivery of gene therapy vectors into the brain of pre-natal or adult rodents, leading to the formation of endogenous brain tumours. These tumours harbour the genetic abnormalities found in human GBM, as well as the histopathological hallmarks and the aggressive invasive behaviour. The use of viral or plasmid based vectors to introduce genetic aberrations permits the tight anatomical restriction of tumour-forming genetic events to specific areas of the brain and reduces the amount of time required to

generate germline transgenic mouse models. Extensive evidences from this developing field suggest that formation of endogenous brain tumours using viral vectors or

plasmid systems to deliver oncogenes is somewhat variable. The degree of penetrance, tumour latency and histopathological characteristics are dependent on the species and age of animals, on the identity of specific genetic, on the vector system used to deliver them and on the anatomical location of genetic alterations.

To recapitulate the initiation of GBM which is thought to arise upon genetic mutations in a few cells, oncogenic transgenes were delivered in a small population of cells in

8 adult mouse brain by region-specific injection of lentiviral vectors encoding H-Ras or AKT. To target astrocytes the Cre-LoxP-controlled lentiviruses were injected in the cortex, hippocampus and subventricular zone of GFAP-Cre mice. Again,

administration of single oncogenes did not induce formation of tumours for up to 10 months. But when Ras and AKT were delivered together in the hippocampal area ~30% of mice exhibited brain tumours that exhibit a high degree of invasiveness within 3-5 months post injection. Only one mouse developed a tumour following transduction in the sub-ventricular zone, and no animals had tumours following transduction into the cortex. Combined delivery of H-Ras and AKT into p53 KO mice greatly increased the tumourigenesis of these vectors leading to 75 and 100% of the mice injected in the subventricular zone and hippocampus, respectively. These tumours also exhibited a much shorter tumour latency with many histopathological characteristics found in human GBM (Marumoto et al., 2009).

A way to form a brain tumour that has histopathological feautures similar to human GBM is the retroviral- mediated delivery of PDGF. Retroviral delivery of PDGF into the adult rat white matter causes that 100% of the animals succumb 14-20 days after injection due to tumour burden (Assanah et al., 2006). However, when retro-PDGF is delivered into the brain of newborn mice, brain tumour formation only occurred in ~40% of the animals within 14-29 weeks. The incidence and grade of brain tumour formation in mice has been suggested to depend on the levels of PDGF expression. Newborn mice were administered with retroviral vectors encoding a PDGF gene that lacks its regulatory sequences and which leads to higher levels of PDGF expression. Within 4-12 weeks, 100% of these mice developed invasive glioblastoma that exhibited neo-vascularization and tumour cell infiltration throughout the brain parenchyma (Calzolari and Malatesta, 2010; Shih et al., 2004).

Retroviral vectors are also employed in other tumour models. In order to mimic the multiple genetic lesions encountered in human GBM, retroviral vectors which encode growth factors and a cycline-dependent kinase (cdk) were injected in the brain of neonatal mice harboring additional mutations in tumour suppressor genes. Moreover, delivery of a constitutively active form of epidermal growth factor receptor gene (EGFR) in combination with basic fibroblast growth factor (bFGF) or ckd4 into the brain of neonatal mice that are deficient in INK4a–ARF or p53 tumour suppressor

9 genes led to formation of GBM in ~50% of the animals, while single mutations were unable of generating tumours (Holland et al., 1998).

These findings support the notion that combination of genetic lesions is required for the induction of endogenous GBM in mice. Additionally, combined genetic aberrations can be targeted to specific cell populations by the development of transgenic mice that express the retroviral receptor under the control of cell-type specific promoters, such as the progenitor nestin promoter or the astrocyte GFAP promoter (Dai and Holland, 2001). This system is very functional because it allows cell-type-specific transfer of oncogenes expressed within retroviral vectors under any type of promoter.

Another recent approach to induce endogenous GBM in mice is the use of the Sleeping Beauty (SB) transposable element to achieve integration of oncogenes in the genome of brain cells of neo-natal immune competent mice (Ohlfest et al., 2005). SB is a synthetic transposable element composed of a transposon DNA substrate and a transposase enzyme. SB transposase mediates excision and insertion of transposon DNA into the host genome, leading to long term expression (Ohlfest et al., 2004). Spontaneous brain tumours were induced by injecting SB-dependent plasmid harboring up to three genetic alterations (AKT, N-RAS, EGRFvIII, and/or shRNA specific for p53) into the lateral cerebral ventricle of neonatal mice of three different strains (Wiesner et al., 2009).

1.3.2 Induced glioma models: human xenograft models and syngeneic models Currently, the majority of glioma models used in the literature involves the use of rodent glioma cells injected in syngenic hosts or the use of human glioma cells implante in nude mice. Implantation of rodent glioma cells has proven an excellent intracranial brain tumour model due to their efficient tumourigenesis; moreover, it is reproducible, with fast growth rates and accurate knowledge of the tumour location. Over the past few decades, several mouse glioma models have been generated based on human genetic abnormalities and the induced gliomas exhibit histological similarities to their human counterparts. Xenograft models that transplant human malignant glioma cells into the brain of immunocompromised mice (such as SCID) have the advantage of being rapid and very useful models for the initial evaluation of novel imaging

10 techniques as new GBM therapies. Unluckily, most human glioma cell lines are not invasive when propagated in vivo (Curtin et al., 2008) and in culture they can loss their

key genetic alterations (such as expression of the mutant EGFR) (Tsurushima et al., 2007), so important in gliomagenesis. This limitation has been overcome by

propagating primary human GBM tumours in the nude mouse (Ozawa et al., 2005). Although their xenogeneic nature impairs the study of immune-mediated anti-tumour strategies, they allow assessing the efficacy of therapeutic approaches in human GBM cells in the context of normal brain tissue. In fact, human xenografts exhibit

histopatological features that resemble the human GBM and retain gene amplifications detected in the in situ tumours (Sun et al., 2011).

Syngeneic murine models are non-immunogenic. So, due to the fact that they have all the advantages of induced tumour (i.e. reproducibility, known site of tumour cell implantation, very cost-effective transplant model because the tumour latency is short and can in this way facilitate screening of potential therapies in a timely fashion) and the capability of being used in no immunosuppressive mice, they constitute an excellent tool. Limitations of these model are that the tumour cells are not of human origin and that the rodents can in some instances require several months to reliably develop glioma tumours.

Although many questions and controversies remain, our understanding of malignant glioma has increased dramatically in recent years. For the first time, we have a clear picture of the human GBM genomic landscape. The continued incorporation and validation of new data using ever more sophisticated animal models will further advance our knowledge about origin, progression and treatment of that disease. Eventually, the accumulation of this knowledge provides great opportunities to improve and even revolutionize current diagnosis and treatment of human malignant glioma, especially GBM (Chen et al., 2012). Among the murine syngeneic models there is the well accepted GL26 syngeneic mouse model of high grade glioma, which is based on intracerebral injection of GL261 cells in C57/BL6 mice (Miyatake et al., 1997; Zagzag et al., 2003).

11 The GL261 glioma is representative of a carcinogen-induced mouse glioma model. It was induced for the first time by Seligman and Shear (1939) through intracranial implantation of 20 methylcholanthrene pellets into mice brains, out of which 11

developed gliomas. One of these gliomas was designated GL261 and was next reported by Ausman and co-workers in 1970. In this study the GL261 glioma was described as having characteristics of ependymoblastoma, with histopathologic features similar to three other gliomas such as ependymoblastoma, glioma 26 (G-26), and

ependymoblastoma A (Ausman et al., 1970). Since that initial report, both GL261 and G-26 have been instead described as containing poorly differentiated cells and

exhibiting features more consistent with GBM (Schold and Bigner, 1983; Wiranowska et al., 1998; Zagzag et al., 2000a). The GL261 model has been frequently used for preclinical testing (Glick et al., 1999; Kjaergaard et al., 2000; Miyatake et al., 1997; Newcomb et al., 2004; Plautz et al., 1997). Although this intracranial model is not a glioma experimental model (GEM), giving rise to ‘‘spontaneous’’ brain tumours as expected for transgenic mice engineered to overexpress a given transgene or have engineered mutations in specific tumour suppressors, it represents an important

syngeneic transplant animal model that uses engraftment of murine GL261 glioma cells into the brain of an immunocompetent animal.

Traditionally, mouse models for glioma have used primarily human U87MG glioma cells, xenografted into immunosuppressed mice (Abe et al., 2003; Eshleman et al., 2002). It seems that this discrepancy for being ‘‘poorly predictive’’ is the fact that U87MG tumours growing in the brains of immunosuppressed mice do not show an ‘‘invasive phenotype’’, characteristic of human GBM. In sharp contrast, tumours formed by the murine GL261 glioma cells have irregularly shaped borders with clearly visible invading tongues of tumour cells, advancing into the brain adjacent to the tumour (Cha et al., 2003; Wiranowska et al., 1998; Zagzag et al., 2003). Numerous poorly differentiated, pleomorphic cells with atypical nuclei were observable

throughout the tumours, including multinucleated cells and cells with hyperchromatic nuclei. Mitotic activity was particularly evident and multiple necrotic areas were visible in irregularly shaped, bandlike patterns of eosinophilic material consisting of non-viable or necrotic cells. Moreover, although not as prominent as in human GBM (densely packed), viable cells lined the necrotic zones in a pseudopalisading pattern characteristic

12 of GBM. An increase in microvascular density was also observed throughout the

tumour and confirmed by immunostaining for CD31 antigen in the endothelial cells (Vannini et al., 2014)

1.4 EPILEPSY

The term epilepsy is used to define several different types of neurological pathologies resulting from different etiologies. They usually are all characterized by the occurrence of unprovoked recurrent seizures, which consists in a period of abnormal (paroxysmal) brain electrical activity. Epilepsy is either genetically determined or acquired

(secondary). The causes of acquired epilepsies are multiple (stroke, cortical trauma, brain tumour, infections, etc.) and the recurring seizures are typically primarily focal (Timofeev et al., 2014). A common feature of acquired epilepsies is neuronal death leading to deafferentation. Normal brain activity requires a balance between activity and inactivity (“silence”) and also between excitation and inhibition. If for any reason the balance is shifted, some homeostatic plasticity can occur to reestablish the balance. Deafferentation strongly decreasee neuronal activity and this triggers an up-regulation of glutamate receptors thus boosting neuronal excitability (for a review see: Turrigiano G). If the up-regulation of neuronal excitability is large, it would predispose the circuit to epilepsy. A period between initial insult and development of epilepsy is called epileptogenesis and its exact mechanisms remain largely unknown, therefore, there is no effective treatment of epileptogenesis.

Neuronal synchronization is able to elicit epileptic events in predisposed networks. Synchronization takes advantage of basic mechanisms: chemical synaptic transmission, electrical synaptic transmission, ephaptic and non-specific interactions such as

alterations in the extracellular ionic balance (Timofeev et al., 2012). Chemical transmission occurs when an action potential is fired by the presynaptic neuron, invading the nerve terminal, allowing calcium to enter in the synaptic terminal, which will trigger the release of synaptic vesicles containing neurotransmitter, and finally causing depolarization or hyperpolarization of the postsynaptic neuron. Incoming sensory information pass through this modality of transmission, and strong, repeated

13 and sterotyped sensory stimulation are know to be able to induce epileptic events in predisposed subjects. On the other hand, electrical synapses use a spike-independent mechanism of communication between neurons connected via gap junctions allowing a direct flux of ions between them. When cells are connected by gap junctions, any change in the membrane potential in one cell will trigger a current flow in the other one leading to corresponding changes. In the neocortex, GABA-releasing interneurons and glial cells are interconnected by gap junctions. However as gap junctions have relatively high resistances, they are best situated to transmit low frequency oscillations, but not fast processes (Galarreta and Hestrin, 2001). Altered Gap junction (increased connexin expression) has been reported in the peritumoural are of some “epileptogenic” glioma (Aronica et al., 2001). Ephaptic interactions instead refer to influences produced by local electric fields. The extracellular currents produced by the activity of neurons constituting the local field potential might directly influence the electrical properties of surrounding neurons (Frohlichand McCormick, 2010). Although these influences are are relatively weak, they might affect the neuronal excitability by exerting a global influence and may provide a significant impact when the network is already quite synchronized (as for example during slow wave sleep or anesthesia). Neocortical seizures are known to happen preferentially during slow wave sleep and are elicited by ketamine-xylazine anesthesia. Finally extracellular ionic composition can be involved in network synchronization since it is able to influence neuronal excitability on different time scales. Normal neuronal activity, which leads to the opening of different ionic channels, produces short-term changes in the extracellular ionic composition. The most affected ion concentrations are for those that have a lower extracellular concentration such as calcium and potassium. For example, during a normal slow oscillation, the extracellular calcium concentration varies from 1.2 mM during silent states to 1.0 mM during active state. The changes in the extracellular milieu are even more dramatic during seizures as extracellular potassium concentration can reach up to 7–18 mM, and the extracellular calcium concentration can decrease to as low as 0.4–0.7 mM (Amzica et al., 2002). These changes dramatically reduce the synaptic excitability and almost abolish any synaptic response. Several epilepsy-inducing factors are also known to alter the extracellular composition in a more stable fashion (i.e. infections and gliomas).

14 Gliomas for example induce several micro-haemorrhage which result in higher levels of Fe2+ _{and lower level of Mg}2+ _{(increasing in both cases the overall excitability).}

Epileptiform activities are therefore the result of a shift in the balance of excitation and inhibition (Nelson and Turrigiano, 1998). One of the most widely used procedures to induce epileptiform discharges consists in blocking inhibition by using GABAergic antagonists (bicuculline, penicillin, etc.). On the other hand, the possible pro-epileptic effect of decreased excitation (or increased inhibition) has been much less investigated. A model that goes in that direction is the trauma-induced epilepsy in which the

excitation is decreased as multiple glutamatergic thalamocortical fibers are severed by the undercut technique (Topolnik et al., 2003). Ketamine–xylazine anesthesia leading to paroxysmal activities in cats could also be considered as a model in which the excitation is decreased, as ketamine is an NMDA receptor antagonist. Finally animal models for glioma show epilepsy and recurrent seizures (with several foci in the peritumoural area). They provide us with an example of a process in which neuronal death and white matter damage (progressively induced by the glioma growth) decreases the overall connectivity in the circuits and this is accompanied by hyperexcitability (that can been seen as a compensatory homeostatic effect as well).

1.5 INTERACTIONS BETWEEN GLIOMA CELLS AND

PERITUMOURAL NEURONS

The glioma mass is not an isolated and self-sustained entity, but instead it participates in a bidirectional interaction with the surrounding neuronal tissue. In fact on one side glioma cells induce hyper-excitability in the nearby tissue, and on the other side neural activity sustains glioma growth. As I already mentioned hyper-excitability could be seen as a homeostatic response to decreased connectivity. However, alternative hypotheses exist on the links between glioma and epilepsy. I start by discussing here the role of two important phenomena producing alterations in the peritumoural area: glutamate

homeostasis and GABAergic inhibition. In the extracellular space of the peritumoural area, higher concentrations of glutamate have been found (Behrens et al., 2000;

Buckingham et al., 2011). This could be due in part to an impaired glutamate reuptake (glioma cells lack the EAAT1/EAAT2 transporters and activated microglia display an

15 impaired clearance abilities (Buckingham & Robel, 2013)). But an increase in the

glutamate release is present as well. Glioma cells in fact overexpress the cystine-glutamate antiporter (system xc-), that exchanges extracellular cystine for intracellular glutamate. Cystine is then metabolized to cysteine which is crucial for the synthesis of the antioxidant glutathione. Moreover the massive glutamate release from xc- system could lead to excitotoxicity in neurons, where it binds and activates NMDA receptors (leading to an intracellular Ca2+ _{increase) and AMPA receptors (leading to increased} excitability). On the other hand neuronal death responds to the needs of free space for the glioma invasion. Sulfasalazine (SAS), a drug already approved by the FDA, blocks system xc-; its administration in a glioma mice model induced a partial rescue of network hyperexcitability and neuronal death (Campbell et al., 2012). Furthermore glutamate is used by glioma cells in a paracrine fashion. Glioma cells express AMPA receptors lacking GlutR1 subunit which allow Ca2+ _{entrance (leading to motility} enhancement and to Pi3K/AKT pathway activation) (Lyons et al., 2007).

The other important player besides glutamate is GABA. It’s intuitive to think that modifications in the GABAergic transmissions can explain changes in the excitability. It has been shown that the peritumoural area presents a loss of GABAergic interneurons and a reduction of inhibitory synapses (Marco et al.. 1997; Campbell et al., 2015).

However recently a new role for GABA has been proposed. Indeed in the peritumoural area modification in the expression levels of the two main chloride transporters

(NKCC1 and KCC2) have been found (Conti et al., 2011). It’s known that altering chloride homeostasis can switch GABAergic activity from inhibitory to excitatory (Ben-Ari, 2002). In the peritumoural area, studies have reported an excessive expression of NKCC1 together with a decrease in its counterpart KCC2, recalling the situation of immature neuron (in which GABA is excitatory). Recent studies confirmed in humans and in a mouse model that neurons from the peritumoural area are depolarized by GABA release (Pallud et al., 2014; Campbell et al, 2015). Immature neurons switch NKCC1 and KCC2 expression when they have reached a “mature” levels of

connectivity. It’s possible to envisage that peritumoural neurons, losing a major part of their connectivity due to glioma expansion, revert to the “immature neurons” profile (homeostatically increasing excitability, while they wait for a never coming new connectivity.)

16 Electrophysiological analysis of the peritumoural areas confirms the presence of

hyperexcitable networks showing neurons with an increased baseline firing (Vannini et al., submitted) which may represent the cellular substrate underlying enhanced

propensity to seizures in the peritumoral area.

If glioma progression is able to influence neural activity, neuronal activity “per se” it’s able to influence glioma growth. Neural activity in fact exerts a physiological mitotic effect on neural precursor cells and on oligodendroglia precursor cells during

development and also in the mature brain (Gibson et al. 2014). Since there are evidences that at least a certain part of gliomas origin from this precursors cells, it is worth to think that neural activity could exert a mitotic influence in glioma cells as well. Culturing glioma cells with optogenetically excitable neurons has allowed to

demonstrate that neural activity promotes glioma growth, and this is mediated by Neuroligin-3 (a synaptic protein released in an activity dependent fashion) (Venkatesh et al. 2015). BDNF is another potential candidate. These findings could explain the organization of glioma cells in perineuronal sattelitosis (Scherer, 1938), an hallmark characterized by tumour cell clustering around cell somata.

5.1 EXPLOITING VISUAL CORTEX TO MESURE GLIOMA INDUCED

NETWORK DISFUNCTION AND HYPEREXCITABILITY

In the precedent section I stressed the presence of an active bidirectional interaction between the tumour and the surrounding neural tissue. It is of great importance for the preclinical research to dispose of a model in which is possible to access the neural circuit state and functionality. This would permit to monitoring the effects of glioma progression on neural networks functionality, and evaluating the impact of available treatments on neural physiology. From a technical point of view longitudinal recordings in awake mice with chronically implanted electrodes are now routinely possible and suit well for our purpose. It's critical the choice of the brain area to implant and record. Sensory cortices have the advantages that interfering with their ongoing neural activity is relatively easy through sensory stimulation. In particular visual cortex is well-known, and it offers several parameters already characterized which can be longitudinally evaluated. Moreover it allow to test intermittent photic stimulations,

17 which is used also in clinical analysis of epileptic patient. Therefore we decided to exploit visual cortex in our study.

5.2 THE VISUAL SYSTEM IN MICE: A QUICK OVERVIEW

There are some differences in the anatomical organisation of visual pathways in the different species, even if the basic aspects are conserved in all mammals. The sensory structures are represented by the eyes: light enters the eye by first passing the cornea and finally reaching the very back of the eye, the retina. The retina is responsible for converting light into neural signals that can be relayed to the brain. The retina is a very specialised sensory structure, consisting of a team of different types of neurons whose role it is to collect light, extract basic information and pass the preprocessed image to visual structures in the brain. These cell types are photoreceptors, bipolar cells,

horizontal cells, amacrine cells, and ganglion cells. They are arranged within the retina in precise layers. Axons from the ganglion cells bundle together to form the optic nerves. Fibres from the nasal half of each retina turn towards the opposite side of the brain in a point called optic chiasm, while the fibres from the temporal half of each retina do not cross. In the rodent visual system the vast majority of the fibres cross at the chiasm (only 3-5% of the optic axons remain ipsilateral), while the percentage of decussating fibres is lower in carnivores and primates. Past the chiasm, retinal ganglion cell axons run within the two optic tracts. Each optic tract carries a representation of the contralateral visual field. Retinal inputs terminate within two major subcortical visual structures, the superior colliculus (SC) and the dorsal geniculate nucleus (dLGN), a portion of the thalamus. In rodents, all ganglion cells project to the SC, and 40% of the retinal fibres send a collateral to the dLGN. The dLGN is the structure that relays input to visual cortex. In each dLGN there is a retinotopic representation of the contralateral visual field. In primates and humans, the dLGN contains six layers, each of whose receives inputs from one eye only. Indeed, retinal axons coming from the two eyes terminate in adjacent but not overlapping eyespecific layers that are strictly

18 receiving eye-specific input (Godement et al. 1984). The inner core is ipsilateral,

surrounded by a contralateral patch.

Projections of neurons in dLGN reach the primary visual cortex, or V1, in the occipital portion of the brain. The V1 is a layered structure (layers I-VI). The major layer of inputs from dLGN is layer IV, then neurons in layer IV relay their information to layers II/III, that in turn communicate to layer V-VI. In carnivores and primates, inputs of each eye reach layer IV into alternating stripes, the ocular dominance (OD) columns (Hubel and Wiesel 1963). In rodents there are no ocular dominance columns, because inputs coming from two eyes converge on the same postsynaptic target cell at the level of layer IV (Antonini et al. 1999). V1 is the first station through the visual pathway where retinal inputs collected separately by the two eyes interacts directly. Although V1 receives input from the two eyes, information concerns always the contralateral half of the visual field. Many mammals have binocular vision, and their visual cortical neurons can respond to stimulation of both eyes, even if the response to one eye can be

predominant (eye preference). The most binocular portion of the primary visual cortex is in correspondence of the cortical representation of the vertical meridian of the visual field, and lies at the V1/V2 border. Together with the dLGN, another important input to V1 is the corpus callosum, the major fibre bundle in the brain interconnecting the two hemispheres, which sends a massive projection to the V1/V2 border. Its specific pattern of connectivity led many researchers to question whether the callosum has a role in determining cortical binocularity, as described more in detail below. Besides ocular dominance columns, V1 has a columnar systems for orientation selectivity, and regions called “blobs” with specific responses for coloured stimuli. These columns communicate together by means of long-range horizontal connections. These

connections allow individual cells to integrate information from a wide area of cortex (Gilbert 1992). Primary visual cortex is responsible for creating the basis of a three-dimensional map of visual space, and extracting features about the form and orientation of objects. Once basic processingn has occurred in V1, the visual signal goes to

secondary visual cortex, V2, which surrounds V1. Secondary visual cortex (V2) is principally responsible for perceiving colours and forms. Primary visual cortex contains two main types of neurons: pyramidal cells are projection neuron, while non-pyramidal cells represent local interneurons. There are several different classes of pyramidal cells

19 and interneurons, and their physiological, anatomical and molecular diversity is the subject of ongoing research.

20

AIM OF THE THESIS

In glioma patients, neural function in the affected brain areas may deteriorate with tumor progression. Neural manifestations (such as headache, sensory disturbances and seizures) often provide the first symptoms by which glioma is diagnosed. Furthermore, existing therapies to contrast glioma growth (including chemotherapy and radiotherapy) often contribute "per se" to the functional deterioration.

A pre-clinical model suited to evaluate neural functionality during glioma progression and following experimental anti-neoplastic treatment would be therefore essential, but nowadays is still missing.

In this thesis, I tried to establish a mouse glioma model in which a chronic electrode implantation allowed longitudinal recordings of neural activity. Visual cortex was chosen as a recording site since it can be easily activated by physiological stimuli, and for the presence of many well established parameters to evaluate its functionality. Moreover, the visual system is also very convenient for the study of network hyperexcitability as it offers the possibility to use photic stimulation (which is also routinely tested in humans in the form of intermittent light stimulation). It is a strong stimulation which is able to elicit epileptic-like events in predisposed networks and brain areas.

21

2 - METHODS

2.1 Mice

C57BL/6N mice at approximately postnatal day 60 were employed in the experimental procedures. Animals are bred in our animal facility and housed in a 12 hours light/dark cycle, with food and water available ad libitum.

All experimental procedures are in conformity to the European Communities Council Directive 86/609/EEC and were approved by the Italian Ministry of Health.

2.2 GL261 Cells

The murine glioma GL261 cell line has been used in our lab from several years and originally was a gift from Dr. C. Sala (CNRNeuroscience Institute, Milan). GL261 cells were grown in complete Dulbecco’s modified Eagle’s medium (DMEM) containing 10% Newborn calf serum, 4.5 g/L glucose, 2 mM glutamine, 100 UI/ml penicillin and 100 mg/ml streptomycin at 37°C in 5% CO2 with media changes three times per week.

2.3 Glioma cells injectio

To induce glioma formation, GL261 cell are injected into the cortex. 8-9 weeks old C57BL/6 mice (male and female) are deeply anesthetized with Hypnorm injection (0,1 ml/10 g; Hypnovel 10%, Midazolam 20%, Water 70%), shaved from between the eyes to behind the ears, and mounted in a stereotaxic apparatus. Successively an incision (approx. 1 cm) in the skin over the rostral skull is performed with a blade. The

remaining gelatinous periostium is removed with small scissors and the skull is cleaned and dried with sterile cotton swabs. Successively, using a dental drill with an ¼’ drill bit, a small hole is drilled into the skull over to the monocular visual cortex (2 mm lateral to the midline and in correspondence with lambda). The hole is made by carefully circling the drill at a slow speed until the skull is soft enough to be picked up by forceps, paying

22 attention not to damage the underlying tissue. The

guided injection is performed afterwards. The

solution containing GL261 cells (20.000 cells/ µl PBS solution) is aspired within a Hamilton syringe

equipped with a thin needle (tip diameter 40 µm). The syringe is connected to a pump and mounted on a motorized three-axis micromanipulator. The needle is lowered into the cortex at a depth of 800µm and 2microl of solution (40.000 cells) is injected at a rate of 1µl/min. After waiting 1-2 minutes the needle is extracted, and successively the surgery proceeded with the implantation of a chronic electrode.

2.4 Chronic electrode implantation. Immediately after the GL261 cell injection, the

chronic recording apparatus is implanted. A screw is positioned over the cerebellum and the ground cable for the implant is carefully soldered to it. A first electrode (a nickel chrome wire) is secured to an insertion rod and mounted in a motorized three axis micromanipulator. The electrode is then moved close to the injection site (approx. 3 mm lateral to lambda) and slowly lowered at the depth of 700 µm within the brain parenchyma. The electrode is secured in his definitive position with an UV-curable cyanoacrylic glue. A second electrode (that will act as the reference electrode) is placed and secured on the top of the dura (approx. 3 mm lateral to lambda). Both the

electrodes and the ground cable are then soldered to a multipin connector. Finally a custom made head bar is posted on the frontal part of the exposed skull (for enabling future head-fixed awake recordings). The skull is covered with cyanoacrylate and the head bar is fixed with a UV gun. Everything is covered and stabilized in the right position with acrylic dental cement. Mice are allowed to recover from anesthesia and then returned to their cages.

Figure 1 - exposed skull with indicated the exact location of G261 cells injection and electrode implantation site (2 and 3mm lateral to lambda respectively)

23 2.5 Methods for awake VEP recordings

After the surgery, two days are allowed for complete recovery of the animals. From day 3 to day 5, the animals are adapted to stay head fixed in front of a monitor in a

plexiglas-restraining device molded to the mouse's body. Head fixation is achieved by seating the head bar in a stainless steel holder (with a clamp and two screws) and connecting it to a stereotaxic arm. During the adaptation, milk rewards are delivered to the animals so that their anxiety slowly decreases. On day 6 after surgery, the first recordings are made by connecting the

multipin connector to a miniature headstage and from that point VEP recordings are performed regularly twice a week.

2.6 Visual Stimuli

Stimuli are generated by computer on a display (Sony; 40 x 30 cm; mean luminance 15 cd/m2_{) by a VSG card (Cambridge Research Systems) and controlled by custom made} software, based on LabView. The display was placed 24 cm in front of the animal and centered on its midline, thereby including the binocular visual field.

Three main classes of stimuli are used, and for each one basic parameters (such as contrast, temporal frequency and spatial frequencies) are varied. Transient stimuli are characterized by a repeated abrupt reversal of a horizontal square wave grating (spatial frequency 0.06, 0.1, 0.2, 0.3, 0.4, 0.5 c/deg; contrast 10%, 20%, 30%, temporal

frequency 1, 1.2, 1.4 Hz). At least 30 events are presented. Steady-state stimuli are based on a horizontal sinusoidal grating reversed in contrast sinusoidally (spatial frequency 0.06, 0.1, 0.2, 0.3, 0.4, 0.5 c/deg., contrast 30%, temporal frequency 4, 6, 8, 10, 12 Hz). At least 90 events are presented. Flashes are characterized by a full screen flash of light lasting 10 or 5 ms (contrast 30%, temporal frequency 1, 2 Hz). A blank stimulus (contrast 0%) is also frequently presented to let the system recover and estimate noise in the recordings.

24 2.7 Signal Processing

Signals coming from the miniature head stage (with unitary gain) are amplified (10’000-fold), band pass filtered (3Hz to100Hz), digitalized by a A/D card (National

Instrument, USA) with a sampling frequency of at least 512 Hz, and fed to a computer. An HumBug noise eliminator is also used if needed to get rid of the 50Hz noise. Signal analysis are made with a custom made software (based on LabView), or using Matlab (with the WaveLet toolbox). In both cases VEP waveforms are obtained by averaging the recorded traces in synchrony with the stimulus contrast reversals. Transient VEP and flash responses are evaluated by measuring the peak to through amplitude of the first major components. Steady state VEP responses are quantified by measuring the amplitude of the second harmonic of the Fourier transform computed from the recorded signal. Oscillatory activity were accessed using Matlab “pwelch” and “spectrogram” function. The signal is divided in window of 0.3 seconds, half

overlapping, and the Fast Furier transform is computed for each segment. Then the power spectrum obtained for each segment is averaged and the output plotted. Contrast threshold, acuity and temporal resolution was measured in each session by taking the lowest contrast, and highest spatial and temporal frequencies able to evoke a response greater than noise (blank stimulus).

2.8 EEG Recording and EEG Analysis

EEG from freely moving mice are acquired on day 8 after surgery (and then once a week). Mice are placed in the test cage and the connector is connected to a miniature head stage. A period of 10 minutes is allowed for habituation and then 50minutes of recording are acquired. Signals are amplified (10’000-fold), band pass filtered (3Hz to 80Hz), digitalized by a A/D card (National Instrument, USA) with a sampling

frequency of at least 200 Hz, and fed to a computer. An HumBug noise eliminator is used if necessary.

The analysis of EEG recordings was performed by setting a threshold (4 times greater than the standard deviation of the baseline amplitude, calculated during quiet,

seizure-25 free periods). All the events exceeding this threshold were considered epileptiform spikes, according to published methods (Antonucci et al., 2008, 2009; Mainardi et al., 2012). Spikes were considered to be clustered together when they were spaced by less than 1 sec. Spike clusters lasting for >4 s were classified as ictal events. Clusters of at least 3 spikes lasting less than 4 sec were counted as interictal events.

For the quantitative analysis of epileptiform alterations, I used for normal animals the data obtained from the third recording session and for glioma bearing mice the data from the session immediately preceding the complete loss of VEP response

2.9 Statistical Analysis

Statistical analysis was performed with SigmaPlot. For VEP analysis differences between recording days in the same group of animal (normal or glioma-bearing) are evaluated by one way repeated measures analysis of variance (ANOVA), whereas differences between groups in respect to different recording day are evaluated by two way repeated measures ANOVA. In the evaluation of longitudinal changes in acuity, contrast threshold and temporal resolution, a two tailed t-test is used. In the

26

3 – RESULTS

In this thesis, I performed longitudinal recordings of visual cortical activity in normal and glioma-injected mice. Initially I concentrated on oscillatory properties of the visual cortex with a particular emphasis on gamma and theta bands. I then evaluated the amplitude variations of Visual Evoked Potentials (VEPs) in response to several stimuli throughout the recording period. Transient, steady state, and flash stimuli was

separately analysed. I considered also other physiological parameters such as contrast threshold, acuity, and temporal resolution, and their longitudinal variation during glioma progression. Finally I describe epileptogenic activity arising in the peri-tumoral zone of glioma-bearing mice.

3.1 – Features of the LFP signals in the baseline condition and during stimuli presentation.

Several oscillations appear and sometime dominate the LFP signal during stimuli presentation and in the baseline condition. In particular I observed that visual stimuli presentation markedly enhances theta oscillations.

Figura 1 - Power spectrum of LFP signals during stimuli presentation, normalized for the blank stimulation. Averaged power spectrum for 20 recordings with transient stimulus (contrast 30%) normalized for the respective blank stimulation. The recordings belong to the same normal animal.

27 Theta activity is not uniform along the trace and it occurs mainly in spots (figure 2). The frequency at which theta activity occurs is ~5.5 Hz and this frequency is stable across different recordings and different stimuli. During visual stimuli presentation theta modulation is markedly enhanced, and it became extended almost along all the signal. For anesthetized mice theta modulation in V1 has never been reported in literature, and in the awake mice just recently reported (Zold and Shuler, 2015))

I investigated if some correlation between theta and gamma activity were present in the temporal domain. EEG recordings where filtered and relative power for different frequency channels were accessed. Correlation was calculated between theta power (from 4.8 to 6.2 Hz) and gamma power (from 30hz to 80hz) for each single recordings. The two oscillation where found to anti-correlate with a correlation index of ~ -0,40.

Figura 2- LFP signals. Representative LFP signals during visual stimuli presentation (B) and during blank stimulation (A). Theta oscillations occurs in burst, and are more frequent when visual stimuli are presented.

28

3.2–Features of Visual Evoked Potential (VEP) waveforms.

Visual evoked potentials (VEP) are calculated by averaging LFP signals in synchrony with the stimulus contrast reversal. Each stimuli is presented at least 30 times

consecutively to obtain a reliable estimation. Between each group of stimuli LFP signals in response to blank stimulation were also recorded to estimate noise and allow the system to recover.

3.2.1 - Typical waveforms.

In Figure 2 representative waveforms for typical visual stimuli are reported. Each stimulus is presented with optimal contrast and spatial frequency for the awake animal (contrast 30%, spatial frequency 0.06 c/deg)

Fig 3A corresponds to a transient alternating horizontal grating. Two reversals of the grating in the period of 1 second generate two similar consecutive waves that consist of a first positive-to-negative peak, followed by some rebound waves. The rebound waves likely represent an “echo” of the stimulus induced theta oscillations, which are synchronized by slow stimulations. Interestingly, no rebound waves are reported in transient VEP from anesthetized mice (Porciatti et al., 1999; Pinto et al., 2009; Allegra et al., 2014).

Figure 3B show an example of a steady state VEP recorded in response to a grating reversing sinusoidally at 10hz. Responses to steady state reverting stimuli usually show a strong modulation at twice the stimulus frequencies, thus the second harmonic

component well represents the main response modulation. Figure 3 - Representative VEP Waveforms. Transient

stimulus (1Hz, contrast 30%) is presented in A, stedy state stimulus (10Hz, contrast 30%) is presnted in B, and flash (1hz) is shown in C

29 Finally figure 3C report a typical waveform obtained in response to a flash (a short period of full screen light, duration 50 ms in this particular example). The waveform is composed by a first positive peak followed by a second larger negative one, with several subsequent rebound waves.

3.2.2 - Late oscillations in VEP waveforms

VEP induced by a 1hz transient stimulus triggers a ≈ 5 Hz

oscillation. This oscillation cannot continue undisturbed since a subsequent reversal of the stimulus induces another VEP.

If the second VEP induce a new oscillation “in phase” with the precedent there will be a summative effect, otherwise there will be the depletion of the previous

oscillation.

I investigated several slightly different temporal frequency for transient stimuli and I found that the strongest summative effect was present at 1.4Hz. I called this effect “resonance” (see Fig. 3D).

Figure 4- Theta oscillations give rise to rebound oscillation. I show VEP for transient stimuli (contrast 30%) at slightly different temporal frequencies (1hz in A, 1.2Hz in B, 1.3Hz in C and 1.4 Hz in D) . It is clear in D a “resonance” effect.

30 3.2.3 – Transient VEP waveforms change during spatial frequency modulation.

Several features of visual stimuli can be modulated to evaluate threshold of sensory perception and to study the underlying changes in network responses.

Figure 5 display responses to stimuli of decreasing spatial frequency. The optimal stimulation is typically considered 0.06c/deg since it evokes the greatest response amplitude. However, changing the spatial frequency of the stimulus leads not only to variations in amplitudes, but in the response waveform as well. In fact the response is composed by two succeeding peaks and the first one is dominant at low spatial frequencies, whereas the second prevails at higher spatial frequencies.

Figure 5 - VEP weveforms during spatial frequencies modulation.. Panel A shows VEP responses for O.3 c/deg; B show the same for 0,2 C/deg; C for =,1 c/deg; D for 0,9 c/deg; E 0,8 c/deg; and F =0.06 c/deg (which account for the largest bars)

31 3.2.3 – Transient VEP waveforms change during contrast modulation.

Figure 6 shows responses to stimuli of increasing contrast. Published data from recordings in anaesthetized animals show a reduction in latency and an increase in amplitude after modulating contrast from 10% to 90% (Porciatti et al, 1999). Here I show that in awake mice there is not a clear change in latency and just a minor change in amplitude. However the waveform markedly changes and while at high contrasts the first positive VEP component is larger, at low contrasts the succeeding negative trough prevails (Fig. 6).

Figure 6 - VEP waveforms During Contrast Modulation. Transient stimuli (temporal freq. 1Hz, spatial freq. 0,06 c/deg) are shown with different contrast. In A contrast 6%, in B contrast 10%, in C contrast 20%, and in D contrast 30%

32 3.2.5 Steady state VEP in the frequency range 4 to 12 Hz vary phase but not amplitude.

Figure 7 shows examples of steady state VEPs in response to grating reversing sinusoidally in contrast at different temporal frequency (from 4Hz to 12Hz).

Recordings in anesthetized animals have shown that maximal responses were

obtained at around 4Hz. Beyond 4Hz the amplitude progressively decreased, eventually vanishing for frequencies around 10Hz (Porciatti et al, 1999).

Here I show that in the awake animal amplitude stays almost constant in the frequency range 4 to 12 Hz. This may be due to an increased inhibitory activity (Haider et al., 2013; Kimura et al., 2014)

Phases of the VEP oscillations, however, continue to vary systematically with stimulus frequency as previously observed in the anesthetized animal

(Porciatti et al 1999))

Figure 7. Steady state stimuli at different temporal frequency. Optimal steady state stimuli (Contrast 30%, Spatial freq. 0,06 c/deg ) are shown in A at 4Hz, in B at 6Hz, in C at 8Hz, in D at 10Hz, in E at12 Hz. Responses are evoked accordingly to the second harmonic of presented stimulus.

33

3.3 – Longitudinal evolution of VEP responses in normal animals

The chronic implant of the recordings apparatus allowed me to record each animal twice a week for one month. This offered for the first time in our lab the possibility to study the evolution of visual responses throughout a long recording period.

The first parameter which I evaluated is the VEP amplitude. For transient and flash stimuli it is assessed by measuring the peak-to-trough amplitude of the first major component of the VEP waveforms, whereas for steady state stimuli a Fourier transformation of the VEP waveform is performed and the amplitude of the second harmonic is considered (see Fig. 2B and Fig. 6). Figure 7 shows the variations of VEP amplitudes throughout the recording period.

Response amplitude for transient stimuli shows a progressive increase during the recording period. The increase is marked in the first three weeks, reaching then a plateau. There is statistical significance for this

enhancement (one way anova, p<0,05) in day 6 vs day 23, day 6 vs day 30, and day 6 vs day 33. This could be explained by the phenomenon of experience-dependent response enhancement described by Frenkel et al., 2006.

Figure 8 - Evolution of VEP amplitude in normal mice. Panel A shows longitudinally the amplitude of VEP responses for transient stimuli (Contrast 30%, Spat. Freq. 0,06 c/deg, Temp Freq 1Hz). Panel B, the same for Stedy Steate stimuli (Contrast 30%, Spat. Freq. 0,06 c/deg) . And panel C refers to Flash.

34 Response amplitude for steady state and flash stimuli do not show any statistically significant variation throughout the recording periods. This demonstrates no significant drift in visual responses which could be caused by gliosis and/or electrode instability.

3.4– Longitudinal evolution of VEP responses in glioma-bearing animals

The same longitudinal analysis described above has been performed in mice injected with GL261 glioma cells. During the recording period, the glioma mass progressively grows in proximity of the chronic electrode in these animals.

Figure 9 show an histological cortical section from a glioma-bearing mouse, 14 days

after GL261 cell

transplant. Note the glioma mass that covers the entire cortical plate on the medial side of the occipital areas. The Figure also indicates the approximate positioning of the recording electrode (3.0 mm from lambda; see also Materials and Methods, Fig. 1).

Figure 10 show the evolution of VEP amplitudes. Responses to all stimuli are consistently altered during glioma progression. Transient stimuli responses show an initial increase (until day 13), Figura 9 – Histological cortical section from a

glioma bearing mice.

Figura 10 – Evolution of VEP recordings throughout the recording period in glioma-bearing mica

35 turning then to a constant decrease. Steady state and flash responses show instead a monotonous decrease.

I performed a statistical analyisis using one way repeated measures Anova Test. I found a significant decrease (p<0.05) of VEP responses for transient stimuli at day 13 vs day 23, 26, 30; day 9 vs day 26, 30; day 6 vs day 30. For steady state stimuli at day 6 vs day 20, 23, 26, 30; day 9 vs day 23 26 30 ; and day 13 vs day 26, 30. For flash at day 6 vs day 23, 26, 30; day 9 vs day 23 26 30 ; and day 13 vs day 26, 30.

Figure 9 show a comparison between normal and glioma mice.

I performed a two way repeated measure Anova Test. I found significant differences (p<0.05) for responses to transient stimuli between glioma and normal animals at days 23, 26, 30, 33; for responses to steady state stimuli at days 23, 26,30; for

responses to flash stimuli at days 23, 26, 30.

Figure 11 - Comparison between VEP amplitude trend in normal and glioma mice. In each panel upper curve refers to normal animal and bottom curve to glioma bearing mice.

36

3.5 – Contrast threshold, Acuity and Temporal resolution.

Contrast threshold, acuity and temporal resolution are three well established parameters which link cortical electrophysiology to sensory perception. They are assessed measuring VEP amplitudes for suboptimal conditions (low contrast, high spatial frequency, high temporal frequency) and taking the highest spatial/temporal frequency and lowest contrast able to evoke a response above noise level. This value is taken as representative of the sensory threshold.

Noise level is calculated by averaging several recordings acquired with blank stimulations. In normal animals, contrast threshold is set at 6%, visual acuity at 0.6c/deg and temporal resolution at 12Hz.

I evaluated longitudinally the evolution of these parameters in normal and glioma injected animals. In order to describe the trend I introduced an index, the “relative variation”, calculated as:

𝑡𝑟𝑒𝑠ℎ𝑜𝑙𝑑 𝑟𝑒𝑙𝑎𝑡𝑖𝑣𝑒 𝑡𝑜 𝑡ℎ𝑒 𝑙𝑎𝑠𝑡 𝑟𝑒𝑐. 𝑠𝑒𝑠𝑠𝑖𝑜𝑛

𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑜𝑓 𝑡ℎ𝑒𝑟𝑒𝑠ℎ𝑜𝑙𝑑 𝑟𝑒𝑙𝑎𝑡𝑖𝑣𝑒 𝑡𝑜 𝑡ℎ𝑒 𝑓𝑖𝑟𝑠𝑡 𝑡ℎ𝑟𝑒𝑒 𝑟𝑒𝑐. 𝑠𝑒𝑠𝑠𝑖𝑜𝑛

If “relative variation” is 1 it means that the visual property under examination remained stable along the recording period.

Contrast threshold was found to remain stable in almost every recorded mouse, with no difference between normal and glioma-bearing animals (Fig. 12A). Conversely, visual acuity was stable in normal animals but it underwent a statistically significant decrease in glioma injected mice (Fig. 12B; t-test, p < 0.05). Representative examples of visual acuity determinations in a glioma-bearing mouse during tumour progression are shown in Fig. 11. Temporal resolution has a larger inter-animal variability, and no significant differences

Figure 12 - Visual Acuity acquired in two different recording session in a Glioma Injected Mouse. In A data from the first week of recordings, whereas in B data from the third week. Arrow indicates the first spatial frequency which is not able to evoke a response beyond the noise.