Response-predictive gene expression profiling of glioma progenitor cells in vitro

TSPO acts as an immune resistance gene involved in the T cell mediated immune control of glioblastoma

Glioblastoma (GB) IDH-wildtype is the most malignant primary brain tumor. It is particularly resistant to current immunotherapies. Translocator protein 18 kDa (TSPO) is upregulated in GB and correlates with malignancy and poor prognosis, but also with increased immune infiltration. Here, we studied the role of TSPO in the regulation of immune resistance of human GB cells. The role of TSPO in tumor immune resistance was experimentally determined in primary brain tumor initiating cells (BTICs) and cell lines through genetic manipulation of TSPO expression and subsequent cocultures with antigen specific cytotoxic T cells and autologous tumor-infiltrating T cells. Death inducing intrinsic and extrinsic apoptotic pathways affected by TSPO were investigated. TSPO-regulated genes mediating apoptosis resistance in BTICs were identified through gene expression analysis and subsequent functional analyses. TSPO transcription in primary GB cells correlated with CD8⁺ T cell infiltration, cytotoxic activity of T cell infiltrate, expression of TNFR and IFNGR and with the activity of their downstream signalling pathways, as well as with the expression of TRAIL receptors. Coculture of BTICs with tumor reactive cytotoxic T cells or with T cell-derived factors induced TSPO up-regulation through T cell derived TNFα and IFNγ. Silencing of TSPO sensitized BTICs against T cell-mediated cytotoxicity. TSPO selectively protected BTICs against TRAIL-induced apoptosis by regulating apoptosis pathways. TSPO also regulated the expression of multiple genes associated with resistance against apoptosis. We conclude that TSPO expression in GB is induced through T cell-derived cytokines TNFα and IFNγ and that TSPO expression protects GB cells against cytotoxic T cell attack through TRAIL. Our data thereby provide an indication that therapeutic targeting of TSPO may be a suitable approach to sensitize GB to immune cell-mediated cytotoxicity by circumventing tumor intrinsic TRAIL resistance.

Heterogeneity of Amino Acid Profiles of Proneural and Mesenchymal Brain-Tumor Initiating Cells

Glioblastomas are highly malignant brain tumors that derive from brain-tumor-initiating cells (BTICs) and can be subdivided into several molecular subtypes. Metformin is an antidiabetic drug currently under investigation as a potential antineoplastic agent. The effects of metformin on glucose metabolism have been extensively studied, but there are only few data on amino acid metabolism. We investigated the basic amino acid profiles of proneural and mesenchymal BTICs to explore a potential distinct utilization and biosynthesis in these subgroups. We further measured extracellular amino acid concentrations of different BTICs at baseline and after treatment with metformin. Effects of metformin on apoptosis and autophagy were determined using Western Blot, annexin V/7-AAD FACS-analyses and a vector containing the human LC3B gene fused to green fluorescent protein. The effects of metformin on BTICs were challenged in an orthotopic BTIC model. The investigated proneural BTICs showed increased activity of the serine and glycine pathway, whereas mesenchymal BTICs in our study preferably metabolized aspartate and glutamate. Metformin treatment led to increased autophagy and strong inhibition of carbon flux from glucose to amino acids in all subtypes. However, oral treatment with metformin at tolerable doses did not significantly inhibit tumor growth in vivo. In conclusion, we found distinct amino acid profiles of proneural and mesenchymal BTICs, and inhibitory effects of metformin on BTICs in vitro. However, further studies are warranted to better understand potential resistance mechanisms against metformin in vivo.

Glioblastoma Invasiveness and Collagen Secretion Are Enhanced by Vitamin C

Aims: Glioblastoma (GB) is one of the most aggressive brain tumors. These tumors modify their metabolism, increasing the expression of glucose transporters, GLUTs, which incorporate glucose and the oxidized form of vitamin C, dehydroascorbic acid (DHA). We hypothesized that GB cells preferentially take up DHA, which is intracellularly reduced and compartmentalized into the endoplasmic reticulum (ER), promoting collagen biosynthesis and an aggressive phenotype. Results: Our results showed that GB cells take up DHA using GLUT1, while GLUT3 and sodium-dependent vitamin C transporter 2 (SVCT2) are preferably intracellular. Using a baculoviral system and reticulum-enriched extracts, we determined that SVCT2 is mainly located in the ER and corresponds to a short isoform. Ascorbic acid (AA) was compartmentalized, stimulating collagen IV secretion and increasing in vitro and in situ cell migration. Finally, orthotopic xenografts induced in immunocompetent guinea pigs showed that vitamin C deficiency retained collagen, reduced blood vessel invasion, and affected glomeruloid vasculature formation, all pathological conditions associated with malignancy. Innovation and Conclusion: We propose a functional role for vitamin C in GB development and progression. Vitamin C is incorporated into the ER of GB cells, where it favors the synthesis of collagen, thus impacting tumor development. Collagen secreted by tumor cells favors the formation of the glomeruloid vasculature and enhances perivascular invasion. Antioxid. Redox Signal. 37, 538-559.

Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning to derive multi‐gene expression signatures that predict individual patient responses to specific tyrosine kinase inhibitors, including erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Support vector machine (SVM) learning was used to train mathematical models that distinguished sensitivity from resistance to these drugs using a novel systems biology‐based approach. This began with expression of genes previously implicated in specific drug responses, then expanded to evaluate genes whose products were related through biochemical pathways and interactions. Optimal pathway‐extended SVMs predicted responses in patients at accuracies of 70% (imatinib), 71% (lapatinib), 83% (sunitinib), 83% (erlotinib), 88% (sorafenib) and 91% (gefitinib). These best performing pathway‐extended models demonstrated improved balance predicting both sensitive and resistant patient categories, with many of these genes having a known role in cancer aetiology. Ensemble machine learning‐based averaging of multiple pathway‐extended models derived for an individual drug increased accuracy to >70% for erlotinib, gefitinib, lapatinib and sorafenib. Through incorporation of novel cancer biomarkers, machine learning‐based pathway‐extended signatures display strong efficacy predicting both sensitive and resistant patient responses to chemotherapy.

Proneural and mesenchymal glioma stem cells display major differences in splicing and lncRNA profiles

Therapy resistance and recurrence in high-grade gliomas are driven by their populations of glioma stem cells (GSCs). Thus, detailed molecular characterization of GSCs is needed to develop more effective therapies. We conducted a study to identify differences in the splicing profile and expression of long non-coding RNAs in proneural and mesenchymal GSC cell lines. Genes related to cell cycle, DNA repair, cilium assembly, and splicing showed the most differences between GSC subgroups. We also identified genes distinctly associated with survival among patients of mesenchymal or proneural subgroups. We determined that multiple long non-coding RNAs with increased expression in mesenchymal GSCs are associated with poor survival of glioblastoma patients. In summary, our study established critical differences between proneural and mesenchymal GSCs in splicing profiles and expression of long non-coding RNA. These splicing isoforms and lncRNA signatures may contribute to the uniqueness of GSC subgroups, thus contributing to cancer phenotypes and explaining differences in therapeutic responses.

Intravital imaging of glioma border morphology reveals distinctive cellular dynamics and contribution to tumor cell invasion

The pathogenesis of glioblastoma (GBM) is characterized by highly invasive behavior allowing dissemination and progression. A conclusive image of the invasive process is not available. The aim of this work was to study invasion dynamics in GBM using an innovative in vivo imaging approach. Primary brain tumor initiating cell lines from IDH-wild type GBM stably expressing H2B-Dendra2 were implanted orthotopically in the brains of SCID mice. Using high-resolution time-lapse intravital imaging, tumor cell migration in the tumor core, border and invasive front was recorded. Tumor cell dynamics at different border configurations were analyzed and multivariate linear modelling of tumor cell spreading was performed. We found tumor border configurations, recapitulating human tumor border morphologies. Not only tumor borders but also the tumor core was composed of highly dynamic cells, with no clear correlation to the ability to spread into the brain. Two types of border configurations contributed to tumor cell spreading through distinct invasion patterns: an invasive margin that executes slow but directed invasion, and a diffuse infiltration margin with fast but less directed movement. By providing a more detailed view on glioma invasion patterns, our study may improve accuracy of prognosis and serve as a basis for personalized therapeutic approaches.

ATF4 contributes to autophagy and survival in sunitinib treated brain tumor initiating cells (BTICs)

Receptor tyrosine kinase (RTK) pathways are known to play an important role in tumor cell proliferation of glioblastoma (GBM). Cellular determinants of RTK-inhibitor sensitivity are important to optimize and tailor treatment strategies. The stress response gene activating transcription factor 4 (ATF4) is involved in homeostasis and cellular protection. However, little is known about its function in GBM. We found that the ATF4/p-eIF2α pathway is activated in response to Sunitinib in primary tumor initiating progenitor cell cultures (BTICs). Furthermore, lysosome entrapment of RTK-inhibitors (RTK-Is) leads to accumulation of autophagosomes. In case of Sunitinib treated cells, autophagy is additionally increased by ATF4 mediated upregulation of autophagy genes. Inhibition of ATF4 by small interfering RNA (siRNA) reduced autophagy and cell proliferation after Sunitinib treatment in a subset of BTIC cultures. Overall, this study suggests a pro-survival role of the ATF4/p-eIF2α pathway in a cell type and treatment specific manner.

Autophagic and Apoptotic Pathways as Targets for Chemotherapy in Glioblastoma

Glioblastoma multiforme is the most malignant and aggressive type of brain tumor, with a mean life expectancy of less than 15 months. This is due in part to the high resistance to apoptosis and moderate resistant to autophagic cell death in glioblastoma cells, and to the poor therapeutic response to conventional therapies. Autophagic cell death represents an alternative mechanism to overcome the resistance of glioblastoma to pro-apoptosis-related therapies. Nevertheless, apoptosis induction plays a major conceptual role in several experimental studies to develop novel therapies against brain tumors. In this review, we outline the different components of the apoptotic and autophagic pathways and explore the mechanisms of resistance to these cell death pathways in glioblastoma cells. Finally, we discuss drugs with clinical and preclinical use that interfere with the mechanisms of survival, proliferation, angiogenesis, migration, invasion, and cell death of malignant cells, favoring the induction of apoptosis and autophagy, or the inhibition of the latter leading to cell death, as well as their therapeutic potential in glioma, and examine new perspectives in this promising research field.

Drug Repurposing of Metabolic Agents in Malignant Glioma

Gliomas are highly invasive brain tumors with short patient survival. One major pathogenic factor is aberrant tumor metabolism, which may be targeted with different specific and unspecific agents. Drug repurposing is of increasing interest in glioma research. Drugs interfering with the patient’s metabolism may also influence glioma metabolism. In this review, we outline definitions and methods for drug repurposing. Furthermore, we give insights into important candidates for a metabolic drug repurposing, namely metformin, statins, non-steroidal anti-inflammatory drugs, disulfiram and lonidamine. Advantages and pitfalls of drug repurposing will finally be discussed.

Stattic and metformin inhibit brain tumor initiating cells by reducing STAT3-phosphorylation

Glioblastoma (GBM) is the most common and malignant type of primary brain tumor and associated with a devastating prognosis. Signal transducer and activator of transcription number 3 (STAT3) is an important pathogenic factor in GBM and can be specifically inhibited with Stattic. Metformin inhibits GBM cell proliferation and migration. Evidence from other tumor models suggests that metformin inhibits STAT3, but there is no specific data on brain tumor initiating cells (BTICs).

We explored proliferation and migration of 7 BTICs and their differentiated counterparts (TCs) after treatment with Stattic, metformin or the combination thereof. Invasion was measured in situ on organotypic brain slice cultures. Protein expression of phosphorylated and total STAT3, as well as AMPK and mTOR signaling were explored using Western blot. To determine functional relevance of STAT3 inhibition by Stattic and metformin, we performed a stable knock-in of STAT3 in selected BTICs.

Inhibition of STAT3 with Stattic reduced proliferation in all BTICs, but only in 4 out of 7 TCs. Migration and invasion were equally inhibited in BTICs and TCs. Treatment with metformin reduced STAT3-phosphorylation in all investigated BTICs and TCs. Combined treatment with Stattic and metformin led to significant additive effects on BTIC proliferation, but not migration or invasion. No additive effects on TCs could be detected. Stable STAT3 knock-in partly attenuated the effects of Stattic and metformin on BTICs.

In conclusion, metformin was found to inhibit STAT3-phosphorylation in BTICs and TCs. Combined specific and unspecific inhibition of STAT3 might represent a promising new strategy in the treatment of glioblastoma.

Metformin inhibits proliferation and migration of glioblastoma cells independently of TGF-β2

To this day, glioblastoma (GBM) remains an incurable brain tumor. Previous research has shown that metformin, an oral anti-diabetic drug, may decrease GBM cell proliferation and migration especially in brain tumor initiating cells (BTICs). As transforming growth factor β 2 (TGF-β2) has been reported to promote high-grade glioma and is inhibited by metformin in other tumors, we explored whether metformin directly interferes with TGF-β2-signaling. Functional investigation of proliferation and migration of primary BTICs after treatment with metformin+/-TGF-β2 revealed that metformin doses as low as 0.01 mM metformin thrice a day were able to inhibit proliferation of susceptible cell lines, whereas migration was impacted only at higher doses. Known cellular mechanisms of metformin, such as increased lactate secretion, reduced oxygen consumption and activated AMPK-signaling, could be confirmed. However, TGF-β2 and metformin did not act as functional antagonists, but both rather inhibited proliferation and/or migration, if significant effects were present. We did not observe a relevant influence of metformin on TGF-β2 mRNA expression (qRT-PCR), TGF-β2 protein expression (ELISA) or SMAD-signaling (Western blot). Therefore, it seems that metformin does not exert its inhibitory effects on GBM BTIC proliferation and migration by altering TGF-β2-signaling. Nonetheless, as low doses of metformin are able to reduce proliferation of certain GBM cells, further exploration of predictors of BTICs' susceptibility to metformin appears justified.

Validation Study: Response-Predictive Gene Expression Profiling of Glioma Progenitor Cells In Vitro

Background

In a previous publication we introduced a novel approach to identify genes that hold predictive information about treatment outcome. A linear regression model was fitted by using the least angle regression algorithm (LARS) with the expression profiles of a construction set of 18 glioma progenitor cells enhanced for brain tumor initiating cells (BTIC) before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated progenitor cells allowed predicting therapy-induced impairment of proliferation in vitro. Prediction performance was validated in leave one out cross validation.

Methods

In this study, we used an additional validation set of 18 serum-free short-term treated in vitro cell cultures to test the predictive properties of the signature in an independent cohort. We assessed proliferation rates together with transcriptome-wide expression profiles after Sunitinib treatment of each individual cell culture, following the methods of the previous publication.

Results

We confirmed treatment-induced expression changes in our validation set, but our signature failed to predict proliferation inhibition. Neither re-calculation of the combined dataset with all 36 BTIC cultures nor separation of samples into TCGA subclasses did generate a proliferation prediction.

Conclusion

Although the gene signature published from our construction set exhibited good prediction accuracy in cross validation, we were not able to validate the signature in an independent validation data set. Reasons could be regression to the mean, the moderate numbers of samples, or too low differences in the response to proliferation inhibition in the validation set. At this stage and based on the presented results, we conclude that the signature does not warrant further developmental steps towards clinical application.