Intratumoral heterogeneity identified at the epigenetic, genetic and transcriptional level in glioblastoma

Quantification and localization of oncogenic receptor tyrosine kinase variant transcripts using molecular inversion probes

Oncogenic membrane receptor tyrosine kinases such as MET and EGFR, or auto-active variants thereof, are important targets for cancer precision therapy. Targeted inhibition of these oncogenic receptors however invariably leads to resistance, resulting from acquisition of resistance-inducing mutations or from selective outgrowth of a priori resistant tumour cells. Most applied molecular protocols cannot distinguish between intracellular and intercellular heterogeneity of oncogene (variant) expression, which may lead to misinterpretation of the molecular make-up of a cancer and suboptimal application of targeted therapies. We here combined two related techniques to allow semiquantitative and localized in situ detection of specific transcript splice variants using single molecule molecular inversion probe (smMIP)-based next generation sequencing and padlock probe-based rolling circle amplification, respectively. We show highly specific padlock probe-based multiplex detection of MET, MET^Δ7-8 and MET^Δ14 transcripts, lacking exons 7-8 and exon 14 respectively, and of EGFR and the auto-active EGFRvIII, lacking exons 2-7. The combination of quantitative transcript variant detection with smMIPs and transcript localization using padlock probes can be used for detection of oncogenic transcripts on the single-cell level, allowing study of tumour heterogeneity. Visualization of tumour heterogeneity can shed light on the biology underlying drug resistance and potentially improve targeted therapeutics.

Sequencing the next generation of glioblastomas

The most aggressive brain malignancy, glioblastoma, accounts for 60-70% of all gliomas and is uniformly fatal. According to the molecular signature, glioblastoma is divided into four subtypes (proneural, neural, classical, and mesenchymal), each with its own genetic background. The Cancer Genome Atlas project provides information about the most common genetic changes in glioblastoma. They involve mutations in TP53, TERT, and PTEN, and amplifications in EFGR, PDGFRA, CDK4, CDK6, MDM2, and MDM4. Recently, epigenetics was used to demonstrate the oncogenic roles of miR-124, miR-137, and miR-128. The most important findings so far are mutations in IDH1/2 and MGMT promoter methylation, which are routinely used as predictive biomarkers in patient care. Current clinical treatment leaves patients with only a 10% chance for 5-year survival. Attempts to define the mutational profile of glioblastoma to identify clinically relevant changes have not yet yielded significant results. This can be attributed to inter- and intra-tumor heterogeneity that is present in most glioblastomas, as well as hypermutation that appears as a consequence of chemotherapy. The evolving field of radiogenomics aims to classify glioblastoma using a combination of magnetic resonance imaging and genomic information. In the era of genomic medicine, next-generation sequencing is extensively used in glioblastoma research because it can detect multiple changes in a single biological sample; its potential in detecting circulating cell-free DNA has been tested in cerebrospinal fluid and plasma, and it shows promise in the examination of the cellular content of extracellular vesicles as a potential source of biomarkers. Next-generation sequencing is making its way into glioblastoma diagnostics. Gene panels like GlioSeq, which includes the most commonly mutated genes, are currently being tested on snap frozen and formalin fixed paraffin embedded tissues. This new methodology is helping to define the "next generation of glioblastomas" - clinically defined and better understood, with greater potential to improve patient care. However, limitations of the necessary infrastructure, space for data storage, technical expertise, and data ownership need to be considered carefully.

Multiregional radiomics features from multiparametric MRI for prediction of MGMT methylation status in glioblastoma multiforme: A multicentre study

OBJECTIVES

To build a reliable radiomics model from multiregional and multiparametric magnetic resonance imaging (MRI) for pretreatment prediction of O⁶-methylguanine-DNA methyltransferase (MGMT) promotor methylation status in glioblastoma multiforme (GBM).

METHODS

In this retrospective multicentre study, 1,705 multiregional radiomics features were automatically extracted from multiparametric MRI. A radiomics model with a minimal set of all-relevant features and a radiomics model with univariately-predictive and non-redundant features were built for MGMT methylation prediction from a primary cohort (133 patients) and tested on an independent validation cohort (60 patients). Predictive models combing clinical factors were built and evaluated. Both radiomics models were assessed on subgroups stratified by clinical factors.

RESULTS

The radiomics model with six all-relevant features allowed pretreatment prediction of MGMT methylation (AUC=0.88, accuracy=80 %), which significantly outperformed the model with eight univariately-predictive and non-redundant features (AUC=0.76, accuracy=70 %). Combing clinical factors with radiomics features did not benefit the prediction performance. The all-relevant model achieved significantly better performance in stratified analysis.

CONCLUSIONS

Radiomics model built from multiregional and multiparameter MRI may serve as a potential imaging biomarker for pretreatment prediction of MGMT methylation in GBM. The all-relevant features have the potential of offering better predictive power than the univariately-predictive and non-redundant features.

KEY POINTS

• Multiregional and multiparametric MRI features reliably predicted MGMT methylation in multicentre cohorts. • All-relevant imaging features predicted MGMT methylation better than univariately-predictive and non-redundant features. • Combing clinical factors with radiomics features did not benefit the prediction performance.

Clinical laboratory and imaging evidence for effectiveness of agarose-agarose macrobeads containing stem-like cells derived from a mouse renal adenocarcinoma cell population (RMBs) in treatment-resistant, advanced metastatic colorectal cancer: Evaluation of a biological-systems approach to cancer therapy (U.S. FDA IND-BB 10091; NCT 02046174, NCT 01053013)

Objective

The complexity, heterogeneity and capacity of malignant neoplastic cells and tumors for rapid change and evolution suggest that living-cell-based biological-systems approaches to cancer treatment are merited. Testing this hypothesis, the tumor marker, metabolic activity, and overall survival (OS) responses, to the use of one such system, implantable macrobeads [RENCA macrobeads (RMBs)], in phase I and IIa clinical trials in advanced, treatment-resistant metastatic colorectal cancer (mCRC) are described here.

Methods

Forty-eight mCRC patients (30 females; 18 males), who had failed all available, approved treatments, underwent RMB implantation (8 RMB/kg body weight) up to 4 times in phase I and phase IIa open-label trials. Physicals, labs [tumor and inflammation markers, lactate dehydrogenase (LDH)] and positron emission tomography-computed tomography (PET-CT) imaging to measure number/volume and metabolic activity of the tumors were performed pre- and 3-month-post-implantation to evaluate safety and initial efficacy (as defined by biological responses). PET-CT maximum standard uptake value (SUV_max) (baseline and d 90; SUV_max ≥2.5), LDH, and carcinoembryonic antigen (CEA) and/or cancer antigen 19-9 (CA 19-9) response (baseline, d 30 and/or d 60) were assessed and compared to OS.

Results

Responses after implantation were characterized by an at least 20% decrease in CEA and/or CA 19-9 in 75% of patients. Fluorodeoxyglucose (FDG)-positive lesions (phase I, 39; 2a, 82) were detected in 37/48 evaluable patients, with 35% stable volume and stable or decreased SUV (10) plus four with necrosis; 10, increased tumor volume, SUV. LDH levels remained stable and low in Responders (R) (d 0-60, 290.4-333.9), but increased steadily in Non-responders (NR) (d 0-60, 382.8-1,278.5) (d 60, P=0.050). Responders to RMBs, indicated by the changes in the above markers, correlated with OS (R mean OS=10.76 months; NR mean OS=4.9 months; P=0.0006).

Conclusions

The correlations of the tumor marker, tumor volume and SUV changes on PET-CT, and LDH levels themselves, and with OS, support the concept of a biological response to RMB implantation and the validity of the biological-systems approach to mCRC. A phase III clinical trial is planned.

An Examination of the Role of Supramaximal Resection of Temporal Lobe Glioblastoma Multiforme

BACKGROUND

Resection of the T1 contrast-enhancing portion of glioblastoma multiforme (GBM) has been shown to increase patient survival, although whether GBM resection beyond these boundaries has an additional survival benefit is not clear. In this study, we examined the effect of resecting the enhancement and a margin of brain tissue surrounding the enhancement in patients with GBM of the temporal lobe.

METHODS

We identified 32 consecutive patients with temporal lobe GBM who underwent initial resection between 2012 and 2015. Progression-free survival (PFS) and overall survival (OS) were analyzed based on the following categories: subtotal resection (STR; <99% of contrast enhancement removed), gross total resection (GTR; 100% of T1 contrast enhancement removed), and supramaximal resection (SMR; removal of T1 contrast enhancement plus removal of at least 1 cm of brain tissue surrounding the enhancement).

RESULTS

Patients undergoing SMR demonstrated a substantially improved median PFS (15 months) compared with those undergoing GTR (7 months) or those undergoing STR (6 months) (P < 0.003). A median OS advantage was also present in the SMR group (24 months) compared with the GTR (11 months) and STR (9 months) groups (P < 0.004). SMR significantly improved PFS (hazard ratio [HR], 0.093; 95% confidence interval [CI], 0.01-0.89; P = 0.039) and OS (HR, 0.169; 95% CI, 0.05-0.57; P < 0.004) when controlling for other variables. The complication rates did not differ among the resection groups (P = 0.66).

CONCLUSIONS

Achieving SMR substantially improved survival in patients with temporal lobe GBM compared with GTR of the enhancement alone.

Intratumoral heterogeneity: pathways to treatment resistance and relapse in human glioblastoma

Intratumoral heterogeneity (ITH) has increasingly being described for multiple cancers as the root cause of therapy resistance. Recent studies have started to explore the scope of ITH in glioblastoma (GBM), a highly aggressive and fatal form of brain tumor, to explain its inevitable therapy resistance and disease relapse. In this review, we detail the emerging data that explores the extensive genetic, cellular and functional ITH present in GBM. We discuss current experimental models of human GBM recurrence and suggest harnessing new technologies (CRISPR-Cas9 screening, CyTOF, cellular barcoding, single cell analysis) to delineate GBM ITH and identify treatment-refractory cell populations, thus opening new therapeutic windows. We will also explore why current therapeutics have failed in clinical trials and how ITH can inform us on developing empiric therapies for the treatment of recurrent GBM.

Microenvironment-Derived Regulation of HIF Signaling Drives Transcriptional Heterogeneity in Glioblastoma Multiforme

The evolving and highly heterogeneous nature of malignant brain tumors underlies their limited response to therapy and poor prognosis. In addition to genetic alterations, highly dynamic processes, such as transcriptional and metabolic reprogramming, play an important role in the development of tumor heterogeneity. The current study reports an adaptive mechanism in which the metabolic environment of malignant glioma drives transcriptional reprogramming. Multiregional analysis of a glioblastoma patient biopsy revealed a metabolic landscape marked by varying stages of hypoxia and creatine enrichment. Creatine treatment and metabolism was further shown to promote a synergistic effect through upregulation of the glycine cleavage system and chemical regulation of prolyl-hydroxylase domain. Consequently, creatine maintained a reduction of reactive oxygen species and change of the α-ketoglutarate/succinate ratio, leading to an inhibition of HIF signaling in primary tumor cell lines. These effects shifted the transcriptional pattern toward a proneural subtype and reduced the rate of cell migration and invasion in vitroImplications: Transcriptional subclasses of glioblastoma multiforme are heterogeneously distributed within the same tumor. This study uncovered a regulatory function of the tumor microenvironment by metabolism-driven transcriptional reprogramming in infiltrating glioma cells. Mol Cancer Res; 16(4); 655-68. ©2018 AACR.

New extracellular factors in glioblastoma multiforme development: neurotensin, growth differentiation factor-15, sphingosine-1-phosphate and cytomegalovirus infection

Recent years have seen considerable progress in understanding the biochemistry of cancer. For example, more significance is now assigned to the tumor microenvironment, especially with regard to intercellular signaling in the tumor niche which depends on many factors secreted by tumor cells. In addition, great progress has been made in understanding the influence of factors such as neurotensin, growth differentiation factor-15 (GDF-15), sphingosine-1-phosphate (S1P), and infection with cytomegalovirus (CMV) on the 'hallmarks of cancer' in glioblastoma multiforme. Therefore, in the present work we describe the influence of these factors on the proliferation and apoptosis of neoplastic cells, cancer stem cells, angiogenesis, migration and invasion, and cancer immune evasion in a glioblastoma multiforme tumor. In particular, we discuss the effect of neurotensin, GDF-15, S1P (including the drug FTY720), and infection with CMV on tumor-associated macrophages (TAM), microglial cells, neutrophil and regulatory T cells (T_reg), on the tumor microenvironment. In order to better understand the role of the aforementioned factors in tumoral processes, we outline the latest models of intratumoral heterogeneity in glioblastoma multiforme. Based on the most recent reports, we discuss the problems of multi-drug therapy in treating glioblastoma multiforme.

PDGF Family Expression in Glioblastoma Multiforme: Data Compilation from Ivy Glioblastoma Atlas Project Database

Glioblastoma Multiforme (GBM) is the most frequent and lethal primary brain cancer. Due to its therapeutic resistance and aggressiveness, its clinical management is challenging. Platelet-derived Growth Factor (PDGF) genes have been enrolled as drivers of this tumour progression as well as potential therapeutic targets. As detailed understanding of the expression pattern of PDGF system in the context of GBM intra- and intertumoral heterogeneity is lacking in the literature, this study aims at characterising PDGF expression in different histologically-defined GBM regions as well as investigating correlation of these genes expression with parameters related to poor prognosis. Z-score normalised expression values of PDGF subunits from multiple slices of 36 GBMs, alongside with clinical and genomic data on those GBMs patients, were compiled from Ivy Glioblastoma Atlas Project – Allen Institute for Brain Science data sets. PDGF subunits show differential expression over distinct regions of GBM and PDGF family is heterogeneously expressed among different brain lobes affected by GBM. Further, PDGF family expression correlates with bad prognosis factors: age at GBM diagnosis, Phosphatase and Tensin Homolog deletion and Isocitrate Dehydrogenase 1 mutation. These findings may aid on clinical management of GBM and development of targeted curative therapies against this devastating tumour.

Assessment of molecular markers demonstrates concordance between samples acquired via stereotactic biopsy and open craniotomy in both anaplastic astrocytomas and glioblastomas

The classification, treatment and prognosis of high-grade gliomas has been shown to correlate with the expression of molecular markers (e.g. MGMT promotor methylation and IDH1 mutations). Acquisition of tumor samples may be obtained via stereotactic biopsy or open craniotomy. Between the years 2009 and 2013, 22 patients initially diagnosed with HGGs via stereotactic biopsy, that ultimately underwent open craniotomy for resection of their tumor were prospectively included in an institutional glioma database. MGMT promotor analysis was performed using methylation-specific (MS)-PCR and IDH1R132H mutation analysis was performed using immunohistochemistry. Three patients (13.7%) exhibited IDH1R132H mutations in samples obtained via stereotactic biopsy. Tissue derived from stereotaxic biopsy was demonstrated to have MGMT promotor methylation in ten patients (45.5%), while a non-methylated MGMT promotor was demonstrated in ten patients (45.5%); inconclusive results were obtained for the remaining two patients (9%) within our cohort. The initial histologic grading, IDH1R132H mutation and MGMT promotor methylation results were confirmed using samples obtained during open craniotomy in all but one patient; here inconclusive MGMT promotor analysis was obtained in contrast to that which was obtained via stereotactic biopsy. Tumor samples acquired via stereotactic biopsy provide accurate information with regard to clinically relevant molecular markers that have been shown to impact patient care decisions. The profile of markers analyzed in our cohort was nearly concordant between those samples obtained via stereotactic biopsy or open craniotomy thereby suggesting that clinical decisions may be based on the molecular profile of the tumor samples obtained via stereotactic biopsy.

Biological activity of tumor-treating fields in preclinical glioma models

Glioblastoma is the most common and aggressive form of intrinsic brain tumor with a very poor prognosis. Thus, novel therapeutic approaches are urgently needed. Tumor-treating fields (TTFields) may represent such a novel treatment option. The aim of this study was to investigate the effects of TTFields on glioma cells, as well as the functional characterization of the underlying mechanisms. Here, we assessed the anti-glioma activity of TTFields in several preclinical models. Applying TTFields resulted in the induction of cell death in a frequency- and intensity-dependent manner in long-term glioma cell lines, as well as glioma-initiating cells. Cell death occurred in the absence of caspase activation, but involved autophagy and necroptosis. Severe alterations in cell cycle progression and aberrant mitotic features, such as poly- and micronucleation, preceded the induction of cell death. Furthermore, exposure to TTFields led to reduced migration and invasion, which are both biological hallmarks of glioma cells. The combination of TTFields with irradiation or the alkylating agent, temozolomide (TMZ), resulted in additive or synergistic effects, and the O⁶-methyl-guanine DNA methyltransferase status did not influence the efficacy of TTFields. Importantly, TMZ-resistant glioma cells were responsive to TTFields application, highlighting the clinical potential of this therapeutic approach. In summary, our results indicate that TTFields induce autophagy, as well as necroptosis and hamper the migration and invasiveness of glioma cells. These findings may allow for a more detailed clinical evaluation of TTFields beyond the clinical data available so far.

Mathematical models of cell phenotype regulation and reprogramming: Make cancer cells sensitive again!

A cell's phenotype is the observable actualization of complex interactions between its genome, epigenome, and local environment. While traditional views in cancer have held that cellular and tumor phenotypes are largely functions of genomic instability, increasing attention has recently been given to epigenetic and microenvironmental influences. Such non-genetic factors allow cancer cells to experience intrinsic diversity and plasticity, and at the tumor level can result in phenotypic heterogeneity and treatment evasion. In 2006, Takahashi and Yamanaka exploited the epigenome's plasticity by "reprogramming" differentiated cells into a pluripotent state by inducing expression of a cocktail of four transcription factors. Recent advances in cancer biology have shown not only that cellular reprogramming is possible for malignant cells, but it may provide a foundation for future therapies. Nevertheless, cell reprogramming experiments are frequently plagued by low efficiency, activation of aberrant transcriptional programs, instability, and often rely on expertise gathered from systems which may not translate directly to cancer. Here, we review a theoretical framework tracing back to Waddington's epigenetic landscape which may be used to derive quantitative and qualitative understanding of cellular reprogramming. Implications for tumor heterogeneity, evolution and adaptation are discussed in the context of designing new treatments to re-sensitize recalcitrant tumors. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

Analysis of Chemopredictive Assay for Targeting Cancer Stem Cells in Glioblastoma Patients

INTRODUCTION

The prognosis of glioblastoma (GBM) treated with standard-of-care maximal surgical resection and concurrent adjuvant temozolomide (TMZ)/radiotherapy remains very poor (less than 15 months). GBMs have been found to contain a small population of cancer stem cells (CSCs) that contribute to tumor propagation, maintenance, and treatment resistance. The highly invasive nature of high-grade gliomas and their inherent resistance to therapy lead to very high rates of recurrence. For these reasons, not all patients with similar diagnoses respond to the same chemotherapy, schedule, or dose. Administration of ineffective anticancer therapy is not only costly but more importantly burdens the patient with unnecessary toxicity and selects for the development of resistant cancer cell clones. We have developed a drug response assay (ChemoID) that identifies the most effective chemotherapy against CSCs and bulk of tumor cells from of a panel of potential treatments, offering great promise for individualized cancer management. Providing the treating physician with drug response information on a panel of approved drugs will aid in personalized therapy selections of the most effective chemotherapy for individual patients, thereby improving outcomes. A prospective study was conducted evaluating the use of the ChemoID drug response assay in GBM patients treated with standard of care.

METHODS

Forty-one GBM patients (mean age 54 years, 59% male), all eligible for a surgical biopsy, were enrolled in an Institutional Review Board-approved protocol, and fresh tissue samples were collected for drug sensitivity testing. Patients were all treated with standard-of-care TMZ plus radiation with or without maximal surgery, depending on the status of the disease. Patients were prospectively monitored for tumor response, time to recurrence, progression-free survival (PFS), and overall survival (OS). Odds ratio (OR) associations of 12-month recurrence, PFS, and OS outcomes were estimated for CSC, bulk tumor, and combined assay responses for the standard-of-care TMZ treatment; sensitivities/specificities, areas under the curve (AUCs), and risk reclassification components were examined.

RESULTS

Median follow-up was 8 months (range 3-49 months). For every 5% increase in in vitro CSC cell kill by TMZ, 12-month patient response (nonrecurrence of cancer) increased two-fold, OR=2.2 (P=.016). Similar but somewhat less supported associations with the bulk tumor test were seen, OR=2.75 (P=.07) for each 5% bulk tumor cell kill by TMZ. Combining CSC and bulk tumor assay results in a single model yielded a statistically supported CSC association, OR=2.36 (P=.036), but a much attenuated remaining bulk tumor association, OR=1.46 (P=.472). AUCs and [sensitivity/specificity] at optimal outpoints (>40% CSC cell kill and >55% bulk tumor cell kill) were AUC=0.989 [sensitivity=100/specificity=97], 0.972 [100/89], and 0.989 [100/97] for the CSC only, bulk tumor only, and combined models, respectively. Risk categorization of patients was improved by 11% when using the CSC test in conjunction with the bulk test (risk reclassification nonevent net reclassification improvement [NRI] and overall NRI=0.111, P=.030). Median recurrence time was 20 months for patients with a positive (>40% cell kill) CSC test versus only 3 months for those with a negative CSC test, whereas median recurrence time was 13 months versus 4 months for patients with a positive (>55% cell kill) bulk test versus negative. Similar favorable results for the CSC test were observed for PFS and OS outcomes. Panel results across 14 potential other treatments indicated that 34/41 (83%) potentially more optimal alternative therapies may have been chosen using CSC results, whereas 27/41 (66%) alternative therapies may have been chosen using bulk tumor results.

CONCLUSIONS

The ChemoID CSC drug response assay has the potential to increase the accuracy of bulk tumor assays to help guide individualized chemotherapy choices. GBM cancer recurrence may occur quickly if the CSC test has a low in vitro cell kill rate even if the bulk tumor test cell kill rate is high.

Organelles - understanding noise and heterogeneity in cell biology at an intermediate scale

Many studies over the years have shown that non-genetic mechanisms for producing cell-to-cell variation can lead to highly variable behaviors across genetically identical populations of cells. Most work to date has focused on gene expression noise as the primary source of phenotypic heterogeneity, yet other sources may also contribute. In this Commentary, we explore organelle-level heterogeneity as a potential secondary source of cellular 'noise' that contributes to phenotypic heterogeneity. We explore mechanisms for generating organelle heterogeneity and present evidence of functional links between organelle morphology and cellular behavior. Given the many instances in which molecular-level heterogeneity has been linked to phenotypic heterogeneity, we posit that organelle heterogeneity may similarly contribute to overall phenotypic heterogeneity and underline the importance of studying organelle heterogeneity to develop a more comprehensive understanding of phenotypic heterogeneity. Finally, we conclude with a discussion of the medical challenges associated with phenotypic heterogeneity and outline how improved methods for characterizing and controlling this heterogeneity may lead to improved therapeutic strategies and outcomes for patients.

Radiomic Phenotyping in Brain Cancer to Unravel Hidden Information in Medical Images

Radiomics is a new area of research in the field of imaging with tremendous potential to unravel the hidden information in digital images. The scope of radiology has grown exponentially over the last two decades; since the advent of radiomics, many quantitative imaging features can now be extracted from medical images through high-throughput computing, and these can be converted into mineable data that can help in linking imaging phenotypes with clinical data, genomics, proteomics, and other "omics" information. In cancer, radiomic imaging analysis aims at extracting imaging features embedded in the imaging data, which can act as a guide in the disease or cancer diagnosis, staging and planning interventions for treating patients, monitor patients on therapy, predict treatment response, and determine patient outcomes.

Pioglitazone Effect on Glioma Stem Cell Lines: Really a Promising Drug Therapy for Glioblastoma?

Glioblastoma multiforme (GBM) represents one of the most frequent malignant brain tumors. Current therapies do not provide real solutions to this pathology. Their failure can be ascribed to a cell subpopulation with stem-like properties called glioma stem cells (GSCs). Therefore, new therapeutic strategies GSC-targeted are needed. PPARγ, a nuclear receptor involved in lipid metabolism, has already been indicated as a promising target for antineoplastic therapies. Recent studies have reported that synthetic PPARγ agonists, already in clinical use for the treatment of type II diabetes, exhibit antineoplastic effects in a wide range of malignant tumor cells, including glioma cells. We investigated the effect of the synthetic PPARγ agonist Pioglitazone on viability, proliferation, morphology, and differentiation in six GSC lines isolated from GBM patients. We also analyzed Pioglitazone-induced changes in transcriptional levels of Wnt/β catenin related genes. Results showed that response to Pioglitazone was heterogeneous inducing an evident decrease of cell viability and proliferation only in a subset of GSC lines. We did not find any sign of cell differentiation neither observing cell morphology nor analyzing the expression of stemness and differentiation markers. Moreover, Wnt/β signaling pathway was only mildly affected from a transcriptional point of view after Pioglitazone exposure.