Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures

Background

In recent years, drug combinations have become increasingly popular to improve therapeutic outcomes in various diseases, including difficult to cure cancers such as the brain cancer glioblastoma. Assessing the interaction between drugs over time is critical for predicting drug combination effectiveness and minimizing the risk of therapy resistance. However, as viability readouts of drug combination experiments are commonly performed as an endpoint where cells are lysed, longitudinal drug-interaction monitoring is currently only possible through combined endpoint assays.

Methods

We provide a method for massive parallel monitoring of drug interactions for 16 drug combinations in 3 glioblastoma models over a time frame of 18 days. In our assay, viabilities of single neurospheres are to be estimated based on image information taken at different time points. Neurosphere images taken on the final day (day 18) were matched to the respective viability measured by CellTiter-Glo 3D on the same day. This allowed to use of machine learning to decode image information to viability values on day 18 as well as for the earlier time points (on days 8, 11, and 15).

Results

Our study shows that neurosphere images allow us to predict cell viability from extrapolated viabilities. This enables to assess of the drug interactions in a time window of 18 days. Our results show a clear and persistent synergistic interaction for several drug combinations over time.

Conclusions

Our method facilitates longitudinal drug-interaction assessment, providing new insights into the temporal-dynamic effects of drug combinations in 3D neurospheres which can help to identify more effective therapies against glioblastoma.

Screening of predicted synergistic multi-target therapies in glioblastoma identifies new treatment strategies

Background

IDH-wildtype glioblastoma (GBM) is a highly malignant primary brain tumor with a median survival of 15 months after standard of care, which highlights the need for improved therapy. Personalized combination therapy has shown to be successful in many other tumor types and could be beneficial for GBM patients.

Methods

We performed the largest drug combination screen to date in GBM, using a high-throughput effort where we selected 90 drug combinations for their activity onto 25 patient-derived GBM cultures. 43 drug combinations were selected for interaction analysis based on their monotherapy efficacy and were tested in a short-term (3 days) as well as long-term (18 days) assay. Synergy was assessed using dose-equivalence and multiplicative survival metrics.

Results

We observed a consistent synergistic interaction for 15 out of 43 drug combinations on patient-derived GBM cultures. From these combinations, 11 out of 15 drug combinations showed a longitudinal synergistic effect on GBM cultures. The highest synergies were observed in the drug combinations Lapatinib with Thapsigargin and Lapatinib with Obatoclax Mesylate, both targeting epidermal growth factor receptor and affecting the apoptosis pathway. To further elaborate on the apoptosis cascade, we investigated other, more clinically relevant, apoptosis inducers and observed a strong synergistic effect while combining Venetoclax (BCL targeting) and AZD5991 (MCL1 targeting).

Conclusions

Overall, we have identified via a high-throughput drug screening several new treatment strategies for GBM. Moreover, an exceptionally strong synergistic interaction was discovered between kinase targeting and apoptosis induction which is suitable for further clinical evaluation as multi-targeted combination therapy.

GENE-60. THE EPITRANSCRIPTOMIC CODE IN LGG: METABOLICALLY REPROGRAMMED IDH-MUTANT GLIOMAS ALTER tRNA MODIFICATION LANDSCAPE

BACKGROUND

Diffuse lower grade gliomas (LGGs) are generally slow growing primary central nervous system tumors that occur in early adult life. The prevalence of isocitrate dehydrogenase (IDH) mutations is high in LGG, and induces excess production of the oncometabolite 2-hydroxyglutarate (2-HG). These gain-of-function mutations play a key role in promoting metabolic reprogramming of the cancer cell that affects activity of α-KG dependent demethylases. Inhibition of DNA demethylase activity leads to glioma with a CpG island methylator phenotype (G-CIMP). Whether the activity of RNA demethylases and methylation status of tRNAs in LGG are modulated by changes in IDH-status is unknown. AIM: To investigate whether IDH mutations play a role in reprogramming of tRNA modifications in adult glioma.

MATERIALS AND METHODS

We combined small RNAseq and LC-MS/MS analysis to identify distinct tRNA processing patterns and methylation signatures in LGG tissues. To address important experimental bottlenecks that limit RNAseq-based detection of tRNA and possibly other modified small noncoding RNAs, we employed a tailored small RNAseq method with validation of specific methylation sites by mass-spectrometry.

RESULTS

Our customized small RNAseq approach yielded >100 fold increase in sequencing reads per tRNA type, thereby dramatically improving tRNA detection when compared to currently used small RNAseq approaches. Moreover, LC-MS/MS analysis revealed a higher abundance of modified nucleosides in tRNA from IDH-mutant LGG compared to IDH-wildtype LGG. Analysis of tRNA from IDH-mutant and IDH-wildtype LGG using the combination of our tailored small RNAseq and LC-MS/MS methodology demonstrated strong differential tRNA expression, tRFs processing and tRNA methylation.

CONCLUSION

We described an approach that makes use of tailored small RNA sequencing combined with mass-spectrometry that enables insights into cancer driven alterations in tRNA methylation patterns and differential tRNA processing signatures. Our data implies that tumor metabolic reprogramming deregulates tRNA methylation, contributing to an altered epitranscriptomic code in IDH-mutant LGG.

Effects of the selective MPS1 inhibitor MPS1-IN-3 on glioblastoma sensitivity to antimitotic drugs

BACKGROUND

Glioblastomas exhibit a high level of chemotherapeutic resistance, including to the antimitotic agents vincristine and taxol. During the mitotic agent-induced arrest, glioblastoma cells are able to perform damage-control and self-repair to continue proliferation. Monopolar spindle 1 (MPS1/TTK) is a checkpoint kinase and a gatekeeper of the mitotic arrest.

METHODS

We used glioblastoma cells to determine the expression of MPS1 and to determine the effects of MPS1 inhibition on mitotic errors and cell viability in combination with vincristine and taxol. The effect of MPS1 inhibition was assessed in different orthotopic glioblastoma mouse models (n = 3-7 mice/group). MPS1 expression levels were examined in relation to patient survival.

RESULTS

Using publicly available gene expression data, we determined that MPS1 overexpression corresponds positively with tumor grade and negatively with patient survival (two-sided t test, P < .001). Patients with high MPS1 expression (n = 203) had a median and mean survival of 487 and 913 days (95% confidence intervals [CI] = 751 to 1075), respectively, and a 2-year survival rate of 35%, whereas patients with intermediate MPS1 expression (n = 140) had a median and mean survival of 858 and 1183 days (95% CI = 1177 to 1189), respectively, and a 2-year survival rate of 56%. We demonstrate that MPS1 inhibition by RNAi results in sensitization to antimitotic agents. We developed a selective small-molecule inhibitor of MPS1, MPS1-IN-3, which caused mitotic aberrancies in glioblastoma cells and, in combination with vincristine, induced mitotic checkpoint override, increased aneuploidy, and augmented cell death. MPS1-IN-3 sensitizes glioblastoma cells to vincristine in orthotopic mouse models (two-sided log-rank test, P < .01), resulting in prolonged survival without toxicity.

CONCLUSIONS

Our results collectively demonstrate that MPS1, a putative therapeutic target in glioblastoma, can be selectively inhibited by MPS1-IN-3 sensitizing glioblastoma cells to antimitotic drugs.