Citations

Abstract BACKGROUND Treatment of high-grade glioma (HGG) remains a challenge. Several groups have developed ex vivo drug sensitivity assays to evaluate susceptibility of the tumor tissue to specific chemotherapeutics. This tool, in addition to molecular analysis of tumors might provide another layer of confidence in choosing treatments for patients with high-grade gliomas. METHODS 3D PredictTM platform (Kiyatec, Greenville, SC, USA) was tested at three academic medical centers in the United States. Twelve patients with newly diagnosed and recurrent HGGs were included. Tumor spheroids created ex vivo were exposed to twelve pre-selected drugs. Responses were reported as: no response, moderate response and response. We analyzed: demographics, histopathology, stage of disease, success rate and results of the ex vivo assay and clinical implications. RESULTS Majority of patients were women (67%). Median age was 58.5. Histology: GBM-83%, HGGs-17%. Eighty three percent of the samples represented recurrent disease. Sixty percent represented first recurrence while the remaining 40% represented 2nd or 3rd recurrence. Eight out of 12 tissue samples (67%) were successfully tested ex vivo. In six cases (75%), the information was used for immediate clinical decision making. In 2 cases, the decision was deferred until the next progression of the disease. The drugs chosen for treatment based on assay results included: olaparib (the assay was positive for response to rucaparib), temozolomide, lomustine, carboplatin and irinotecan. CONCLUSIONS This platform is easy to use in a standard clinical setting, the success rate for creating viable spheroids for drug sensitivity testing is high and the information obtained can be useful in clinical practice. Addition of other agents to the assay, correlation with molecular testing of the tumor tissue and attempt to assess response to drug combinations should be considered in further development of this technology. Prospective clinical trial is needed to validate this approach for routine clinical use.

Abstract AIMS High-grade glioma continues to have dismal survival with current standard-of-care treatment, owing in part to its intra- and inter-patient heterogeneity. Typical diagnostic biopsies are taken from the dense tumor core to determine the presence of abnormal cells and the status of a few key genes (e.g. IDH1, MGMT). However, the tumor core is typically resected, leaving behind possibly genetically, transcriptomically and/or phenotypically distinct invasive margins that repopulate the disease. As these remaining populations are the ones ultimately being treated, it is important to know their compositional differences from the tumor core. We aim to identify the phenotypic niches defined by the relative composition of key cellular populations and understand their variation amongst patients. METHOD We have established an image-localized research biopsy study, that samples from both the invasive margin and tumor core. From this protocol, we currently have 202 samples from 58 patients with available bulk RNA-Seq, collected between Mayo Clinic and Barrow Neurological Institute. Using a single-cell reference dataset from our collaborators at Columbia University, we used CIBERSORTx, a deconvolution method, to predict relative abundances of 7 normal, 6 glioma, and 5 immune cell states for each sample. RESULTS We find that these cell state abundances connect to patient survival and show regional differences. For example, proneural glioma states were higher in invasive regions, whereas proliferative and mesenchymal states were higher in the tumor core. CONCLUSIONS Our analysis demonstrates a need to characterize the residual tissue following glioma resection to better understand the recurrent disease.

Abstract BACKGROUND Treatment of recurrent high-grade glioma remains a clinical challenge. There are very few agents active in this disease and short of enrollment in a clinical trial, the choice of therapy for a patient at the time of recurrence remains challenging. Several groups, including our own have developed ex vivo drug sensitivity assays to evaluate susceptibility of the tumor tissue to specific chemotherapeutics. To our knowledge, there is only one commercially available platform from the US based company Kiyatec. This tool, in addition to the molecular analysis of the tumor might provide another layer of confidence in choosing treatments for patients with recurrent high-grade gliomas. MATERIAL AND METHODS We present the data from our initial experience with the 3D PredictTM platform (Kiyatec, Greenville, SC, USA). We used the platform for 6 patients with recurrent high-grade gliomas undergoing tumor resection at the time of recurrence. We followed the company protocol for obtaining, preserving and shipping the tissue. RESULTS Out of the 6 specimens shipped for analysis, 4 assays were completed with full results available for analysis and clinical use. In two cases, the ex vivo tissue expansion was unsuccessful and drug testing was not completed. For the remaining 4 cases, spheroids created from the expansion of the harvested tissue were exposed to 12 drugs (temozolomide, lomustine, procarbazine, abemaciclib, carboplatin, dabrafenib, etoposide, everolimus, irinotecan, osimertinib, rucaparib and trametinib). We have observed different levels of sensitivity to several agents graded as: NO RESPONSE, MODERATE RESPONSE and RESPONSE. In 3 cases the results were used for clinical decision making and 2 patients were started on temozlomidede and carboplatin respectively and remain on treatment. In one case where sensitivity to etoposide was detected, we were not able to proceed with therapy due to insurance denial for the chosen drug. CONCLUSION In our experience, this platform is easy to use in a standard clinical setting, the success rate for creating viable spheroids for testing is high and the information derived from the drug sensitivity testing can be useful in clinical practice. Large, prospective clinical trial is need to validate this approach for routine clinical use.