Validated Technology may Offer Real Possibilities to Improve Care for Glioblastoma Patients

In a recently adopted bipartisan resolution passed by the United States Senate, July 21, 2021, is designated as Glioblastoma Awareness Day, highlighting the severity of this aggressive brain cancer in honor of Arizona Senator John McCain, who passed away from glioblastoma almost three years ago, and the more than 10,000 Americans who die from this disease every year.

Today, fewer than 10% of patients survive longer than five years. Pharmaceutical and clinical efforts have only resulted in modest increases in overall survival since the disease was first described in the 1920s.

The treatment of high-grade gliomas, including glioblastoma or GBM the most common primary brain tumor in adults, has remained virtually unchanged over the last decades, presenting an opportunity to improve care through shifting the paradigm toward individualized medicine for the treatment of the disease.

Because of the aggressive nature of the disease, and limited treatment options an assay to help predict patient-specific responses to treatment – within an actionable timeframe before the initiation of treatment, such a personalized approach would benefit patients. [2]

The current standard of care for the treatment of newly diagnosed glioblastoma is, according to NCCN guidelines, recommends surgical resection to the maximal and safe extent feasible, and clinical trial enrollment or concurrent adjuvant radiotherapy with Temozolomide (Temodar®; Merck Sharp & Dohme Corp., a subsidiary of Merck & Co). [3]

Following first-line therapy, tumor progression is nearly universal within 6–9 months.  Time to the second recurrence is generally shorter in duration.

The treatment of recurrent high-grade gliomas is due to these time constraints and the increasingly aggressive nature of the disease considered difficult and is often problematic. Choosing a ‘standard of care’ second-line therapy is, for a number of reasons, complex and in some instances controversial. [4][5] The poor prognosis of glioblastoma (generally less than 15 months) emphasizes the critical unmet medical need for developing a treatment stratification system to improve outcomes through personalized treatment strategies.  However, with the exception of patient treatment selection in clinical trials, predictive modeling designed asses patient-specific response and efficacy of individual chemotherapy based on chemosensitivity ex vivo have not been endorsed by the American Society of Clinical Oncology (ASCO). [6][7][8]

The failure of existing assays to accurately predict patient specific-responses to treatment may be based on accuracy and the inability to present results in an actionable timeframe.

A new approach
Using a new approach, researchers at KIYATEC, previously validated an assay that prospectively and accurately predicts (89%, P = .0004) response to first-line chemotherapy in newly diagnosed ovarian cancer patients with results returned within 7 business days of each patient’s surgery and a clinically meaningful positive predictive value of 100% [9]

The assay test leverages KIYATEC’s proprietary ex vivo 3D cell culture platforms to accurately model and predicts response to approved and investigational cancer drugs targeting a spectrum of solid tumors. The platform’s technology is designed to address the gap-defining limitations of current cancer drug selection.

Based on these outcomes in ovarian cancer, the researchers, looking at the unmet medical need in the treatment of high-grade gliomas, including glioblastoma modified their platform technology to facilitate testing in high-grade gliomas and analytically and clinically validated the new assay for the individualized selection of chemotherapy specific for high-grade gliomas.

Following clinician input and potential efficacy in high-grade gliomas the researchers validated 12 drugs for the drug panel-based, including agents listed in current NCCN guidelines and those tested in clinical trials. They established optimal drug exposure duration for each drug was established against a panel of glioma cell lines to ensure assay readouts were not an artifact of extended or shortened exposure times. And finally, they measured drug response every 24 hours, and optimal exposure times were defined as producing an IC₅₀ value midway of the drug concentration range tested.[9]

Interim analyses
The trial included fifty-five patients with newly diagnosed or recurrent high-grade gliomas who enrolled from November 2014 to July 2018. Samples from 44 patients were utilized in assay development, analytical validation, and the determination of response range categories. The remaining 11 patients were combined with an additional 96 patients enrolled from January 2019 to December 2020 as part of the clinical study 3D-PREDICT

Following an interim data analysis of the prospective, open-label, multi-institutional, non-interventional 3D-PREDICT study, published in the June 16, 2021 edition of Neuro-Oncology Advances, confirms that a new test offers a clinically meaningful prediction of patient-specific responses to the standard of care therapy, prior to treatment, in newly diagnosed glioblastoma and other high-grade glioma patients.[10]

A goal of the study, which continues to enroll, was for the test’s prospective, patient-specific response prediction to achieve statistical significance for predictive accuracy. The 3D-PREDICT study met this goal early, at its interim data analysis, an achievement that is uncommon for innovations in oncology. For clinicians and payors, the publication establishes the successful analytical validation and early clinical validation of KIYATEC’s 3D Predict™ Glioma assay.

Accuracy of the assay
The test results accurately identified the patients as future temozolomide responders or future non-responders prior to the initiation of drug treatment. The future responder group had a statistically significant 6-month comparative increase in overall survival. Since test results are available only seven days after surgery, this creates an opportunity to improve outcomes for each predicted non-responder by providing the possibility of patient-specific treatment strategies. In the future, these results may also prove useful to improve outcomes for each predicted responder through patient-specific combination strategies.

Successful response-prediction for newly diagnosed patients follows the company’s previous success with predicting treatment response in recurrent high-grade glioma patients.

In December 2020, the company announced a clinical case series demonstrating that use of their test doubled these patients’ median time to progression over what would be expected without use of the test. In addition, the earlier announcement demonstrated successful clinical use of the targeted agent dabrafenib in two patients that were not identified by genetic sequencing. By identifying successful responses to drugs that would have been missed by today’s testing, KIYATEC’s results expanded the successful treatment options for these patients.

“Decision making in our framework is based on patient-specific evidence, embodying truly personalized medicine. Evidence of response before the first dose is administered creates options that were not previously available when it comes to treatment,” noted Matthew Gevaert, Ph.D., Chief Executive Officer of KIYATEC.

Compared to other approaches, tests developed using KIYATEC’s 3D ex vivo cell culture platform demonstrate increased biological fidelity, which was first reported in 2019 in ovarian cancer. In newly diagnosed ovarian cancer patients, the company’s test prospectively and accurately predicted response to first-line chemotherapy with 89% accuracy.

The new GBM results now establish comparable predictive accuracy in two solid tumors, with eight additional cancers in the company’s pipeline.

Clinical trials
3D Prediction of Patient-Specific Response (3D-PREDICT) – NCT03561207

Highlights of prescribing information
Temozolomide (Temodar®; Merck & Co) [Prescribing Information]

Reference
[1] Koshy M, Villano JL, Dolecek TA, Howard A, Mahmood U, Chmura SJ, Weichselbaum RR, McCarthy BJ. Improved survival time trends for glioblastoma using the SEER 17 population-based registries. J Neurooncol. 2012 Mar;107(1):207-12. doi: 10.1007/s11060-011-0738-7. Epub 2011 Oct 9. PMID: 21984115; PMCID: PMC4077033.
[2] Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, Belanger K, Brandes AA, Marosi C, Bogdahn U, Curschmann J, Janzer RC, Ludwin SK, Gorlia T, Allgeier A, Lacombe D, Cairncross JG, Eisenhauer E, Mirimanoff RO; European Organisation for Research and Treatment of Cancer Brain Tumor and Radiotherapy Groups; National Cancer Institute of Canada Clinical Trials Group. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med. 2005 Mar 10;352(10):987-96. doi: 10.1056/NEJMoa043330. PMID: 15758009.
[3] Central Nervous System Cancers (Version 3.2020 National Comprehensive Cancer Network. Online. Last accessed on June 17, 2021
[4] Wlodarczyk A, Grot D, Stoczynska-Fidelus E, Rieske P. Gaps and Doubts in Search to Recognize Glioblastoma Cellular Origin and Tumor Initiating Cells. J Oncol. 2020 Jul 22;2020:6783627. doi: 10.1155/2020/6783627. PMID: 32774372; PMCID: PMC7396023.
[5] Franceschi E. Second-Line Chemotherapy in Recurrent Glioblastoma–Still Controversial. Oncol Res Treat. 2015;38(7-8):345-6. doi: 10.1159/000435903. Epub 2015 Jul 1. PMID: 26278577.
[6] Ono A, Kanno H, Hayashi A, Nishimura S, Kyuma Y, Sato H, Ito S, Shimizu N, Chang CC, Gondo G, Yamamoto I, Sasaki T, Tanaka M. Collagen gel matrix assay as an in vitro chemosensitivity test for malignant astrocytic tumors. Int J Clin Oncol. 2007 Apr;12(2):125-30. doi: 10.1007/s10147-006-0636-8. Epub 2007 Apr 27. PMID: 17443280.
[7] Ranjan T, Howard CM, Yu A, Xu L, Aziz K, Jho D, Leonardo J, Hameed MA, Karlovits SM, Wegner RE, Fuhrer R, Lirette ST, Denning KL, Valluri J, Claudio PP. Cancer Stem Cell Chemotherapeutics Assay for Prospective Treatment of Recurrent Glioblastoma and Progressive Anaplastic Glioma: A Single-Institution Case Series. Transl Oncol. 2020 Apr;13(4):100755. doi: 10.1016/j.tranon.2020.100755. Epub 2020 Mar 17. PMID: 32197147; PMCID: PMC7078520.
[8] Burstein HJ, Mangu PB, Somerfield MR, Schrag D, Samson D, Holt L, Zelman D, Ajani JA; American Society of Clinical Oncology. American Society of Clinical Oncology clinical practice guideline update on the use of chemotherapy sensitivity and resistance assays. J Clin Oncol. 2011 Aug 20;29(24):3328-30. doi: 10.1200/JCO.2011.36.0354. Epub 2011 Jul 25. PMID: 21788567.
[9] Shuford S, Wilhelm C, Rayner M, Elrod A, Millard M, Mattingly C, Lotstein A, Smith AM, Guo QJ, O’Donnell L, Elder J, Puls L, Weroha SJ, Hou X, Zanfagnin V, Nick A, Stany MP, Maxwell GL, Conrads T, Sood AK, Orr D, Holmes LM, Gevaert M, Crosswell HE, DesRochers TM. Prospective Validation of an Ex Vivo, Patient-Derived 3D Spheroid Model for Response Predictions in Newly Diagnosed Ovarian Cancer. Sci Rep. 2019 Aug 1;9(1):11153. doi: 10.1038/s41598-019-47578-7. PMID: 31371750; PMCID: PMC6671958.
[10] Shuford S, Lipinski L, Abad A, Smith AM, Rayner M, O’Donnell L, Stuart J, Mechtler LL, Fabiano AJ, Edenfield J, et al. Prospective prediction of clinical drug response in high-grade gliomas using an ex vivo 3D cell culture assay. Neuro-Oncology Advances, May 7, 2021, Volume 3, issue 1, January-December 2021, vdab065. [Article]

Featured image: Despairing woman with brain cancer. Photo courtesy: © 2018 – 2021 Fotolia/Adobe. Used with permission.