Glioblastomas are the most common malignant brain tumors in adults. Despite resection of the tumor, combined radio- and chemotherapy and new-targeted therapy approaches, the average life expectancy is only 15 months with a 3-year survival rate of less than 5%. Invasive growth of tumor cells into the surrounding brain tissue complicates treatment and causes recurrence. Imaging techniques such as magnetic resonance imaging (MRI) are conventionally used for diagnosis and for monitoring after surgery in order to detect tumor lesions. However, next to tumor progression, contrast enhancement could also result from pseudoprogression or radiation necrosis. Similarly, next to therapy response, a reduction of contrast enhancement could also mimic a success in therapy (pseudoresponse). Furthermore, the use of targeted therapies requires the molecular detection of biomarkers, which is often performed on tissue biopsies. During therapy, resistance mechanisms to therapy may develop, which have a significant impact on the success of the therapy. Repeated biopsies are needed to distinguish tumor progress from therapy-associated tissue changes and simultaneously detect therapy resistance. Often they are not feasible due to the high risk for the patient. Currently, there are methods to improve monitoring in glioblastoma patients. Besides improved imaging techniques, liquid biopsies are a promising method to detect tumor progression. At the same time, liquid biopsies also allow molecular characterization of the lesions. A key advantage over tissue biopsies is that they are minimally invasive, making them well suited for longitudinal tumor monitoring. For clinical application of liquid biopsies in the form of blood and CSF, components such as circulating tumor cells, circulating tumor DNA, extracellular vesicles, or tumor-educated platelets are used, with the former two probably being the most common tumor markers at present. In this study, a highly sensitive next generation sequencing-based method was established to detect tumor mutations in plasma and CSF of glioblastoma patients. To this end, crucial sample preparation steps were initially optimized. Therefore, four isolation kits extracting cell-free DNA from plasma were compared and the best-performing kit was chosen for the analysis of patient material. Furthermore, a multi-gene next generation sequencing panel (cfDNA-GBM panel) was designed specifically for use in liquid biopsies from glioblastoma patients and tested on a reference standard for cell-free DNA with mutations of different allele frequencies. The newly designed cfDNA-GBM panel, which uses hybrid-capture based enrichment, was compared to a primer-extension based panel. Due to the more consistent coverage of target regions, superior sensitivity, and better clinical applicability due to its smaller size, the cfDNA-GBM panel was used for subsequent clinical investigations. In both enrichments, unique molecular barcodes were used to label all original fragments and thus identify and eliminate errors in subsequent data analysis that occur during amplification in library preparation This increases the sensitivity of the method. During the establishment of the methodology, the use of molecular barcodes clarified the limitation of sequence information due to the small input amount of cell-free DNA. For tumor tissue analysis, an already established larger panel was adapted and extended based on the results of a proof of concept study.
After the establishment of the sensitive method, clinical samples of glioblastoma patients were analyzed. Isolation and analysis of cell-free DNA from plasma and CSF resulted in highly variable amounts of cell-free DNA with characteristic oligonucleosomal fragment lengths. Furthermore, no difference in the amount or fragmentation of cell-free DNA from pre- or post-surgery plasma was determined. To increase the amount of cell-free DNA for sequencing, the amount of blood samples was increased from 10 ml (5 patients) to 50 ml (9 patients). Detection of circulating tumor DNA in plasma and CSF from glioblastoma patients was performed using two strategies. In a first approach, somatic tumor mutations were detected in genomic DNA from tumor tissue, which were searched for in the sequence data of liquid biopsies in a second step. In this approach, an increased detection rate (in 56% of patients compared to 25% in 10 ml blood samples) of circulating tumor DNA was detected in blood samples with a volume of 50 ml. Almost all tumor mutations lying in the target region of the smaller cfDNA-GBM panel could be detected in CSF (92%) with similar allele frequencies to those detected in the tumor. In a second strategy, somatic variants were detected in plasma and CSF without prior knowledge of variants in tumor tissue. Interestingly, three variants were detected in the CSF of one patient, which occurred with an allele frequency over 5% in the CSF, while they were not detectable in the analyzed tumor tissue. These variants may be indicators for tumor heterogeneity that was not accessible by analyzing sections of tumor tissue. Finally, mutation-specific probes were designed for three tumor-somatic variants detected in the patients' plasma to validate them by digital PCR. A pair of probes for a mutation in PTEN was successfully established to robustly detect minimal allele frequencies down to 0.1% but could not validate the mutation in cell-free DNA from plasma of the respective patient. Overall, it was shown that analysis of tumor somatic mutations using the cfDNA-GBM sequencing panel designed and established in this study is limited in the analysis of cell-free DNA from plasma of patients with glioblastomas, whereas the detection of circulating tumor DNA from CSF is promising.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:85362 |
| Date | 08 May 2023 |
| Creators | Jahn, Winnie |
| Contributors | Klink, Barbara, Aust, Daniela, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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