Resistance-promoting effects of ependymoma treatment revealed through genomic analysis of multiple recurrences in a single patient

Abstract

As in other brain tumors, multiple recurrences after complete resection and irradiation of supratentorial ependymoma are common and frequently result in patient death. This standard-of-care treatment was established in the pregenomic era without the ability to evaluate the effect that mutagenic therapies may exert on tumor evolution and in promoting resistance, recurrence, and death. We seized a rare opportunity to characterize treatment effects and the evolution of a single patient's ependymoma across four recurrences after different therapies. A combination of high-depth whole-genome and exome-based DNA sequencing of germline and tumor specimens, RNA sequencing of tumor specimens, and advanced computational analyses were used. Treatment with radiation and chemotherapies resulted in a substantial increase in mutational burden and diversification of the tumor subclonal architecture without eradication of the founding clone. Notable somatic alterations included a MEN1 driver, several epigenetic modifiers, and therapy-induced mutations that impacted multiple other cancer-relevant pathways and altered the neoantigen landscape. These genomic data provided new mechanistic insights into the genesis of ependymoma and pathways of resistance. They also revealed that radiation and chemotherapy were significant forces in shaping the increased subclonal complexity of each tumor recurrence while also failing to eradicate the founding clone. This raises the question of whether standard-of-care treatments have similar consequences in other patients with ependymoma and other types of brain tumors. If so, the perspective obtained by real-time genomic characterization of a tumor may be essential for making effective patient-specific and adaptive clinical decisions.

A general approach for detecting expressed mutations in AML cells using single cell RNA-sequencing

“…Four cases of de novo AML and one of secondary AML were selected for study (clinical details in https://github.com/genome/scrna_mutations ). eWGS was used in conjunction with well-established variant detection pipelines to generate a set of high-confidence mutation calls for each case, and bulk RNA-sequencing was used to determine which mutations were expressed in each tumor sample (Methods) 25 . eWGS (Fig.…”

“…eWGS combines whole-genome sequencing with targeted exon capture to yield high coverage (~150×) of the exome, and lower genome-wide coverage in the tumor (~45×) and normal (~25×) samples. Using a previously described protocol 25 , eWGS sequencing libraries, including WGS libraries (350 bp inserts) and targeted libraries (250 bp inserts), were constructed with a KAPA HTP kit on a SciClone instrument. Targeted libraries were captured with the IDT exome reagent spiked with AML recurrently mutated genes 51 (~40 Mb).…”

Genetic Abnormalities, Clonal Evolution, and Cancer Stem Cells of Brain Tumors

“…The development of genetic studies now offer the possibility of evaluating the impact of chemo-radiation on tumor evolution and on the development of resistance and recurrence. Thus, a recent study explored the impact of chemo-radiation on the tumor genetic alterations [235]. Thus, treatment with radiation and chemotherapies induced a substantial increase in mutational burden and in subclonal diversification and complexity of tumor subclonal architecture, without eradication of the founding tumor clone.…”

Mutation detection in thousands of acute myeloid leukemia cells using single cell RNA-sequencing

“…For each case, we performed enhanced whole genome sequencing (eWGS) on bone marrow and matched normal tissue to identify germline and somatic variants. Libraries were captured using an IDT exome reagent enhanced with AML recurrently mutated genes 16 , then combined with WGS libraries and sequenced on an Illumina HiSeq4000, as described previously 17 . Germline mutations were called using GATK HaplotypeCaller v3.5 18 were detected using an ensemble mutation calling approach, with detailed protocols as previously published 19 .…”