Abstract
Meningiomas are the most common primary intracranial tumors, but meningioma metastases are rare. Accordingly, the clinical workup, diagnostic testing, and molecular classification of metastatic meningioma is incompletely understood. Here, we present a case report of multiply recurrent meningioma complicated by liver metastasis. We discuss the patient presentation, imaging findings, and conventional histopathologic characterization of both the intracranial lesion and the metastatic focus. Further, we perform multiplatform molecular profiling, comprised of DNA methylation arrays and RNA-sequencing, of six stereotactically-guided samples from the intracranial meningioma and a single ultrasound-guided liver metastasis biopsy. Our results show that DNA methylation clusters distinguish the liver metastasis from the intracranial meningioma samples, and identify a small focus of hepatocyte contamination with the liver biopsy. Nonetheless, DNA methylation-based classification accurately identifies the liver metastasis as a meningioma with high confidence. We also find that clustering of RNA-sequencing results distinguishes the liver metastasis from the intracranial meningiomas samples, but that differential gene expression classification is confounded by hepatocyte-specific gene expression programs in the liver metastasis. In sum, this case report sheds light on the comparative biology of intracranial and metastatic meningioma. Furthermore, our results support methylation-based classification as a robust method of diagnosing metastatic lesions, underscore the broad utility of DNA methylation array profiling in diagnostic pathology, and caution against the routine use of bulk RNA-sequencing for identifying tumor signatures in heterogeneous metastatic lesions.
Highlights
Meningiomas metastases are rare, occurring in less than 1% of all cases [1,2,3]
This study was limited to whole exome sequencing (WES), which, in contrast to DNA methylation profiling and RNAsequencing (RNA-seq), cannot stratify the vast majority of meningiomas according to clinical outcomes [8, 9]
In summary, we performed DNA methylation profiling and RNA-seq of intracranial and metastatic samples from a recurrent meningioma. We found that both DNA methylation and RNA-seq distinguished the metastasis from intracranial meningioma samples, but while DNA methylation-based classification correctly identified the metastatic sample as meningioma in origin, RNA-seq of the same metastatic sample was confounded by hepatocyte contamination, even though the vast majority of the sample was comprised of meningioma cells
Summary
Meningiomas metastases are rare, occurring in less than 1% of all cases [1,2,3]. the rate of metastasis increases to 2% for World Health Organization (WHO) grade II meningiomas, and is nearly 9% for WHO grade III meningiomas [4], most frequently in the lungs, liver, lymph nodes, or bone [3, 5, 6]. Unsupervised hierarchical clustering of methylation data revealed that the liver metastasis demonstrated a distinct epigenetic profile from the 6 intracranial lesions (Fig. 2a), likely resulting from hepatocellular contamination in the metastatic sample. We did observe 4 CNVs that were present in the intracranial lesions but lost in the liver metastasis, which may have been driven, in part, by the underlying normal hepatocyte contamination in the metastatic sample These changes did not appear to affect DNA methylation-based tumor classification, and could, alternatively, have been reflective of metastasis of a meningioma clone not captured in the 6 intracranial meningioma samples we profiled. We selected genes with a log fold change greater than 2, which resulted in 628 enriched genes in the intracranial meningioma samples, and 726 enriched genes in the metastasis
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