An optimized workflow to improve reliability of detection of KIAA1549:BRAF fusions from RNA sequencing data

LOGGIC Core BioClinical Data Bank: Added clinical value of RNA-Seq in an international molecular diagnostic registry for pediatric low-grade glioma patients

BACKGROUND

The international, multicenter registry LOGGIC Core BioClinical Data Bank aims to enhance the understanding of tumor biology in pediatric low-grade glioma (pLGG) and provide clinical and molecular data to support treatment decisions and interventional trial participation. Hence, the question arises whether implementation of RNA sequencing (RNA-Seq) using fresh frozen (FrFr) tumor tissue in addition to gene panel and DNA methylation analysis improves diagnostic accuracy and provides additional clinical benefit.

METHODS

Analysis of patients aged 0 to 21 years, enrolled in Germany between April 2019 and February 2021, and for whom FrFr tissue was available. Central reference histopathology, immunohistochemistry, 850k DNA methylation analysis, gene panel sequencing, and RNA-Seq were performed.

RESULTS

FrFr tissue was available in 178/379 enrolled cases. RNA-Seq was performed on 125 of these samples. We confirmed KIAA1549::BRAF-fusion (n = 71), BRAF V600E-mutation (n = 12), and alterations in FGFR1 (n = 14) as the most frequent alterations, among other common molecular drivers (n = 12). N = 16 cases (13%) presented rare gene fusions (eg, TPM3::NTRK1, EWSR1::VGLL1, SH3PXD2A::HTRA1, PDGFB::LRP1, GOPC::ROS1). In n = 27 cases (22%), RNA-Seq detected a driver alteration not otherwise identified (22/27 actionable). The rate of driver alteration detection was hereby increased from 75% to 97%. Furthermore, FGFR1 internal tandem duplications (n = 6) were only detected by RNA-Seq using current bioinformatics pipelines, leading to a change in analysis protocols.

CONCLUSIONS

The addition of RNA-Seq to current diagnostic methods improves diagnostic accuracy, making precision oncology treatments (MEKi/RAFi/ERKi/NTRKi/FGFRi/ROSi) more accessible. We propose to include RNA-Seq as part of routine diagnostics for all pLGG patients, especially when no common pLGG alteration was identified.

Detection and genomic analysis of BRAF fusions in Juvenile Pilocytic Astrocytoma through the combination and integration of multi-omic data

BACKGROUND

Juvenile Pilocytic Astrocytomas (JPAs) are one of the most common pediatric brain tumors, and they are driven by aberrant activation of the mitogen-activated protein kinase (MAPK) signaling pathway. RAF-fusions are the most common genetic alterations identified in JPAs, with the prototypical KIAA1549-BRAF fusion leading to loss of BRAF's auto-inhibitory domain and subsequent constitutive kinase activation. JPAs are highly vascular and show pervasive immune infiltration, which can lead to low tumor cell purity in clinical samples. This can result in gene fusions that are difficult to detect with conventional omics approaches including RNA-Seq.

METHODS

To this effect, we applied RNA-Seq as well as linked-read whole-genome sequencing and in situ Hi-C as new approaches to detect and characterize low-frequency gene fusions at the genomic, transcriptomic and spatial level.

RESULTS

Integration of these datasets allowed the identification and detailed characterization of two novel BRAF fusion partners, PTPRZ1 and TOP2B, in addition to the canonical fusion with partner KIAA1549. Additionally, our Hi-C datasets enabled investigations of 3D genome architecture in JPAs which showed a high level of correlation in 3D compartment annotations between JPAs compared to other pediatric tumors, and high similarity to normal adult astrocytes. We detected interactions between BRAF and its fusion partners exclusively in tumor samples containing BRAF fusions.

CONCLUSIONS

We demonstrate the power of integrating multi-omic datasets to identify low frequency fusions and characterize the JPA genome at high resolution. We suggest that linked-reads and Hi-C could be used in clinic for the detection and characterization of JPAs.

Bioinformatics workflows for clinical applications in precision oncology

High-throughput molecular profiling of tumors is a fundamental aspect of precision oncology, enabling the identification of genomic alterations that can be targeted therapeutically. In this context, a patient is matched to a specific drug or therapy based on the tumor's underlying genetic driver events rather than the histologic classification. This approach requires extensive bioinformatics methodology and workflows, including raw sequencing data processing and quality control, variant calling and annotation, integration of different molecular data types, visualization and finally reporting the data to physicians, cancer researchers and pharmacologists in a format that is readily interpretable for clinical decision making. This review comprises a broad overview of these bioinformatics aspects and discusses the multiple analytical, technical and interpretational challenges that remain to efficiently translate molecular findings into personalized treatment recommendations.

Accurate calling of KIAA1549-BRAF fusions from DNA of human brain tumours using methylation array-based copy number and gene panel sequencing data

AIMS

KIAA1549-BRAF fusions occur in certain brain tumours and provide druggable targets due to a constitutive activation of the MAP-kinase pathway. We introduce workflows for calling the KIAA1549-BRAF fusion from DNA methylation array-derived copy number as well as DNA panel sequencing data.

METHODS

Copy number profiles were analysed by automated screening and visual verification of a tandem duplication on chromosome 7q34, indicative of the KIAA1549-BRAF fusion. Pilocytic astrocytomas of the ICGC cohort with known fusion status were used for validation. KIAA1549-BRAF fusions were called from DNA panel sequencing data using the fusion callers Manta, Arriba with modified filtering criteria and deFuse. We screened DNA methylation and panel sequencing data of 7790 specimens from brain tumour and sarcoma entities.

RESULTS

We identified the fusion in 337 brain tumours with both DNA methylation and panel sequencing data. Among these, we detected the fusion from copy number data in 84% and from DNA panel sequencing data in more than 90% using Arriba with modified filters. While in 74% the KIAA1549-BRAF fusion was detected from both methylation array-derived copy number and panel sequencing data, in 9% it was detected from copy number data only and in 16% from panel data only. The fusion was almost exclusively found in pilocytic astrocytomas, diffuse leptomeningeal glioneuronal tumours and high-grade astrocytomas with piloid features.

CONCLUSIONS

The KIAA1549-BRAF fusion can be reliably detected from either DNA methylation array or DNA panel data. The use of both methods is recommended for the most sensitive detection of this diagnostically and therapeutically important marker.

Molecular characterization of CNS paragangliomas identifies cauda equina paragangliomas as a distinct tumor entity

Paragangliomas/pheochromocytomas are rare neuroendocrine tumors that arise from the adrenal gland or ganglia at various sites throughout the body. They display a remarkable diversity of driver alterations and are associated with germline mutations in up to 40% of the cases. Comprehensive molecular profiling of abdomino-thoracic paragangliomas revealed four molecularly defined and clinically relevant subtypes. Paragangliomas of the cauda equina region are considered to belong to one of the defined molecular subtypes, but a systematic molecular analysis has not yet been performed. In this study, we analyzed genome-wide DNA methylation profiles of 57 cauda equina paragangliomas and show that these tumors are epigenetically distinct from non-spinal paragangliomas and other tumors. In contrast to paragangliomas of other sites, chromosomal imbalances are widely lacking in cauda equina paragangliomas. Furthermore, RNA and DNA exome sequencing revealed that frequent genetic alterations found in non-spinal paragangliomas—including the prognostically relevant SDH mutations—are absent in cauda equina paragangliomas. Histologically, cauda equina paragangliomas show frequently gangliocytic differentiation and strong immunoreactivity to pan-cytokeratin and cytokeratin 18, which is not common in paragangliomas of other sites. None of our cases had a familial paraganglioma syndrome. Tumors rarely recurred (9%) or presented with multiple lesions within the spinal compartment (7%), but did not metastasize outside the CNS. In summary, we show that cauda equina paragangliomas represent a distinct, sporadic tumor entity defined by a unique clinical and morpho-molecular profile.