Abstract 6634: Enhanced detection of gene fusions in sarcoma using Genomic Proximity Mapping in FFPE tissue
Abstract Sarcomas are soft-tissue tumors that pose significant diagnostic challenges for clinical laboratories. With more than 80 subtypes, accurate classification of sarcomas is crucial for providing valuable prognostic and therapeutic guidance. Gene fusions are a hallmark of many sarcoma subtypes, offering pathognomonic markers for diagnosis. Routine pathological diagnosis typically involves hematoxylin and eosin (H&E) staining and immunohistochemistry (IHC), with diagnostic samples most commonly preserved as formalin-fixed, paraffin-embedded (FFPE) specimens. However, FFPE preservation precludes conventional chromosome analysis and presents challenges for molecular tests such as those require high molecular weight DNA (i.e. long read sequencing and optical genome mapping). In addition, current methods, such as fluorescence in situ hybridization (FISH) and targeted RNA-seq panels, have limitations, including the restricted number of genes interrogated, dependence on known gene rearrangement breakpoints or chimera transcripts, and sensitivity to RNA quality, especially in FFPE samples. To address these limitations, we developed a new protocol for genome-wide detection of chromosomal abnormalities using Genomic Proximity Mapping (GPM) technology. GPM is a next-generation cytogenomic technique that employs proximity ligation and low-pass sequencing to identify structural variants and gene fusions across the entire genome. As a DNA-based, genome-wide assay, GPM overcomes the primary constraints of FISH and targeted gene panel by RNA-seq. To evaluate the performance of GPM, we applied it to 12 sarcoma samples that had previously underperformed or failed Anchored Multiplex PCR (AMP) analysis using the FusionPlex solid tumor gene panel. In all cases, GPM not only recapitulated the previous findings but also identified additional pathognomonic fusions in 33% of cases where targeted RNA-seq methods failed due to RNA quality issues or the limited scope of targeted analysis. Overall, GPM detected novel structural variants genome-wide and identified definitive gene fusions were in 8 sarcoma subtypes, achieving a sensitivity >0.9 and specificity of 1. In addition to detecting translocations, inversions, and insertions, GPM can identify novel gene fusions, deletions, duplications/amplifications, and copy-neutral loss of heterozygosity. GPM represents a novel, genome-wide approach to identifying both known and novel gene fusions, as well as other chromosomal abnormalities, in FFPE tissue. It enhances sarcoma classification where other methods fail, addressing the limitations of current cytogenetic and other NGS technologies. Citation Format: Yajuan J. Liu, He Fang, Maika Malig, Emily Reister, Mary Wood, Ivan Liachko, Stephen M. Eacker. Enhanced detection of gene fusions in sarcoma using Genomic Proximity Mapping in FFPE tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6634.
Authors
- Emily Reister
- Ivan Liachko (ORCID: https://orcid.org/0000-0001-6972-6705)
- Stephen Eacker (ORCID: https://orcid.org/0000-0002-9678-1192)
- Yajuan J. Liu (ORCID: https://orcid.org/0000-0001-6040-3109)
- Maika Malig (ORCID: https://orcid.org/0000-0002-2535-6607)
- Mary Wood (ORCID: https://orcid.org/0000-0002-4138-9599)
- Fang He
Institutions
- Kaiser Permanente (US)
- University of Washington (US)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1158/1538-7445.am2025-6634
- Primary Topic
- Molecular Biology Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00