Transcriptomic analysis of novel tumor suppressor gene fusions in bone sarcomas

• Published in: Journal of clinical oncology Vol. 42; no. 16_suppl; p. 11523
• Main Authors: Ivanov, Danil, Kushnarev, Vladimir, Yong, Sheila T., Kotlov, Nikita, Chernyshov, Konstantin, Bagaev, Alexander, Fowler, Nathan Hale, Conley, Anthony Paul, Cote, Gregory Michael, Chawla, Sant P.
• Format: Journal Article
• Language: English
• Published: American Society of Clinical Oncology 01.06.2024
• ISSN: 0732-183X; 1527-7755
• DOI: 10.1200/JCO.2024.42.16_suppl.11523

11523Background: Despite the evolution of therapeutic strategies for sarcomas in the past four decades, survival in the metastatic setting remains poor. This underscores the urgent need to explore new diagnostic and treatment avenues to improve patient outcomes. Harnessing the capability of RNA sequencing (RNA-seq) to detect gene fusions de-novo, we analyzed treated bone sarcoma samples with the aim to uncover gene fusions and breakpoints that are potentially relevant as clinical biomarkers and treatment targets. Methods: We analyzed 83 formalin-fixed, paraffin-embedded tumor samples of treated bone sarcomas, including osteosarcomas, chondrosarcomas, chordomas, and Ewing sarcomas. These samples were subject to in-depth whole exome analysis and bulk RNA-seq. RNA-seq was employed to identify gene fusions, with STAR-fusion utilized for sequence calling. Quality control of all NGS samples was performed using FastQC, FastQ Screen, RSeQC, and MultiQC. Tumor purity was assessed via pathological and bioinformatics examination with the threshold set at 20%. Fusions involving tumor suppressor genes listed in the OncoKB database were investigated further. A comprehensive literature search on PubMed and Google Scholar as well as analysis of the FusionGDB and COSMIC databases were performed to verify candidates of novel gene fusions. We also compared our samples with those in the publicly available MSK sarcoma cohort and 11 osteosarcoma cell line datasets. Results: We detected 238 gene fusions in all samples analyzed. Among these fusions, 18 (16 previously unknown, 2 previously reported) involving known tumor suppressor genes were present in 14 samples (17%). Among the 16 previously unknown fusions, 8 were indicative of potential loss-of-function variants of tumor suppressors: TP53-NF1, TP53-CEMIP, CTNNBL1-RB1, PRPF40A-FBXW7, VAMP2-MSH3,and ETV6-ATM in osteosarcoma; BRD4-TP53 in unspecified bone sarcoma; and FBXW7-ZNF770 in Ewing sarcoma. Furthermore, we also uncovered a novel breakpoint combination in EWSR1-ETV4 in Ewing sarcoma that links exon 9 of EWSR1to exon 9 of ETV4. Conclusions: Our comprehensive transcriptomic analysis of treated sarcoma samples uncovered previously unknown gene fusions involving tumor suppressor genes and a unique breakpoint combination in an oncogene. These findings emphasize the crucial role of RNA-seq not only in advancing genomic research of sarcomas, but also in identifying potential biomarkers/targets and devising new treatment strategies for this rare cancer.