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Chordoma is a rare, orphan cancer arising from embryonal precursors of bone. Surgery and radiotherapy (RT) provide excellent local control, often at the price of significant morbidity because of the structures involved and the need for relatively high doses of RT; however, recurrence remains high. Although our understanding of the genetic changes that occur in chordoma is evolving rapidly, this knowledge has yet to translate into treatments. We performed comprehensive DNA (paired tumor/normal whole-exome and shallow whole-genome) and RNA (tumor whole-transcriptome) next-generation sequencing analyses of archival sacral and clivus chordoma specimens. Incorporation of transcriptomic data enabled the identification of gene overexpression and expressed DNA alterations, thus providing additional support for potential therapeutic targets. In three patients, we identified alterations that may be amenable to off-label FDA-approved treatments for other tumor types. These alterations include FGFR1 overexpression (ponatinib, pazopanib) and copy-number duplication of CDK4 (palbociclib) and ERBB3 (gefitinib). In a third patient, germline DNA demonstrated predicted pathogenic changes in CHEK2 and ATM , which may have predisposed the patient to developing chordoma at a young age and may also be associated with potential sensitivity to PARP inhibitors because of homologous recombination repair deficiency. Last, in the fourth patient, a missense mutation in IGF1R was identified, suggesting potential activity for investigational anti-IGF1R strategies. Our findings demonstrate that chordoma patients present with aberrations in overlapping pathways. These results provide support for targeting the IGF1R/FGFR/EGFR and CDK4/6 pathways as treatment strategies for chordoma patients. This study underscores the value of comprehensive genomic and transcriptomic analysis in the development of rational, individualized treatment plans for chordoma.

Identification of therapeutic targets in chordoma through comprehensive genomic and transcriptomic analyses