EPCO-32. IDENTIFICATION OF PROGNOSTIC CHORDOMA SUBGROUPS USING DNA METHYLATION SIGNATURES IN TISSUE AND PLASMA. (12th November 2021)

• Record Type: Journal Article
• Authors: Zuccato, Jeffrey; Patil, Vikas; Mansouri, Sheila; Liu, Jeffrey; Nassiri, Farshad; Mamatjan, Yasin; Chakravarthy, Ankur; Karimi, Shirin; Almeida, Joao Paulo; Bernat, Anne-Laure; Hasen, Mohammed; Khan, Shahbaz; Kislinger, Thomas; Sinha, Namita; Froelich, Sébastien; Adle-Biassette, Homa; Aldape, Kenneth; De Carvalho, Daniel; Zadeh, Gelareh
• Is Part Of: Neuro-oncology. Volume 23: Supplement 6(2021)
• Page Start: vi9
• Page End: vi9
• Publication Date: 2021-11-12
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noab196.031
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: BACKGROUND: Chordomas are malignant bone cancers arising from the skull-base and spine that are rare but cause devastating central nervous system morbidities. Survival is highly variable despite surgery and radiotherapy as 10% live under 1 year and 30-35% survive over 20 years. There are currently no reliable prognostic factors and this limits our ability to tailor patient treatment to their risk. Accordingly, this work identifies epigenetic prognostic chordoma subgroups that are detectable non-invasively through plasma methylomes to guide treatment. METHODS: A total of 68 chordoma surgical specimens resected between 1996-2018 across three international centres underwent DNA methylation profiling. Cell-free methylated tumor DNA immunoprecipitation and high-throughput sequencing was performed on available matched plasma samples. RESULTS: Two stable tumor clusters were identified through consensus clustering of tissue methylation data. Clusters had statistically significantly different disease-specific survivals (log-rank p=0.0062) independent of clinical factors in a multivariable Cox analysis (HR=16.5, 95%CI: 2.8-96, p=0.0018). The poorer-performing " Immune-infiltrated " cluster had genes hypomethylated at promoters, typically resulting in transcription, within immune-related pathways and higher immune cell abundance within tumors. The better-performing " Cellular " cluster showed higher tumor cellularity plus cell-to-cell interaction and extracellular matrix pathway hypomethylation. Fifty chordoma-versus-other binomial generalized linear models built using plasma methylome data distinguished chordomas from meningiomas and spinal metastases, as representative clinical differential diagnoses, in random left-out 20% testing sets (mean AUROC=0.84, 95%CI: 0.52-1.00). Plasma-based methylation signatures were highly correlated with tissue-based signals within both poor-performing (median r=0.69, 95%CI: 0.66-0.72) and better-performing cluster tumors (median r=0.67, 95%CI: 0.62-0.72). CONCLUSIONS: The first identification of two distinct prognostic epigenetic chordoma subgroups is shown here with " Immune-infiltrated" tumors having a poorer prognosis than " Cellular" tumors. Plasma methylomes can be utilized for non-invasive chordoma diagnosis and subtyping. This work may transform chordoma treatment decision-making by guiding surgical planning in advance to match resection aggressiveness with patient prognosis.