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Prediction of brain metastasis development with DNA methylation signatures.
Zuccato, Jeffrey A; Mamatjan, Yasin; Nassiri, Farshad; Ajisebutu, Andrew; Liu, Jeffrey C; Muazzam, Ammara; Singh, Olivia; Zhang, Wen; Voisin, Mathew; Mirhadi, Shideh; Suppiah, Suganth; Wybenga-Groot, Leanne; Tajik, Alireza; Simpson, Craig; Saarela, Olli; Tsao, Ming S; Kislinger, Thomas; Aldape, Kenneth D; Moran, Michael F; Patil, Vikas; Zadeh, Gelareh.
Affiliation
  • Zuccato JA; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
  • Mamatjan Y; Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
  • Nassiri F; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
  • Ajisebutu A; The Faculty of Science, Thompson Rivers University, Kamloops, BC, Canada.
  • Liu JC; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
  • Muazzam A; Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
  • Singh O; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
  • Zhang W; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
  • Voisin M; Program in Cell Biology, Hospital for Sick Children, Toronto, Ontario, Canada.
  • Mirhadi S; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
  • Suppiah S; Program in Cell Biology, Hospital for Sick Children, Toronto, Ontario, Canada.
  • Wybenga-Groot L; Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
  • Tajik A; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
  • Simpson C; Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
  • Saarela O; Program in Cell Biology, Hospital for Sick Children, Toronto, Ontario, Canada.
  • Tsao MS; Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
  • Kislinger T; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
  • Aldape KD; Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
  • Moran MF; Program in Cell Biology, Hospital for Sick Children, Toronto, Ontario, Canada.
  • Patil V; SPARC BioCentre, Hospital for Sick Children, Toronto, Ontario, Canada.
  • Zadeh G; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
Nat Med ; 2024 Oct 08.
Article in En | MEDLINE | ID: mdl-39379704
ABSTRACT
Brain metastases (BMs) are the most common and among the deadliest brain tumors. Currently, there are no reliable predictors of BM development from primary cancer, which limits early intervention. Lung adenocarcinoma (LUAD) is the most common BM source and here we obtained 402 tumor and plasma samples from a large cohort of patients with LUAD with or without BM (n = 346). LUAD DNA methylation signatures were evaluated to build and validate an accurate model predicting BM development from LUAD, which was integrated with clinical factors to provide comprehensive patient-specific BM risk probabilities in a nomogram. Additionally, immune and cell interaction gene sets were differentially methylated at promoters in BM versus paired primary LUAD and had aligning dysregulation in the proteome. Immune cells were differentially abundant in BM versus LUAD. Finally, liquid biomarkers identified from methylated cell-free DNA sequenced in plasma were used to generate and validate accurate classifiers for early BM detection. Overall, LUAD methylomes can be leveraged to predict and noninvasively identify BM, moving toward improved patient outcomes with personalized treatment.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Nat Med / Nat. med / Nature medicine Journal subject: BIOLOGIA MOLECULAR / MEDICINA Year: 2024 Document type: Article Affiliation country: Canada Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Nat Med / Nat. med / Nature medicine Journal subject: BIOLOGIA MOLECULAR / MEDICINA Year: 2024 Document type: Article Affiliation country: Canada Country of publication: United States