Methylated markers accurately distinguish primary central nervous system lymphomas (PCNSL) from other CNS tumors.


Journal

Clinical epigenetics
ISSN: 1868-7083
Titre abrégé: Clin Epigenetics
Pays: Germany
ID NLM: 101516977

Informations de publication

Date de publication:
05 05 2021
Historique:
received: 17 03 2021
accepted: 22 04 2021
entrez: 6 5 2021
pubmed: 7 5 2021
medline: 27 1 2022
Statut: epublish

Résumé

Definitive diagnosis of primary central nervous system lymphoma (PCNSL) requires invasive surgical brain biopsy, causing treatment delays. In this paper, we identified and validated tumor-specific markers that can distinguish PCNSL from other CNS tumors in tissues. In a pilot study, we tested these newly identified markers in plasma. The Methylation Outlier Detector program was used to identify markers in TCGA dataset of 48 diffuse large B-cell lymphoma (DLBCL) and 656 glioblastomas and lower-grade gliomas. Eight methylated markers clearly distinguished DLBCL from gliomas. Marker performance was verified (ROC-AUC of ≥ 0.989) in samples from several GEO datasets (95 PCNSL; 2112 other primary CNS tumors of 11 types). Next, we developed a novel, efficient assay called Tailed Amplicon Multiplexed-Methylation-Specific PCR (TAM-MSP), which uses two of the methylation markers, cg0504 and SCG3 triplexed with ACTB. FFPE tissue sections (25 cases each) of PCNSL and eight types of other primary CNS tumors were analyzed using TAM-MSP. TAM-MSP distinguished PCNSL from the other primary CNS tumors with 100% accuracy (AUC = 1.00, 95% CI 0.95-1.00, P < 0.001). The TAM-MSP assay also detected as few as 5 copies of fully methylated plasma DNA spiked into 0.5 ml of healthy plasma. In a pilot study of plasma from 15 PCNSL, 5 other CNS tumors and 6 healthy individuals, methylation in cg0504 and SCG3 was detectable in 3/15 PCNSL samples (20%). The Methylation Outlier Detector program identified methylated markers that distinguish PCNSL from other CNS tumors with accuracy. The high level of accuracy achieved by these markers was validated in tissues by a novel method, TAM-MSP. These studies lay a strong foundation for a liquid biopsy-based test to detect PCNSL-specific circulating tumor DNA.

Sections du résumé

BACKGROUND
Definitive diagnosis of primary central nervous system lymphoma (PCNSL) requires invasive surgical brain biopsy, causing treatment delays. In this paper, we identified and validated tumor-specific markers that can distinguish PCNSL from other CNS tumors in tissues. In a pilot study, we tested these newly identified markers in plasma.
RESULTS
The Methylation Outlier Detector program was used to identify markers in TCGA dataset of 48 diffuse large B-cell lymphoma (DLBCL) and 656 glioblastomas and lower-grade gliomas. Eight methylated markers clearly distinguished DLBCL from gliomas. Marker performance was verified (ROC-AUC of ≥ 0.989) in samples from several GEO datasets (95 PCNSL; 2112 other primary CNS tumors of 11 types). Next, we developed a novel, efficient assay called Tailed Amplicon Multiplexed-Methylation-Specific PCR (TAM-MSP), which uses two of the methylation markers, cg0504 and SCG3 triplexed with ACTB. FFPE tissue sections (25 cases each) of PCNSL and eight types of other primary CNS tumors were analyzed using TAM-MSP. TAM-MSP distinguished PCNSL from the other primary CNS tumors with 100% accuracy (AUC = 1.00, 95% CI 0.95-1.00, P < 0.001). The TAM-MSP assay also detected as few as 5 copies of fully methylated plasma DNA spiked into 0.5 ml of healthy plasma. In a pilot study of plasma from 15 PCNSL, 5 other CNS tumors and 6 healthy individuals, methylation in cg0504 and SCG3 was detectable in 3/15 PCNSL samples (20%).
CONCLUSION
The Methylation Outlier Detector program identified methylated markers that distinguish PCNSL from other CNS tumors with accuracy. The high level of accuracy achieved by these markers was validated in tissues by a novel method, TAM-MSP. These studies lay a strong foundation for a liquid biopsy-based test to detect PCNSL-specific circulating tumor DNA.

Identifiants

pubmed: 33952317
doi: 10.1186/s13148-021-01091-9
pii: 10.1186/s13148-021-01091-9
pmc: PMC8097855
doi:

Substances chimiques

Biomarkers, Tumor 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

104

Subventions

Organisme : U.S. Department of Defense
ID : W81XWH1810482
Organisme : U.S. Department of Defense
ID : W81XWH-18-1-0018
Organisme : NIH HHS
ID : 1 R37 CA230400
Pays : United States
Organisme : NIH HHS
ID : 1 U01 CA230691
Pays : United States

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Auteurs

Bradley M Downs (BM)

Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21231, USA.

Wanjun Ding (W)

Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, People's Republic of China. dingwanjun66@126.com.

Leslie M Cope (LM)

Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21231, USA.

Christopher B Umbricht (CB)

Departments of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, 21231, USA.

Wenge Li (W)

Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, People's Republic of China.

Huihua He (H)

Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, People's Republic of China.

Xiaokang Ke (X)

Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, People's Republic of China.

Matthias Holdhoff (M)

Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21231, USA.

Chetan Bettegowda (C)

Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21231, USA.

Weiping Tao (W)

Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, People's Republic of China. taowpwp@sina.com.

Saraswati Sukumar (S)

Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21231, USA. saras@jhmi.edu.

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Classifications MeSH