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Patrick J Cimino

Publications and source records attributed to Patrick J Cimino.

2 recordsLinked to original sources

High-grade astrocytoma with piloid features: a clinical and genomic analysis of prognostic factors using a large cohort.

BACKGROUND: High-grade astrocytoma with piloid features (HGAP) is a recently defined tumor type that is not well-understood. Prognostic factors of clinical outcomes are not well-established. METHODS: Methylation profiling was performed on tumor samples, many at the National Cancer Institute (NCI) Laboratory of Pathology, and others from publicly available sources. Methylation classifier scores of ≥ 0.90 to the HGAP class on the NCI-Bethesda classifier version 3 were included. Clinical features were collected from the medical record. Survival analyses were performed using the Kaplan-Meier and Cox-proportional hazards methods. RESULTS: The cohort comprised 421 patients. There were high rates of ATRX alteration (62%), CDKN2A/B homozygous loss (78%) and MGMT promoter methylation (53%). MAPK alterations were identified in 74% of evaluable samples. The median age was 46 years, and posterior fossa location was predominant (52%). The median overall survival (OS) was 88 months. Older age (p = 0.01) and the presence of an ATRX alteration (p = 0.04) were found to be negative prognostic factors. The presence of cystic features on magnetic resonance imaging (MRI) was found to be favorably prognostic (p = 0.01). Factors that were not significantly associated with prognosis included histologic high-grade features, CDKN2A/B homozygous deletion, MGMT promoter methylation, extent of resection, and presence of NF1 syndrome. CONCLUSIONS: This large cohort establishes relative frequencies of several important markers. Additionally, older age, the presence of an ATRX alteration, and cystic features on MRI were found to be prognostic. Our work may aid in optimizing treatment regimens for patients with this tumor type.

ATRX alteration

Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome.

Meningiomas, although mostly benign, can be recurrent and fatal. World Health Organization (WHO) grading of the tumor does not always identify high-risk meningioma, and better characterizations of their aggressive biology are needed. To approach this problem, we combined 13 bulk RNA sequencing (RNA-seq) datasets to create a dimension-reduced reference landscape of 1,298 meningiomas. The clinical and genomic metadata effectively correlated with landscape regions, which led to the identification of meningioma subtypes with specific biological signatures. The time to recurrence also correlated with the map location. Further, we developed an algorithm that maps new patients onto this landscape, where the nearest neighbors predict outcome. This study highlights the utility of combining bulk transcriptomic datasets to visualize the complexity of tumor populations. Further, we provide an interactive tool for understanding the disease and predicting patient outcomes. This resource is accessible via the online tool Oncoscape, where the scientific community can explore the meningioma landscape.

Meningioma