Dataset Information

A Prognostic Gene-Expression Signature and Risk Score for Meningioma Recurrence After Resection.

ABSTRACT:

Background

Prognostic markers for meningioma are needed to risk-stratify patients and guide postoperative surveillance and adjuvant therapy.

Objective

To identify a prognostic gene signature for meningioma recurrence and mortality after resection using targeted gene-expression analysis.

Methods

Targeted gene-expression analysis was used to interrogate a discovery cohort of 96 meningiomas and an independent validation cohort of 56 meningiomas with comprehensive clinical follow-up data from separate institutions. Bioinformatic analysis was used to identify prognostic genes and generate a gene-signature risk score between 0 and 1 for local recurrence.

Results

We identified a 36-gene signature of meningioma recurrence after resection that achieved an area under the curve of 0.86 in identifying tumors at risk for adverse clinical outcomes. The gene-signature risk score compared favorably to World Health Organization (WHO) grade in stratifying cases by local freedom from recurrence (LFFR, P < .001 vs .09, log-rank test), shorter time to failure (TTF, F-test, P < .0001), and overall survival (OS, P < .0001 vs .07) and was independently associated with worse LFFR (relative risk [RR] 1.56, 95% CI 1.30-1.90) and OS (RR 1.32, 95% CI 1.07-1.64), after adjusting for clinical covariates. When tested on an independent validation cohort, the gene-signature risk score remained associated with shorter TTF (F-test, P = .002), compared favorably to WHO grade in stratifying cases by OS (P = .003 vs P = .10), and was significantly associated with worse OS (RR 1.86, 95% CI 1.19-2.88) on multivariate analysis.

Conclusion

The prognostic meningioma gene-expression signature and risk score presented may be useful for identifying patients at risk for recurrence.

SUBMITTER: Chen WC

PROVIDER: S-EPMC7735867 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

A Prognostic Gene-Expression Signature and Risk Score for Meningioma Recurrence After Resection.

Chen William C WC Vasudevan Harish N HN Choudhury Abrar A Pekmezci Melike M Lucas Calixto-Hope G CG Phillips Joanna J Magill Stephen T ST Susko Matthew S MS Braunstein Steve E SE Oberheim Bush Nancy Ann NA Boreta Lauren L Nakamura Jean L JL Villanueva-Meyer Javier E JE Sneed Penny K PK Perry Arie A McDermott Michael W MW Solomon David A DA Theodosopoulos Philip V PV Raleigh David R DR

Neurosurgery 20201201 1

<h4>Background</h4>Prognostic markers for meningioma are needed to risk-stratify patients and guide postoperative surveillance and adjuvant therapy.<h4>Objective</h4>To identify a prognostic gene signature for meningioma recurrence and mortality after resection using targeted gene-expression analysis.<h4>Methods</h4>Targeted gene-expression analysis was used to interrogate a discovery cohort of 96 meningiomas and an independent validation cohort of 56 meningiomas with comprehensive clinical foll ...[more]

PMID: 32860417

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Project description:BackgroundPrimary liver cancer, dominated by hepatocellular carcinoma (HCC), is one of the most common cancer types and the third leading cause of cancer death in 2020. Previous studies have shown that liquid-liquid phase separation (LLPS) plays an important role in the occurrence and development of cancer including HCC, but its influence on the patient prognosis is still unknown. It is necessary to explore the effect of LLPS genes on prognosis to accurately forecast the prognosis of HCC patients and identify relevant targeted therapeutic sites.MethodsUsing The Cancer Genome Atlas dataset and PhaSepDB dataset, we identified LLPS genes linked to the overall survival (OS) of HCC patients. We applied Least Absolute Shrinkage and Selection Operator (LASSO) Cox penalized regression analysis to choose the best genes for the risk score prognostic signature. We then analysed the validation dataset and evaluated the effectiveness of the risk score prognostic signature. Finally, we performed quantitative real-time PCR experiments to validate the genes in the prognostic signature.ResultsWe identified 43 differentially expressed LLPS genes that were associated with the OS of HCC patients. Five of these genes (BMX, FYN, KPNA2, PFKFB4, and SPP1) were selected to generate a prognostic risk score signature. Patients in the low-risk group were associated with better OS than those in the high-risk group in both the training dataset and the validation dataset. We found that BMX and FYN had lower expression levels in HCC tumour tissues, whereas KPNA2, PFKFB4, and SPP1 had higher expression levels in HCC tumour tissues. The validation demonstrated that the five-LLPS gene risk score signature has the capability of predicting the OS of HCC patients.ConclusionOur study constructed a five-LLPS gene risk score signature that can be applied as an effective and convenient prognostic tool. These five genes might serve as potential targets for therapy and the treatment of HCC.

Dataset Information

A Prognostic Gene-Expression Signature and Risk Score for Meningioma Recurrence After Resection.

Background

Objective

Methods

Results

Conclusion

Publications

A Prognostic Gene-Expression Signature and Risk Score for Meningioma Recurrence After Resection.

Similar Datasets

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