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Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses.
Raleigh, David; Chen, William; Choudhury, Abrar; Youngblood, Mark; Polley, Mei-Yin; Lucas, Calixto-Hope; Mirchia, Kanish; Maas, Sybren; Suwala, Abigail; Won, Minhee; Bayley, James; Harmanci, Akdes; Harmanci, Arif; Klisch, Tiemo; Nguyen, Minh; Vasudevan, Harish; McCortney, Kathleen; Yu, Theresa; Bhave, Varun; Lam, Tai-Chung; Pu, Jenny; Leung, Gilberto; Chang, Jason; Perlow, Haley; Palmer, Joshua; Haberler, Christine; Berghoff, Anna; Preusser, Matthias; Nicolaides, Theodore; Mawrin, Christian; Agnihotri, Sameer; Resnick, Adam; Rood, Brian; Chew, Jessica; Young, Jacob; Boreta, Lauren; Braunstein, Steve; Schulte, Jessica; Butowski, Nicholas; Santagata, Sandro; Spetzler, David; Bush, Nancy Ann Oberheim; Villanueva-Meyer, Javier; Chandler, James; Solomon, David; Rogers, C; Pugh, Stephanie; Mehta, Minesh; Sneed, Penny; Berger, Mitchel.
Afiliação
  • Raleigh D; University of California San Francisco.
  • Chen W; UCSF.
  • Choudhury A; University of California, San Francisco.
  • Youngblood M; Northwestern University.
  • Polley MY; NRG Statistics and Data Management Center.
  • Lucas CH; Johns Hopkins.
  • Mirchia K; Mayo Clinic.
  • Maas S; Leiden University Medical Center.
  • Suwala A; Heidelberg University Hospital.
  • Won M; NRG Statistics and Data Management Center.
  • Bayley J; Baylor College of Medicine.
  • Harmanci A; Baylor College of Medicine.
  • Harmanci A; THE UNIV OF TX HEATH SCIENCE CTR.
  • Klisch T; Baylor College of Medicine.
  • Nguyen M; University of California San Francisco.
  • Vasudevan H; University of California San Francisco.
  • McCortney K; Northwestern University.
  • Yu T; University of California San Francisco.
  • Bhave V; Brigham and Women's Hospital.
  • Lam TC; The University of Hong Kong.
  • Pu J; The University of Hong Kong.
  • Leung G; The University of Hong Kong.
  • Chang J; University of California San Francisco.
  • Perlow H; The Ohio State University.
  • Palmer J; The Ohios State University James Comprehensive Cancer Center.
  • Haberler C; Medical University of Vienna.
  • Berghoff A; Medical University of Vienna.
  • Preusser M; Medical University of Vienna.
  • Nicolaides T; Caris Life Sciences.
  • Mawrin C; University Hospital Magdeburg.
  • Agnihotri S; Sonia and Arthur Labatt Brain Tumour Research Centre.
  • Resnick A; The Children's Hospital of Philadelphia.
  • Rood B; Center for Cancer and Immunology Research, Children's National Research Institute.
  • Chew J; University of California San Francisco.
  • Young J; University of California San Francisco.
  • Boreta L; University of California San Francisco.
  • Braunstein S; Department of Radiation Oncology, University of California San Francisco, San Francisco California.
  • Schulte J; University of California San Diego.
  • Butowski N; University of California, San Francisco.
  • Santagata S; Brigham and Women's Hospital.
  • Spetzler D; Caris Life Sciences International.
  • Bush NAO; University of California San Francisco.
  • Villanueva-Meyer J; UCSF.
  • Chandler J; Northwestern University.
  • Solomon D; University of California, San Francisco.
  • Rogers C; NRG Statistics and Data Management Center.
  • Pugh S; NRG Oncology Statistics and Data Management Center.
  • Mehta M; NRG Statistics and Data Management Center.
  • Sneed P; University of California San Francisco.
  • Berger M; University of California San Francisco (UCSF).
Res Sq ; 2023 Mar 20.
Article em En | MEDLINE | ID: mdl-36993741
ABSTRACT

Background:

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and current indications for postoperative radiotherapy are controversial. Recent studies have proposed prognostic meningioma classification systems using DNA methylation profiling, copy number variants, DNA sequencing, RNA sequencing, histology, or integrated models based on multiple combined features. Targeted gene expression profiling has generated robust biomarkers integrating multiple molecular features for other cancers, but is understudied for meningiomas.

Methods:

Targeted gene expression profiling was performed on 173 meningiomas and an optimized gene expression biomarker (34 genes) and risk score (0 to 1) was developed to predict clinical outcomes. Clinical and analytical validation was performed on independent meningiomas from 12 institutions across 3 continents (N = 1856), including 103 meningiomas from a prospective clinical trial. Gene expression biomarker performance was compared to 9 other classification systems.

Results:

The gene expression biomarker improved discrimination of postoperative meningioma outcomes compared to all other classification systems tested in the independent clinical validation cohort for local recurrence (5-year area under the curve [AUC] 0.81) and overall survival (5-year AUC 0.80). The increase in area under the curve compared to the current standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval [CI] 0.07-0.17, P < 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% CI 0.37-0.78, P = 0.0001) and re-classified up to 52.0% meningiomas compared to conventional clinical criteria, suggesting postoperative management could be refined for 29.8% of patients.

Conclusions:

A targeted gene expression biomarker improves discrimination of meningioma outcomes compared to recent classification systems and predicts postoperative radiotherapy responses.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article