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Sci Transl Med. 2019 Jan 2;11(473). pii: eaao5253. doi: 10.1126/scitranslmed.aao5253.

Sex differences in GBM revealed by analysis of patient imaging, transcriptome, and survival data.

Author information

1
Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA.
2
Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA.
3
Precision Neurotherapeutics Innovation Program, Mathematical NeuroOncology Lab, Mayo Clinic, Phoenix, AZ 85054, USA.
4
Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, MO 63110, USA.
5
School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85281, USA.
6
Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland OH, 44195, USA.
7
Cancer and Cell Biology Division, TGen, Phoenix, AZ 85004, USA.
8
Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO 63110, USA.
9
Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA.
10
Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA.
11
Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, MO 63110, USA. rubin_j@wustl.edu jingqinluo@wustl.edu.
12
Siteman Cancer Center Biostatistics Core, Washington University School of Medicine, St. Louis, MO 63110, USA.
13
Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA. rubin_j@wustl.edu jingqinluo@wustl.edu.

Abstract

Sex differences in the incidence and outcome of human disease are broadly recognized but, in most cases, not sufficiently understood to enable sex-specific approaches to treatment. Glioblastoma (GBM), the most common malignant brain tumor, provides a case in point. Despite well-established differences in incidence and emerging indications of differences in outcome, there are few insights that distinguish male and female GBM at the molecular level or allow specific targeting of these biological differences. Here, using a quantitative imaging-based measure of response, we found that standard therapy is more effective in female compared with male patients with GBM. We then applied a computational algorithm to linked GBM transcriptome and outcome data and identified sex-specific molecular subtypes of GBM in which cell cycle and integrin signaling are the critical determinants of survival for male and female patients, respectively. The clinical relevance of cell cycle and integrin signaling pathway signatures was further established through correlations between gene expression and in vitro chemotherapy sensitivity in a panel of male and female patient-derived GBM cell lines. Together, these results suggest that greater precision in GBM molecular subtyping can be achieved through sex-specific analyses and that improved outcomes for all patients might be accomplished by tailoring treatment to sex differences in molecular mechanisms.

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