Proteogenomic and metabolomic characterization of human glioblastoma.

in Cancer cell by Liang-Bo Wang, Alla Karpova, Marina A Gritsenko, Jennifer E Kyle, Song Cao, Yize Li, Dmitry Rykunov, Antonio Colaprico, Joseph H Rothstein, Runyu Hong, Vasileios Stathias, MacIntosh Cornwell, Francesca Petralia, Yige Wu, Boris Reva, Karsten Krug, Pietro Pugliese, Emily Kawaler, Lindsey K Olsen, Wen-Wei Liang, Xiaoyu Song, Yongchao Dou, Michael C Wendl, Wagma Caravan, Wenke Liu, Daniel Cui Zhou, Jiayi Ji, Chia-Feng Tsai, Vladislav A Petyuk, Jamie Moon, Weiping Ma, Rosalie K Chu, Karl K Weitz, Ronald J Moore, Matthew E Monroe, Rui Zhao, Xiaolu Yang, Seungyeul Yoo, Azra Krek, Alexis Demopoulos, Houxiang Zhu, Matthew A Wyczalkowski, Joshua F McMichael, Brittany L Henderson, Caleb M Lindgren, Hannah Boekweg, Shuangjia Lu, Jessika Baral, Lijun Yao, Kelly G Stratton, Lisa M Bramer, Erika Zink, Sneha P Couvillion, Kent J Bloodsworth, Shankha Satpathy, Weiva Sieh, Simina M Boca, Stephan Schürer, Feng Chen, Maciej Wiznerowicz, Karen A Ketchum, Emily S Boja, Christopher R Kinsinger, Ana I Robles, Tara Hiltke, Mathangi Thiagarajan, Alexey I Nesvizhskii, Bing Zhang, D R Mani, Michele Ceccarelli, Xi S Chen, Sandra L Cottingham, Qing Kay Li, Albert H Kim, David Fenyö, Kelly V Ruggles, Henry Rodriguez, Mehdi Mesri, Samuel H Payne, Adam C Resnick, Pei Wang, Richard D Smith, Antonio Iavarone, Milan G Chheda, Jill S Barnholtz-Sloan, Karin D Rodland, Tao Liu, Li Ding,

TLDR

  • The study looked at Glioblastoma (GBM), a very aggressive type of brain cancer. They used a lot of different types of data, like genomic, proteomic, post-translational modification and metabolomic data, to understand how GBM works. They found some things that could help with treatment, like specific phosphorylation events and metabolic changes. The study has important implications for the field of research and clinical practice, but there are some limitations that need to be addressed in future research.

Abstract

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment.

Overview

  • The study aims to understand the molecular pathogenesis of Glioblastoma (GBM) using integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs. The hypothesis being tested is that this analysis will provide insights into GBM biology and identify potential targets for treatment. The methodology used includes bulk omics methodologies, snRNA-seq, and correlation with specific expression and histone acetylation patterns. The primary objective of the study is to identify key phosphorylation events, immune subtypes, and metabolic changes in GBM.

Comparative Analysis & Findings

  • The study compares the outcomes observed under different experimental conditions or interventions, including phosphorylation events, immune subtypes, and metabolic changes in GBM. The results show that specific phosphorylation events, such as phosphorylated PTPN11 and PLCG1, could mediate oncogenic pathway activation and serve as potential targets for treatment. Immune subtypes with distinct immune cell types are discovered, which are correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. The study also identifies specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. The key findings of the study support the hypothesis that this integrated analysis provides insights into GBM biology and identifies potential targets for treatment.

Implications and Future Directions

  • The study's findings have significant implications for the field of research and clinical practice, as they provide insights into the molecular pathogenesis of GBM and identify potential targets for treatment. However, the study also has limitations, such as the small sample size and the need for further validation. Future research directions could include larger sample sizes, validation of the findings using additional methodologies, and exploration of the clinical implications of the identified targets. The study highlights the importance of integrating multiple omics data types to gain a comprehensive understanding of GBM biology and inform personalized treatment strategies.
Read Full Article