Abstract B38: Tumor heterogeneity evaluation in glioblastomas using microarray of polysomal mRNAs
Authors: Fernanda C. S. Lupinacci, Hermano M. Bellato, Martin Roffe, Hellen Kuasne, Tiago G. Santos, Victor P. Andrade, Paulo Sanematsu, Vilma R. Martins, Silvia R. Rogatto, Glaucia N M Hajj
Journal: Cancer Research (2017)

Abstract Glioblastoma is the most common primary brain malignancy in adults and one of the most aggressive cancers. The overall treatment outcome of this tumor type remains unsatisfactory even though advanced multimodal treatments including surgery, chemotherapy, and radiotherapy have been available for decades. The median survival of patients is typically less than 2 years. Insights into the genetic landscape of glioblastomas have been achieved by high-throughput studies and patterns of gene expression have been able to identify molecular subgroups with putative prognostic or predictive significance. However, this approach provides little information about protein expression levels, since the expression of mRNAs do not necessarily reflect the levels of proteins. In addition, the establishment of molecular subgroups is compounded by the endemic problem of tumor heterogeneity, since subtype classifiers are variably expressed across individual cells within a tumor and the impact of sampling bias has not been addressed. More importantly, the relationships between different sources of intratumoral heterogeneity—genetic, transcriptional and functional—remain obscure. Thus, to evaluate such intratumoral heterogeneity is fundamental to demonstrate potential therapeutic targets, source of tumor recurrences and potential prognostic implications. Herein, we evaluated a specific transcriptomic and translatomic signature of the glioblastoma heterogeneity at the single-patient level. We performed a sampling of 8 pieces from a single glioblastoma tumor. The samples could be histologically classified as high or low grade and total and polysomal mRNA was isolated and identified by microarray. By comparing histologically high vs low grade tumors we were able to identify 42 differentially transcribed and 138 differentially translated genes. Among the differentially translated genes validated by qPCR there are many related to proliferation, development and cancer, such as FOXC1, HOXB5, SNAI2, LOX, WISP1, ITGA11 and COL5A2. Thus, our results demonstrate that the isolation of mRNA engaged in translation can be used to identify biomarkers of tumor progression, leading to new therapeutic approaches. In addition, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy. Ethical approval: 1775/13. Funding support: FAPESP 2013/03315-2, 2014/15550-9 Citation Format: Fernanda C. S. Lupinacci, Hermano M. Bellato, Martin Roffe, Hellen Kuasne, Tiago G. Santos, Victor P. Andrade, Paulo Sanematsu, Jr., Vilma R. Martins, Silvia R. Rogatto, Glaucia N M Hajj. Tumor heterogeneity evaluation in glioblastomas using microarray of polysomal mRNAs. [abstract]. In: Proceedings of the AACR Special Conference on Translational Control of Cancer: A New Frontier in Cancer Biology and Therapy; 2016 Oct 27-30; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2017;77(6 Suppl):Abstract nr B38.