# MODELING MALIGNANT PROGRESSION IN GLIOMA > **NIH NIH R01** · BAYLOR COLLEGE OF MEDICINE · 2020 · $350,000 ## Abstract SUMMARY Glioma is the most common and deadliest primary brain tumor in humans. Highly malignant gliomas often arise from more indolent lower grade gliomas. Although patients with low-grade gliomas (LGG) may survive for many years, their tumors almost inevitably progress to high-grade gliomas (HGG), after which death occurs in 12 to 15 months. The process of malignant progression is poorly understood. Our published studies (funded by a Mentored Clinical Scientist Program [K08]) showed that anti-apoptotic signaling plays a key role in facilitating the progression of LGG to HGG. We also showed that suppression of apoptosis caused profound immunosuppression in the tumor microenvironment. Furthermore, we have shown, using several immunotherapeutic strategies, that reversing intratumoral immunosuppression can mitigate malignant progression in a murine model of glioma. We now hypothesize that antiapoptotic signaling promotes malignant progression in glioma by inducing an immunosuppressive tumor microenvironment. A major obstacle to studying malignant progression has been the lack of matched patient samples of LGGs and the HGGs to which they progress. However, we have identified over 250 patients who were treated for both LGG and later HGG at MD Anderson Cancer Center. The analysis of matched tumor samples from these patients represents a unique opportunity for the study of malignant progression. In the proposed work, we will take advantage of next- generation sequencing (NGS) to investigate the mechanisms through which LGG degenerates to HGG. In Aim 1, we will use NGS to identify anti-apoptotic genes that are overexpressed in HGGs relative to LGGs. A functional analysis of these genes in an immune competent murine model of glioma will determine their immunosuppression- and malignant transformation–promoting effects. In Aim 2, we will study two antiapoptotic genes (MCL-1 and BIRC3) that have emerged as lead facilitators of immunosuppression from analysis of TCGA LGG and HGG expression data as well as our own internal cohort of patients. We will model these genes in vivo to determine their impact on malignant progression. In Aim 3, we will profile our specimens to identify transcription factors that activate chemokines known to cause the intratumoral influx of key immunosuppressive cells. These transcription factors will be modeled in vivo to determine their effect on malignant progression. Identifying the factors that contribute to malignant progression will potentially enable us to mitigate the causes of progression. Thus, tumors may be maintained in the more indolent low-grade state rather than progressing to HGG, significantly prolonging survival. Ultimately, our results may also be applicable to other tumor types that demonstrate progression from a low- to high-grade lesion. This work is being done in collaboration with recognized experts in gene expression profiling, computational biology, biostatistics, and brain tumor immunology. We will also leve... ## Key facts - **NIH application ID:** 10293981 - **Project number:** 7R01NS094615-06 - **Recipient organization:** BAYLOR COLLEGE OF MEDICINE - **Principal Investigator:** Ganesh Rao - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $350,000 - **Award type:** 7 - **Project period:** 2020-10-30 → 2023-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10293981 ## Citation > US National Institutes of Health, RePORTER application 10293981, MODELING MALIGNANT PROGRESSION IN GLIOMA (7R01NS094615-06). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10293981. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*