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File (tmp-LBN-Report_PH-DMPK-UAB-19-001_SRI-42127 _Mouse IP Plasma Brain PK) provides pharmacokinetic data for Fig. S14.

File (DATA FILE S1 Lead optimization-SAR-Chemical compound synthesis-11-03-2020-SZ v4, pdf format 297 pages) provides a detailed and sequential description of the chemical synthesis of compounds evaluated in this study and a docking study for SRI-42127 compound with SRI-42127-binding sites at HuR.

Supplementary materials including tables, figures, and detailed methods.

File (tmp-LBN-Data-Kinase_Inhibition-050719) provides the kinase profiling data (10-point titration results, Scientific's SelectScreen{trade mark, serif} Kinase Profiling, Thermo Fisher) for SRI-41666 and SRI-42127 compounds for Fig. S4.

File (samples Report Nabors 061019-proteomics) provides proteomic data for neurospheres treated with SRI-42127 versus control for Fig. S13.

File (samples Report Nabors 061019-2-top hits) provides proteomic annotated data for top hits after neurosphere treatment with SRI-42127 compound versus control for Fig. S13.

File (individual enrichment gene plots) provides enrichment gene plots at a high resolution for a summary of the gene ontology enrichment analysis illustrated in Fig. 6.

File (tmp-LBN-Inhibitor vs DMSO DESeq2 annotated results with normalized counts) provides RNA-Seq annotated data for Fig. 6 and Table 1, which illustrate transcriptome analysis for PDGx neurospheres treated with SRI-42127 compound versus control.

The development of novel therapeutics that exploit alterations in the activation state of key cellular signaling pathways due to mutations in upstream regulators has generated the field of personalized medicine. These first-generation efforts have focused on actionable mutations identified by deep sequencing of large numbers of tumor samples. We propose that a second-generation opportunity exists by exploiting key downstream “nodes of control” that contribute to oncogenesis and are inappropriately activated due to loss of upstream regulation and microenvironmental influences. The RNA-binding protein HuR represents such a node. Because HuR functionality in cancer cells is dependent on HuR dimerization and its nuclear/cytoplasmic shuttling, we developed a new class of molecules targeting HuR protein dimerization. A structure–activity relationship algorithm enabled development of inhibitors of HuR multimer formation that were soluble, had micromolar activity, and penetrated the blood–brain barrier. These inhibitors were evaluated for activity validation and specificity in a robust cell-based assay of HuR dimerization. SRI-42127, a molecule that met these criteria, inhibited HuR multimer formation across primary patient-derived glioblastoma xenolines (PDGx), leading to arrest of proliferation, induction of apoptosis, and inhibition of colony formation. SRI-42127 had favorable attributes with central nervous system penetration and inhibited tumor growth in mouse models. RNA and protein analysis of SRI-42127–treated PDGx xenolines across glioblastoma molecular subtypes confirmed attenuation of targets upregulated by HuR. These results highlight how focusing on key attributes of HuR that contribute to cancer progression, namely cytoplasmic localization and multimerization, has led to the development of a novel, highly effective inhibitor. Significance: These findings utilize a cell-based mechanism of action assay with a structure–activity relationship compound development pathway to discover inhibitors that target HuR dimerization, a mechanism required for cancer promotion.

PURPOSE Neurocognitive functioning (NCF), mood disturbances, physical functioning, and social support all share a relationship with health-related quality of life (HRQOL). However, a characterization of these relationships in persons with brain metastases (BM) has yet to be identified. METHODS Ninety-three newly diagnosed persons with BM were administered a cognitive battery to assess neurocognitive functioning, mood disturbances, physical functioning, and social support. The Functional Assessment of Cancer Treatment (FACT) scale was used to measure HRQOL. RESULTS Mood and physical function correlated with lower HRQOL in every measured domain. Verbal learning and memory correlated with every FACT subscale except emotional quality of life. Social support also correlated with several HRQOL domains. Stepwise linear regressions revealed that mood was the predominate predictor of HRQOL. Social support, physical functioning, verbal learning, and memory also contribute to HRQOL, but to a lesser extent. CONCLUSION HRQOL is a complex construct affected by mood, physical functioning, and learning and memory. Mood is a domain-independent predictor of HRQOL, while non-mood variables predict HRQOL in domain-specific ways. Thus, multifactorial baseline assessments of persons with BM are encouraged to help mitigate the impact that BM has on HRQOL.

Objective Neurocognitive functioning (NCF), mood disturbances, physical functioning, and social support all share a relationship with health-related quality of life (HRQOL). However, investigations into these relationships have not been conducted in persons with brain metastases (BM). Patients and methods Ninety-three newly diagnosed persons with BM were administered various cognitive batteries. Data were collected across a wide range of categories (ie, cognitive, demographic, disease/treatment, mood, social support, physical functioning). The Functional Assessment of Cancer Treatment (FACT) scale was used to measure HRQOL. Results Mood and physical function correlated with lower HRQOL in every measured domain. Verbal learning and memory correlated with every FACT subscale except emotional quality of life. Social support also correlated with several HRQOL domains. Stepwise linear regression revealed that mood predicted general well-being and several FACT subscales, including physical, emotional and cognitive well-being. Social support and physical health were predictive of general well-being. Verbal learning and memory predicted cognitive well-being. Conclusion HRQOL is a complex construct affected by numerous variables. In particular, mood, physical functioning, and learning and memory were important predictors of HRQOL, and clinicians are encouraged to obtain information in these areas during baseline assessments in persons with BM.

The purpose of this study is to determine the role of the complement immune system in glioma and/or glioma therapy. Glioblastoma (GBM) is the most common primary malignant brain tumor in adults. It is accompanied by a devastating prognosis; the median survival is 12-14 months, with less than 10 percent of patients living for more than two years after diagnosis. Unfortunately, current treatment options are limited, and many initially promising drugs have failed phase three clinical trials. One potential and relatively unexplored target for co-therapy in GBM is the complement immune system. Historically, the focus of work with complement has been on its role in innate immunity, where it can aid in the recognition and elimination of pathogens or undesired host material. More recent work, however, has revealed a key function of complement as a “double-edged sword” in the CNS. While the cascade is necessary for CNS development and homeostasis, overactive complement can lead to the hallmark neuroinflammation and neurodegeneration seen in conditions like Alzheimer's, multiple sclerosis, and traumatic brain injuries. Yet despite the presence of complement receptors on nearly all CNS cells and the direct role that complement plays in multiple neuroinflammatory diseases, very few studies have examined complement expression in brain tumors. The current project seeks to bridge this gap in knowledge by assessing the impact of complement on glioma. This effort began by selecting candidate genes, as the complement family contains over 50 members. To do so, data from the publicly available Cancer Genome Atlas (TCGA) was mined, providing 14 targets of interest for further analysis. Cell-based experiments were performed in three GBM patient-derived xenolines (PDx): XD456, JX6, and JX10. mRNA expression was determined via TaqMan real-time PCR. Protein levels were assessed via Western blot. Overall, seven of the 14 initial targets demonstrated clear over-expression in all three human GBM PDx cell lines. This expression was not changed upon treatment with glioma growth factors such as epidermal or fibroblast growth factor (EGF or FGF). Intriguingly, however, the degree of over-expression varied by cell line, even when these lines were derived from patients assigned to the same molecular GBM subtype. For example, at the RNA level and in comparison to other cell lines, complement factor H (a C3 inhibitor) was up to six times higher in XD456, and clusterin (a MAC inhibitor) was nearly 18-fold higher in JX10. These data suggest that the current system for classifying tumor subtype may be missing important factors. Finally, when compared back to TCGA data, overexpression of these targets was associated with significantly worse tumor phenotype and patient survival. This project has critically identified components of the complement system that are upregulated in GBM and strongly correlated to survival. Ultimately, these data may provide the first potential targets for complement-based co-therapeutics to be explored in future studies. Citation Format: Emily Nicole Hayward, Xiuhua Yang, Natalia Filippova, Jennifer A. Calano, David Namkoong, Stefan Kovac, Louis B. Nabors. Characterization and analysis of the complement immune system in glioblastoma (GBM) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3335.