Biology subjects

Golemis, E. A.

Publications and source records attributed to Golemis, E. A..

6 recordsLinked to original sources

bioRxiv2023

Trogocytosis of cancer-associated fibroblasts promotes pancreatic cancer growth and immune suppression via phospholipid scramblase anoctamin 6 (ANO6).

In pancreatic ductal adenocarcinoma (PDAC), the fibroblastic stroma constitutes most of the tumor mass and is remarkably devoid of functional blood vessels. This raises an unresolved question of how PDAC cells obtain essential metabolites and water-insoluble lipids. We have found a critical role for cancer-associated fibroblasts (CAFs) in obtaining and transferring lipids from blood-borne particles to PDAC cells via trogocytosis of CAF plasma membranes. We have also determined that CAF-expressed phospholipid scramblase anoctamin 6 (ANO6) is an essential CAF trogocytosis regulator required to promote PDAC cell survival. During trogocytosis, cancer cells and CAFs form synapse-like plasma membranes contacts that induce cytosolic calcium influx in CAFs via Orai channels. This influx activates ANO6 and results in phosphatidylserine exposure on CAF plasma membrane initiating trogocytosis and transfer of membrane lipids, including cholesterol, to PDAC cells. Importantly, ANO6-dependent trogocytosis also supports the immunosuppressive function of pancreatic CAFs towards cytotoxic T cells by promoting transfer of excessive amounts of cholesterol. Further, blockade of ANO6 antagonizes tumor growth via disruption of delivery of exogenous cholesterol to cancer cells and reverses immune suppression suggesting a potential new strategy for PDAC therapy.

cancer biology↗

bioRxiv2023

Musashi-2 (MSI2) regulation of DNA damage response in lung cancer

Lung cancer is one of the most common types of cancers worldwide. Non-small cell lung cancer (NSCLC), typically caused by KRAS and TP53 driver mutations, represents the majority of all new lung cancer diagnoses. Overexpression of the RNA-binding protein (RBP) Musashi-2 (MSI2) has been associated with NSCLC progression. To investigate the role of MSI2 in NSCLC development, we compared the tumorigenesis in mice with lung-specific Kras-activating mutation and Trp53 deletion, with and without Msi2 deletion (KP versus KPM2 mice). KPM2 mice showed decreased lung tumorigenesis in comparison with KP mice what supports published data. In addition, using cell lines from KP and KPM2 tumors, and human NSCLC cell lines, we found that MSI2 directly binds ATM/Atm mRNA and regulates its translation. MSI2 depletion impaired DNA damage response (DDR) signaling and sensitized human and murine NSCLC cells to treatment with PARP inhibitors in vitro and in vivo. Taken together, we conclude that MSI2 supports lung tumorigenesis, in part, by direct positive regulation of ATM protein expression and DDR. This adds the knowledge of MSI2 function in lung cancer development. Targeting MSI2 may be a promising strategy to treat lung cancer. SignificanceThis study shows the novel role of Musashi-2 as regulator of ATM expression and DDR in lung cancer.

cancer biology↗

bioRxiv2023

Rationally designed inhibitors of the Musashi protein-RNA interaction by hotspot mimicry

RNA-binding proteins (RBPs) are key post-transcriptional regulators of gene expression, and thus underlie many important biological processes. Here, we developed a strategy that entails extracting a "hotspot pharmacophore" from the structure of a protein-RNA complex, to create a template for designing small-molecule inhibitors and for exploring the selectivity of the resulting inhibitors. We demonstrate this approach by designing inhibitors of Musashi proteins MSI1 and MSI2, key regulators of mRNA stability and translation that are upregulated in many cancers. We report this novel series of MSI1/MSI2 inhibitors is specific and active in biochemical, biophysical, and cellular assays. This study extends the paradigm of "hotspots" from protein-protein complexes to protein-RNA complexes, supports the "druggability" of RNA-binding protein surfaces, and represents one of the first rationally-designed inhibitors of non-enzymatic RNA-binding proteins. Owing to its simplicity and generality, we anticipate that this approach may also be used to develop inhibitors of many other RNA-binding proteins; we also consider the prospects of identifying potential off-target interactions by searching for other RBPs that recognize their cognate RNAs using similar interaction geometries. Beyond inhibitors, we also expect that compounds designed using this approach can serve as warheads for new PROTACs that selectively degrade RNA-binding proteins.

biochemistry↗

bioRxiv2022

An expanded classification of active, inactive, and druggable RAS conformations

For many human cancers and tumor-associated diseases, mutations in the RAS isoforms (KRAS, NRAS, and HRAS) are the most common oncogenic alterations, making these proteins high-priority therapeutic targets. Effectively targeting the RAS isoforms requires an exact understanding of their active, inactive, and druggable conformations. However, there is no structure-guided catalogue of RAS conformations to guide therapeutic targeting or examining the structural impact of RAS mutations. We present an expanded classification of RAS conformations based on analyzing their catalytic switch 1 (SW1) and switch 2 (SW2) loops. From all 721 available human KRAS, NRAS, and HRAS structures in the Protein Data Bank (PDB) (206 RAS-protein complexes, 190 inhibitor-bound, and 325 unbound, including 204 WT and 517 mutated structures), we created a broad conformational classification based on the spatial positions of residue Y32 in SW1 and residue Y71 in SW2. Subsequently, we defined additional conformational subsets (some previously undescribed) by clustering all well modeled SW1 and SW2 loops using a density-based machine learning algorithm with a backbone dihedral-based distance metric. In all, we identified three SW1 conformations and nine SW2 conformations, each which are associated with different nucleotide states (GTP-bound, nucleotide-free, and GDP-bound) and specific bound proteins or inhibitor sites. The GTP-bound SW1 conformation can be further subdivided based on the hydrogen (H)-bond type made between residue Y32 and the GTP {gamma}-phosphate: water-mediated, direct, or no H-bond. Further analyzing these structures clarified the catalytic impact of the G12D and G12V RAS mutations, and the inhibitor chemistries that bind to each druggable RAS conformation. To facilitate future RAS structural analyses, we have created a web database, called Rascore, presenting an updated and searchable dataset of human KRAS, NRAS, and HRAS structures in the PDB, and which includes a page for analyzing user uploaded RAS structures by our algorithm (http://dunbrack.fccc.edu/rascore/). SignificanceAnalyzing >700 experimentally determined RAS structures helped define an expanded landscape of active, inactive and druggable RAS conformations, the structural impact of common RAS mutations, and previously uncharacterized RAS-inhibitor binding modes.

bioinformatics↗

bioRxiv2020

Prevalence of pathogenic variants in DNA damage response genes in patients undergoing cancer risk assessment and reporting a personal history of early-onset renal cancer

PurposePathogenic variants (PVs) in a number of genes are known to increase the risk of hereditary renal cancer (hRC). However, many early-onset RC (eoRC) patients undergoing genetic testing lack PVs in hRC genes; thus, their genetic risk remains undefined. To determine if PVs in DNA damage response (DDR) genes are enriched in a convenience sample of eoRC patients undergoing genetic testing. Materials and MethodsRetrospective review of results for 844 unselected eoRC patients, undergoing genetic testing with a multi-gene cancer panel by Ambry Genetics [between July 2012 and December 2016]. The patients were tested with CancerNext and/or CancerNext Expanded panels for a variety of indications. Identified PVs were compared with patient characteristics. ResultsMean age of RC diagnosis was 48 years [range 24-60]. In addition to eoRC, 57.9% patients tested reported at least one additional cancer; breast cancer being the most common (40.1% of females, 2.5% of males). PVs in cancer risk genes were identified in 12.8% of patients--3.7% in RC-specific genes, and 8.55% in DDR genes. DDR gene PVs were most commonly identified in CHEK2, BRCA1/2, and ATM. Among the 2.1% of patients with a BRCA1/2 PV, <50% reported a personal history of hereditary breast/ovarian-associated cancer. No association between age of RC diagnosis, and prevalence of PVs in RC-specific or DDR genes was observed. ConclusionsMulti-gene panel testing including DDR genes may provide a more comprehensive risk assessment in unselected eoRC patients, and their families. Validation in larger datasets is needed to characterize the association with eoRC.

genetics↗

bioRxiv2019

Cholesterol deprivation induces TGFβ signaling to promote basal differentiation in pancreatic cancer

Oncogenic transformation alters the metabolism of cellular nutrients to sustain tumor growth. We here define a mechanism by which modifications in cholesterol metabolism control the formation of pancreatic ductal adenocarcinoma (PDAC). Disruption of distal cholesterol biosynthesis by means of conditional inactivation of Nsdhl in mice bearing a tumor-inducing Kras mutation (KrasG12D) prevented PDAC formation in the context of a heterozygous Trp53f/+genotype without impairing normal pancreatic development. In mice with pancreatic Nsdhl ablation and homozygous loss of Trp53, the emerging tumors presented with the aggressive basal (mesenchymal) phenotype as opposed to the classic (glandular) PDAC. This paralleled significantly reduced expression of cholesterol metabolic pathway genes in human basal PDAC subtype. Mechanistically, we demonstrate that genetic or metabolic cholesterol deprivation stabilizes the transforming growth factor beta (TGF{beta}) receptor to activate pro-mesenchymal effectors in human and murine PDAC, providing a direct mechanism by which cholesterol metabolism can condition tumor differentiation.

cancer biology↗