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Meyer, J. E.

Publications and source records attributed to Meyer, J. E..

2 recordsLinked to original sources

Pulsed low-dose-rate radiation (PLDR) reduces the tumor-promoting responses induced by conventional chemoradiation in pancreatic cancer-associated fibroblasts

Pancreatic cancer is becoming increasingly deadly, with treatment options limited due to, among others, the complex tumor microenvironment (TME). This short communications study investigates pulsed low-dose-rate radiation (PLDR) as a potential alternative to conventional radiotherapy for pancreatic cancer neoadjuvant treatment. Our ex vivo research demonstrates that PLDR, in combination with chemotherapy, promotes a shift from tumor-promoting to tumor-suppressing properties in a key component of the pancreatic cancer microenvironment we called CAFu (cancer-associated fibroblasts and selfgenerated extracellular matrix functional units). This beneficial effect translates to reduced desmoplasia (fibrous tumor expansion) and suggests PLDRs potential to improve total neoadjuvant therapy effectiveness. To comprehensively assess this functional shift, we developed the HOST-Factor, a single score integrating multiple biomarkers. This tool provides a more accurate picture of CAFu function compared to individual biomarkers and could be valuable for guiding and monitoring future therapeutic strategies. Our findings support the ongoing NCT04452357 clinical trial testing PLDR safety and TME normalization potential in pancreatic cancer patients. The HOST-Factor will be used in samples collected from this trial to validate its potential as a key tool for personalized medicine in this aggressive disease.

cancer biology↗

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↗