Biology subjects

Camphausen, K.

Publications and source records attributed to Camphausen, K..

6 recordsLinked to original sources

bioRxiv2026

Radiosensitization of Glioblastoma by the K-ras Inhibitor RMC-6236

PurposeGlioblastoma (GBM) is characterized by poor clinical outcomes and marked resistance to radiotherapy. Because effective radiosensitizing strategies for GBM remain limited, we investigated whether inhibition of KRAS/RAS signaling could enhance radiation response in GBM. In particular, we evaluated the radiosensitizing potential of RMC-6236, an RAS(ON) multiselective inhibitor that suppresses active RAS signaling across multiple RAS-dependent states. Experimental DesignHuman GBM cell lines (U251, LN-18, ACPK1, and OSU61) were treated with radiation, with or without genetic or pharmacological KRAS inhibition. KRAS signaling was suppressed by siRNA-mediated knockdown or RMC-6236 treatment. Radiation-induced KRAS activation and downstream MAPK signaling were assessed by Raf-RBD pull-down assays and immunoblotting. Radiosensitivity was evaluated using clonogenic survival assay. DNA damage persistence, cell cycle distribution, and mitotic catastrophe were analyzed by {gamma}H2AX immunofluorescence, flow cytometry, and nuclear morphology assessment, respectively. In vivo therapeutic efficacy was examined in an orthotopic U251 xenograft model. ResultsRadiation-induced transient activation and increased KRAS protein expression of KRAS, accompanied by activation of ERK, JNK, and p38 signaling in GBM cells. siKRAS suppressed radiation-induced KRAS and MAPK activation, and significantly enhanced radiosensitivity in all four GBM cell lines. Similarly, RMC-6236 inhibited radiation-induced KRAS activation and attenuated downstream MAPK signaling without reducing the total KRAS protein expression. RMC-6236 significantly increased the radiosensitivity across all GBM cell lines, with dose enhancement factors ranging from 1.33 1.46. Mechanistically, combined treatment with RMC-6236 and radiation increased persistent {gamma}H2AX foci and enhanced mitotic catastrophe without producing consistent redistribution of cells into radiosensitive cell cycle phases. In an orthotopic GBM model, the combination of RMC-6236 and radiation significantly prolonged survival compared to that of the control and radiation alone. ConclusionsThese findings indicate that radiation-induced KRAS signaling is a functionally important mediator of radioresistance in GBM and demonstrate that inhibition of KRAS/RAS signaling enhances the radiation response in vitro and in vivo. RMC-6236 may represent a promising radiosensitizing strategy for GBM by suppressing adaptive RAS/MAPK signaling and promoting persistent DNA damage and mitotic catastrophe following irradiation. However, clinical trials of this combination are warranted.

neuroscience↗

bioRxiv2024

CPSM: R-package of an Automated Machine Learning Pipeline for Predicting the Survival Probability of Single Cancer Patient

Accurate survival prediction is vital for optimizing treatment strategies in clinical practice. The advent of high-throughput multi-omics data and computational methods has enabled machine learning (ML) models for survival analysis. However, handling high-dimensional omics data remains challenging. This study introduces the Cancer Patient Survival Model (CPSM), an R package developed to provide individualized survival predictions through a fully integrated and reproducible computational pipeline. The CPSM package encompasses nine modules that streamline the survival modeling workflow, organized into four key stages: (1) Data Preprocessing and Normalization, (2) Feature Selection, (3) Survival Prediction Model Development, and (4) Visualization. The visual tools facilitate the interpretation of survival predictions, enhancing clinical decision-making. By providing an end-to-end solution for multi-omics data integration and analysis, CPSM not only enhances the precision of survival predictions but also aids in discovering clinically relevant biomarkers. Availability and ImplementationThe CPSM Package is freely available at the GitHub URL: https://github.com/hks5august/CPSM

bioinformatics↗

bioRxiv2022

Taxanes act as vascular disrupting agents and increase rate of metastasis when combined with anti-angiogenic therapy

Taxanes are known to have a profound effect on endothelial cells and the vasculature even at low doses. Here, we show that taxanes, rather than being anti-angiogenic, function more as vascular disrupting agents (VDAs), although they exert a different mechanism of vascular permeabilization when compared to traditional VDAs such as combretastatins. In the tumor context, this VDA-effect leads to a rapid vascular collapse and acute hypoxia. Concomitant treatment with anti-VEGF drugs aggravates hypoxia by blocking vasculogenic rescue mechanisms. While this results in a strong growth-suppressing effect on the tumor, it also increases its invasiveness and metastatic potential. We demonstrate that combination of anti-angiogenic drugs with taxanes blocks tumor reperfusion, intensifies intravasation of circulating tumor cells (CTCs) and strongly increases metastasis. Anti-VEGF drugs are commonly applied in combination with cytotoxic drugs including taxanes. Our findings have significant implications for the clinical use of this drug combination.

cancer biology↗

bioRxiv2022

Glioma-BioDP: Database for Visualization of Molecular Profiles to Improve Prognosis of Brain Cancer

Cancer researchers often seek user-friendly interactive tools for validation, exploration, analysis, and visualization of molecular profiles in cancer patient samples. To aid researchers working on both low-and high-grade gliomas, we developed Glioma-BioDP, a web tool for exploration and visualization of RNA and protein expression profiles of interest in these tumor types. Glioma-BioDP is an extended version of our earlier published tool GBM-BioDP. In this version we have included expression data from both the low-and high-grade glioma patient samples from The Cancer Genome Atlas and enabled querying by mRNA, microRNA, and protein level expression data from Illumina HiSeq and RPPA platforms respectively. Glioma-BioDP enables users to explore the association of genes, proteins, and miRNA expression with molecular and/or histological subtypes of gliomas, surgical resection status and survival. The prognostic significance and visualization of the selected expression profiles can be explored using interactive utilities provided. This tool also enables potential validation and generation of new hypotheses of novel therapies impacting gliomas that aid in personalization of treatment for optimum outcomes. AvailabilityGlioma-BioDP web tool with user manual is available from: https://glioma-biodp.nci.nih.gov Contact: uma@mail.nih.gov

cancer biology↗

bioRxiv2021

Cysteine is a limiting factor for glioma proliferation and survival

Nutritional intervention is becoming more prevalent as adjuvant therapy for many cancers in view of the tumor dependence on external sources for some nutrients. We report the dependence of glioma cells on exogenous cysteine/cystine, despite this amino acid being nonessential. 13C-tracing and the analysis of cystathionine synthase and cystathioninase levels revealed the metabolic landscape attributable to cysteine deprivation, and the disconnection between the methionine cycle and the transsulfuration pathway. Therefore, we explored the nutritional deprivation in a mouse model of glioma. Animals subjected to a cysteine/cystine-free diet survived longer, with concomitant reductions in glutathione and cysteine plasma levels. At the end point, however, tumors displayed the ability to synthesize glutathione, although higher levels of oxidative stress were detected. We observed a compensation from the nutritional intervention revealed as the recovery of cysteine-related metabolites in plasma. Our study highlights a time window where cysteine deprivation can be exploited for additional therapeutic strategies.

cancer biology↗

bioRxiv2020

A simple, high-throughput method of protein and label removal from extracellular vesicle samples

Evidence continues to increase of the clinical utility extracellular vesicles (EVs) can provide as translational biomarkers. While a wide variety of EV isolation and purification methods have been implemented, few techniques are high-throughput and scalable for removing excess fluorescent reagents (e.g. dyes, antibodies). EVs are too small to be recovered from routine cell-processing procedures, such as filtration or centrifugation. The lack of suitable methods for removing unbound labels, especially in optical assays, is a major roadblock to accurate EV phenotyping and utilization of EV assays in a translational or clinical setting. Therefore, we developed a method for using a multi-modal resin, referred to as EV-Clean, to remove unbound labels from EV samples, and we demonstrate improvement in flow cytometric EV analysis with the use of this EV-Clean method.

biochemistry↗