Oral Steroids for Regorafenib-induced Fatigue/Malaise in Unresectable mCRC (KSCC1402/HGCSG1402)
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Cancer,Fatigue,Rectal Cancer
PROVIDER: 2178064 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Colorectal cancer (CRC) remains the third leading cause of cancer-related deaths worldwide, with its incidence continuing to rise. Regorafenib, a multi-kinase inhibitor approved as a palliative treatment, extends survival in patients with metastatic CRC (mCRC) who have failed standard therapies. However, the clinical benefit of regorafenib is limited to a subset of patients, is typically short-lived, and is often accompanied by significant toxicity. The mechanisms by which CRC cells develop resistance to regorafenib remain poorly understood.In this study, we investigated resistance mechanisms to regorafenib using a preclinical mouse colon organoid model. Transcriptomic analysis of Apc wild-type and Apc-deficient organoids treated with regorafenib revealed an upregulation of epithelial-to-mesenchymal transition (EMT), accompanied by alterations in the secretome and increased activation of phosphorylated Erk1/2. Notably, co-treatment with an autophagy inhibitor suppressed regorafenib-induced EMT and its associated secretory phenotype, resulting in reduced cell proliferation and enhanced apoptosis in mouse organoids. The effectiveness of this drug combination was further supported by cell viability assays in human CRC cell lines. In contrast, primary mouse colon fibroblasts displayed greater resistance to both single-agent and combination regorafenib treatments. In summary, our findings using a preclinical organoid model suggest that autophagy inhibition may offer a promising strategy to mitigate chemoresistance and reduce toxicity associated with regorafenib treatment in mCRC patients.
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Project description:We demonstrate that regorafenib treatment suppresses multiple canonical pathways and transcriptions factors We used microarrays to analyze the potential mechanism by which regorafenib regulates gene expression.
2022-04-28 | GSE149131 | GEO
Project description:Developing effective model systems to evaluate new potential chemotherapeutic reagents is critical. Three-dimensional cell cultures, such as spheroids, aid in bridging the gap between commonly used monolayer cell cultures and significantly more complex and expensive animal models. Spheroid model systems contain pathophysiological and chemical gradients similar to an in vivo tumor, which ultimately form distinct cellular subpopulations. In the spatial SILAC model, labels are pulsed into the spheroid at discrete time windows during development. These media pulses result in labeled proteins in distinct regions of the spheroid, which allows for tracing of quantitative proteomic changes to be correlated to different cellular subregions. In this study, we use the Spatial SILAC model to evaluate the proteomic response of a colon carcinoma spheroid to the multikinase inhibitor Regorafenib. We determined regorafenib to be an effective kinase inhibitor which significantly altered whole spheroid proliferation and resulted in increased apoptosis when the signal was averaged for all cells in the culture. However, when regorafenib treatment is more closely examined among the cellular subpopulations, drastic differences are observed for how the drug impacted the proteome of the necrotic spheroid core and the proliferating outer regions. Whole spheroid and outer region analysis shows that regorafenib treatment inhibited critical pathways such as mTOR signaling, ERK/MAPK signaling, and colorectal cancer metastasis signaling. However, analysis of the core shows that regorafenib had an entirely different effect, including upregulation of MAPK1 and KRAS, possibly indicating drug resistance within these late apoptotic cells. Ultimately, these combinatory studies can be used to further understanding of drug metabolism is different cellular subpopulations and provide valuable information to ultimately improve the accuracy of therapeutic testing.
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Project description:Background. Chronic fatiguing illness remains a poorly understood syndrome of unknown pathogenesis. We attempted to identify biomarkers for chronic fatiguing illness using microarrays to query the transcriptome in peripheral blood leukocytes. Methods. Cases were 44 individuals who were clinically evaluated and found to meet standard international criteria for chronic fatigue syndrome or idiopathic chronic fatigue, and controls were their monozygotic co-twins who were clinically evaluated and never had even one month of impairing fatigue. Biological sampling conditions were standardized and RNA stabilizing media were used. These methodological features provide rigorous control for bias resulting from case-control mismatched ancestry and experimental error. Individual gene expression profiles were assessed using Affymetrix Human Genome U133 Plus 2.0 arrays. Findings. There were no significant differences in gene expression for any transcript. Conclusions. Contrary to our expectations, we were unable to identify a biomarker for chronic fatiguing illness in the transcriptome of peripheral blood leukocytes suggesting that positive findings in prior studies may have resulted from experimental bias. Cases were 44 individuals who were clinically evaluated and found to meet standard international criteria for chronic fatigue syndrome or idiopathic chronic fatigue, and controls were their monozygotic co-twins who were clinically evaluated and never had even one month of impairing fatigue.
2009-05-12 | E-GEOD-16059 | biostudies-arrayexpress
Project description:We report the RNA sequencing data from the REPEAT study, in which patients with beyond first-line esophagogastric cancer were treated with regorafenib and paclitaxel. For the RNA sequencing, biopsies from metastatic lesions were obtained on baseline (n=21) and fifteen days following treatment initiation (n=13). PURPOSE: Regorafenib monotherapy, a multikinase-inhibitor of angiogenesis, tumor microenvironment, and oncogenesis, showed promising results in gastric cancer. We aimed to assess the tolerability of regorafenib and paclitaxel in advanced esophagogastric cancer (EGC) patients refractory to first-line treatment, and explore potential biomarkers. METHODS: Patients received paclitaxel (80 mg/m2) on days 1, 8, and 15 of a 28-day cycle and regorafenib (80/120/160 mg) on day 1-21 in the dose-escalation cohort, and the maximum-tolerated dose (MTD) in the dose-expansion cohort. Exploratory, overall- (OS) and progression-free survival (PFS) were compared to a propensity-score matched cohort receiving standard second/third line systemic treatment. Paclitaxel pharmacokinetics were assessed using D1 and D15 samples. We performed ELISA measurements of galectin-1, RNA sequencing and shallow whole-genome sequencing of metastatic tumor biopsies for biomarker analyses. RESULTS: In the dose-escalation cohort (n=14), the MTD of regorafenib was 120 mg. Thirty-four patients were enrolled in the dose-expansion cohort. Most common toxicities (all grades; grade ≥3) were fatigue (79%; 4%) and sensory neuropathy (63%; 4%). Best responses achieved were partial response (28%) and stable disease (54%). Median OS and PFS were 7.8 and 4.2 months, respectively (median follow-up 7.8 months). OS (p=0.08) and PFS (p=0.81) were not significantly improved compared to the matched cohort. Paclitaxel concentrations were significantly increased with regorafenib (D15) compared with paclitaxel only (D1; p<0.05); no associations were observed with toxicity or efficacy. An increase in circulating galectin-1 compared to baseline was associated with shorter OS (p<0.01). Enrichment of angiogenesis-related gene expression was observed in short-survivors measured by RNA sequencing. Chromosome 19q13.12-q13.2 amplification was associated with shorter OS (p=0.02) and PFS (p=0.02). CONCLUSION: Treatment with regorafenib and paclitaxel is tolerable and shows promising efficacy in advanced EGC refractory to first-line treatment. Galectin-1 and chromosome 19q13.12-q13.2 amplification could serve as negative predictive biomarkers for treatment response.
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Project description:Fatigue is a debilitating condition with a significant impact on patientsâ quality of life. Fatigue is frequently reported by patients suffering from primary Sjo Ìgrenâs Syndrome (pSS), a chronic autoimmune condition characterised by dryness of the eyes and the mouth. However, although fatigue is common in pSS, it does not manifest in all sufferers, providing an excellent model with which to explore the potential underpinning biological mechanisms. Whole blood samples from 131 fully-phenotyped pSS patients, stratified for the presence of fatigue, collected by the UK primary Sj Ìogrenâs Syndrome Registry were used for whole genome microarray. The resulting data were analysed both on a gene by gene basis and using pre-defined groups of genes. Finally, gene set enrichment analysis (GSEA) was used as a feature selection technique for input into a support vector machine (SVM) classifier. Classification was assessed using area under curve (AUC) of receiver operator characteristic and standard error of Wilcoxon statistic, SE(W). Contributor: The UK Primary Sjögrenâs syndrome registry
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Project description:Genome-wide analysis of DNA methylation profiles from patients with Sjögren's syndrome with high versus low fatigue levels using the Illumina Infinium HumanMethylation450 Beadchip array. Background Chronic fatigue is a common, disabling, and poorly understood phenomenon. Recent studies indicate that epigenetic mechanisms may be involved in the expression of fatigue, a prominent feature of primary Sjögrenâs syndrome (pSS). The aim of this study was to investigate whether DNA methylation profiles of whole blood are associated with fatigue in patients with pSS. Methods 48 pSS patients with high (n=24) or low (n=24) fatigue as measured by a visual analogue scale were included. Genome-wide DNA methylation was investigated using the Illumina HumanMethylation450 BeadChip array. Case-case study including Sjögren's patients with high fatigue (n=24) and patients with low fatigue levels (n=24)
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