Dataset Information

Microsatellite Status and IκBα Expression Levels Predict Sensitivity to Pharmaceutical Curcumin in Colorectal Cancer Cells.

ABSTRACT: Clinical utilization of curcumin in colorectal cancer (CRC) was revived as a result of the development of novel curcumin formulations with improved bioavailability. Additionally, identification of biomarkers for curcumin sensitivity would also promote successful clinical applications. Here, we wanted to identify such biomarkers in order to establish a predictive model for curcumin sensitivity. Thirty-two low-passage CRC cell lines with specified tumor characteristics were included. Curcumin suppressed cell proliferation, yet sensitivity levels were distinct. Most curcumin-sensitive CRC cell lines were microsatellite stable and expressed high levels of IκBα. The predictive capacity of this biomarker combination possessed a statistical significance of 72% probability to distinguish correctly between curcumin-sensitive and -resistant CRC cell lines. Detailed functional analyses were performed with three sensitive and three resistant CRC cell lines. As curcumin's mode of action, inhibition of NF-κB p65 activation via IκBα was identified. In consequence, we hypothesize that novel curcumin formulations-either alone or, more likely, in combination with standard therapeutics-can be expected to prove clinically beneficial for CRC patients with high IκBα expression levels.

SUBMITTER: Lu L

PROVIDER: S-EPMC8870219 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Microsatellite Status and IκBα Expression Levels Predict Sensitivity to Pharmaceutical Curcumin in Colorectal Cancer Cells.

Lu Lili L Przybylla Randy R Shang Yuru Y Dai Meng M Krohn Mathias M Krämer Oliver Holger OH Mullins Christina Susanne CS Linnebacher Michael M

Cancers 20220217 4

Clinical utilization of curcumin in colorectal cancer (CRC) was revived as a result of the development of novel curcumin formulations with improved bioavailability. Additionally, identification of biomarkers for curcumin sensitivity would also promote successful clinical applications. Here, we wanted to identify such biomarkers in order to establish a predictive model for curcumin sensitivity. Thirty-two low-passage CRC cell lines with specified tumor characteristics were included. Curcumin supp ...[more]

PMID: 35205780

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Project description:BackgroundMicrosatellite instability (MSI) status is a strong predictor of response to immunotherapy of colorectal cancer. Radiogenomic approaches promise the ability to gain insight into the underlying tumor biology using non-invasive routine clinical images. This study investigates the association between tumor morphology and the status of MSI versus microsatellite stability (MSS), validating a novel radiomic signature on an external multicenter cohort.MethodsPreoperative computed tomography scans with matched MSI status were retrospectively collected for 243 colorectal cancer patients from three hospitals: Seoul National University Hospital (SNUH); Netherlands Cancer Institute (NKI); and Fondazione IRCCS Istituto Nazionale dei Tumori, Milan Italy (INT). Radiologists delineated primary tumors in each scan, from which radiomic features were extracted. Machine learning models trained on SNUH data to identify MSI tumors underwent external validation using NKI and INT images. Performances were compared in terms of area under the receiving operating curve (AUROC).ResultsWe identified a radiomic signature comprising seven radiomic features that were predictive of tumors with MSS or MSI (AUROC 0.69, 95% confidence interval [CI] 0.54-0.84, p = 0.018). Integrating radiomic and clinical data into an algorithm improved predictive performance to an AUROC of 0.78 (95% CI 0.60-0.91, p = 0.002) and enhanced the reliability of the predictions.ConclusionDifferences in the radiomic morphological phenotype between tumors MSS or MSI could be detected using radiogenomic approaches. Future research involving large-scale multicenter prospective studies that combine various diagnostic data is necessary to refine and validate more robust, potentially tumor-agnostic MSI radiogenomic models.Relevance statementNoninvasive radiomic signatures derived from computed tomography scans can predict MSI in colorectal cancer, potentially augmenting traditional biopsy-based methods and enhancing personalized treatment strategies.Key pointsNoninvasive CT-based radiomics predicted MSI in colorectal cancer, enhancing stratification. A seven-feature radiomic signature differentiated tumors with MSI from those with MSS in multicenter cohorts. Integrating radiomic and clinical data improved the algorithm's predictive performance.

Dataset Information

Microsatellite Status and IκBα Expression Levels Predict Sensitivity to Pharmaceutical Curcumin in Colorectal Cancer Cells.

Publications

Microsatellite Status and IκBα Expression Levels Predict Sensitivity to Pharmaceutical Curcumin in Colorectal Cancer Cells.

Similar Datasets

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