Ultra-Performance Liquid Chromatography/Mass Spectrometry-Based Metabolomics for Discovering Potential Biomarkers and Metabolic Pathways of Colorectal Cancer in Mouse Model (ApcMin/+) and Revealing the Effect of Honokiol

Natural Products and Derivatives Targeting Metabolic Reprogramming in Colorectal Cancer: A Comprehensive Review

Metabolic reprogramming is a critical pathogenesis of colorectal cancer (CRC), referring to metabolic disorders that cancer cells make in response to the stimulating pressure. Metabolic reprogramming induces changes in genetic material and promotes CRC progression and has been proven to be an efficient target of CRC. As natural products have garnered interest due to notable pharmacological effects and potential in counteracting chemoresistance, an increasing body of research is delving into the impact of these natural products on the metabolic reprogramming associated with CRC. In this review, we collected published data from the Web of Science and PubMed, covering the period from January 1980 to October 2023. This article focuses on five central facets of metabolic alterations in cancer cells, glucose metabolism, mitochondrial oxidative phosphorylation (OXPHOS), amino acid metabolism, fatty acid synthesis, and nucleotide metabolism, to provide an overview of recent advancements in natural product interventions targeting metabolic reprogramming in CRC. Our analysis underscores the potential of natural products in disrupting the metabolic pathways of CRC, suggesting promising therapeutic targets for CRC and expanding treatment options for metabolic-associated ailments.

Transcriptomic correlates of cell cycle checkpoints with distinct prognosis, molecular characteristics, immunological regulation, and therapeutic response in colorectal adenocarcinoma

Backgrounds

Colorectal adenocarcinoma (COAD), accounting for the most common subtype of colorectal cancer (CRC), is a kind of malignant digestive tumor. Some cell cycle checkpoints (CCCs) have been found to contribute to CRC progression, whereas the functional roles of a lot of CCCs, especially the integrated role of checkpoint mechanism in the cell cycle, remain unclear.

Materials and methods

The Genomic Data Commons (GDC) The Cancer Genome Atlas (TCGA) COAD cohort was retrieved as the training dataset, and GSE24551 and GSE29623 were downloaded from Gene Expression Omnibus (GEO) as the validation datasets. A total of 209 CCC-related genes were derived from the Gene Ontology Consortium and were subsequently enrolled in the univariate, multivariate, and least absolute shrinkage and selection operator (LASSO) Cox regression analyses, finally defining a CCC signature. Cell proliferation and Transwell assay analyses were utilized to evaluate the functional roles of signature-related CCCs. The underlying CCC signature, molecular characteristics, immune-related features, and therapeutic response were finally estimated. The Genomics of Drug Sensitivity in Cancer (GDSC) database was employed for the evaluation of chemotherapeutic responses.

Results

The aberrant gene expression of CCCs greatly contributed to COAD development and progression. Univariate Cox regression analysis identified 27 CCC-related genes significantly affecting the overall survival (OS) of COAD patients; subsequently, LASSO analysis determined a novel CCC signature. Noticeably, CDK5RAP2, MAD1L1, NBN, RGCC, and ZNF207 were first identified to be correlated with the prognosis of COAD, and it was proven that all of them were significantly correlated with the proliferation and invasion of HCT116 and SW480 cells. In TCGA COAD cohort, CCC signature robustly stratified COAD patients into high and low CCC score groups (median OS: 57.24 months vs. unreached, p< 0.0001), simultaneously, with the good AUC values for OS prediction at 1, 2, and 3 years were 0.74, 0.78, and 0.77. Furthermore, the prognostic capacity of the CCC signature was verified in the GSE24551 and GSE29623 datasets, and the CCC signature was independent of clinical features. Moreover, a higher CCC score always indicated worse OS, regardless of clinical features, histological subtypes, or molecular subgroups. Intriguingly, functional enrichment analysis confirmed the CCC score was markedly associated with extracellular, matrix and immune (chemokine)-related signaling, cell cycle-related signaling, and metabolisms. Impressively, a higher CCC score was positively correlated with a majority of chemokines, receptors, immunostimulators, and anticancer immunity, indicating a relatively immune-promoting microenvironment. In addition, GSE173839, GSE25066, GSE41998, and GSE194040 dataset analyses of the underlying CCC signature suggested that durvalumab with olaparib and paclitaxel, taxane-anthracycline chemotherapy, neoadjuvant cyclophosphamide/doxorubicin with ixabepilone or paclitaxel, and immunotherapeutic strategies might be suitable for COAD patients with higher CCC score. Eventually, the GDSC database analysis showed that lower CCC scores were likely to be more sensitive to 5-fluorouracil, bosutinib, gemcitabine, gefitinib, methotrexate, mitomycin C, and temozolomide, while patients with higher CCC score seemed to have a higher level of sensitivity to bortezomib and elesclomol.

Conclusion

The novel CCC signature exhibited a good ability for prognosis prediction for COAD patients, and the CCC score was found to be highly correlated with molecular features, immune-related characteristics, and therapeutic responses, which would greatly promote clinical management and precision medicine for COAD.

Metabolomics analysis of amino acid and fatty acids in colorectal cancer patients based on tandem mass spectrometry

Metabolic differences between colorectal cancer (CRC) and NI (NI) play an important role in early diagnoses and in-time treatments. We investigated the metabolic alterations between CRC patients and NI, and identified some potential biomarkers, and these biomarkers might be used as indicators for diagnosis of CRC. In this study, there were 79 NI, 50 CRC I patients, 52 CRC II patients, 56 CRC III patients, and 52 CRC IV patients. MS-MS was used to measure the metabolic alterations. Univariate and multivariate data analysis and metabolic pathway analysis were applied to analyze metabolic data and determine differential metabolites. These indicators revealed that amino acid and fatty acids could separate these groups. Several metabolites indicated an excellent variables capability in the separation of CRC patients and NI. Ornithine, arginine, octadecanoyl carnitine, palmitoyl carnitine, adipoyl carnitine, and butyryl carnitine/propanoyl carnitine were selected to distinguish the CRC patients and NI. And methionine and propanoyl carnitine, were directly linked to different stages of CRC. Receiver operating characteristics curves and variables importance in projection both represented an excellent performance of these metabolites. In conclusion, we assessed the difference between CRC patients and NI, which supports guidelines for an early diagnosis and effective treatment.

Acylcarnitines: Can They Be Biomarkers of Diabetic Nephropathy?

Diabetic nephropathy (DN), one of the most serious microvascular complications of diabetes mellitus (DM), may progress to end-stage renal disease (ESRD). Current biochemical biomarkers, such as urinary albumin excretion rate (UAER), have limitations for early screening and monitoring of DN. Recent studies have identified some metabolites as candidate biomarkers for early detection of DN. In this review, we summarize the role of dysregulated acylcarnitines (AcylCNs) in DN pathophysiology. Lower abundance of short- and medium-chain AcylCNs and higher long-chain AcylCNs often occurred in DM with normal albuminuria and microalbuminuria, compared with advanced stages of DN. The increase of long-chain AcylCNs was supposed to be an adaptive compensation in fat acids (FAs) oxidation in the early stage of DN. Conversely, the decrease of long-chain AcylCNs was due to incomplete oxidation of FAs in advanced stage of DN. Thus, AcylCNs may serve as sensitive biomarkers in predicting the risk of DN.