Convergent genomic diversity and novel BCAA metabolism in intrahepatic cholangiocarcinoma

Role of Gut Microbial Metabolites in the Pathogenesis of Primary Liver Cancers

Hepatobiliary malignancies, which include hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are the sixth most common cancers and the third leading cause of cancer-related death worldwide. Hepatic carcinogenesis is highly stimulated by chronic inflammation, defined as fibrosis deposition, and an aberrant imbalance between liver necrosis and nodular regeneration. In this context, the gut-liver axis and gut microbiota have demonstrated a critical role in the pathogenesis of HCC, as dysbiosis and altered intestinal permeability promote bacterial translocation, leading to chronic liver inflammation and tumorigenesis through several pathways. A few data exist on the role of the gut microbiota or bacteria resident in the biliary tract in the pathogenesis of CCA, and some microbial metabolites, such as choline and bile acids, seem to show an association. In this review, we analyze the impact of the gut microbiota and its metabolites on HCC and CCA development and the role of gut dysbiosis as a biomarker of hepatobiliary cancer risk and of response during anti-tumor therapy. We also discuss the future application of gut microbiota in hepatobiliary cancer management.

Plasma Metabolic Profiles-Based Prediction of Induction Chemotherapy Efficacy in Nasopharyngeal Carcinoma: Results of a Bidirectional Clinical Trial

PURPOSE

The efficacy of induction chemotherapy (IC) as a primary treatment for advanced nasopharyngeal carcinoma (NPC) remains a topic of debate, with a lack of dependable biomarkers for predicting its efficacy. This study seeks to establish a predictive classifier using plasma metabolomics profiles.

PATIENTS AND METHODS

A total of 166 NPC patients enrolled in the clinical trial NCT05682703 who were undergoing IC were included in the study. Plasma lipoprotein profiles were obtained using 1H-nuclear magnetic resonance before and after IC treatment. An artificial intelligence-assisted radiomics method was developed to effectively evaluate its efficacy. Metabolic biomarkers were identified through a machine learning approach based on a discovery cohort and subsequently validated in a validation cohort that mimicked the most unfavorable real-world scenario.

RESULTS

Our research findings indicate that the effectiveness of IC varies among individual patients, with a correlation observed between efficacy and changes in metabolite profiles. Using machine learning techniques, it was determined that the extreme gradient boosting model exhibited notable efficacy, attaining an area under the curve (AUC) value of 0.792 (95% CI, 0.668-0.913). In the validation cohort, the model exhibited strong stability and generalizability, with an AUC of 0.786 (95% CI, 0.533-0.922).

CONCLUSIONS

In this study, we found that dysregulation of plasma lipoprotein may result in resistance to IC in NPC patients. The prediction model constructed based on the plasma metabolites' profile has good predictive capabilities and potential for real-world generalization. This discovery has implications for the development of treatment strategies and may offer insight into potential targets for enhancing the effectiveness of IC.

Commentary: Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in cholangiocarcinoma

Machine learning has made great progress in the field of medicine, especially in oncology research showing significant potential. In this paper, the application of machine learning in the study of cholangiocarcinoma was discussed. By developing a novel intra-tumor heterogeneity feature, the study successfully achieved accurate prediction of prognosis and immunotherapy effect in patients with cholangiocarcinoma. This study not only provides strong support for personalized treatment, but also provides key information for clinicians to develop more effective treatment strategies. This breakthrough marks the continuous evolution of machine learning in cancer research and brings new hope for the future development of the medical field. Our study lays a solid foundation for deepening the understanding of the biological characteristics of cholangiocarcinoma and improving the therapeutic effect, and provides a useful reference for more extensive cancer research.

Branched-Chain Amino Acid Degradation Pathway was Inactivated in Colorectal Cancer: Results from a Proteomics Study

Background: Colorectal cancer (CRC) ranks third in terms of cancer incidence and fourth in terms of cancer-related deaths worldwide. Identifying potential biomarkers of CRC is crucial for treatment and drug development. Methods: In this study, we established a C57B/6N mouse model of colon carcinogenesis using azoxymethane-dextran sodium sulfate (AOM-DSS) treatment for 14 weeks to identify proteins associated with colon cancer. An isobaric tag for relative and absolute quantitation (iTRAQ)-based proteomic analysis was conducted on the cell membrane components enriched in the colonic mucosa. Additionally, tumor tissues and adjacent normal colon tissues were collected from patients with colon cancer for comparative protein and metabolite analyses. Results: In total, 74 differentially expressed proteins were identified in the tumor tissue samples from AOM/DSS-treated mice compared to both the adjacent tissue samples from AOM/DSS-treated mice and tissue samples from saline-treated control mice. Bioinformatics analysis revealed eight downregulated proteins enriched in the branched-chain amino acids pathway (valine, leucine, and isoleucine degradation). Moreover, these proteins are already known to be associated with the survival rate of patients with cancer. Targeted metabolomics showed increased levels of valine, leucine, and isoleucine in tumor tissues compared to those in adjacent normal tissues in patients with colon cancer. Furthermore, a real-time PCR experiment demonstrated that Aldehyde dehydrogenase, mitochondrial (short protein name ALDH2, gene name Aldh2) and Hydroxyacyl-coenzyme A dehydrogenase, mitochondrial (short protein name HCDH, gene name Hadh) (two genes) in the pathway of branched-chain amino acids) were downregulated in patients with colon cancer (colon tumor tissues vs. their adjacent colon tissues). ALDH2 expression was further validated by western blotting in AOM/DSS-treated mouse model and in clinical samples. Conclusion: This study highlighted the inactivation of the branched-chain amino acid degradation pathway in colon cancer and identified ALDH2 and HCDH as potential biomarkers for diagnosing colon cancer and developing new therapeutic strategies.

Integrated physiological, transcriptome, and metabolome analyses of the hepatopancreas of Litopenaeus vannamei under cold stress

Temperature is a limiting factor in the growth of aquatic organisms and can directly affect many chemical and biological processes, including metabolic enzyme activity, aerobic respiration, and signal transduction. In this study, physiological, transcriptomic, and metabolomic analyses were performed to characterize the response of Litopenaeus vannamei to cold stress. We subjected L. vannamei to gradually decreasing temperatures (24 °C, 20 °C, 18 °C, 14 °C, and 12 °C) and studied the changes in the hepatopancreas. The results showed that extreme cold stress (12 °C) caused structural damage to the hepatopancreas of L. vannamei. However, shrimp exhibited response mechanisms to enhance cold tolerance, through regulating changes in key genes and metabolites in amino acid, lipid metabolism, and carbohydrate metabolism, including (a) increased level of methylation in cells to enhance cold tolerance; (b) increased content of critical amino acids, such as proline, alanine, glutamic acid and taurine, to ameliorate energy metabolism, protect cells from cold-induced osmotic imbalance, and promote ion transport and DNA repair; (c) accumulation of unsaturated fatty acids to improve cell membrane fluidity; and (d) regulation of the metabolic pattern shift to rely on anaerobic metabolism with a gradual decrease in aerobic metabolism and enhance glycolysis to produce enough ATP to maintain energy metabolic balance. When the temperature dropped further, cold stress impaired antioxidant and immune defense responses in shrimp. This study provides an integrated analysis of the physiology, transcriptome, and metabolome of L. vannamei in response to cold stress.

Transcending frontiers in prostate cancer: the role of oncometabolites on epigenetic regulation, CSCs, and tumor microenvironment to identify new therapeutic strategies

Prostate cancer, as one of the most prevalent malignancies in males, exhibits an approximate 5-year survival rate of 95% in advanced stages. A myriad of molecular events and mutations, including the accumulation of oncometabolites, underpin the genesis and progression of this cancer type. Despite growing research demonstrating the pivotal role of oncometabolites in supporting various cancers, including prostate cancer, the root causes of their accumulation, especially in the absence of enzymatic mutations, remain elusive. Consequently, identifying a tangible therapeutic target poses a formidable challenge. In this review, we aim to delve deeper into the implications of oncometabolite accumulation in prostate cancer. We center our focus on the consequential epigenetic alterations and impacts on cancer stem cells, with the ultimate goal of outlining novel therapeutic strategies.