Cancer Biology & Medicine最新文献

Hepatocellular carcinoma (HCC) is a prevalent and aggressive liver malignancy. The interplay between bile acids (BAs) and the gut microbiota has emerged as a critical factor in HCC development and progression. Under normal conditions, BA metabolism is tightly regulated through a bidirectional interplay between gut microorganisms and BAs. The gut microbiota plays a critical role in BA metabolism, and BAs are endogenous signaling molecules that help maintain liver and intestinal homeostasis. Of note, dysbiotic changes in the gut microbiota during pathogenesis and cancer development can disrupt BA homeostasis, thereby leading to liver inflammation and fibrosis, and ultimately contributing to HCC development. Therefore, understanding the intricate interplay between BAs and the gut microbiota is crucial for elucidating the mechanisms underlying hepatocarcinogenesis. In this review, we comprehensively explore the roles and functions of BA metabolism, with a focus on the interactions between BAs and gut microorganisms in HCC. Additionally, therapeutic strategies targeting BA metabolism and the gut microbiota are discussed, including the use of BA agonists/antagonists, probiotic/prebiotic and dietary interventions, fecal microbiota transplantation, and engineered bacteria. In summary, understanding the complex BA-microbiota crosstalk can provide valuable insights into HCC development and facilitate the development of innovative therapeutic approaches for liver malignancy.

Objective: Epigenetic abnormalities have a critical role in breast cancer by regulating gene expression; however, the intricate interrelationships and key roles of approximately 400 epigenetic regulators in breast cancer remain elusive. It is important to decipher the comprehensive epigenetic regulatory network in breast cancer cells to identify master epigenetic regulators and potential therapeutic targets.

Methods: We employed high-throughput sequencing-based high-throughput screening (HTS²) to effectively detect changes in the expression of 2,986 genes following the knockdown of 400 epigenetic regulators. Then, bioinformatics analysis tools were used for the resulting gene expression signatures to investigate the epigenetic regulations in breast cancer.

Results: Utilizing these gene expression signatures, we classified the epigenetic regulators into five distinct clusters, each characterized by specific functions. We discovered functional similarities between BAZ2B and SETMAR, as well as CLOCK and CBX3. Moreover, we observed that CLOCK functions in a manner opposite to that of HDAC8 in downstream gene regulation. Notably, we constructed an epigenetic regulatory network based on the gene expression signatures, which revealed 8 distinct modules and identified 10 master epigenetic regulators in breast cancer.

Conclusions: Our work deciphered the extensive regulation among hundreds of epigenetic regulators. The identification of 10 master epigenetic regulators offers promising therapeutic targets for breast cancer treatment.

Cancer is the leading cause of death worldwide. Early detection of cancer can lower the mortality of all types of cancer; however, effective early-detection biomarkers are lacking for most types of cancers. DNA methylation has always been a major target of interest because DNA methylation usually occurs before other detectable genetic changes. While investigating the common features of cancer using a novel guide positioning sequencing for DNA methylation, a series of universal cancer only markers (UCOMs) have emerged as strong candidates for effective and accurate early detection of cancer. While the clinical value of current cancer biomarkers is diminished by low sensitivity and/or low specificity, the unique characteristics of UCOMs ensure clinically meaningful results. Validation of the clinical potential of UCOMs in lung, cervical, endometrial, and urothelial cancers further supports the application of UCOMs in multiple cancer types and various clinical scenarios. In fact, the applications of UCOMs are currently under active investigation with further evaluation in the early detection of cancer, auxiliary diagnosis, treatment efficacy, and recurrence monitoring. The molecular mechanisms by which UCOMs detect cancers are the next important topics to be investigated. The application of UCOMs in real-world scenarios also requires implementation and refinement.