Research progress on the effect of gut and tumor microbiota on antitumor efficacy and adverse effects of chemotherapy drugs

The role of microbial metabolites in endocrine tumorigenesis: From the mechanistic insights to potential therapeutic biomarkers

Microbial metabolites have been indicated to communicate with the host's endocrine system, regulating hormone production, immune-endocrine communications, and interactions along the gut-brain axis, eventually affecting the occurrence of endocrine cancer. Furthermore, microbiota metabolites such as short-chain fatty acids (SCFAs) have been found to affect the tumor microenvironment and boost immunity against tumors. SCFAs, including butyrate and acetate, have been demonstrated to exert anti-proliferative and anti-protective activity on pancreatic cancer cells. The employing of microbial metabolic products in conjunction with radiation and chemotherapy has shown promising outcomes in terms of reducing treatment side effects and boosting effectiveness. Certain metabolites, such as valerate and butyrate, have been made known to improve the efficiency of CAR T-cell treatment, whilst others, such as indole-derived tryptophan metabolites, have been shown to inhibit tumor immunity. This review explores the intricate interplay between microbial metabolites and endocrine tumorigenesis, spanning mechanistic insights to the discovery of potential therapeutic biomarkers.

Biochemical implications of robotic surgery: a new frontier in the operating room

Robotic surgery represents a milestone in surgical procedures, offering advantages such as less invasive methods, elimination of tremors, scaled motion, and 3D visualization. This in-depth analysis explores the complex biochemical effects of robotic methods. The use of pneumoperitoneum and steep Trendelenburg positioning can decrease pulmonary compliance and splanchnic perfusion while increasing hypercarbia. However, robotic surgery reduces surgical stress and inflammation by minimizing tissue trauma. This contributes to faster recovery but may limit immune function. Robotic procedures also limit ischemia-reperfusion injury and oxidative damage compared to open surgery. They also help preserve native antioxidant defenses and coagulation. In a clinical setting, robotic procedures reduce blood loss, pain, complications, and length of stay compared to traditional procedures. However, risks remain, including device failure, the need for conversion to open surgery and increased costs. On the oncology side, there is still debate about margins, recurrence, and long-term survival. The advent of advanced technologies, such as intraoperative biosensors, localized drug delivery systems, and the incorporation of artificial intelligence, may further improve the efficiency of robotic surgery. However, ethical dilemmas regarding patient consent, privacy, access, and regulation of this disruptive innovation need to be addressed. Overall, this review sheds light on the complex biochemical implications of robotic surgery and highlights areas that require additional mechanistic investigation. It presents a comprehensive approach to responsibly maximize the potential of robotic surgery to improve patient outcomes, integrating technical skill with careful consideration of physiological and ethical issues.

Multi-scale topology and position feature learning and relationship-aware graph reasoning for prediction of drug-related microbes

MOTIVATION

The human microbiome may impact the effectiveness of drugs by modulating their activities and toxicities. Predicting candidate microbes for drugs can facilitate the exploration of the therapeutic effects of drugs. Most recent methods concentrate on constructing of the prediction models based on graph reasoning. They fail to sufficiently exploit the topology and position information, the heterogeneity of multiple types of nodes and connections, and the long-distance correlations among nodes in microbe-drug heterogeneous graph.

RESULTS

We propose a new microbe-drug association prediction model, NGMDA, to encode the position and topological features of microbe (drug) nodes, and fuse the different types of features from neighbors and the whole heterogeneous graph. First, we formulate the position and topology features of microbe (drug) nodes by t-step random walks, and the features reveal the topological neighborhoods at multiple scales and the position of each node. Second, as the features of nodes are high-dimensional and sparse, we designed an embedding enhancement strategy based on supervised fully connected autoencoders to form the embeddings with representative features and the more discriminative node distributions. Third, we propose an adaptive neighbor feature fusion module, which fuses features of neighbors by the constructed position- and topology-sensitive heterogeneous graph neural networks. A novel self-attention mechanism is developed to estimate the importance of the position and topology of each neighbor to a target node. Finally, a heterogeneous graph feature fusion module is constructed to learn the long-distance correlations among the nodes in the whole heterogeneous graph by a relationship-aware graph transformer. Relationship-aware graph transformer contains the strategy for encoding the connection relationship types among the nodes, which is helpful for integrating the diverse semantics of these connections. The extensive comparison experimental results demonstrate NGMDA's superior performance over five state-of-the-art prediction methods. The ablation experiment shows the contributions of the multi-scale topology and position feature learning, the embedding enhancement strategy, the neighbor feature fusion, and the heterogeneous graph feature fusion. Case studies over three drugs further indicate that NGMDA has ability in discovering the potential drug-related microbes.

AVAILABILITY AND IMPLEMENTATION

Source codes and Supplementary Material are available at https://github.com/pingxuan-hlju/NGMDA.

Microbial Therapy and Breast Cancer Management: Exploring Mechanisms, Clinical Efficacy, and Integration within the One Health Approach

This comprehensive review elucidates the profound relationship between the human microbiome and breast cancer management. Recent findings highlight the significance of microbial alterations in tissue, such as the gut and the breast, and their role in influencing the breast cancer risk, development, progression, and treatment outcomes. We delve into how the gut microbiome can modulate systemic inflammatory responses and estrogen levels, thereby impacting cancer initiation and therapeutic drug efficacy. Furthermore, we explore the unique microbial diversity within breast tissue, indicating potential imbalances brought about by cancer and highlighting specific microbes as promising therapeutic targets. Emphasizing a holistic One Health approach, this review underscores the importance of integrating insights from human, animal, and environmental health to gain a deeper understanding of the complex microbe-cancer interplay. As the field advances, the strategic manipulation of the microbiome and its metabolites presents innovative prospects for the enhancement of cancer diagnostics and therapeutics. However, rigorous clinical trials remain essential to confirm the potential of microbiota-based interventions in breast cancer management.

Exploring the Involvement of Gut Microbiota in Cancer Therapy-Induced Cardiotoxicity

Trillions of microbes in the human intestinal tract, including bacteria, viruses, fungi, and protozoa, are collectively referred to as the gut microbiome. Recent technological developments have led to a significant increase in our understanding of the human microbiome. It has been discovered that the microbiome affects both health and the progression of diseases, including cancer and heart disease. Several studies have indicated that the gut microbiota may serve as a potential target in cancer therapy modulation, by enhancing the effectiveness of chemotherapy and/or immunotherapy. Moreover, altered microbiome composition has been linked to the long-term effects of cancer therapy; for example, the deleterious effects of chemotherapy on microbial diversity can, in turn, lead to acute dysbiosis and serious gastrointestinal toxicity. Specifically, the relationship between the microbiome and cardiac diseases in cancer patients following therapy is poorly understood. In this article, we provide a summary of the role of the microbiome in cancer treatment, while also speculating on a potential connection between treatment-related microbial changes and cardiotoxicity. Through a brief review of the literature, we further explore which bacterial families or genera were differentially affected in cancer treatment and cardiac disease. A deeper understanding of the link between the gut microbiome and cardiotoxicity caused by cancer treatment may help lower the risk of this critical and potentially fatal side effect.