Individual variability in drug response (IVDR) can be a major cause of adverse drug reactions (ADRs) and prolonged therapy, resulting in a substantial health and economic burden. Despite extensive research in pharmacogenomics regarding the impact of individual genetic background on pharmacokinetics (PK) and pharmacodynamics (PD), genetic diversity explains only a limited proportion of IVDR. The role of gut microbiota, also known as the second genome, and its metabolites in modulating therapeutic outcomes in human diseases have been highlighted by recent studies. Consequently, the burgeoning field of pharmacomicrobiomics aims to explore the correlation between microbiota variation and IVDR or ADRs. This review presents an up-to-date overview of the intricate interactions between gut microbiota and classical therapeutic agents for human systemic diseases, including cancer, cardiovascular diseases (CVDs), endocrine diseases, and others. We summarise how microbiota, directly and indirectly, modify the absorption, distribution, metabolism, and excretion (ADME) of drugs. Conversely, drugs can also modulate the composition and function of gut microbiota, leading to changes in microbial metabolism and immune response. We also discuss the practical challenges, strategies, and opportunities in this field, emphasizing the critical need to develop an innovative approach to multi-omics, integrate various data types, including human and microbiota genomic data, as well as translate lab data into clinical practice. To sum up, pharmacomicrobiomics represents a promising avenue to address IVDR and improve patient outcomes, and further research in this field is imperative to unlock its full potential for precision medicine.

Psoriasis affects the health of myriad populations around the world. The pathogenesis is multifactorial, and the exact driving factor remains unclear. This condition arises from the interaction between hyperproliferative keratinocytes and infiltrating immune cells, with poor prognosis and high recurrence. Better clinical treatments remain to be explored. There is much evidence that alterations in the skin and intestinal microbiome play an important role in the pathogenesis of psoriasis, and restoration of the microbiome is a promising preventive and therapeutic strategy for psoriasis. Herein, we have reviewed recent studies on the psoriasis-related microbiome in an attempt to confidently identify the “core” microbiome of psoriasis patients, understand the role of microbiome in the pathogenesis of psoriasis, and explore new therapeutic strategies for psoriasis through microbial intervention.

Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction of tacrolimus stable dose (TSD) in a large Chinese cohort. A total of 1,045 renal transplant patients were recruited, 80% of which were randomly selected as the “derivation cohort” to develop dose-prediction algorithm, while the remaining 20% constituted the “validation cohort” to test the final selected algorithm. MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied and their performances were compared in this work. Among all the machine learning models, RT performed best in both derivation [0.71 (0.67–0.76)] and validation cohorts [0.73 (0.63–0.82)]. In addition, the ideal rate of RT was 4% higher than that of MLR. To our knowledge, this is the first study to use machine learning models to predict TSD, which will further facilitate personalized medicine in tacrolimus administration in the future.

Radioresistance is the main obstacle in the clinical management of nasopharyngeal carcinoma (NPC). linc00312 is deregulated in a number of human cancers, including NPC. However, the detailed functions and underlying mechanisms of linc00312 in regulating radiosensitivity of NPC remains unknown. In this study, cox regression analysis was used to assess the association between linc00312 and NPC patients’ survival after radiotherapy. Our results reveal that linc00312 is significantly down-regulated in NPC tissues and patients with higher expression of linc00312 are significantly associated with longer overall survival and better short-term radiotherapy efficacy. Overexpression of linc00312 could increase the sensitivity of NPC cells to ionizing radiation, as indicated by clonogenic survival assay, comet assay, and flow cytometry. Mechanistically, RNA pull down and RNA immunoprecipitation were performed to investigate the binding proteins of linc00312. linc00312 directly binds to DNA-PKcs, hinders the recruitment of DNA-PKcs to Ku80, and inhibits phosphorylation of AKT–DNA–PKcs axis, therefore inhibiting the DNA damage signal sensation and transduction in the NHEJ repair pathway. In addition, linc00312 impairs DNA repair and cell cycle control by suppressing MRN–ATM–CHK2 signal and ATR–CHK1 signal. In summary, we identified DNA-PKcs as the binding protein of linc00312 and revealed a novel mechanism of linc00312 in the DNA damage response, providing evidence for a potential therapeutic strategy in NPC.

The gut microbiota crucially regulates the efficacy of immune checkpoint inhibitor (ICI) based immunotherapy, but the underlying mechanisms remain unclear at the single-cell resolution. Using single-cell RNA sequencing and subsequent validations, we investigate gut microbiota-ICI synergy by profiling the tumor microenvironment (TME) and elucidating critical cellular interactions in mouse models. Our findings reveal that intact gut microbiota combined with ICIs may synergistically increase the proportions of CD8 ⁺, CD4 ⁺, and γδ T cells, reduce glycolysis metabolism, and reverse exhausted CD8 ⁺ T cells into memory/effector CD8 ⁺ T cells, enhancing antitumor response. This synergistic effect also induces macrophage reprogramming from M2 protumor Spp1 ⁺ tumor-associated macrophages (TAMs) to Cd74 ⁺ TAMs, which act as antigen-presenting cells (APCs). These macrophage subtypes show a negative correlation within tumors, particularly during fecal microbiota transplantation. Depleting Spp1 ⁺ TAMs in Spp1 conditional knockout mice boosts ICI efficacy and T cell infiltration, regardless of gut microbiota status, suggesting a potential upstream role of the gut microbiota and highlighting the crucial negative impact of Spp1 ⁺ TAMs during macrophage reprogramming on immunotherapy outcomes. Mechanistically, we propose a γδ T cell-APC-CD8 ⁺ T cell axis, where gut microbiota and ICIs enhance Cd40lg expression on γδ T cells, activating Cd40 overexpressing APCs (e.g., Cd74 ⁺ TAMs) through CD40-CD40L-related NF-κB signaling and boosting CD8 ⁺ T cell responses via CD86-CD28 interactions. These findings highlight the potential importance of γδ T cells and SPP1-related macrophage reprogramming in activating CD8 ⁺ T cells, as well as the synergistic effect of gut microbiota and ICIs in immunotherapy through modulating the TME.

Bile acids (BAs) exert a profound influence on the body’s pathophysiology by intricately shaping the composition of gut bacteria. However, the complex interplay between BAs and gut microbiota has impeded a systematic exploration of their impact on intestinal bacteria. Initially, we investigated the effects of 21 BAs on the growth of 65 gut bacterial strains in vitro. Subsequently, we examined the impact of BAs on the overall composition of intestinal bacteria, both in vivo and in vitro. The results unveiled distinct effects of various BAs on different intestinal strains and their diverse impacts on the composition of gut bacteria. Mechanistically, the inhibition of intestinal strains by BAs occurs through the accumulation of these acids within the strains. The intracellular accumulation of deoxycholic acid (DCA) significantly influenced the growth of intestinal bacteria by impacting ribosome transcription and amino-acid metabolism. The metabolomic analysis underscores the pronounced impact of DCA on amino-acid profiles in both in vivo and in vitro settings. This study not only elucidates the effects of BAs on a diverse range of bacterial strains and their role in shaping the gut microbiota but also reveals underlying mechanisms essential for understanding and maintaining a healthy gut microbiota.