Precision Clinical Medicine最新文献

Objectives: Inflammatory bowel disease is driven by dysregulated CD4⁺ T cell responses to the intestinal microbiota. While T cells can exacerbate inflammation by producing proinflammatory cytokines, they also produce anti-inflammatory mediators, such as interleukin 10 (IL-10) and IL-22. However, the metabolic programs that regulate IL-10 and IL-22 production remain incompletely defined.

Methods: We used CBir1 transgenic mice and in vitro Th1 polarization assays to investigate how metabolic pathways regulate T cell production of IL-10 and IL-22. A panel of metabolic inhibitors was tested for their effects on cytokine expression. Transcriptional mechanisms were assessed using bulk RNA sequencing, qPCR, Enzyme-linked immunosorbent (ELISA), and CRISPR-Cas9-mediated gene editing. Functional relevance was validated using Citrobacter rodentium infection and T cell suppression assays in vivo and in vitro.

Results: Among tested metabolic inhibitors, dichloroacetate (DCA) significantly enhanced IL-10 and IL-22 production by CD4⁺ T cells. DCA increased maximal oxygen consumption and decreased lactate secretion in T cells. Mechanistically, DCA upregulated aryl hydrocarbon receptor (Ahr) and downregulated Bhlhe40, without affecting Prdm1. Pharmacologic inhibition of Ahr suppressed DCA-induced IL-22, but not IL-10, while Bhlhe40 knockout enhanced IL-10 production, identifying distinct transcriptional regulators for each cytokine. Functionally, DCA-treated Th1 cells suppressed naïve T cell proliferation via IL-10. In an in vivo experiment, DCA treatment protected mice from C. rodentium-induced colitis.

Conclusions: Our findings demonstrate that DCA enhances IL-22 and IL-10 production in Th1 cells through Ahr and Bhlhe40, respectively. These results identify a novel metabolic mechanism by which DCA promotes mucosal immune regulation and highlight its potential as a therapeutic strategy for inflammatory bowel disease.

Background: Penile squamous cell carcinoma (PSCC) is a rare yet potentially lethal malignancy, often resulting in devastating disfigurement, with a 5-year survival rate of only ∼50%. Human papillomavirus (HPV) infection is implicated in approximately half of PSCC cases and is associated with improved clinical outcomes; however, the underlying mechanisms remain poorly understood.

Methods: To elucidate HPV-associated differences in the tumor microenvironment, we performed single-cell RNA sequencing on tumors from 11 treatment-naïve PSCC patients, analyzing a total of 52 980 single cells. Unsupervised clustering identified 49 distinct cellular clusters across immune and stromal compartments.

Results: HPV-positive tumors exhibited an increased abundance of mast cells and a reduction in the proliferative macrophages subpopulation compared to HPV-negative tumors. Notably, CD8⁺ T cells in HPV-positive PSCC expressed lower levels of immune checkpoint molecules, suggesting a less exhausted immune state. Conversely, TIGIT and its ligands were significantly enriched in HPV-negative tumors, potentially fostering an immunosuppressive niche.

Conclusion: Collectively, our study delineates the single-cell landscape of PSCC and highlights distinct tumor microenvironment remodeling associated with HPV status, suggesting that the reduced immunosuppression in HPV-positive tumors may underlie their more favorable prognosis.

Hepatocellular carcinoma (HCC) is the predominant malignant liver tumor, characterized by high morbidity, mortality, and rapid progression, and it ranks among the leading causes of cancer-related fatalities worldwide. Its treatment is facing the severe challenge of resistance to targeted drugs and immunotherapy. Bile acids (BAs) are products of cholesterol metabolism, that not only regulate lipid digestion and absorption, but also influence the development of HCC by modulating inflammation and metabolism. Dysregulation of BA metabolism is closely linked to resistance against targeted therapies and immunotherapies. BAs reduce the efficacy of targeted drugs by influencing enzymes involved in drug metabolism and drug efflux transporters, moreover, BAs also lead to immunotherapeutic resistance by regulating the formation of the immunosuppressive tumor microenvironment. Therefore, regulating BA metabolism has the potential to overcome drug resistance of targeted therapy and immunotherapy, which could be a promising treatment strategy. This review not only summarizes the roles of BA metabolism in HCC development and drug resistance, but also further explores the rationality and necessity of targeting BAs to enhance the survival of HCC patients.

Cholangiocarcinoma (CCA) is a biologically diverse and highly aggressive cancer that arises from the biliary epithelium. It is typically divided into intrahepatic, perihilar, and distal types, each with distinct clinical behavior, genetic alterations, and therapeutic responses. Worldwide, the global incidence of CCA has risen steadily, accounting for nearly 15% of liver cancers and ∼3% of all gastrointestinal malignancies. CCA often presents at an advanced stage due to its silent onset and shows poor responsiveness to conventional chemotherapy, resulting in high mortality, accounting for ∼2% of cancer-related deaths worldwide. Risk factors include parasitic infections like liver flukes and chronic biliary diseases such as cholelithiasis and primary sclerosing cholangitis, although most cases have unknown origins. While early-stage patients may benefit from surgical resection or liver transplantation, these options are often not viable in advanced disease due to high relapse rates. In cases of unresectable or metastatic CCA, treatment remains difficult due to resistance and a lack of effective targeted therapies. This review systematically integrates the genomic, epigenetic, and signaling network mechanisms underlying CCA with their translational implications, providing a critical synthesis of the rapidly evolving field of targeted therapies, including recently approved Food and Drug Administration treatments and emerging novel agents. We specifically emphasize the key mechanisms of therapeutic resistance and corresponding strategies to overcome them, present an updated evaluation of vulnerabilities across distinct molecular subgroups, and explore the major challenges and future trajectories for advancing biomarker-driven precision medicine in CCA, thereby offering a forward-looking and clinically relevant perspective.

Background: No studies have explored the genetic differences between the Chinese and other ethnic hypertrophic cardiomyopathy (HCM) populations.

Methods: This cross-sectional study included Chinese patients (n = 593) with HCM and controls (n = 491) who underwent whole-exome sequencing. Rare variants in 16 validated HCM genes were assessed and compared with a United Kingdom HCM cohort (n = 1 232) and controls (n = 344 745).

Results: Chinese HCM patients have a higher proportion of rare variants (52.8% vs 13.6%, P < 0.001) but have a similar proportion of pathogenic (P) or likely pathogenic (LP) variants compared to the UK cohort. In addition, the Chinese cohort had additional associations with the combined thin filament genes (P = 1.29E-9) and myosin light chain genes (P = 4.43E-3). The United Kingdom cohort was significantly associated with MYBPC3 non-truncating variants (P = 2.99E-7). By classifying variants using the tool genebe, the variants of uncertain significance were minimized to 46.8% compared to other tools (63.3% by Intervar; 91.3% by CardioClassifier). Furthermore, we report that c.3624del in MYBPC3 and c.300C > G in TNNT2 account for 2.9% and 1.5% of all Chinese HCM cases, respectively.

Conclusion: Our findings suggested that patients of Chinese ancestry with HCM have a higher proportion of rare variants but are less likely to be classified as P/LP variants in HCM genes than those of European origin. The variants of c.3624del in MYBPC3 and c.300C > G in TNNT2 were specific to Chinese individuals and provide important insights into the ethnic differences of HCM genetic architecture.

Protein glycosylation is a critical post-translational modification that influences protein folding, localization, stability, and functional interactions by attaching glycans to specific sites. This process is crucial for biological functions of glycoproteins, and aberrant glycosylation can lead to genetic disorders, immune system issues, and multi-organ pathologies. Recent advancements in glycoproteomic technologies have made the study of protein glycosylation a key focus for understanding the pathogenesis of kidney diseases. This review provides a comprehensive overview of protein glycosylation mechanisms, its biological roles, molecular pathways, and significant functions in renal physiology and pathology. It specifically highlights the dynamic changes and regulatory networks associated with aberrant glycosylation in kidney diseases such as immunoglobulin A nephropathy, diabetic kidney disease, autosomal dominant polycystic kidney disease, renal cell carcinoma, and acute kidney injury. It also evaluates the clinical applications of related technologies and biomarkers. Additionally, it discusses the challenges in developing glycosylation-targeted therapeutic strategies. Future research should focus on clarifying cell-specific glycosylation regulatory networks in the kidney, integrating glycobiology with multi-omics approaches, and improving precision diagnostics and treatment for kidney diseases.

Background: Single-cell RNA-sequencing (scRNA-seq) has emerged as a powerful tool for cancer research, enabling in-depth characterization of tumor heterogeneity at the single-cell level. Recently, several scRNA-seq copy number variation (scCNV) inference methods have been developed, expanding the application of scRNA-seq to study genetic heterogeneity in cancer using transcriptomic data. However, the fidelity of these methods has not been investigated systematically.

Methods: We benchmarked five commonly used scCNV inference methods: HoneyBADGER, CopyKAT, CaSpER, inferCNV, and sciCNV. We evaluated their performance across four different scRNA-seq platforms using data from our previous multicenter study. We evaluated scCNV performance further using scRNA-seq datasets derived from mixed samples consisting of five human lung adenocarcinoma cell lines and also sequenced tissues from a small cell lung cancer patient and used the data to validate our findings with a clinical scRNA-seq dataset.

Results: We found that the sensitivity and specificity of the five scCNV inference methods varied, depending on the selection of reference data, sequencing depth, and read length. CopyKAT and CaSpER outperformed other methods overall, while inferCNV, sciCNV, and CopyKAT performed better than other methods in subclone identification. We found that batch effects significantly affected the performance of subclone identification in mixed datasets in most methods we tested.

Conclusion: Our benchmarking study revealed the strengths and weaknesses of each of these scCNV inference methods and provided guidance for selecting the optimal CNV inference method using scRNA-seq data.

The gut virome, an essential component of the intestinal microbiome, constitutes ∼0.1% of the total microbial biomass but contains a far greater number of particles than bacteria, with phages making up 90%-95% of this virome. This review systematically examines the developmental patterns of the gut virome, focusing on factors influencing its composition, including diet, environment, host genetics, and immunity. Additionally, it explores the gut virome's associations with various diseases, its interactions with gut bacteria and the immune system, and its emerging clinical applications.

Objectives: To investigate the risk factors in patients with drug-resistant tuberculosis (DR-TB) and clinical characteristics related to unfavorable anti-TB treatment outcomes.

Methods: A total of 961 pulmonary tuberculosis (TB) patients were included at West China Hospital of Sichuan University from January 2008 to November 2023. We analyzed the differences of clinical characteristics between DR-TB and drug-sensitive tuberculosis (DS-TB), and then compared these features in DR-TB patients with different outcomes. Multivariable logistic regression models were employed to quantify risk factors associated with DR-TB and adverse treatment outcomes.

Results: Among 961 pulmonary TB patients, a history of anti-TB treatment [odds ratio (OR), 3.289; 95% confidence interval (CI), 2.359-4.604] and CT-scan cavities (OR, 1.512; 95% CI, 1.052-2.168) increased DR-TB risk. A total of 214 DR-TB patients were followed for a median of 24.5 months. Among them, 116/214 (54.2%) patients achieved favorable outcomes. Prior anti-TB treatment (OR, 1.927; 95% CI, 1.033-3.640), multidrug-resistant tuberculosis (MDR-TB) (OR, 2.558; 95% CI, 1.272-5.252), positive sputum bacteriology (OR, 2.116; 95% CI, 1.100-4.134), and pleural effusion (OR, 2.097; 95% CI, 1.093-4.082) were associated with unfavorable outcomes, while isoniazid-resistant TB patients showed better outcomes (OR, 0.401; 95% CI, 0.181-0.853). The clinical model for unfavorable outcome prediction of DR-TB achieved an area under the curve (AUC) of 0.754 (95% CI, 0.690-0.818).

Conclusions: Treatment history of anti-TB not only increases the risk of the emergence of DR-TB, but also potentially leads to treatment failure during re-treatment in DR-TB patients. Drug resistance subtypes, radiological characteristics, and the results of sputum smear or culture may affect the treatment outcome of DR-TB.