Precision Clinical Medicine最新文献

Background: Intratumor heterogeneity is common in cancers, with different cell subtypes supporting each other to become more malignant. Nasopharyngeal carcinoma (NPC), a highly metastatic cancer, shows significant heterogeneity among its cells. This study investigates how NPC cell subtypes with varying metastatic potentials influence each other through exosome-transmitted molecules.

Methods: Exosomes were purified and characterized. MicroRNA expression was analyzed via sequencing and qRT-PCR. The effects of miR-30a-5p on migration, invasion, and metastasis were evaluated in vitro and in vivo. Its impact on desmoglein glycoprotein (DSG2) was assessed using dual-luciferase assays and Western blotting. Immunohistochemistry (IHC) and statistical models linked miR-30a-5p/DSG2 levels to patient prognosis.

Results: Different NPC cell subtypes transmit metastatic potential via exosomes. High-metastatic cells enhance the migration, invasion, and metastasis of low-metastatic cells through exosome-transmitted miR-30a-5p. Plasma levels of exosomal miR-30a-5p are reliable indicators of NPC prognosis. miR-30a-5p may promote metastasis by targeting DSG2 and modulating Wnt signaling. Plasma exosomal miR-30a-5p inversely correlates with DSG2 levels, predicting patient outcomes.

Conclusion: High-metastatic NPC cells can increase the metastatic potential of low-metastatic cells through exosome-transmitted miR-30a-5p, which is a valuable prognostic marker assessable via liquid biopsy.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract, and its pathogenesis is believed to be associated with an imbalance between commensal organisms and the intestinal immune system. This imbalance is significantly influenced by the intestinal microbiota and metabolites and plays a critical role in maintaining intestinal mucosal homeostasis. However, disturbances in the intestinal microbiota cause dysregulated immune responses and consequently induce intestinal inflammation. Recent studies have illustrated the roles of the intestinal microbiota in the pathogenesis of IBD and underscored the potential of precision diagnosis and therapy. This work summarises recent progress in this field and particularly focuses on the application of the intestinal microbiota and metabolites in the precision diagnosis, prognosis assessment, treatment effectiveness evaluation, and therapeutic management of IBD.

Type 2 diabetes mellitus (T2DM) is a metabolic disease that is characterized by chronic hyperglycaemia. MicroRNAs (miRNAs) are single-stranded, small non-coding RNAs that play important roles in post-transcriptional gene regulation. They are negative regulators of their target messenger RNAs (mRNAs), in which they bind either to inhibit mRNA translation, or to induce mRNA decay. Similar to proteins, miRNAs exist in different isoforms (isomiRs). miRNAs and isomiRs are selectively loaded into small extracellular vesicles, such as the exosomes, to protect them from RNase degradation. In T2DM, exosomal miRNAs produced by different cell types are transported among the primary sites of insulin action. These interorgan crosstalk regulate various T2DM-associated pathways such as adipocyte inflammation, insulin signalling, and β cells dysfunction among many others. In this review, we first focus on the mechanism of exosome biogenesis, followed by miRNA biogenesis and isomiR formation. Next, we discuss the roles of exosomal miRNAs and isomiRs in the development of T2DM and provide evidence from clinical studies to support their potential roles as T2DM biomarkers. Lastly, we highlight the use of exosomal miRNAs and isomiRs in personalized medicine, as well as addressing the current challenges and future opportunities in this field. This review summarizes how research on exosomal miRNAs and isomiRs has developed from the very basic to clinical applications, with the goal of advancing towards the era of personalized medicine.

Objective: This study aimed to find out whether phenotypic age could mediate the protective effects of a healthy lifestyle on mortality.

Methods: We included adult participants with available data for individual phenotypic age (PhenoAge) and Life's Essential 8 (LE8) scores from the National Health and Nutrition Examination Survey 2005-2010 (three cycles) and linked mortality records until 31 December 2019. Adjusted hazard ratios (HR) were estimated to evaluate the associations of PhenoAge and LE8 scores with all-cause and cardiovascular mortality risk. Mediation analyses were performed to estimate the proportional contribution of PhenoAge to the effect of LE8 on mortality risks.

Results: A 1-year increment in PhenoAge was associated with a higher risk of all-cause (HR = 1.04 [95% confidence interval, 1.04-1.05]) and cardiovascular (HR = 1.04 [95% confidence interval, 1.04-1.05]) mortality, independent of chronological age, demographic characteristics, and disease history. High level of LE8 (score: 80-100) was associated with a 3.30-year younger PhenoAge. PhenoAge was estimated to mediate 36 and 22% of the effect of LE8 on all-cause and cardiovascular mortality, respectively (all P < 0.001). As for single-metric scores of LE8, PhenoAge mediated 30%, 11%, 9%, and 7% of the effects of the healthy diet, smoking status, blood pressure, and physical activity on all-cause mortality risk, respectively (all P < 0.05).

Conclusion: Adherence to LE8 recommendations slows phenotypic aging. PhenoAge could mediate the effect of LE8 on mortality risk.

Background: The prognosis of breast cancer is often unfavorable, emphasizing the need for early metastasis risk detection and accurate treatment predictions. This study aimed to develop a novel multi-modal deep learning model using preoperative data to predict disease-free survival (DFS).

Methods: We retrospectively collected pathology imaging, molecular and clinical data from The Cancer Genome Atlas and one independent institution in China. We developed a novel Deep Learning Clinical Medicine Based Pathological Gene Multi-modal (DeepClinMed-PGM) model for DFS prediction, integrating clinicopathological data with molecular insights. The patients included the training cohort (n = 741), internal validation cohort (n = 184), and external testing cohort (n = 95).

Result: Integrating multi-modal data into the DeepClinMed-PGM model significantly improved area under the receiver operating characteristic curve (AUC) values. In the training cohort, AUC values for 1-, 3-, and 5-year DFS predictions increased to 0.979, 0.957, and 0.871, while in the external testing cohort, the values reached 0.851, 0.878, and 0.938 for 1-, 2-, and 3-year DFS predictions, respectively. The DeepClinMed-PGM's robust discriminative capabilities were consistently evident across various cohorts, including the training cohort [hazard ratio (HR) 0.027, 95% confidence interval (CI) 0.0016-0.046, P < 0.0001], the internal validation cohort (HR 0.117, 95% CI 0.041-0.334, P < 0.0001), and the external cohort (HR 0.061, 95% CI 0.017-0.218, P < 0.0001). Additionally, the DeepClinMed-PGM model demonstrated C-index values of 0.925, 0.823, and 0.864 within the three cohorts, respectively.

Conclusion: This study introduces an approach to breast cancer prognosis, integrating imaging and molecular and clinical data for enhanced predictive accuracy, offering promise for personalized treatment strategies.

Background: The Inspiration4 (I4) mission, the first all-civilian orbital flight mission, investigated the physiological effects of short-duration spaceflight through a multi-omic approach. Despite advances, there remains much to learn about human adaptation to spaceflight's unique challenges, including microgravity, immune system perturbations, and radiation exposure.

Methods: To provide a detailed genetics analysis of the mission, we collected dried blood spots pre-, during, and post-flight for DNA extraction. Telomere length was measured by quantitative PCR, while whole genome and cfDNA sequencing provided insight into genomic stability and immune adaptations. A robust bioinformatic pipeline was used for data analysis, including variant calling to assess mutational burden.

Result: Telomere elongation occurred during spaceflight and shortened after return to Earth. Cell-free DNA analysis revealed increased immune cell signatures post-flight. No significant clonal hematopoiesis of indeterminate potential (CHIP) or whole-genome instability was observed. The long-term gene expression changes across immune cells suggested cellular adaptations to the space environment persisting months post-flight.

Conclusion: Our findings provide valuable insights into the physiological consequences of short-duration spaceflight, with telomere dynamics and immune cell gene expression adapting to spaceflight and persisting after return to Earth. CHIP sequencing data will serve as a reference point for studying the early development of CHIP in astronauts, an understudied phenomenon as previous studies have focused on career astronauts. This study will serve as a reference point for future commercial and non-commercial spaceflight, low Earth orbit (LEO) missions, and deep-space exploration.