Precision Clinical Medicine最新文献

Introduction: The Kasabach-Merritt phenomenon (KMP) is a severe complication of kaposiform hemangioendothelioma (KHE). The risk factors for KMP need further investigation.

Methods: The medical records of patients with KHE were reviewed. Univariate and multivariate logistic regression models were used for the risk factors for KMP, and the area under the receiver operator characteristic (ROC) curve was used to assess the predictive power of risk factors.

Results: A total of 338 patients with KHE were enrolled. The incidence of KMP was 45.9%. Age of onset (P < 0.001, odds ratio [OR] 0.939; 95% confidence interval [CI] 0.914-0.966), lesion size (P < 0.001, OR 1.944; 95% CI 1.646-2.296), mixed type (P = 0.030, OR 2.428; 95% CI 1.092-5.397), deep type (P = 0.010, OR 4.006; 95% CI 1.389-11.556), and mediastinal or retroperitoneal lesion location (P = 0.019, OR 11.864; 95% CI 1.497-94.003) were correlated with KMP occurrence through multivariate logistic regression. ROC curve analysis revealed that the optimal cutoffs were 4.75 months for the age of onset (P < 0.001, OR 7.206, 95% CI 4.073-12.749) and a lesion diameter of 5.35 cm (P < 0.001, OR 11.817, 95% CI 7.084-19.714). Bounded by a lesion size of 5.35 cm, we found significant differences in tumor morphology, age of onset, treatments, and hematological parameters. Using an onset age of 4.75 months as a cutoff, we found significant differences in tumor morphology, lesion size, hematological parameters, and prognosis.

Conclusion: For KHE patients with an onset age <4.75 months and/or lesion diameter >5.35 cm, clinicians should be wary of the occurrence of KMP. Active management is recommended to improve the prognosis.

The desmoplastic and complex tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC) has presented tremendous challenges for developing effective therapeutic strategies. Strategies targeting tumor stroma, albeit with great potential, have met with limited success due to the lack of knowledge on the molecular dynamics within the tumor microenvironment (TME). In pursuit of a better understanding of the influence of miRNAs on TME reprogramming and to explore circulating miRNAs as diagnostic and prognostic biomarkers for PDAC, using RNA-seq, miRNA-seq, and single-cell RNA-seq (scRNA-seq), we investigated the dysregulated signaling pathways in PDAC TME modulated by miRNAs from plasma and tumor tissue. Our bulk RNA-seq in PDAC tumor tissue identified 1445 significantly differentially expressed genes with extracellular matrix and structure organization as the top enriched pathways. Our miRNA-seq identified 322 and 49 abnormally expressed miRNAs in PDAC patient plasma and tumor tissue, respectively. We found many of the TME signaling pathways were targeted by those dysregulated miRNAs in PDAC plasma. Combined with scRNA-seq from patient PDAC tumor, our results revealed that these dysregulated miRNAs were closely associated with extracellular matrix (ECM) remodeling, cell-ECM communication, epithelial-mesenchymal transition, as well as immunosuppression orchestrated by different cellular components of TME. The findings of this study could assist the development of miRNA-based stromal targeting biomarkers or therapy for PDAC patients.

Traditional stepwise approach usually adjusts the treatment regimen based on changes in asthma symptoms and severity to achieve good asthma control. However, due to the generalized heterogeneity and complexity of asthma, its therapeutic efficacy in difficult-to-treat asthma is limited. Recently, a precision medicine approach based on the identification and intervention of treatable traits of chronic airway disease has been proposed and appears to be of greater benefit to asthmatics. We reported a 71-year-old male with uncontrolled asthma and multiple exacerbations over the past year. He complained of persistent dyspnea despite high-dose of inhaled corticosteroids plus other controllers. Does this patient have some potential treatable traits contributing to difficult-to-treat asthma? Through a multidimensional assessment of three domains including pulmonary, extrapulmonary, and behavioral/risk factors, 15 treatable traits were identified in the patient, mainly including airflow limitation, eosinophilic airway inflammation, small airway dysfunction, exacerbation prone, dilated cardiomyopathy, diabetes mellitus, inhaler device polypharmacy, smoking, and the absence of an asthma action plan. After targeted treatment for these treatable traits, the patient experienced significant improvement in dyspnea and he could maintain good asthma control with low-dose inhaled corticosteroids and long-acting β₂-agonist. This study shows that, in response to the limitation of a stepwise approach to therapy, treatable traits is a new strategy where patients are individually assessed for a specified set of treatable problems, and an individualized treatment program is developed and implemented based on this multidimensional assessment, especially for difficult-to-treat asthma.

Exploring useful prognostic markers and developing a robust prognostic model for patients with prostate cancer are crucial for clinical practice. We applied a deep learning algorithm to construct a prognostic model and proposed the deep learning-based ferroptosis score (DLF_score) for the prediction of prognosis and potential chemotherapy sensitivity in prostate cancer. Based on this prognostic model, there was a statistically significant difference in the disease-free survival probability between patients with high and low DLF_score in the The Cancer Genome Atlas (TCGA) cohort (P < 0.0001). In the validation cohort GSE116918, we also observed a consistent conclusion with the training set (P = 0.02). Additionally, functional enrichment analysis showed that DNA repair, RNA splicing signaling, organelle assembly, and regulation of centrosome cycle pathways might regulate prostate cancer through ferroptosis. Meanwhile, the prognostic model we constructed also had application value in predicting drug sensitivity. We predicted some potential drugs for the treatment of prostate cancer through AutoDock, which could potentially be used for prostate cancer treatment.

Precision cardiology aims to implement personalized health care and precise medical decisions based on the specific characteristics of individuals. Metabolic remodeling plays a causal role in the pathogenesis of heart failure (HF). Changes in metabolic pathways such as substrate preference, high-energy phosphate metabolism and amino acid metabolism, are involved in pathological structural remodeling and functional impairment. These metabolic alterations are usually not restricted in the cardiac tissue, but also manifest in circulation. In clinical practice, blood sample is routinely used for HF screening. Metabolomics is an emerging omics technology that provides an efficient way to acquire dynamic metabolic profiles in circulation. An increasing number of metabolic biomarkers have been implicated in disease progression, making it possible to fight HF in a more effective and precise way. This review summarizes the modern analytical techniques in metabolomics as well as emerging circulating metabolites during the pathogenesis of HF, aiming to provide new insights into the prevention, diagnosis and treatment of HF in the era of precision medicine.

A commentary on "Multi-omics single-cell data integration and regulatory inference with graph-linked embedding".

To investigate the role of patient-derived organoid (PDO) model in the precision medicine of advanced clear cell renal cell carcinoma (ccRCC), we retrospectively analyzed the clinical data of seven cases of ccRCC diagnosed by operation and pathology in Renji Hospital from September 2021 to September 2022. The seven patients were diagnosed with advanced ccRCC with or without remote metastasis. Cytoreductive and radical nephrectomy was performed respectively. To predict the response to immunotherapy and provide personalized medicine recommendation, a PDO model based on air-liquid interface system was established from the surgical resected tumor and subsequent drug screening was performed. Hematoxylin and eosin (H&E) staining and immunohistochemistry revealed that the PDO recapitulated the histological feature of parent tumor. Immunofluorescence staining identified that CD3⁺ T cells, SMA⁺ cancer associated fibroblasts, and CD31⁺ endothelial cells were preserved in PDO models. Fluorescence activated cell sorter (FACS) revealed an evidently increased ratio of CD8⁺/CD4⁺ T cells and apoptotic tumor cells in PDO treated with toripalimab than those treated with IgG4. The results showed that toripalimab is able to rescue the excessive death of CD8⁺ T cells by critically reversing the immune exhaustion state of ccRCC in PDO model. This research validated that PDO is a promising and faithful preclinical model for prediction of immunotherapy response in patients with ccRCC.