Personalized medicine最新文献

The use of cancer organoids represents a major advancement in oncology research, addressing the limitations of traditional 2D cell cultures. Optimized protocols now allow the generation of organoids from a wide range of tumor types, including breast, skin, lung, head and neck, and endometrial cancers. These three-dimensional models more accurately replicate the architecture and complexity of patient tumors compared to 2D cultures, spheroids derived from cell lines, or Patient-Derived Tumor Organoids (PDOs) xenografts (PDTXs). This improved fidelity is largely due to the inclusion of the tumor microenvironment (TME) and the potential for immune system interactions, as shown in studies involving co-cultures with peripheral blood mononuclear cells (PBMCs). Patient-Derived Tumor Organoids (PDOs) organoids (PDOs) have emerged as a powerful platform for preclinical testing, enabling the prediction of patient-specific responses to therapies prior to clinical application. Furthermore, PDOs support the discovery of novel biomarkers and the establishment of biobanks, offering valuable insights into cancer biology and helping to overcome persistent challenges in the field. In this context, we will discuss the methods for generating PDOs, the critical role of selecting appropriate culture media and growth factors tailored to different tumor types, and the analytical techniques to verify the extent to which PDOs recapitulate the original tumor tissue.

Aim: This study aimed to explore the Chinese public's experiences with, perceptions of, attitudes toward, and willingness to use genetic testing (GT) in the precision medicine era.

Methods: A total of 4,208 individuals from 33 provinces in China were recruited to complete a self-administered questionnaire in December 2018.

Results: More than half of the respondents believed that GT does more good than harm, while only 5.8% believed that it does more harm than good. Nearly 60% of the respondents expressed willingness to use GT. Higher awareness of GT was correlated with more positive attitudes toward it and a greater willingness to use it. However, the general public had an uneven exposure and susceptibility to misinformation. More educated respondents demonstrated a better understanding of GT but remained vulnerable to the influence of misinformation. Additionally, younger generations tended to be more critical of GT but were more willing to use it than earlier generations.

Conclusions: The study reveals a high level of acceptance of GT among the Chinese public, while also suggesting that educational and regulatory measures are needed to improve public understanding of GT and address their particular concerns regarding genetic testing and precision medicine.

Background: Urinary bladder cancer (UBC), the tenth most common globally with a male predominance, has its risk factors like smoking and single nucleotide polymorphisms (SNPs), yet the MYC gene's role, especially the rs9642880 GT/TT polymorphism on chromosome 8q24.21, in cancer susceptibility is underexplored.

Methods: We searched in Medline, Scopus and Web of Science databases for relevant studies. Odds ratios (OR) with 95% confidence intervals (CIs) were computed using DerSimonian and Laird random-effect models. Heterogeneity was assessed using I² statistics. Statistical analyses were performed using R, version 4.4.2.

Results: Data from 53,957 subjects was analyzed, including 8,002 UBC patients and 45,955 controls, with median age ranging from 44.5 to 68.7 years. We found significant association between the rs9642880 GT/TT polymorphism and increased UBC risk (OR 1.249, 95% CI 1.188-1.297, p < 0.001). This association was consistent across American (OR 1.43 95% CI 1.20-1.70), Asian (OR 1.25 95% CI 1.17-1.34), and Caucasian (OR 1.21 95% CI 1.13-1.29) ethnic groups, with low heterogeneity (I² = 0%). Subgroup analyses by genotyping method and source of control further supported these results.

Conclusion: This meta-analysis provides robust evidence that the T allele of the rs9642880 polymorphism in the MYC gene significantly increases susceptibility to UBC across Asian, American, and Caucasian populations.

Background: Congenital heart disease (CHD) is a condition characterized by structural or functional abnormalities of the cardiovascular system present at birth. This study investigated the correlation between microRNA-21 (miR-21) rs1292037 and rs13137 polymorphisms and children with CHD.

Materials and methods: The study included 305 CHD children and 303 healthy children. The TaqMan real-time fluorescent quantitative PCR (qPCR) method was used to genotype miR-21 SNPs. The RT-qPCR method was adopted to quantify the miR-21 expression. Multivariate logistic regression analysis was performed to investigate the CHD risk factors.

Results: The rs1292037 TC (OR = 1.527, 95% CI = 1.045-2.231, p = 0.028), CC (OR = 1.747, 95% CI = 1.114-2.742, p = 0.015) genotypes, and C allele (OR = 1.338, 95% CI = 1.068-1.677, p = 0.011) might be strongly associated with an elevated risk of CHD. MiR-21 was upregulated in CHD patients (p < 0.05). Individuals with the rs1292037 TC and CC genotypes exhibited higher miR-21 expression (p < 0.05). In contrast, no significant differences in miR-21 expression were observed among genotypes at rs13137 (p > 0.05). MiR-21, rs1292037, left ventricular end-systolic diameter, and ejection fraction were significantly linked to disease risk (p < 0.05), whereas rs13137 did not show a significant association with disease risk.

Conclusion: The miR-21 rs1292037 polymorphism was significantly linked to CHD genetic predisposition, while the rs13137 polymorphism had no strong association.

Background: Genetic variations in non-coding RNAs, including MIR31HG, which hosts microRNA-31, have been linked to breast cancer (BC) susceptibility. Current study aimed to evaluate the correlation between two MIR31HG variants (rs72703442 and rs55683539) and the risk of developing BC in women from western Iran.

Materials and methods: A case-control study was conducted with 120 BC patients and 120 age-matched healthy controls. Peripheral blood was collected, and genotyping was performed using the Amplification Refractory Mutation System (ARMS). Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated under different genetic models to determine BC risk. Associations between variants and clinicopathological features were also examined.

Results: The rs72703442-TT genotype was -associated with a reduced BC risk in the recessive model (TT vs. CT + CC; OR = 0.55, 95% CI = 0.31-0.99, p = 0.05). Similarly, the rs55683539-AA genotype demonstrated a protective effect under the dominant model (GA + AA vs. GG; OR = 0.47, 95% CI = 0.26-0.86, p = 0.013). No significant associations were observed between either polymorphism and clinicopathological features.

Conclusion: These findings suggest that MIR31HG polymorphisms rs72703442 and rs55683539 may confer a protective effect against BC in this population, although no association with clinical features was observed. Larger multiethnic studies are needed to validate these associations and clarify underlying mechanisms.

Type 1 Diabetes (T1D) is a chronic autoimmune disease marked by the progressive immune-mediated destruction of insulin-producing pancreatic beta-cells. The clinical management of T1D is complicated by its heterogeneity and the variability in individual responses to treatment. Personalized medicine has emerged as a promising strategy to address these challenges by tailoring interventions to individual patient profiles. Circulating microRNAs (miRNAs) - small, non-coding RNAs found in bodily fluids - represent potential biomarkers across various diseases, including T1D. This review examines the role of circulating miRNAs in advancing personalized medicine for T1D, emphasizing on their application in the response prediction of innovative therapeutic strategies. We discuss key miRNAs -detectable in blood plasma- implicated in modulating immune responses and beta-cell function and associated with patient-specific differences in disease onset, progression, and therapeutic responses, underscoring their potential in refining treatment strategies. We explore how miRNA signatures can enhance clinical decision-making by predicting disease progression, assessing susceptibility to complications, and monitoring responses to newly proposed therapies, thus leveraging these more precise and individualized treatment regimens, improving the effectiveness and outcomes of T1D management. The integration of circulating miRNAs into personalized treatment frameworks represents a transformative opportunity to advance T1D care and improve patients' outcomes.

Background: Gaucher disease (GD) is the most common lysosomal storage disorder caused by biallelic pathogenic variants in GBA1, resulting in deficient β-glucocerebrosidase activity. Clinical characterization of rare GBA1 variants is crucial for understanding disease heterogeneity. We report an extremely rare GBA1 variant previously catalogued at the sequence level in HGMD and UniProtKB, and recently listed in ClinVar without a clinical significance assertion, but lacking phenotypic data.

Case presentation: A 23-year-old male presented with fatigue, chills, shivering, and diffuse bone pain. Physical examination revealed hepatosplenomegaly, and laboratory tests showed moderate thrombocytopenia. Leukocyte β-glucocerebrosidase activity was markedly reduced (0.90 nmol/mg/h), and plasma Lyso-Gb1 was highly elevated (431.3 ng/mL; reference <14.0 ng/mL). DXA (Dual-energy X-ray Absorptiometry) demonstrated osteopenia (lumbar spine Z-score: -2.3). Genetic analysis identified a homozygous GBA1 NM_000157.4:c.245C>T (p.Thr82Ile; rs1141811) variant. Family screening showed heterozygosity in both parents and one sibling.

Conclusion: This report provides the first comprehensive clinical characterization of the rare GBA1 p.Thr82Ile variant, expanding the phenotypic spectrum of Type 1 GD.

Aim: Leukemias are heterogenous hematologic malignancies broadly classified into myeloid and lymphoid lineages, each with distinct molecular and clinical features. Here we aime to identify lineage-specific molecular vulnerabilities in myeloid and lymphoid leukemias and use them to guide targeted therapy and rational drug repurposing.

Materials & methods: A meta-analysis of 19 GEO datasets comprising >2,600 samples from acute and chronic leukemia subtypes was performed. Differentially expressed genes (DEGs) were identified and subjected to functional enrichment and protein-protein interaction (PPI) network analyses. Hub genes were identified for drug repurposing using the LINCS L1000CDS2. Candidate compounds were validated by performing molecular docking, dynamics simulations and MTT assays on multiple leukemia cell lines.

Results: 269 DEGs in myeloid and 316 DEGs in lymphoid leukemias were identified. Enrichment analysis showed that DNA replication and cell cycle pathways drive myeloid leukemias, while lymphoid leukemias are associated with transcriptional regulation and immune signaling. Hub genes included CCNB1, KIF11, EGFR and JUN. SN-38 and C646 were identified as promising candidates from drug repurposing. Docking and molecular dynamics simulations confirmed strong binding to IGF1R and RBP2. MTT assays revealed significant, time- and dose-dependent cytotoxicity.

Conclusion: This integrative approach links transcriptomics with drug discovery and preclinical validation. Lineage-specific vulnerabilities were uncovered, providing a framework for precision therapy and rational drug repurposing in leukemia.

Background: In urinary bladder cancer, early diagnosis plays a key role for effective patient management. Moreover, accurate prediction of genetic mutations plays a critical role in identifying biomarkers for prognosis and therapy.

Methods: Mutation types and other details were collected from publicly available datasets of human bladder cancer cell lines. A multilevel ensemble model was designed by integrating an Artificial Neural Network (ANN) with a Random Forest (RF) classifier. The model was trained and validated on DNA sequence data to predict mutation types, specifically base pair insertions and deletions. Performance was compared against traditional machine learning models including SVM, naive Bayes, and decision trees.

Results: The proposed ensemble model achieved nearly 95% prediction accuracy, significantly outperforming conventional approaches. The integration of ANN and RF improved classification robustness and reliability in mutation type prediction. This study presents the development of a predictive model for mutation detection in bladder cancer using an AI-based approach.

Conclusion: This novel study highlights the potential of AI techniques for early detection of mutations in urinary bladder cancer. The highly accurate prediction capability of the developed model offers promise for identifying diagnostic and prognostic mutational landscapes to guide future therapeutic strategies.

Adamantinoma is a rare bone tumor characterized by a propensity for local recurrence and distant metastasis. Management of metastatic disease remains challenging owing to the absence of standardized therapy and the limited efficacy of conventional chemotherapy. This case report describes a young woman with adamantinoma harboring an XRCC2 frameshift mutation. She showed a sustained clinical response to fourth-line treatment with the PARP inhibitor olaparib, which lasted 15 months and led to improved performance status. Subsequent progression led to combination therapy with atezolizumab and bevacizumab, maintaining stable disease for eight months. Molecularly guided treatment resulted in an overall survival of 25 months.