Identification of potential therapeutic targets for breast cancer using Mendelian randomization analysis and drug target prediction.

Breast cancer stands as the foremost cause of cancer-related mortality among women, presenting a substantial economic impact on society. The limitations in current therapeutic options, coupled with poor patient tolerance, underscore the urgent need for novel treatments. Our study embarked on a genomic association exploration of breast cancer, leveraging whole-genome sequencing data from the Finngen database, complemented by expression quantitative trait loci (eQTL) insights from the eQTLGen and GTEx Consortiums. An initial investigation was conducted through summary-based Mendelian randomization (MR) to pinpoint primary eQTLs. Analysis of blood specimens revealed 103 eQTLs significantly correlated with breast cancer. Focusing our efforts, we identified 19 candidates with potential therapeutic significance. Further scrutiny via two-sample MR pinpointed UROD, LMO4, HORMAD1, and ZSWIM5 as promising targets for breast cancer therapy. Our research sheds light on new avenues for the treatment of breast cancer, highlighting the potential of genomic association studies in uncovering viable therapeutic targets.

Establishment of a nomogram model in predicting risk factors of post-operative complications after laparoscopic anterior resection for rectal cancer.

OBJECTIVE: We aimed to analyse the risk factors of complications after laparoscopic anterior resection of rectal cancer, and to establish a nomogram prediction model and evaluate its accuracy. PATIENTS AND METHODS: We retrospectively analysed the clinical data of 180 patients undergoing laparoscopic anterior resection of rectal cancer. Univariate analysis and multivariate logistic regression analysis were used to screen the potential risk factors of post-operative complications of Grade II and establish a nomogram model. The receiver operating characteristic (ROC) curve and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the discrimination and coincidence of the model, and the calibration curve was used to internally verify. RESULTS: A total of 53 patients (29.4%) with rectal cancer had Grade II post-operative complications. Multivariate logistic regression analysis showed that age (odds ratio [OR] =1.085, P < 0.001), body mass index ≥24 kg/m 2 (OR = 2. 763, P = 0. 008), tumour diameter ≥5 cm (OR = 3. 572, P = 0.002), tumour distance from anal margin ≤6 cm (OR = 2.729, P = 0.012) and operation time ≥180 min (OR = 2.243, P = 0.032) were independent risk factors for Grade II post-operative complications. The area under the ROC was 0.782 (95% confidence interval: 0.706-0.858, sensitivity: 66.0%, specificity: 76.4%) in the nomogram prediction model. Hosmer-Lemeshow goodness-of-fit test showed χ2 = 9.350, P = 0.314. CONCLUSION: Based on five independent risk factors, the nomogram prediction model has a good predictive performance for post-operative complications after laparoscopic anterior resection of rectal cancer, which is helpful to early identify high-risk people and formulate clinical intervention measures.

Application of Mendelian randomization to assess host gene-gut microbiota correlations in patients with esophageal cancer.

Background: Increasing evidence suggests that esophageal cancer (ESCA) may be correlated with gut flora. However, their causal connection remains unclear. This study aimed to evaluate potential causal linkages and gene-gut microbiome associations between the gut microbiota and ESCA using Mendelian randomization (MR). Methods: We analyzed the data using genome-wide association studies. The exposure factor and outcome variable were the gut microbiota and ESCA, respectively. The MR-Egger method, weighted median, inverse-variance weighted method, heterogeneity test, sensitivity analysis, and multiplicity analysis were used for the MR analysis. And it was validated using an external dataset. Further meta-analysis was performed to validate the robustness of this relationship. Finally, we annotated single nucleotide polymorphisms in the gut microbiota that were causally associated with ESCA to explore possible host gene-gut microbiota correlations in patients with ESCA. Results: We identified four species with potential associations with ESCA. Three of these species had a negative causal relationship with ESCA (odds ratio (OR): 0.961; 95% confidence interval (CI): 0.923-0.971; p = 0.047 for Romboutsia; OR: 0.972; 95% CI: 0.921-0.961; p = 0.018 for Lachnospira; OR: 0.948; 95% CI: 0.912-0.970; p = 0.032 for Eubacterium). A positive causal relationship was observed between one bacterial group and ESCA (OR: 1.105; 95% CI: 1.010-1.072; p = 0.018 for Veillonella). External datasets show the same trend. This is further supported by meta-analysis. None of the data showed pleiotropy, and leave-one-out analysis indicated the reliability of these findings. The gut microbiomes of patients with ESCA may correlate with the 19 identified genes. Conclusion: Our data indicate a potential causal link between these four gut bacteria and ESCA and identify a correlation between host genes and gut microbiota in ESCA, offering novel therapeutic options.

Comparison of diagnostic accuracy of three-dimensional transvaginal ultrasound and magnetic resonance imaging in the diagnosis of scar pregnancy.

Objectives: To compare the accuracy of three-dimensional transvaginal ultrasound and magnetic resonance imaging in the diagnosis of scar pregnancy. Methods: The records of 54 patients with scar pregnancy, who underwent three-dimensional transvaginal ultrasound and magnetic resonance imaging (MRI), from June 2015 to November 2021 were reviewed. Surgery / histopathology of operative findings were analyzed as gold standard to compare the diagnosis of the two examination methods. Results: The detection rate of scar pregnancy by three-dimensional transvaginal ultrasound was 94.44%, which was not significantly different from MRI (96.30%, P>0.05). The accuracy, specificity and sensitivity of transvaginal three-dimensional ultrasonography in the diagnosis of scar pregnancy were 94.44%, 66.67% and 96.08%, respectively, and were not significantly different from MRI, 96.30%, 50.00% and 98.08% (P>0.05). The detection rates of yolk sac, embryo and heart tube pulsation by three-dimensional transvaginal ultrasound were higher than those detected by MRI (P<0.05). The detection rates of intrathecal hemorrhage, scar infiltration and uterine hematocele by MRI were significantly higher compared to three-dimensional transvaginal ultrasound (P<0.05). There was no significant difference between the two methods (P>0.05). Conclusion: Both three-dimensional transvaginal ultrasound and MRI have good diagnostic efficacy in the diagnosis of scar pregnancy. Detection rates of scar pregnancy diagnostic criteria differ between the two methods, and if necessary, the two methods can be used together, to further improve the diagnostic accuracy of scar pregnancy.