Studying the impact of marital status on diagnosis and survival prediction in pancreatic ductal carcinoma using machine learning methods.

Pancreatic cancer is a commonly occurring malignant tumor, with pancreatic ductal carcinoma (PDAC) accounting for approximately 95% of cases. According of its poor prognosis, identifying prognostic factors of pancreatic ductal carcinoma can provide physicians with a reliable theoretical foundation when predicting patient survival. This study aimed to analyze the impact of marital status on survival outcomes of PDAC patients using propensity score matching and machine learning. The goal was to develop a prognosis prediction model specific to married patients with PDAC. We extracted a total of 206,968 patient records of pancreatic cancer from the SEER database. To ensure the baseline characteristics of married and unmarried individuals were balanced, we used a 1:1 propensity matching score. We then conducted Kaplan-Meier analysis and Cox proportional-hazards regression to examine the impact of marital status on PDAC survival before and after matching. Additionally, we developed machine learning models to predict 5-year CSS and OS for married patients with PDAC specifically. In total, 24,044 PDAC patients were included in this study. After 1:1 propensity matching, 8043 married patients and 8,043 unmarried patients were successfully enrolled. Multivariate analysis and the Kaplan-Meier curves demonstrated that unmarried individuals had a poorer survival rate than their married counterparts. Among the algorithms tested, the random forest performed the best, with 0.734 5-year CSS and 0.795 5-year OS AUC. This study found a significant association between marital status and survival in PDAC patients. Married patients had the best prognosis, while widowed patients had the worst. The random forest is a reliable model for predicting survival in married patients with PDAC.

A study on the impact of marital status on the survival status of prostate cancer patients based on propensity score matching.

Marital status is an independent prognostic factor for survival in many types of cancers, but its prognostic impact on patients with prostate cancer (PCa) has not been established. The aim of this study was to explore the independent prognostic factors of PCa and to investigate the effect of marital status on survival outcomes in patients with different stratified by PCa. Using the surveillance, epidemiology, and end results (SEER) database, we collected data on 584,655 PCa patients diagnosed between 1975 and 2019. Marital status was classified as married, divorced, widowed, and single. We used the Kaplan-Meier analysis and single multivariate Cox proportional hazards regression analysis to determine the effect of marital status on overall survival (OS) and cancer-specific survival (CSS). In addition, we performed subgroup analyses for different ages, Gleason score and PSA values, and performed a 1:1 propensity score matching (PSM) to reduce the impact of confounding factors to obtain more accurate matching results. According to our findings, marital status was an independent prognostic factor for the survival of PCa patients and a better prognosis of married patients. Moreover, we also found that factors such as age, TNM stage, Gleason score, and PSA concentration were also considered as important predictors for the prognosis of PCa. The above findings can facilitate early detection and treatment of high-risk PCa patients, prolong their life and reduce family burden.

Cuproptosis-related genes predict prognosis and trastuzumab therapeutic response in HER2-positive breast cancer.

Breast cancer is the most common diagnosed cancer, the HER2-positive subtype account for 15% of all breast cancer. HER2-targeted therapy is the mainstay treatment for HER2-positive breast cancer. Cuproptosis is a novel form of programmed cell death, and is caused by mitochondrial lipoylation and destabilization of iron-sulfur proteins triggered by copper, which was considered as a key player in various biological processes. However, the roles of cuproptosis-related genes in HER2-positive breast cancer remain largely unknown. In the present study, we constructed a prognostic prediction model of HER2-positive breast cancer patients using TCGA database. Dysregulated genes for cells resistant to HER2-targeted therapy were analyzed in the GEO dataset. KEGG pathway, GO enrichment and GSEA was performed respectively. The immune landscape of DLAT was analyzed by CIBERSORT algorithm and TIDE algorithm. HER2-positive breast cancer patients with high CRGs risk score showed shorter OS. DLAT was downregulated and correlated with better survival of HER2-positive breast cancer patients (HR = 3.30, p = 0.022). High expressed DLAT was associated with resistant to HER2-targeted therapy. Knocking down DLAT with siRNA increased sensitivity of breast cancer to trastuzumab. KEGG pathway and GO enrichment of DEGs indicated that DLAT participates in various pathways correlated with organelle fission, chromosome segregation, nuclear division, hormone-mediated signaling pathway, regulation of intracellular estrogen receptor signaling pathway, condensed chromosome and PPAR signaling pathway. There was a negative correlation between TIDE and DLAT expression (r = - 0.292, p < 0.001), which means high DLAT expression is an indicator of sensitivity to immunotherapy. In conclusion, our study constructed a four CRGs signature prognostic prediction model and identified DLAT as an independent prognostic factor and associated with resistant to HER2-targeted therapy for HER2-positive breast cancer patients.

Nanozyme colorimetric sensing of L-cysteine and copper ions based on PtCo nanoparticles@multi-walled carbon nanotubes.

In this work, PtCo bimetallic nanoparticles supported on multi-walled carbon nanotubes (PtCo@MWCNTs) nanohybrid was prepared simply and used for the first time as a novel nanozyme in the colorimetric sensing of L-cysteine (L-Cys) and Cu2+. Due to its strong enzyme-like catalytic activity, the prepared PtCo@MWCNTs nanohybrid can catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to form ox-TMB without H2O2. Interestingly, the oxidase-like active of PtCo@MWCNTs was effectively suppressed by L-Cys, which could reduce ox-TMB to colorless TMB and lead to a pronounced blue fading, and the absorbance at 652 nm gradually decreased with increasing L-Cys concentration. On the other hand, the nanozyme activity of PtCo@MWCNTs can be recovered due to the complexation between L-Cys and Cu2+. Therefore, a colorimetric method based on PtCo@MWCNTs nanozyme was established to detect L-Cys and Cu2+. The results show that the assay platform has simple, rapid, sensitive performance and good selectivity. The detection limits for L-Cys and Cu2+ are 0.041 µM and 0.056 µM, respectively, coupled with the linearities of 0.01 ~ 60.0 µM and 0.05 ~ 80.0 µM. The successful first application of PtCo bimetal-based nanozyme in colorimetric sensing herein opens a new direction for nanozyme and colorimetric analysis, showing great potential applications.

Screening a DNA Aptamer Specifically Targeting Integrin ß3 and Partially Inhibiting Tumor Cell Migration.

Due to its key roles in malignant tumor progression and reprograming of the tumor microenvironment, integrin ß3 has attracted great attention as a new target for tumor therapy. However, the structure-function relationship of integrins ß3 remains incompletely understood, leading to the shortage of specific and effective targeting probes. This work uses a purified extracellular domain of integrin ß3 and integrin ß3-positive cells to screen aptamers, specifically targeting integrin ß3 in the native conformation on live cells through the SELEX approach. Following meticulous truncation and characterization of the initial aptamer candidates, the optimized aptamer S10yh2 was produced, exhibiting a low equilibrium dissociation constant (Kd) in the nanomolar range. S10yh2 displays specific recognition of cancer cells with varying levels of integrin ß3 expression and demonstrates favorable stability in serum. Subsequent analysis of docking sites revealed that S10yh2 binds to the seven amino acid residues located in the core region of integrin ß3. The S10yh2 aptamer can downregulate the level of integrin heterodimer αvß3 on integrin ß3 overexpressed cancer cells and partially inhibit cell migration behavior. In summary, S10yh2 is a promising probe with a small size, simple synthesis, good stability, high binding affinity, and selectivity. It therefore holds great potential for investigating the structure-function relationship of integrins.

DPP6 and MFAP5 are associated with immune infiltration as diagnostic biomarkers in distinguishing uterine leiomyosarcoma from leiomyoma.

Objective: Uterine leiomyosarcoma (ULMS) is the most common subtype of uterine sarcoma and is difficult to discern from uterine leiomyoma (ULM) preoperatively. The aim of the study was to determine the potential and significance of immune-related diagnostic biomarkers in distinguishing ULMS from ULM. Methods: Two public gene expression profiles (GSE36610 and GSE64763) from the GEO datasets containing ULMS and ULM samples were downloaded. Differentially expressed genes (DEGs) were selected and determined among 37 ULMS and 25 ULM control samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Disease Ontology (DO) enrichment analyses as well as gene set enrichment analysis (GSEA). The candidate biomarkers were identified by least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analyses. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the biomarker expression levels and diagnostic value in ULMS were verified in the GSE9511 and GSE68295 datasets (12 ULMS and 10 ULM), and validated by immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in ULMS. Result: In total, 55 DEGs were recognized via GO analysis, and KEGG analyses revealed that the DEGs were enriched in nuclear division, and cell cycle. The recognized DEGs were primarily implicated in non-small cell lung carcinoma and breast carcinoma. Gene sets related to the cell cycle and DNA replication were activated in ULMS. DPP6 and MFAP5 were distinguished as diagnostic biomarkers of ULMS (AUC = 0.957, AUC = 0.899, respectively), and they were verified in the GSE9511 and GSE68295 datasets (AUC = 0.983, AUC = 0.942, respectively). The low expression of DPP6 and MFAP5 were associated with ULMS. In addition, the analysis of the immune microenvironment indicated that resting mast cells were positively correlated with DPP6 and MFAP5 expression and that eosinophils and M0 macrophages were negatively correlated with DPP6 expression (P<0.05). Conclusion: These findings indicated that DPP6 and MFAP5 are diagnostic biomarkers of ULMS, thereby offering a novel perspective for future studies on the occurrence, function and molecular mechanisms of ULMS.

Identification of Core Genes Shared by Endometrial Cancer and Ovarian Cancer Using an Integrated Approach.

Ovarian cancer (OC) is one of the most commonly diagnosed cancers among women. Moreover, Endometrial cancer (EC) is a usual genital tract cancer in females; however, the hub genes and molecular pathways shared by these two cancers have not been surveyed yet. So, this study aimed to identify the common candidate genes or biomarkers and molecular pathways in OC and EC. Differences in the expressed genes between these two microarray data sets were detected. Pathway enrichment analysis and gene ontology (GO) was also performed and protein-protein interactions (PPI) network analysis was done using Cytoscape and the most important genes were identified by the Cytohubba plugin. We found that 154 common DEGs shared by OC and EC were also detected. 10 hub proteins were identified as follows: CDC20, BUB1, CENPF, KIF11, CCNB2, FOXM1, TTK, TOP2A, DEPDC1, and NCAPG. The most important and significant miRNAs were identified to be hsa-mir-186-5p, hsa-mir-192-5p, hsa-mir-215-5p, and hsa-mir-193b-3p regulated expressions of the DEGs.  This investigation demonstrated that these hub genes and their miRNA might be key genes with great effects on OC and EC. However, more studies are needed for a better understanding of the role of these hub genes and their function in these two cancers.

Protective effects of upregulated HO-1 gene against the apoptosis of human retinal pigment epithelial cells in vitro.

AIM: To investigate the protective effect of heme oxygenase-1 (HO-1) against H2O2-induced apoptosis in human ARPE-19 cells. METHODS: The lentiviral vector expressing HO-1 was prepared and transfected into apoptotic ARPE-19 cells induced by H2O2. Functional experiments including cell counting kit-8 (CCK-8) assay, flow cytometry (FCM) and mitochondrial membrane potential assay were conducted. RESULTS: The ultrastructure of ARPE-19 cells was observed using transmission electron microscope (TEM). It was found that exogenous HO-1 significantly ameliorated H2O2-induced loss of cell viability, apoptosis and intracellular levels of reactive oxygen species (ROS) in ARPE-19 cells. The overexpression of HO-1 facilitated the transfer of nuclear factor erythroid-2-related factor 2 (Nrf2) from cytoplasm to nucleus, which in turn upregualted expressions HO-1 and B-cell lymphoma-2 (Bcl-2). Furthermore, HO-1 upregulation further inhibited H2O2-induced release of cysteinyl aspartate specific proteinase-3 (caspase-3). CONCLUSION: Exogenous HO-1 protect ARPE-19 cells against H2O2-induced oxidative stress by regulating the expressions of Nrf2, HO-1, Bcl-2, and caspase-3.

Zinc protects sperm from being damaged by reactive oxygen species in assisted reproduction techniques.

The aim of this study was to explore the effect of zinc on hydrogen peroxide-induced sperm damage in assisted reproduction techniques. First, sperms were selected from semen samples of 20 healthy men prepared by density gradient centrifugation. Selected sperm were treated with either 0.001% H(2)O(2), 12.5 nM ZnCL(2), 0.001% H(2)O(2) + 12.5 nM ZnCL(2) or 0.9% NaCl(2) (control). After this treatment, the motility, viability, membrane integrity and DNA fragmentation of sperms in each group were analysed by Goodline sperm detection system, optical microscopy and sperm DNA fragmentation assay. Poorer motility, vitality, membrane integrity and more DNA damage were found in sperms treated by H(2)O(2), compared with control. When sperms were treated with both H(2)O(2) and zinc, however, all indicators were improved compared with H(2)O(2) alone. There was a close association between oxidative stimulation and sperm injury; zinc could inhibit hydrogen peroxide-induced damage of sperm in assisted reproductive technology. However, the presence of zinc in culture medium can decrease the sperm quality without addition of peroxide.

[Genetic diagnosis of thalassemia mutations with free fetal DNA in pregnant plasma].

This research was aimed to develop a simple, rapid, accurate and non-invasive method by means of flow-through hybridization technology, which can be used for molecular screening and early prenatal diagnosis for detecting common ß-thalassemias mutational genotypes. By using PCR technology combined with flow-through hybridization of low-density gene chip technology, the 6 sets of PCR primer single tube multiplex PCR system and 29 types of DNA probes were designed, then the mutational thalassemias in foetus DNA was rapidly detected in total of 60 anaemia pregnant women plasma. The results showed that 4 cases with deletional α-thalassemias, 3 cases with ß-thalassemias, 1 case with mixed type of α & ß-thalassemias were detected in foetus DNA of 60 pregnant women plasmas. It is concluded that the method presented in this study is easy to handle, rapid, reliable and cost-effective for detecting 3 common deletional α-thalassemias and 17 common mutational ß-thalassemia.