Ten years of achievements in biological and medical sciences

Comparison of ocular surface assessment outcomes between healthy controls and patients with obstructive sleep apnea-hypopnea syndrome: a meta-analysis of the literature

Objective: This meta-analysis aims to determine whether ocular surface alterations are associated with disease severity in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). Methods: The protocol for this systematic review and meta-analysis was registered in PROSPERO. We conducted the search in six electronic databases (China National Knowledge Infrastructure, EMBASE, Cochrane Library, Web of Science, Wanfang, and PubMed) from since the construction of the databases to 30 December 2022. The standard mean difference (SMD) and correlation coefficients are reported as measures of the effect size in the presence of retrieved data. In addition, the random effects model or fixed effects model was used in a combined analysis. Stata 11.0 and R 3.6.1 were used for statistical analyses of the data. Results: A total of 15 studies satisfied the inclusion criteria for this study. The prevalence of floppy eyelid syndrome (FES) and dry eye syndrome in patients with obstructive sleep apnea-hypopnea syndrome was 40 and 48%, respectively. In addition, the Schirmer 1 value and tear break-up time (TBUT) were remarkably reduced in patients with OSAHS when compared to that of the controls. The ocular surface disease index (OSDI) scores, Oxford corneal staining scores, and the rates of loss in the meibomian glands were elevated in patients with obstructive sleep apnea-hypopnea syndrome when compared to that of the controls, especially those with severe disease. Moreover, the Schirmer 1 value and tear break-up time exhibited a negative correlation with the apnea-hypopnea index (AHI), and the OSDI showed a positive association with the apnea-hypopnea index. Conclusion: Patients with OSAHS had a greater prevalence of FES than the healthy controls. They also showed lower Schirmer 1 value and tear break-up time but had a higher OSDI, Oxford corneal staining scores, and rates of loss in the meibomian glands than the healthy controls. Clinical Trial Registration: (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=392527).

Pan-Cancer DNA Methylation Analysis and Tumor Origin Identification of Carcinoma of Unknown Primary Site Based on Multi-Omics

The metastatic cancer of unknown primary (CUP) sites remains a leading cause of cancer death with few therapeutic options. The aberrant DNA methylation (DNAm) is the most important risk factor for cancer, which has certain tissue specificity. However, how DNAm alterations in tumors differ among the regulatory network of multi-omics remains largely unexplored. Therefore, there is room for improvement in our accuracy in the prediction of tumor origin sites and a need for better understanding of the underlying mechanisms. In our study, an integrative analysis based on multi-omics data and molecular regulatory network uncovered genome-wide methylation mechanism and identified 23 epi-driver genes. Apart from the promoter region, we also found that the aberrant methylation within the gene body or intergenic region was significantly associated with gene expression. Significant enrichment analysis of the epi-driver genes indicated that these genes were highly related to cellular mechanisms of tumorigenesis, including T-cell differentiation, cell proliferation, and signal transduction. Based on the ensemble algorithm, six CpG sites located in five epi-driver genes were selected to construct a tissue-specific classifier with a better accuracy (>95%) using TCGA datasets. In the independent datasets and the metastatic cancer datasets from GEO, the accuracy of distinguishing tumor subtypes or original sites was more than 90%, showing better robustness and stability. In summary, the integration analysis of large-scale omics data revealed complex regulation of DNAm across various cancer types and identified the epi-driver genes participating in tumorigenesis. Based on the aberrant methylation status located in epi-driver genes, a classifier that provided the highest accuracy in tracing back to the primary sites of metastatic cancer was established. Our study provides a comprehensive and multi-omics view of DNAm-associated changes across cancer types and has potential for clinical application.

Integrative analysis identifies potential DNA methylation biomarkers for pan-cancer diagnosis and prognosis

DNA methylation status is closely associated with diverse diseases, and is generally more stable than gene expression, thus abnormal DNA methylation could be important biomarkers for tumor diagnosis, treatment and prognosis. However, the signatures regarding DNA methylation changes for pan-cancer diagnosis and prognosis are less explored. Here we systematically analyzed the genome-wide DNA methylation patterns in diverse TCGA cancers with machine learning. We identified seven CpG sites that could effectively discriminate tumor samples from adjacent normal tissue samples for 12 main cancers of TCGA (1216 samples, AUC > 0.99). Those seven potential diagnostic biomarkers were further validated in the other 9 different TCGA cancers and 4 independent datasets (AUC > 0.92). Three out of the seven CpG sites were correlated with cell division, DNA replication and cell cycle. We also identified 12 CpG sites that can effectively distinguish 26 different cancers (7605 samples), and the result was repeatable in independent datasets as well as two disparate tumors with metastases (micro-average AUC > 0.89). Furthermore, a series of potential signatures that could significantly predict the prognosis of tumor patients for 7 different cancer were identified via survival analysis (p-value < 1e-4). Collectively, DNA methylation patterns vary greatly between tumor and adjacent normal tissues, as well as among different types of cancers. Our identified signatures may aid the decision of clinical diagnosis and prognosis for pan-cancer and the potential cancer-specific biomarkers could be used to predict the primary site of metastatic breast and prostate cancers.