CRISPR/Cas9 based gene editing of Frizzled class receptor 6 (FZD6) reveals its role in depressive symptoms through disrupting Wnt/ß-catenin signaling pathway.

INTRODUCTION: As one of the common psychiatric diseases, depression poses serious threats to human health. Although many genes have been nominated for depression, few of them were investigated in details at the molecular level. OBJECTIVES: To demonstrate Frizzled class receptor 6 (FZD6) functions in depression through disrupting Wnt/ß-catenin signal pathway. METHODS: The FZD6 edited cell line and mouse model were generated by using CRISPR/Cas9 technique. The expression of key genes and proteins in Wnt/ß-catenin pathway was determined by qRT-PCR and Western blotting, respectively. Animal behavioral tests, including open field test (OFT), elevated plus maze test (EPM), forced swimming test (FST), tail suspension test (TST), and sucrose preference test (SPT), were employed to determine anxiety- and depressive-like behaviors. Immunofluorescent staining was used to assess cell proliferation in the hippocampus of mouse brain. RESULTS: Among patients with depression, FZD6, one of the receptors of Wnt ligand, was significantly decreased. In CRISPR/Cas9-based FZD6 knockdown cells, we showed that FZD6 plays a significant role in regulating expression of genes involved in Wnt/ß-catenin pathway. Subsequently behavioral studies on Fzd6 knockdown mice (with a 5-nucleotide deletion; Fzd6-Δ5) revealed significant changes in depressive symptoms, including increased immobility duration in FST, less preference of sucrose in SPT, reduction of distance traveled in OFT, and decreased time spent in open arms in EPM. Immunofluorescent staining showed decreased cell proliferation in the hippocampus of Fzd6-Δ5 mice with reduced number of Ki67+ and PCNA+ cells. Moreover, decreased Gsk3ß mRNA expression, phosphorylated GSK3ß, and cytoplasmic ß-catenin in the hippocampus of Fzd6-Δ5 mice provided further evidence supporting the role of Fzd6 in depression. CONCLUSION: Together, above findings proved the significant role of FZD6 in depression through its effect on hippocampal cell proliferation and its ability to regulate canonical Wnt/ß-catenin pathway.

Novel insights into molecular patterns of ROS1 fusions in a large Chinese NSCLC cohort: a multicenter study.

ROS proto-oncogene 1, receptor tyrosine kinase (ROS1) rearrangements are a crucial therapeutic target in non-small cell lung cancer (NSCLC). However, there is limited comprehensive analysis of the molecular patterns of ROS1 fusions. This study aimed to address this gap by analysing 135 ROS1 fusions from 134 Chinese NSCLC patients using next-generation sequencing (NGS). The fusions were categorized into common and uncommon based on their incidence. Our study revealed, for the first time, a unique distribution preference of breakpoints within ROS1, with common fusions occurring in introns 31-33 and uncommon fusions occurring in introns 34 and 35. Additionally, we identified previously unknown breakpoints within intron 28 of ROS1. Furthermore, we identified a close association between the distribution patterns of fusion partners and breakpoints on ROS1, providing important insights into the molecular landscape of ROS1 fusions. We also confirmed the presence of inconsistent breakpoints in ROS1 fusions between DNA-based NGS and RNA-based NGS through rigorous validation methods. These inconsistencies were attributed to alternative splicing resulting in out-of-frame or exonic ROS1 fusions. These findings significantly contribute to our understanding of the molecular characteristics of ROS1 fusions, which have implications for panel design and the treatment of NSCLC patients with ROS1 rearrangements.

Congenital cataracts affect the retinal visual cycle and mitochondrial function: A multi-omics study of GJA8 knockout rabbits.

Congenital cataracts are a threat to visual development in children, and the visual impairment persists after surgical treatment; however, the mechanisms involved remain unclear. Previous clinical studies have identified the effect of congenital cataracts on retinal morphology and function. To further understand the molecular mechanisms by which congenital cataracts affect retinal development, we analyzed retina samples from 7-week-old GJA8-knockout rabbits with congenital cataracts and controls by four-dimensional label-free quantification proteomics and untargeted metabolomics. Bioinformatics analysis of proteomic data showed that retinol metabolism, oxidative phosphorylation, and fatty acid degradation pathways were downregulated in the retinas of rabbits with congenital cataracts, indicating that their visual cycle and mitochondrial function were affected. Additional validation of differentially abundant proteins related to the visual cycle and mitochondrial function was performed using Parallel reaction monitoring and western blot experiments. Untargeted metabolome analysis showed significant upregulation of the antioxidant glutathione and ascorbic acid in the retinas of rabbits with congenital cataracts, indicating that their oxidative stress balance was not dysregulated. SIGNIFICANCE: Congenital cataracts in children can alter retinal structure and function, yet the mechanisms are uncertain. Here is the first study to use proteomics and metabolomics approaches to investigate the effects of congenital cataracts on retinal development in the early postnatal period. Our findings suggest that congenital cataracts have an impact on the retinal visual cycle and mitochondrial function. These findings give insight on the molecular pathways behind congenital cataract-induced visual function impairment in the early postnatal period.

Molecular characterization of genomic breakpoints of ALK rearrangements in non-small cell lung cancer.

ALK rearrangement is called the 'diamond mutation' in non-small cell lung cancer (NSCLC). Accurately identifying patients who are candidates for ALK inhibitors is a key step in making clinical treatment decisions. In this study, a total of 783 ALK rearrangement-positive NSCLC cases were identified by DNA-based next-generation sequencing (NGS), including 731 patients with EML4-ALK and 52 patients with other ALK rearrangements. Diverse genomic breakpoints of ALK rearrangements were identified. Approximately 94.4% (739/783) of the cases carried ALK rearrangements with genomic breakpoints in the introns of ALK and its partner genes, and 2.8% (21/739) of these cases resulted in frameshift transcripts of ALK. Meanwhile, 5.6% (44/783) of the ALK rearrangement-positive cases had breakpoints in the exons that would be expected to result in abnormal transcripts. RNA-based NGS was performed to analyse the aberrant fusions at the transcript level. Some of these rearranged DNAs were not transcribed, and the others were fixed by some mechanisms so that the fusion kinase proteins could be expressed. Altogether, these findings emphasize that, when using DNA-based NGS, functional RNA fusions should be confirmed in cases with uncommon/frameshift rearrangement by RNA-based assays.

Identification of a Novel Functional Non-synonymous Single Nucleotide Polymorphism in Frizzled Class Receptor 6 Gene for Involvement in Depressive Symptoms.

Although numerous susceptibility loci for depression have been identified in recent years, their biological function and molecular mechanism remain largely unknown. By using an exome-wide association study for depressive symptoms assessed by the Center for Epidemiological Studies Depression (CES-D) score, we discovered a novel missense single nucleotide polymorphism (SNP), rs61753730 (Q152E), located in the fourth exon of the frizzled class receptor 6 gene (FZD6), which is a potential causal variant and is significantly associated with the CES-D score. Computer-based in silico analysis revealed that the protein configuration and stability, as well as the secondary structure of FZD6 differed greatly between the wild-type (WT) and Q152E mutant. We further found that rs61753730 significantly affected the luciferase activity and expression of FZD6 in an allele-specific way. Finally, we generated Fzd6-knockin (Fzd6-KI) mice with rs61753730 mutation using the CRISPR/Cas9 genome editing system and found that these mice presented greater immobility in the forced swimming test, less preference for sucrose in the sucrose preference test, as well as decreased center entries, center time, and distance traveled in the open filed test compared with WT mice after exposed to chronic social defeat stress. These results indicate the involvement of rs61753730 in depression. Taken together, our findings demonstrate that SNP rs61753730 is a novel functional variant and plays an important role in depressive symptoms.

Integrative Analysis of Epigenome and Transcriptome Data Reveals Aberrantly Methylated Promoters and Enhancers in Hepatocellular Carcinoma.

DNA methylation is a key transcription regulator, whose aberration was ubiquitous and important in most cancers including hepatocellular carcinoma (HCC). Whole-genome bisulfite sequencing (WGBS) was conducted for comparison of DNA methylation in tumor and adjacent tissues from 33 HCC patients, accompanying RNA-seq to determine differentially methylated region-associated, differentially expressed genes (DMR-DEGs), which were independently replicated in the TCGA-LIHC cohort and experimentally validated via 5-aza-2-deoxycytidine (5-azadC) demethylation. A total of 9,867,700 CpG sites showed significantly differential methylation in HCC. Integrations of mRNA-seq, histone ChIP-seq, and WGBS data identified 611 high-confidence DMR-DEGs. Enrichment analysis demonstrated activation of multiple molecular pathways related to cell cycle and DNA repair, accompanying repression of several critical metabolism pathways such as tyrosine and monocarboxylic acid metabolism. In TCGA-LIHC, we replicated about 53% of identified DMR-DEGs and highlighted the prognostic significance of combinations of methylation and expression of nine DMR-DEGs, which were more efficient prognostic biomarkers than considering either type of data alone. Finally, we validated 22/23 (95.7%) DMR-DEGs in 5-azadC-treated LO2 and/or HepG2 cells. In conclusion, integration of epigenome and transcriptome data depicted activation of multiple pivotal cell cycle-related pathways and repression of several metabolic pathways triggered by aberrant DNA methylation of promoters and enhancers in HCC.

Accuracy of Newer Generation IOL Power Calculation Formulas in Eyes With High Axial Myopia.

PURPOSE: To compare the accuracy of the Barrett Universal II, Emmetropia Verifying Optical (EVO), Haigis, Kane, and SRK/T formulas for intraocular lens power calculation in patients with high axial myopia. METHODS: In this retrospective study, 175 eyes (175 patients) that underwent uneventful cataract surgery were enrolled. According to the axial length (AL), the eyes were divided into long AL (26 ⩽ AL < 28 mm), super long AL (28 ⩽ AL < 30 mm), and extremely long AL (⩾ 30 mm). The mean absolute prediction errors (MAE) 3 months postoperatively and the percentage of eyes within different prediction error were compared, followed by subgroup analysis. RESULTS: The MAE and percentage of eyes within ±0.50 diopters (D) of the five formulas were as follows: Barrett Universal II (0.342, 74.9%), EVO 2.0 (0.314, 82.3%), Haigis (0.336, 74.9%), Kane (0.318, 78.9%), and SRK/T (0.398, 69.7%) (P = .552 and .071, respectively). Although no significant difference was found among the five formulas in the super and extremely long AL groups (P = .792 and .227, respectively), the EVO 2.0 formula achieved the highest accuracy (88.9%, 72 of 81) in the long AL group (P = .049). Moreover, the accuracy of the EVO 2.0 and Haigis formulas was stable, regardless of AL. The SRK/T formula showed a negative trend in the long and super long AL groups, whereas the Barrett Universal II, Kane, and SRK/T formulas showed positive trends in the extremely long AL group. CONCLUSIONS: Overall, the EVO 2.0 and Kane formulas achieved better results in patients with high axial myopia, whereas the other three formulas showed slightly poor outcomes. [J Refract Surg. 2021;37(11):754-758.].

Landscape analysis of lncRNAs shows that DDX11-AS1 promotes cell-cycle progression in liver cancer through the PARP1/p53 axis.

Although long non-coding RNAs (lncRNAs) play important roles in tumorigenesis, the underlying mechanisms are unclear. Transcriptomic analysis of 33 hepatocellular carcinoma (HCC) samples revealed that the most enriched pathway for differentially expressed genes was related to the cell cycle process, where DDX11-AS1 is the most significant lncRNA. Upregulation of DDX11-AS1 expression through demethylation was significantly associated with a poor prognosis. Further mechanistic studies revealed that DDX11-AS1 promoted the growth of HCC by interacting with PARP1 through attenuating its binding to p53, leading to downregulated expression of p53 for inhibiting the transcription of downstream genes such as p21. Knockdown of DDX11-AS1 expression in xenograft mice using anti-DDX11-AS1 oligonucleotide suppressed liver tumor proliferation. These findings indicate that DDX11-AS1 plays a role in the development of liver cancer by affecting the cell cycle.

Identification of Diagnostic Markers for Major Depressive Disorder Using Machine Learning Methods.

BACKGROUND: Major depressive disorder (MDD) is a global health challenge that impacts the quality of patients' lives severely. The disorder can manifest in many forms with different combinations of symptoms, which makes its clinical diagnosis difficult. Robust biomarkers are greatly needed to improve diagnosis and to understand the etiology of the disease. The main purpose of this study was to create a predictive model for MDD diagnosis based on peripheral blood transcriptomes. MATERIALS AND METHODS: We collected nine RNA expression datasets for MDD patients and healthy samples from the Gene Expression Omnibus database. After a series of quality control and heterogeneity tests, 302 samples from six studies were deemed suitable for the study. R package "MetaOmics" was applied for systematic meta-analysis of genome-wide expression data. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic effectiveness of individual genes. To obtain a better diagnostic model, we also adopted the support vector machine (SVM), random forest (RF), k-nearest neighbors (kNN), and naive Bayesian (NB) tools for modeling, with the RF method being used for feature selection. RESULTS: Our analysis revealed six differentially expressed genes (AKR1C3, ARG1, KLRB1, MAFG, TPST1, and WWC3) with a false discovery rate (FDR) < 0.05 between MDD patients and control subjects. We then evaluated the diagnostic ability of these genes individually. With single gene prediction, we achieved a corresponding area under the curve (AUC) value of 0.63 ± 0.04, 0.67 ± 0.07, 0.70 ± 0.11, 0.64 ± 0.08, 0.68 ± 0.07, and 0.62 ± 0.09, respectively, for these genes. Next, we constructed the classifiers of SVM, RF, kNN, and NB with an AUC of 0.84 ± 0.09, 0.81 ± 0.10, 0.73 ± 0.11, and 0.83 ± 0.09, respectively, in validation datasets, suggesting that the SVM classifier might be superior for constructing an MDD diagnostic model. The final SVM classifier including 70 feature genes was capable of distinguishing MDD samples from healthy controls and yielded an AUC of 0.78 in an independent dataset. CONCLUSION: This study provides new insights into potential biomarkers through meta-analysis of GEO data. Constructing different machine learning models based on these biomarkers could be a valuable approach for diagnosing MDD in clinical practice.

Early changes in retinal microcirculation after uncomplicated cataract surgery using an active-fluidics system.

PURPOSE: To evaluate the early changes in retinal microcirculation after uncomplicated cataract surgery using an active-fluidics system. MATERIALS AND METHODS: Patients underwent uncomplicated cataract surgery for both eyes were enrolled. The two eyes of the patients were randomly assigned to two groups, the active-fluidics group and the gravity-fluidics group. One eye using an active-fluidics system, and the other using a gravity-fluidics system. Optical coherence tomography angiography (OCTA) was performed at 1 day, 7 days, 30 days, and 90 days after surgery. RESULTS: Fifty eyes (25 patients) were included in the final analysis. A significantly lower cumulative dissipated energy (CDE), estimated fluid usage (EFU), and total aspiration time (TAT) were observed in the active-fluidics group (all P<0.05). The superficial vessel density at parafoveal region increased at 7 days and 30 days after cataract surgery in the eyes of both the active-fluidics and gravity-fluidics groups, with the fluctuation in eyes of the gravity-fluidics group more significant. The vessel density of deep capillary plexus remained stable during the follow-up period. Significant changes of retinal thickness in macular region (fovea, parafovea) were observed in eyes of the gravity-fluidics group through the comparison of corresponding values at different time points (p = 0.008, 0.005). No significant change in retinal thickness was observed in eyes of the active-fluidics. CONCLUSIONS: Retinal microcirculation and thickness were disturbed after cataract surgery using the gravity-fluidics infusion system. The active-fluidics system not only improved the surgical efficacy but also protected the retinal vasculature during cataract surgery. CLINICAL TRIALS REGISTRATION: The study has been registered at www.clinicaltrials.gov with its clinical trial accession number of NCT0130500.

Identification of LIFR, PIK3R1, and MMP12 as Novel Prognostic Signatures in Gallbladder Cancer Using Network-Based Module Analysis.

Background: Gallbladder cancer (GBC) is a rare and aggressive malignancy of the biliary tract with a dismal survival rate. Effective biomarkers and therapeutic targets are urgently needed. Methods: We analyzed gene expression profiles of GBC to identify differentially expressed genes (DEGs) and then used these DEGs to identify functional module biomarkers based on protein functional interaction (FI) networks. We further evaluated the module-gene protein expression and clinical significance with immunohistochemistry staining (IHC) in a tissue microarray (TMA) from 80 GBC samples. Results: Five functional modules were identified. Module 0 included classical cancer signaling pathways, such as Ras and PI3K-Akt; and modules 1-4 included genes associated with muscle cells, fibrinogen, extracellular matrix, and integrins, respectively. We validated the expression of LIFR, PIK3R1, and MMP12, which were hubs or functional nodes in modules. Compared with paired peritumoural tissues, we found that the expression of LIFR (P = 0.002) and PIK3R1 (P = 0.046) proteins were significantly downregulated, and MMP12 (P = 0.006) was significantly upregulated. Further prognostic analysis showed that patients with low expression of LIFR had shorter overall survival than those with high expression (log-rank test P = 0.028), the same trend as for PIK3R1 (P = 0.053) and MMP12 (P = 0.006). Multivariate analysis indicated that expression of MMP12 protein (hazard ratio [HR] = 0.429; 95% confidence interval [CI] 0.198, 0.930; P = 0.032) was one of the significant independent prognostic factors for overall survival. Conclusions: We found a highly reliable FI network, which revealed LIFR, PIK3R1, and MMP12 as novel prognostic biomarker candidates for GBC. These findings could accelerate biomarker discovery and therapeutic development in this cancer.