Disrupted topologic efficiency of brain functional connectome in de novo Parkinson's disease with depression.

Growing evidence supports that depression in Parkinson's disease (PD) depends on disruptions in specific neural networks rather than regional dysfunction. According to the resting-state functional magnetic resonance imaging data, the study attempted to decipher the alterations in the topological properties of brain networks in de novo depression in PD (DPD). The study also explored the neural network basis for depressive symptoms in PD. We recruited 20 DPD, 37 non-depressed PD and 41 healthy controls (HC). The Graph theory and network-based statistical methods helped analyse the topological properties of brain functional networks and anomalous subnetworks across these groups. The relationship between altered properties and depression severity was also investigated. DPD revealed significantly reduced nodal efficiency in the left superior temporal gyrus. Additionally, DPD decreased five hubs, primarily located in the temporal-occipital cortex, and increased seven hubs, mainly distributed in the limbic cortico-basal ganglia circuit. The betweenness centrality of the left Medio Ventral Occipital Cortex was positively associated with depressive scores in DPD. In contrast to HC, DPD had a multi-connected subnetwork with significantly lower connectivity, primarily distributed in the visual, somatomotor, dorsal attention and default networks. Regional topological disruptions in the temporal-occipital region are critical in the DPD neurological mechanism. It might suggest a potential network biomarker among newly diagnosed DPD patients.

Prediction of Ki-67 expression in gastrointestinal stromal tumors using radiomics of plain and multiphase contrast-enhanced CT.

OBJECTIVE: To study the value of radiomics models based on plain and multiphase contrast-enhanced CT to predict Ki-67 expression in gastrointestinal stromal tumors (GISTs). METHODS: A total of 215 patients with GISTs were retrospectively analyzed, including 150 patients in one hospital as the training set and 65 patients in another hospital as the external verification set. The tumor at the largest level of CT images was delineated as the region of interest (ROI). The maximum diameter of the ROI was defined as the tumor size. A total of 851 radiomics features were extracted from each ROI by 3D Slicer Radiomics. After dimensionality reduction, three machine learning classification algorithms including logistic regression (LR), random forest (RF), and support vector machine (SVM) were used for Ki-67 expression prediction. Using a multivariable logistic model, a nomogram was established to predict the expression of Ki-67 individually. RESULTS: Delong tests showed that the SVM models had the highest accuracy in the arterial phase (Z value 0.217-1.139) and venous phase (Z value 0.022-1.396). For the plain phase, LR and SVM models had the highest accuracy (Z value 0.874-1.824, 1.139-1.763). For the delayed phase, LR models had the highest accuracy (Z value 0.056-1.824). For the combined phase, RF models had the highest accuracy (Z value 0.232-1.978). There was no significant difference among the above models for KI-67 expression prediction (Z value 0.022-1.978). A nomogram was developed with a C-index of 0.913 (95% CI, 0.878 to 0.956). CONCLUSIONS: Radiomics of both plain and enhanced CT images could accurately predict the expression of Ki-67 in GIST. For patients who were not suitable to use contrast agents, plain scan could be used as an alternative. CLINICAL RELEVANCE STATEMENT: CT radiomics could accurately predict the expression of Ki-67 in GIST, which has a great clinical value in reflecting the proliferative activity of tumor cells and helping determine whether a patient is suitable for adjuvant therapy with imatinib. KEY POINTS: • Radiomics of both plain and enhanced CT images could accurately predict the expression of Ki-67 in GIST. • For patients who were not suitable to use contrast agents, plain scan could be used as an alternative. • A radiomics nomogram was developed to allow personalized preoperative evaluation with high accuracy.

MFAP2 enhances cisplatin resistance in gastric cancer cells by regulating autophagy.

Background: Cisplatin (CDDP) is of importance in cancer treatment and widely used in advanced gastric cancer (GC). However, its clinical usage is limited due to its resistance, and the regulatory mechanism of CDDP resistance in GC has not yet been fully elucidated. In this study, we first conducted a comprehensive study to investigate the role of MFAP2 through bioinformatics analysis. Methods: The Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were applied to downloadgene expression data and clinicopathologic data, and the differentially expressed genes (DEGs) were further analyzed. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and survival analysis were conducted. Furthermore, according to the clinicopathological characteristics of TCGA, clinical correlation analysis was conducted, and a receiver operating characteristic curve (ROC) was plotted. Results: We revealed that FAP, INHBA and MFAP2 were good diagnostic factors of GC. However, the mechanism of MFAP2 in GC remains elusive, especially in the aspect of chemotherapy resistance. We developed the CDDP-resistant cell line, and found that MFAP2 was upregulated in CDDP-resistant cells, and MFAP2-knockdown improved CDDP sensitivity. Finally, we found that MFAP2 enhanced CDDP resistance by inducing autophagy in drug-resistant cell lines. Conclusions: The above results suggested that MFAP2 could affect the chemotherapy resistance by altering the level of autophagy in GC patients as a potential therapeutic target.

Monitoring Substantia Nigra Degeneration Using Free Water Imaging across Prodromal and Clinical Parkinson's Disease.

BACKGROUND: Substantia nigra (SN) free water has been suggested as a good surrogate marker in Parkinson's disease (PD). However, its usefulness for diagnosing prodromal PD (pPD) and monitoring disease progression warrants further validation. OBJECTIVE: The aim was to investigate SN free water values across prodromal and clinical stages of PD. METHODS: Four groups were enrolled in this study: 48 healthy controls (HC), 43 pPD patients, 50 de novo PD (dnPD) patients, and 49 medicated PD (mPD) patients. Based on diffusion tensor images, free water maps were calculated, and SN free water values were extracted from the anterior SN (ASN) and posterior SN (PSN). The SN free water values were compared among the four groups, and associations between free water and clinical symptoms were explored. The distinguishing power of PSN free water was evaluated using the receiver operating characteristic curve analysis. Follow-up was performed for 14 pPD patients. RESULTS: PSN free water in the pPD group was significantly higher than that in the HC group and significantly lower than that in the dnPD group. Surprisingly, the mPD group showed decreased PSN free water compared to the dnPD group. There was a positive correlation between motor symptoms and PSN free water in the pPD and dnPD groups. Longitudinal analysis showed a significant increase in PSN free water in pPD patients over time. CONCLUSIONS: The PSN free water increased from prodromal to early clinical stages, but the trend might be reversed in late disease stages. This biphasic trend should be considered when applying this marker in future studies. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Association of GBA genotype with motor and cognitive decline in Chinese Parkinson's disease patients.

Objective: Variants in the glucocerebrosidase (GBA) gene are the most common and significant risk factor for Parkinson's disease (PD). However, the impact of GBA variants on PD disease progression in the Chinese population remains unclear. This study aimed to explore the significance of GBA status on motor and cognitive impairment in a longitudinal cohort of Chinese patients with PD. Methods: The entire GBA gene was screened by long-range polymerase chain reaction (LR-PCR) and next generation sequencing (NGS). A total of 43 GBA-related PD (GBA-PD) and 246 non-GBA-mutated PD (NM-PD) patients with complete clinical data at baseline and at least one follow-up were recruited for this study. The associations of GBA genotype with rate of motor and cognitive decline, as measured by Unified PD Rating Scale (UPDRS) motor and Montreal Cognitive Assessment (MoCA), were assessed by linear mixed-effect models. Results: The estimated (standard error, SE) UPDRS motor [2.25 (0.38) points/year] and MoCA [-0.53 (0.11) points/year] progression rates in the GBA-PD group were significantly faster than those in the NM-PD group [1.35 (0.19); -0.29 (0.04) points/year; respectively]. In addition, the GBA-PD group showed significantly faster estimated (SE) bradykinesia [1.04 (0.18) points/year], axial impairment [0.38 (0.07) points/year], and visuospatial/executive [-0.15 (0.03) points/year] progression rates than the NM-PD group [0.62 (0.10); 0.17 (0.04); -0.07 (0.01) points/year; respectively]. Conclusion: GBA-PD is associated with faster motor and cognitive decline, specifically greater disability in terms of bradykinesia, axial impairment, and visuospatial/executive function. Better understanding of GBA-PD progression may help predict prognosis and improve clinical trial design.

P4HA3 promotes clear cell renal cell carcinoma progression via the PI3K/AKT/GSK3ß pathway.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma. P4HA3 is a key enzyme in collagen biosynthesis and has emerged as important molecules in regulation of proliferation, invasion, and metastasis in various tumor types. The role of P4HA3 in the development of ccRCC has remained to be elucidated. Genes expression, prognostic, and enrichment analyses were carried out with bioinformatics analysis. The efficiency of P4HA3 knockdown was confirmed by real-time quantitative PCR and Western blotting. The cellular functions were analyzed by CCK-8, EdU, wound healing, and transwell assays. The levels of related proteins expression were analyzed by Western blotting. P4HA3 was highly expressed in ccRCC compared with normal tissue samples from the TCGA database. Kaplan-Meier curves results showed that the expression level of P4HA3 was significantly negatively correlated with overall survival of patients. P4HA3 expression knockdown inhibited the proliferation, migration, and invasion of ccRCC cells, as demonstrated by in vitro experiments. In addition, GSEA results revealed that P4HA3 may be related to EMT and involved in the PI3K-AKT-GSK3ß pathway in ccRCC; this was tentatively confirmed through Western blotting. P4HA3 may induce ccRCC progression via the PI3K-AKT-GSK3ß signaling pathway and could represent a potential therapeutic target.

Pan-cancer analysis based on epigenetic modification explains the value of HJURP in the tumor microenvironment.

To analyze the expression levels, prognostic value and immune infiltration association of Holliday junction protein (HJURP) as well as its feasibility as a pan-cancer biomarker for different cancers. The Protter online tool was utilized to obtain the localization of HJURP, then the methylation of HJURP in tumors were further explored. Thereafter, the mRNA data and clinical characteristics of 33 tumor types from TCGA database were obtained to investigate the expression and prognostic relationship of HJURP in different tumor types. Finally, the composition pattern and immune infiltration of HJURP in different tumors were detected in Tumor Immune Estimation Resource. HJURP was abnormally expressed in most of the cancer types and subtypes in TCGA database. Also, it was associated with poor prognosis of different cohorts. At the same time, the results also showed that HJURP was related to tumor immune evasion through different mechanisms, including T cell rejection and methylation in different cancer types. Besides, the methylation of HJURP was inversely proportional to mRNA expression levels, which mediated the dysfunctional phenotypes of T cells and poor prognosis of different cancer types. Alternatively, our results indicated that HJURP expression was associated with immune cell infiltration in a variety of cancers. HJURP may serve as an oncogenic molecule, and its expression and immune infiltration characteristics can be used as a biomarker for cancer detection, prognosis, treatment design and follow-up.

High CENPA expression in papillary renal cell carcinoma tissues is associated with poor prognosis.

OBJECTIVE: This work focused on investigating the relation of centromeric protein A (CENPA) gene expression with prognosis of papillary renal cell carcinoma (PRCC). METHODS: We obtained data from PRCC cases in TCGA. Thereafter, CENPA levels between the paired PRCC and matched non-carcinoma samples were analyzed by Wilcoxon rank-sum test, while the relations of clinicopathological characteristics with CENPA level were examined by logistic regression and Wilcoxon rank-sum test. The prognostic value of CENPA was assessed by plotting the receiver operating feature curve (ROC) and calculating the value of area under curve (AUC). In addition, relations between clinicopathological characteristics and PRCC survival were analyzed through Kaplan-Meier (KM) and Cox regression analyses. After dividing the total number of patients into the trial cohort and the validation cohort in a ratio of 7:3, we constructed a nomogram in trial cohort according to multivariate Cox regression results for predicting how CENPA affected patient survival and used the calibration curve to verify its accuracy in both cohorts. We also determined CENPA levels within cancer and matched non-carcinoma samples through immunohistochemistry (IHC). Finally, we utilized functional enrichment for identifying key pathways related to differentially expressed genes (DEGs) between PRCC cases with CENPA up-regulation and down-regulation. RESULTS: CENPA expression enhanced in PRCC tissues compared with healthy counterparts (P < 0.001). CENPA up-regulation was related to pathological TNM stage and clinical stage (P < 0.05). Meanwhile, the ROC curves indicated that CENPA had a remarkable diagnostic capacity for PRCC, and the expression of CENPA can significantly improve the predictive accuracy of pathological TNM stage and clinical stage for PRCC. As revealed by KM curves, PRCC cases with CENPA up-regulation were associated with poor survival compared with those with CENPA down-regulation (Risk ratio, RR = 3.07, 95% CI: 1.58-5.97, P = 0.001). In the meantime, univariate as well as multivariate analysis showed an independent association of CENPA with overall survival (OS, P < 0.05) and the nomogram demonstrated superior predictive ability in both cohorts. IHC analysis indicated that PRCC cases showed an increased CENPA positive rate compared with controls. As revealed by functional annotations, CENPA was enriched into pathways associated with neuroactive ligand receptor interactions, cytokine receptor interactions, extracellular matrix regulators, extracellular matrix glycoproteins and nuclear matrisome. CONCLUSION: CENPA expression increases within PRCC samples, which predicts dismal PRCC survival. CENPA may become a molecular prognostic marker and therapeutic target for PRCC patients.

Identification of a chromatin regulator signature and potential prognostic ability for adrenocortical carcinoma.

Objective: Adrenocortical carcinoma (ACC) is a rare malignant tumor. Chromatin regulators (CRs) can drive epigenetic changes, which have been considered as one of the most vital hallmarks of tumors. This study aimed to explore the CR signature for ACC in order to clarify the molecular basis of ACC's pathogenic mechanism and provide novel methods to diagnose and treat ACC clinically. Methods: This study obtained transcriptome sequencing datasets of ACC patients and sequencing data on normal adrenal tissues in TCGA and GTEx databases, respectively. Meanwhile, prognostic genes were selected through Lasso and Cox regression analyses. Using the transcriptome sequencing datasets of ACC patients downloaded from the GEO database to finish validation, we performed Kaplan-Meier (KM) analysis for evaluating the differential survival between low- and high-risk groups. Then, this work constructed the risk model for predicting ACC prognosis. TIMER 2.0 was employed to assess the differences in immune infiltration between the two groups. Furthermore, this work adopted the R package "pRRophetic" for exploring and estimating the sensitivity of patients to different chemotherapeutic agents. Results: A 5-CR model was established to predict ACC survival, and the CR signature was confirmed as a factor in order to independently predict ACC patient prognosis. In addition, a nomogram composed of the risk score and clinical T stage performed well in the prediction of patients' prognosis. Differentially expressed CRs (DECRs) were mostly associated with the cell cycle, base excision repair, colon cancer, gene duplication, homologous recombination, and other signaling pathways for the high-risk group. As for the low-risk group, DECRs were mainly enriched in allograft rejection, drug metabolism of cytochrome P450, metabolism of xenogeneic organisms by cytochrome P450, retinol metabolism, and other signaling pathways. According to TIMER analysis, the immune infiltration degrees of endothelial cells, M2 macrophages, myeloid dendritic cells, CD4+ Th1 cells, NKT cells, and M0 macrophages showed significant statistical differences between the high- and low-risk groups, and high infiltration levels of M0 and M2 macrophages were more pronounced in higher T stage (T3 and T4), N stage (N1), and clinical stages (III and IV). In addition, high-risk cases exhibited higher sensitivity to etoposide and doxorubicin. Additionally, low-risk patients had significantly decreased expression of RRM1 compared with high-risk cases, suggesting the better effect of mitotane treatment. Conclusion: This study identified the DECRs, which might be related to ACC genesis and progression. The pathways enriched by these DECRs were screened, and these DECRs were verified with excellent significance for estimating ACC survival. Drug sensitivity analysis also supported the current clinical treatment plan. Moreover, this study will provide reliable ideas and evidence for diagnosing and treating ACC in the clinic.

Exploration of Core Genes in ACTH-Independent Macronodular Adrenal Hyperplasia.

This study explores the core genes involved in the pathogenesis of ACTH-independent macronodular adrenal hyperplasia (AIMAH), so as to provide robust biomarkers for the clinical diagnosis and treatment of this disease. Gene Expression Omnibus (GEO) database was used to obtain GSE25031 microarray dataset. R package "limma" was applied to identify differentially expressed genes (DEGs) between AIMAH and normal samples. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was employed to perform Gene Ontology (GO) annotation for the DEGs, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted. A protein-protein interaction network (PPI) was constructed using the STRING online website and visualized using the Cytoscape software. The key modules and hub genes were then identified. Finally, Gene Set Enrichment Analysis (GESA) enrichment analysis was carried out to find the signaling pathways of significant clinical value in AIMAH. A total of 295 DEGs between AIMAH and healthy samples were screened out, including 164 upregulated genes and 131 downregulated genes. Combining enrichment analysis and PPI network construction, there were 5 signifiant pathways and 10 hub genes, among which 3 genes (FOS, FOSB, and DUSP1) were identified as potential core genes of clinical significance in AIMAH. In conclusion, the 3 core genes, FOS, FOSB, and DUSP1, identified here might be potential biomarkers for AIMAH, and the current study is of guiding significance for clinical diagnosis and treatment of this disease.

Prevalence and genotype-phenotype correlations of GBA-related Parkinson disease in a large Chinese cohort.

BACKGROUND AND PURPOSE: Variants in the glucocerebrosidase (GBA) gene are recognized as a common and important genetic risk factor for Parkinson disease (PD). However, the impact of variant severity on the clinical phenotype of PD in the Chinese population remains unclear. Thus, the present study aimed to determine the frequency of GBA-related PD (GBA-PD) and the relationship of GBA variant severity with clinical characteristics in a large Chinese cohort. METHODS: Long-range polymerase chain reaction and next generation sequencing were performed for the entire GBA gene. GBA variant severity was classified into five classes: mild, severe, risk, complex, and unknown. RESULTS: Among the total 737 PD patients, 47 GBA variants were detected in 79 (10.72%) patients, and the most common GBA variants were R163Q, L444P, and R120W. Complete demographic and clinical data were obtained for 673 patients, which revealed that 18.50% of early onset PD patients had GBA variants. Compared with patients without GBA variants, GBA-PD patients experienced PD onset an average of 4 years earlier and had more severe motor and nonmotor symptoms. Patients carrying severe and complex variants had a higher burden of nonmotor symptoms, especially depression, and more mood/cognitive and gastrointestinal symptoms than patients carrying mild variants. CONCLUSIONS: GBA-PD is highly prevalent in the Chinese population. The severity of GBA variants underlies distinct phenotypic spectrums, with PD patients carrying severe and complex variants seeming to have similar phenotypes. PD patient stratification by GBA variant severity should become a prerequisite for selecting specific treatments.

Subjective Cognitive Complaints in Newly-Diagnosed Parkinson's Disease With and Without Mild Cognitive Impairment.

Background: Subjective cognitive complaints (SCCs) and mild cognitive impairment (MCI) are common among patients with Parkinson's disease (PD). However, the relationship between SCCs and MCI is not well understood. Herein, we aimed to investigate whether there are any differences in the prevalence and risk factors of SCCs between early PD patients with and without MCI. Methods: Overall, 108 newly diagnosed, untreated PD patients underwent comprehensive neuropsychological assessments. PD patients with mild cognitive impairment (PD-MCI) were diagnosed according to the MCI level II criteria. Furthermore, SCCs were measured with the Cognitive Complaints Interview (CCI). Logistic regression analysis, after adjusting for confounding variable, was performed in order to investigate risk factors of SCCs in PD-MCI patients and PD patients with normal cognition (PD-NC). Results: Furthermore, 42 (42.3%) participants reported SCCs and 53 (53.5%) participants were diagnosed with PD-MCI. The prevalence of SCCs in PD-MCI and PD-NC participants was 30.3% and 12.1%, respectively. Logistic regression analyses revealed that the presence of SCCs in PD-MCI group was significantly associated with Non-Motor Symptoms Questionnaire (NMSQ) score (OR = 1.340, 95%CI = 1.115-1.610, p = 0.002), while the presence of SCCs in PD-NC group was significantly associated with time of Stroop Color-Word Test card C (OR = 1.050, 95%CI = 1.009-1.119, p = 0.016). Conclusion: SCCs are frequent among patients with early PD. The prevalence and risk factor of SCCs are distinct in PD with and without MCI. These findings suggest that SCCs in early PD with different cognitive status appear to have different pathogenicity.

Single-Cell Sequencing to Identify Six Heat Shock Protein (HSP) Genes-Mediated Progression Subtypes of Clear Cell Renal Cell Carcinoma.

BACKGROUND: Heat shock proteins (HSPs) are widely involved in tumor occurrence and development and are prognostic markers for multiple tumors. However, the role of HSPs in clear cell renal cell carcinoma (ccRCC) remains unclear. METHODS: We used Cytoscape to identify hub genes in the ccRCC single-cell sequencing data set from the Gene Expression Omnibus (GEO) data repository. We identified subtypes, C1 and C2, of The Cancer Genome Atlas (TCGA) patients based on the expression of hub genes using unsupervised consensus clustering. Principal component analysis (PCA) was used to verify the clustering differences, and Kaplan-Meier (K-M) estimate was used to verify the survival differences between C1 and C2 patients. We used TIMER 2.0 and CIBERSORT to evaluate the immune cell infiltration of HSP genes and C1 and C2 patients. The R package "pRRophetic" was used to evaluate the sensitivity in C1 and C2 patients to the four first-line treatment drugs. RESULTS: We identified six hub genes (HSP90AA1, HSPH1, HSPA1B, HSPA8, and HSPA1A) encoding HSP, five of which were significantly downregulated in TCGA group, and four had a protective effect on prognosis (p <0.05). Survival analysis showed that C1 patients had a better overall survival (p <0.001). TIMER 2.0 analysis showed that three HSP genes were significantly correlated with the infiltration of CD4+ T cells and CD4+ Th1 cells (|cor|>0.5, p<0.001). CIBERSORT showed significant differences in multiple infiltrating immune cells between C1 and C2 patients. Meanwhile, the expression of PD1 was significantly lower in C1 patients than in C2 patients, and the expression of PDL1 is the another way around. Drug sensitivity analysis showed that C1 patients were more sensitive to sorafenib, pazopanib, and axitinib (p <0.001). CONCLUSION: Our research revealed two molecular subtypes of ccRCC based on 6 HSP genes, and revealed significant differences between the two subtypes in terms of clinical prognosis, immune infiltration, and drug sensitivity.

Development and Validation of Epigenetic Modification-Related Signals for the Diagnosis and Prognosis of Hepatocellular Carcinoma.

BACKGROUND: Increasing evidence has indicated that abnormal epigenetic factors such as RNA m6A modification, histone modification, DNA methylation, RNA binding proteins and transcription factors are correlated with hepatocarcinogenesis. However, it is unknown how epigenetic modification-associated genes contribute to the occurrence and clinical outcome of hepatocellular carcinoma (HCC). Thus, we constructed the epigenetic modification-associated models that may enhance the diagnosis and prognosis of HCC. METHODS: In this study, we focused on the clinical value of epigenetic modification-associated genes for HCC. Our gene expression data were collected from TCGA and HCC data sets from the GEO database to ensure the reliability of the data. Their functions were analyzed by bioinformatics methods. We used lasso regression, Support vector machine (SVM), logistic regression and Cox regression to construct the diagnostic and prognostic models. We also constructed a nomogram of the practicability of the above-mentioned prognostic model. The above results were verified in an independent liver cancer data set from the ICGC database and clinical samples. Furthermore, we carried out pan-cancer analysis to verify the specificity of the above model and screened a wide range of drug candidates. RESULTS: Many epigenetic modification-associated genes were significantly different in HCC and normal liver tissues. The gene signatures showed a good ability to predict the occurrence and survival of HCC patients, as verified by DCA and ROC curve analysis. CONCLUSION: Gene signatures based on epigenetic modification-associated genes can be used to identify the occurrence and prognosis of liver cancer.

Puerarin induces apoptosis in prostate cancer cells via inactivation of the Keap1/Nrf2/ARE signaling pathway.

In this study, we examined the antitumor effects of Puerarin (PEU) on androgen-independent (DU145 and PC-3) and androgen-dependent (LNCaP) prostate cancer cells, and explored its potential mechanisms. Supplement with PEU (2.5 µM, 5 µM, and 10 µM) exhibited a marked inhibitory effect against the growth of DU145 and PC-3 cells, especially beyond 24 h, whereas there is only slight growth inhibitory effect on LNCaP cells at the high concentration of 10 µM at 72 h. This loss of cell viability in DU145 and PC-3 cells by PEU was mediated by the induction of apoptosis via up-regulation of Bax and cleaved-caspase-3, but downregulation of Bcl-2. Moreover, more intracellular ROS and LDH production were observed in DU145 and PC-3 cells upon PEU treatment. Meanwhile, the amount of pro-inflammatory cytokines (IL-1ß and IL-6) was increased, but the content of anti-inflammatory cytokines IL-10 was attenuated. Additionally, PEU pretreatment resulted in an increase of Keap1 protein expression, and a decline of Nrf2, HO-1 and NQO1 protein expression in DU145 and PC3 cells. The present findings indicated that PEU exerted its antitumor activities toward androgen-independent prostate cancer cells via inactivation of Keap1/NrF2/ARE signaling pathway.

Identification of a 6-Gene Signature Associated with Resistance to Tyrosine Kinase Inhibitors: Prognosis for Clear Cell Renal Cell Carcinoma.

BACKGROUND Tyrosine kinase inhibitors (TKIs) are used to treat metastatic disease associated with clear cell renal cell carcinoma (ccRCC); however, most patients develop resistance after 6 to 15 months. As such, identifying biomarkers of TKI resistance may be useful for prognosis. MATERIAL AND METHODS We analyzed ChIP-seq data related to TKI resistance from the Gene Expression Omnibus and RNA-Seq and clinical data from The Cancer Genome Atlas database. We used univariate Cox analysis and Cox regression/Lasso analysis to determine a risk score. The Kaplan-Meier estimate and receiver operating characteristic curve verified the risk score's sensitivity and specificity. The stratified analysis and the univariate and multivariate analyses revealed its predictive power. We predicted survival time by constructing a nomogram. RESULTS Of the 32 differentially expressed genes (DEGs) related to TKI resistance, 6 (ACE2, MMP24, SLC44A4, C1R, C1ORF194, ADAMTS15) were used to establish a risk score. Kaplan-Meier analysis showed that high-risk patients had shorter median survival times than low-risk patients, notably among those with metastatic disease (1.51 vs. 4.55 years). The stratified analysis revealed that patients with advanced disease had relatively higher risk scores than patients at early stages (P<0.001). Univariate analysis independently associated the 6-DEGs signature with the prognosis of metastatic ccRCC (hazard ratio, 1.217; 95% confidence interval, 1.090-1.358). The nomogram we constructed based on 6-DEGs signature and clinical parameters predicted survival time accurately. CONCLUSIONS We identified a 6-DEGs signature that permitted us to establish a risk score related to TKI resistance that can serve as a reliable biomarker for predicting the survival of patients with ccRCC.

Ultrasound-mediated nanobubble destruction (UMND) facilitates the delivery of VEGFR2-targeted CD-TK-loaded cationic nanobubbles in the treatment of bladder cancer.

BACKGROUND: The CD-TK double suicide gene has become an effective therapy for bladder cancer. A novel molecular-targeted ultrasound (US) method has been developed to precisely guide nanobubbles loaded with this gene to regions within bladder tumor cells and is widely used due to its efficiency in delivering drugs to the target tumor. METHODS: Uniform nanoscaled nanobubbles loaded with CD-TK double suicide gene were developed using a thin-film hydration sonication, carbodiimide chemistry approaches, and electrostatic adsorption methods. RESULTS: In the present study, we synthesized CD-TK double suicide gene-loaded cationic nanobubbles conjugated with anti-VEGFR2 that can bind with VEGFR2-positive cells. Fluorescence and flow cytometry evidence show that CD-TK double suicide gene-loaded nanobubbles were successfully developed. CD-TK-CNBs delivered via US-mediated nanobubble destruction (UMND) enhanced transfection efficiency, overexpression of CD-TK double suicide gene, and tumor cell apoptosis, and inhibited tumor cell growth in vitro. CONCLUSIONS: These CD-TK-CNBs may become a novel treatment for bladder cancer.

TMEM16A as a Potential Biomarker in the Diagnosis and Prognosis of Lung Cancer.

BACKGROUND: Transmembrane protein 16A (TMEM16A), also known as ANO1 (anoctamin-1), was reported to be vital in the growth and invasion of several malignancies. However, role of TMEM16A in lung cancer remained unclear. The aim of this study was to evaluate the expression of TMEM16A and its significance in lung cancer. METHODS: qRT-PCR and Western blots were performed to evaluate the TMEM16A mRNA and protein expression. Proliferation and invasion of H1299 cancer cells were evaluated by CCK-8 and transwell assays. Tumor volumes in nude mice implanted with H1299 cells were assessed once every week for 5 weeks by measuring 2 perpendicular dimensions. Immunofluorescent staining revealed expression of TMEM16A in nude mice cancer tissues. RESULTS: Our findings provided compelling evidence that TMEM16A production in H1299 cells is 2.1 times higher than observations in HBE16 cells. We showed that overexpression of TMEM16A contributed to the proliferation of H1299 cells. Moreover, T16Ainh-A01, a specific TMEM16A inhibitor or shRNA targeting TMEM16A somewhat inhibited lung tumor cell growth and invasion as evident from in vitro studies and from in vivo xenograft-tumor growth. Inhibition of TMEM16A strongly suppressed EGFR phosphorylation and growth of lung cancer cells. Furthermore, a reduction of p-RAS and p-ERK1/2 was also observed. CONCLUSION: TMEM16A promoted growth and invasion in lung cancer cells via an EGFR/ MAPK-dependent signaling pathway. So we infer TMEM16A membrane protein may have potential to serve as a biomarker in lung cancer.