Shining light on chiral inorganic nanomaterials for biological issues.

The rapid development of chiral inorganic nanostructures has greatly expanded from intrinsically chiral nanoparticles to more sophisticated assemblies made by organics, metals, semiconductors, and their hybrids. Among them, lots of studies concerning on hybrid complex of chiral molecules with achiral nanoparticles (NPs) and superstructures with chiral configurations were accordingly conducted due to the great advances such as highly enhanced biocompatibility with low cytotoxicity and enhanced penetration and retention capability, programmable surface functionality with engineerable building blocks, and more importantly tunable chirality in a controlled manner, leading to revolutionary designs of new biomaterials for synergistic cancer therapy, control of enantiomeric enzymatic reactions, integration of metabolism and pathology via bio-to nano or structural chirality. Herein, in this review our objective is to emphasize current research state and clinical applications of chiral nanomaterials in biological systems with special attentions to chiral metal- or semiconductor-based nanostructures in terms of the basic synthesis, related circular dichroism effects at optical frequencies, mechanisms of induced optical chirality and their performances in biomedical applications such as phototherapy, bio-imaging, neurodegenerative diseases, gene editing, cellular activity and sensing of biomarkers so as to provide insights into this fascinating field for peer researchers.

Gene Instability-Related lncRNA Prognostic Model of Melanoma Patients via Machine Learning Strategy.

BACKGROUND: Melanoma is a common tumor characterized by a high mortality rate in its late stage. After metastasis, current treatment methods are relatively ineffective. Many studies have shown that long noncoding RNA (lncRNA) may participate in gene mutation and genomic instability in cancer. METHODS: We downloaded transcriptome data, mutation data, and clinical follow-up data of melanoma patients from The Cancer Genome Atlas. We divided samples into groups according to the number of somatic cell mutations and then performed a differential analysis to screen out the differentially expressed genes. We then divided samples into genomic unstable and genomic stable groups. We compared lncRNA expression profiles in these groups and constructed a protein-coding genes network coexpressed with selected lncRNA to analyze the pathways enriched by these genes. Two machine learning methods, least absolute shrinkage and selector operation (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), were applied to conduct the lncRNA-related prognostic model. Afterward, we performed survival analysis, risk correlation analysis, independent prognostic analysis, and clinical subgroup model validation. Finally, through wound healing assay and transwell assay, the function of AATBC was verified by A375 cell lines. RESULTS: We screened 61 prognostic-related lncRNAs and constructed an lncRNA-mRNA coexpression network based on these lncRNAs. Seven lncRNAs were selected as common characteristic factors based on the two machine learning methods. The model formula was as follows: risk score = 0.085∗AATBC + 0.190∗ AC026689.1-0.117∗AC083799.1 + 0.036∗ AC091544.6-0.039∗ LINC01287-0.291∗ SPRY4.AS1 + 0.056∗ ZNF667.AS1. The seven lncRNAs in this formula are key candidates. Cell experiments have verified that knocking down AATBC in A375 cell lines can reduce the proliferation and invasion ability of melanoma cells. CONCLUSION: The lncRNA we identified provides a new way to study lncRNA's role in the genomic instability of melanoma. Our findings may provide essential candidate biomarkers for the diagnosis and treatment of melanoma.

Identification of Keratinocyte Differentiation-Involved Genes for Metastatic Melanoma by Gene Expression Profiles.

BACKGROUND: Melanoma is the deadliest type of skin cancer. Until now, its pathological mechanisms, particularly the mechanism of metastasis, remain largely unknown. Our study on the identification of genes in association with metastasis for melanoma provides a novel understanding of melanoma. METHODS: From the Gene Expression Omnibus (GEO) database, the gene expression microarray datasets GSE46517, GSE7553, and GSE8401 were downloaded. We made use of R aiming at analyzing the differentially expressed genes (DEGs) between metastatic and nonmetastatic melanoma. R was also used in differentially expressed miRNA (DEM) data mining from GSE18509, GSE19387, GSE24996, GSE34460, GSE35579, GSE36236, and GSE54492 datasets referring to Li's study. Based on the DEG and DEM data, we performed functional enrichment analysis through the application of the DAVID database. Furthermore, we constructed the protein-protein interaction (PPI) network and established functional modules by making use of the STRING database. Through making use of Cytoscape, the PPI results were visualized. We predicted the targets of the DEMs through applying TargetScan, miRanda, and PITA databases and identified the overlapping genes between DEGs and predicted targets, followed by the construction of DEM-DEG pair network. The expressions of these keratinocyte differentiation-involved genes in Module 1 were identified based on the data from TCGA. RESULTS: 239 DEGs were screened out in all 3 datasets, which were inclusive of 21 positively regulated genes and 218 negatively regulated genes. Based on these 239 DEGs, we finished constructing the PPI network which was formed from 225 nodes and 846 edges. We finished establishing 3 functional modules. And we analyzed 92 overlapping genes and 26 miRNA, including 11 upregulated genes targeted by 11 negatively regulated DEMs and 81 downregulated genes targeted by 15 positively regulated DEMs. As proof of the differential expression of metastasis-associated genes, eleven keratinocyte differentiation-involved genes, including LOR, EVPL, SPRR1A, FLG, SPRR1B, SPRR2B, TGM1, DSP, CSTA, CDSN, and IVL in Module 1, were obviously downregulated in metastatic melanoma tissue in comparison with primary melanoma tissue based on the data from TCGA. CONCLUSION: 239 melanoma metastasis-associated genes and 26 differentially expressed miRNA were identified in our study. The keratinocyte differentiation-involved genes may take part in melanoma metastasis, providing a latent molecular mechanism for this disease.

A Systematic Review and Meta-analysis of Telephone-Based Therapy Targeting Depressive Symptoms Among Low-Income People Living with HIV.

People living with human immunodeficiency virus (PLWH) has been reported to have a high prevalence of depressive symptoms. Low-income populations account for a large proportion of PLWH, hence indicating a high level of depressive symptoms in low-income PLWH. Telephone-based therapy has been shown to be effective for treating PLWH's depressive symptoms, but its effects among low-income PLWH remain unclear. The purpose of this meta-analysis was to evaluate the effects of telephone-based therapy targeting depressive symptoms among low-income PLWH. Six databases (PubMed, EMBASE, Web of Science, China National Knowledge Infrastructure, VIP Database and Wanfang Data) were searched until May 2020 using search terms related to telephone-based therapy, depressive symptoms, and PLWH. Eight studies were included in the meta-analysis. Both postintervention effects (primary outcome) and long-term effects (secondary outcome) were evaluated using a random effects model. The meta-analysis revealed a small to moderate effect size (g = - 0.29, 95% CI - 0.51, - 0.06) on reducing depressive symptom scores (Z = 2.51, p = 0.01) in telephone-based intervention group compared with the control group at postintervention. However, there was no statistically significant long-term effects (Z = 0.77, p = 0.44) at follow-up. For postintervention effects, calculation of the I2 index indicated moderate heterogeneity (I2 = 50%); sensitivity analysis and subgroup analysis were performed to explore the source of heterogeneity. Ethnic group was classified into minority and majority which refers to most of the population were ethnic minority and majority respectively. Between-group differences were found across ethnic groups. The results suggested that there was a slightly stronger effect of telephone-based therapy in low-income PLWH than among PLWH in general, but its long-term effect requires future investigation. The effects of the intervention were better among the ethnic majority subgroups of low-income PLWH. Treatment format and intervention duration might also influence the intervention effects. However, the overall quality of evidence was low and directly impacted on the interpretation of our results, suggesting that more high-quality random controlled trial (RCT)/longitudinal studies with less selection and detection bias, less inconsistency and less indirectness are needed when applying telephone-based therapy to low-income PLWH with depressive symptoms in further studies.

RESUMEN: Se ha informado de que las personas con el virus de la inmunodeficiencia humana (PLWH) tienen un alto riesgo de síntomas depresivos, y las personas de bajos ingresos ocupan una gran proporción de PLWH. El objetivo de este análisis es evaluar los efectos de la terapia telefónica para los síntomas depresivos en personas con PLWH de bajos ingresos. Se realizaron búsquedas en seis bases de datos hasta mayo de 2020, incluidos ocho estudios. En comparación con el grupo de control, el análisis reveló que en el grupo de intervención telefónica contaba con un efecto pequeño a moderado (g = -0.29, IC 95% -0.51, -0.06) en la reducción de las puntuaciones de síntomas depresivos (Z = 2.51, p = 0.01). Sin embargo, no hubo efectos estadísticamente significativos a largo plazo (Z = 0.77, p = 0.44) en el seguimiento. Se encontraron diferencias entre grupos desde los grupos étnicos. Los resultados mostraron que el efecto de la terapia telefónica era levemente más fuerte que el de PLWH general en las PLWH de bajos ingresos, pero la evidencia general de baja calidad impactó en la interpretación de nuestros resultados.

The effects of beta-blocker use on cancer prognosis: a meta-analysis based on 319,006 patients.

BACKGROUND: Beta-blockers are antihypertensive drugs and have shown potential in cancer prognosis. However, this benefit has not been well defined due to inconsistent results from the published studies. METHODS: To investigate the association between administration of beta-blocker and cancer prognosis, we performed a meta-analysis. A literature search of PubMed, Embase, Cochrane Library, and Web of Science was conducted to identify all relevant studies published up to September 1, 2017. Thirty-six studies involving 319,006 patients were included. Hazard ratios were pooled using a random-effects model. Subgroup analyses were conducted by stratifying ethnicity, duration of drug use, cancer stage, sample size, beta-blocker type, chronological order of drug use, and different types of cancers. RESULTS: Overall, there was no evidence to suggest an association between beta-blocker use and overall survival (HR=0.94, 95% CI: 0.87-1.03), all-cause mortality (HR=0.99, 95% CI: 0.94-1.05), disease-free survival (HR=0.59, 95% CI: 0.30-1.17), progression-free survival (HR=0.90, 95% CI: 0.79-1.02), and recurrence-free survival (HR=0.99, 95% CI: 0.76-1.28), as well. In contrast, beta-blocker use was significantly associated with better cancer-specific survival (CSS) (HR=0.78, 95% CI: 0.65-0.95). Subgroup analysis generally supported main results. But there is still heterogeneity among cancer types that beta-blocker use is associated with improved survival among patients with ovarian cancer, pancreatic cancer, and melanoma. CONCLUSION: The present meta-analysis generally demonstrates no association between beta-blocker use and cancer prognosis except for CSS in all population groups examined. High-quality studies should be conducted to confirm this conclusion in future.

The epidermal growth factor tyrosine kinase inhibitor AG1478 and erlotinib reverse ABCG2-mediated drug resistance.

ABCG2 is an important member of ATP-binding cassette (ABC) transporter shown to confer drug resistance in cancer cells. Recent studies show that an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI), gefitinib, is able to modulate the function of ABCG2 and reverse ABCG2-mediated multidrug resistance (MDR) in cancer cells. Additionally, ABCG2 expression has been shown to impact treatment efficacy and development of side-effects in patients receiving gefitinib. However, it is unclear whether other EGFR TKIs interact with ABCG2 in a similar manner. In the present study, we investigated the interaction of two other EGFR TKIs, AG1478 and erlotinib, with ABCG2. Our data show that AG1478 and erlotinib potently sensitized drug-resistant cells overexpressing either wild-type or mutated ABCG2 to the ABCG2 substrate anti-cancer drugs flavopiridol and mitoxantrone. Neither AG1478 nor erlotinib sensitized ABCG2-overexpressing cells to drugs that are not substrates of ABCG2 nor did they impact drug sensitivity of parental cells. Furthermore, AG1478 and erlotinib were able to significantly enhance the intracellular accumulation of mitoxantrone in cells expressing either wild-type or mutated ABCG2. Additionally, they did not alter the protein expression of ABCG2 in the ABCG2-overexpressing cells. Taken together, we conclude that AG1478 and erlotinib potently reverse ABCG2-mediated MDR through directly inhibiting the drug efflux function of ABCG2 in the ABCG2-overexpressing cells. These results will be useful in the development of novel and more effective EGFR TKIs as well as the development of combinational chemotherapeutic strategies.