High expression of PD-L1 mainly occurs in non-small cell lung cancer patients with squamous cell carcinoma or poor differentiation.

Background: Lung cancer is one of the most lethal cancers worldwide, but studies have shown that the higher the expression of programmed cell death protein 1 ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC), the more likely it will benefit from anti-PD-L1 immunotherapy. The purpose of our study was to collect and analyze abundant clinical samples in order to provide evidence for clinicians and patients who might consider anti-PD-L1 immunotherapy while jointly formulating treatment plans. Methods: On the one hand, we obtained cases from The Cancer Genome Atlas (TCGA) database, including 498 lung squamous cell cancer (LUSC) patients and 515 lung adenocarcinoma (LUAD) patients. We studied the lung caner driver gene in LUSC and LUAD. On the other hand, PD-L1 expression was detected in lung cancer tissues of 1,008 NSCLC patients with immunohistochemistry staining (IHC), and we studied the correlation between PD-L1 protein expression and clinicopathological characteristics. Results: PD-L1 expression was higher in LUSC than in LUAD at the mRNA level. In univariate analysis, PD-L1 expression at the protein level was higher in patients who were males, were LUSC, were smokers, had a tumor diameter >3 cm, had poor differentiation, or had stages III~IV disease. In multivariate analysis, PD-L1 expression was higher in patients who were LUSC or in poor differentiation. Conclusion: In term of protein level, PD-L1 expression was higher in NSCLC patients who were LUSC or in poor differentiation. We recommend that PD-L1 IHC detection can be routinely performed in such populations that are likely to benefit most from PD-L1 immunotherapy.

Principle and Application of Frequency-Domain Characteristic Analysis of Fractional-Order Memristor.

Scaling fractional-order memristor circuit is important for realizing a fractional-order memristor. However, the effective operating-frequency range, operation order, and fractional-order memristance of the scaling fractional-order memristor circuit have not been studied thoroughly; that is, the fractional-order memristance in the effective operating-frequency range has not been calculated quantitatively. The fractional-order memristance is a similar and equally important concept as memristance, memcapacitance, and meminductance. In this paper, the frequency-domain characteristic-analysis principle of the fractional-order memristor is proposed based on the order- and F-frequency characteristic functions. The reasons for selecting the order- and F-frequency characteristic functions are explained. Subsequently, the correctness of the frequency-domain characteristic analysis using the order- and F-frequency characteristic functions is verified from multiple perspectives. Finally, the principle of the frequency-domain characteristic analysis is applied to the recently realized chain-scaling fractional-order memristor circuit. The results of this study indicate that the principle of the frequency-domain characteristic analysis of the fractional-order memristor can successfully calculate the fractional-order memristance of the chain-scaling fractional-order memristor circuit. The proposed principle of frequency-domain characteristic analysis can also be applied to mem-elements, such as memristors, memcapacitors, and meminductors. The main contribution of this study is the principle of the frequency-domain characteristic analysis of the fractional-order memristor based on the order- and F-frequency characteristic functions.

Statistical Methods for Microbiome Compositional Data Network Inference: A Survey.

Microbes can be found almost everywhere in the world. They are not isolated, but rather interact with each other and establish connections with their living environments. Studying these interactions is essential to an understanding of the organization and complex interplay of microbial communities, as well as the structure and dynamics of various ecosystems. A widely used approach toward this objective involves the inference of microbiome interaction networks. However, owing to the compositional, high-dimensional, sparse, and heterogeneous nature of observed microbial data, applying network inference methods to estimate their associations is challenging. In addition, external environmental interference and biological concerns also make it more difficult to deal with the network inference. In this article, we provide a comprehensive review of emerging microbiome interaction network inference methods. According to various research targets, estimated networks are divided into four main categories: correlation networks, conditional correlation networks, mixture networks, and differential networks. Their assumptions, high-level ideas, advantages, as well as limitations, are presented in this review. Since real microbial interactions can be complex and dynamic, no unifying method has, to date, captured all the aspects of interest. In addition, we discuss the challenges now confronting current microbial interaction study and future prospects. Finally, we point out several feasible directions of microbial network inference analysis and highlight that future research requires the joint promotion of statistical computation methods and experimental techniques.

Single-cell RNA-seq data semi-supervised clustering and annotation via structural regularized domain adaptation.

MOTIVATION: The rapid development of single-cell RNA sequencing (scRNA-seq) technologies allows us to explore tissue heterogeneity at the cellular level. The identification of cell types plays an essential role in the analysis of scRNA-seq data, which, in turn, influences the discovery of regulatory genes that induce heterogeneity. As the scale of sequencing data increases, the classical method of combining clustering and differential expression analysis to annotate cells becomes more costly in terms of both labor and resources. Existing scRNA-seq supervised classification method can alleviate this issue through learning a classifier trained on the labeled reference data and then making a prediction based on the unlabeled target data. However, such label transference strategy carries with risks, such as susceptibility to batch effect and further compromise of inherent discrimination of target data. RESULTS: In this article, inspired by unsupervised domain adaptation, we propose a flexible single cell semi-supervised clustering and annotation framework, scSemiCluster, which integrates the reference data and target data for training. We utilize structure similarity regularization on the reference domain to restrict the clustering solutions of the target domain. We also incorporates pairwise constraints in the feature learning process such that cells belonging to the same cluster are close to each other, and cells belonging to different clusters are far from each other in the latent space. Notably, without explicit domain alignment and batch effect correction, scSemiCluster outperforms other state-of-the-art, single-cell supervised classification and semi-supervised clustering annotation algorithms in both simulation and real data. To the best of our knowledge, we are the first to use both deep discriminative clustering and deep generative clustering techniques in the single-cell field. AVAILABILITYAND IMPLEMENTATION: An implementation of scSemiCluster is available from https://github.com/xuebaliang/scSemiCluster. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A comprehensive pan-cancer study of fibroblast growth factor receptor aberrations in Chinese cancer patients.

BACKGROUND: The prevalence and types of fibroblast growth factor receptor (FGFR) mutations vary significantly among different ethnic groups. The optimal application of FGFR inhibitors depends on these variations being comprehensively understood. However, such an analysis has yet to be conducted in Chinese patients. METHODS: We retrospectively screened the genomic profiling results of 10,582 Chinese cancer patients across 16 cancer types to investigate the frequency and distribution of FGFR aberrations. RESULTS: FGFR aberrations were identified in 745 patients, equating to an overall prevalence of 7.0%. A majority of the aberrations occurred on FGFR1 (56.8%), which was followed by FGFR3 (17.7%), FGFR2 (14.4%), and FGFR4 (2.8%). Further, 8.5% of patients had aberrations of more than 1 FGFR gene. The most common types of aberrations were amplification (53.7%), other mutations (38.8%), and fusions (5.6%). FGFR fusion and amplification occurred concurrently in 1.9% of the patients. FGFR aberrations were detected in 12 of the 16 cancers, with the highest prevalence belonging to colorectal cancer (CRC) (31%). Other FGFR-aberrant cancer types included stomach (16.8%), breast (14.3%), and esophageal (12.7%) cancer. Breast tumors were also more likely than other cancer types to have concurrent FGFR rearrangements and amplifications (P<0.001). In comparison with the public dataset, our cohort had a significantly higher number of FGFR aberrations in colorectal (P<0.001) and breast cancer (P=0.05). CONCLUSIONS: Among the Chinese cancer patients in our study, the overall prevalence of FGFR aberrations was 7.0%. FGFR1 amplification was the most common genetic alteration in CRC, breast cancer, and lung cancer; while FGFR2 amplification was more commonly observed in gastric cancer than in other cancers in our cohort. Our study advances the understanding of the distribution of FGFR aberrations in various cancer types in the Chinese population, which will facilitate the further development of FGFR inhibitors.

ANXA1­derived peptides suppress gastric and colon cancer cell growth by targeting EphA2 degradation.

EphA2 (EPH receptor A2) (erythropoietin­producing hepatocellular receptor tyrosine kinase subtype A2) plays a crucial role in human cancers, and is a promising target for the development of new anticancer drugs. In this study, we showed that the interaction of Annexin A1 (ANXA1) and EphA2 increased EphA2 stability by inhibiting its proteasome degradation in gastric cancer (GC) and colon cancer (CC) cells, and the amino acid residues 20­30 and 28­30 of ANXA1 N terminal were responsible for binding and stabilizing EphA2. Based on the amino acid residues of ANXA1 responsible for binding EphA2, we developed ANXA1­derived 3 amino acid­long (SKG) and 11 amino acid­long peptides (EYVQTVKSSKG) in fusion to cell­penetrating peptide, named as A1(28­30) and A1(20­30) respectively, and found that A1(28­30) and A1(20­30) blocked the binding of ANXA1 with EphA2, targeted EphA2 degradation, and suppressed the growth of GC and CC cells in vitro and in mice. Our data demonstrated that ANXA1 was able to bind and stabilize EphA2 in GC and CC cells, and disruption of ANXA1­EphA2 interaction by the two ANXA1­derived peptides inhibited the growth of GC and CC cells by targeting EphA2 degradation, presenting a potential strategy for treating GC and CC with these peptides.

Integrating Deep Supervised, Self-Supervised and Unsupervised Learning for Single-Cell RNA-seq Clustering and Annotation.

As single-cell RNA sequencing technologies mature, massive gene expression profiles can be obtained. Consequently, cell clustering and annotation become two crucial and fundamental procedures affecting other specific downstream analyses. Most existing single-cell RNA-seq (scRNA-seq) data clustering algorithms do not take into account the available cell annotation results on the same tissues or organisms from other laboratories. Nonetheless, such data could assist and guide the clustering process on the target dataset. Identifying marker genes through differential expression analysis to manually annotate large amounts of cells also costs labor and resources. Therefore, in this paper, we propose a novel end-to-end cell supervised clustering and annotation framework called scAnCluster, which fully utilizes the cell type labels available from reference data to facilitate the cell clustering and annotation on the unlabeled target data. Our algorithm integrates deep supervised learning, self-supervised learning and unsupervised learning techniques together, and it outperforms other customized scRNA-seq supervised clustering methods in both simulation and real data. It is particularly worth noting that our method performs well on the challenging task of discovering novel cell types that are absent in the reference data.

Comparison of EML4-ALK fusion gene positive rate in different detection methods and samples of non-small cell lung cancer.

Objective: To evaluate differences of EML4-ALK positive rates in tissues samples between immunohistochemistry, reverse transcriptase polymerase chain reaction and the next-generation sequencing method. Besides, to compare the differences of EML4-ALK positive rates in blood samples and tissue samples by next-generation sequencing. The results provide a basis for the selection of a suitable EML4-ALK fusion gene detection method. Methods: Immunohistochemistry analysis of EML4-ALK in tumors was performed on samples from 2631 patients with non-small cell lung cancer. The mutation of EML4-ALK in the tissue samples of 399 patients with non-small cell lung cancer was detected by reverse transcription polymerase chain reaction. Next-generation sequencing was used to detect the mutation of EML4-ALK in 1505 non-small cell lung cancer patients, including 1208 tissue samples and 297 blood samples. Results: The positive incidence of EML4-ALK by immunohistochemistry was 7.11% (187/2631). Histologically, 9.51% (170/1787) of the samples were lung adenocarcinomas, and 2.01% (17/844) were squamous cell carcinomas. The positive rate of EML4-ALK was 8.52% (34/399) in 399 patients with non-small cell lung cancer, as detected by reverse transcription polymerase chain reaction; the mutation rate of adenocarcinoma was 11.62% (33/284), and the mutation rate of squamous cell carcinoma was 0.86% (1/115). In 1208 patients with non-small cell lung cancer with tissue samples, the positive rate of EML4-ALK was 4.88% (59/1208), as determined by next-generation sequencing, the mutation rate of adenocarcinoma was 5.84% (58/994), and the mutation rate of squamous cell carcinoma was 0.47% (1/214). The positive rate of EML4-ALK detected by reverse transcription polymerase chain reaction was higher than that detected by immunohistochemistry. Compared with the next-generation sequencing results, the positive rates of EML4-ALK detected by immunohistochemistry and reverse transcription polymerase chain reaction were higher, and the differences were significant (p<0.05). In blood samples from 297 patients with non-small cell lung cancer, the positive rate of EML4-ALK detected by next-generation sequencing was 3.70% (11/297), the mutation rate of adenocarcinoma was 3.82% (10/262), and the mutation rate of squamous cell carcinoma was 2.86% (1/35). The EML4-ALK positive rate of the tissue samples was thus higher than that of the blood biopsy samples. Conclusion: Among the three methods for detecting EML4-ALK, reverse transcription polymerase chain reaction has the highest positive rate, followed by immunohistochemistry, and next-generation sequencing has the lowest positive rate. The positive detection rate of EML4-ALK in tissue samples by next-generation sequencing was higher than that in blood samples.

Comparative study on the mutational profile of adenocarcinoma and squamous cell carcinoma predominant histologic subtypes in Chinese non-small cell lung cancer patients.

BACKGROUND: Distinction in the mutational profile between the common histological types, lung adenocarcinoma (LUAD) and squamous cell lung carcinoma (LUSC) has been well-established. However, comprehensive mutation profiles of the predominant histological subtypes within LUAD and LUSC remains elusive. METHODS: We analyzed the mutational profile of 318 Chinese NSCLC patients of adenocarcinoma and squamous cell carcinoma predominant subtypes from seven hospitals using capture-based ultra-deep sequencing of 68 lung cancer-related genes. RESULTS: Of the 318 NSCLC patients, 215 were diagnosed with LUAD and 103 with LUSC. Adenocarcinoma in situ and acinar adenocarcinoma were the most predominant subtypes of LUAD. On the other hand, keratinizing squamous cell carcinoma was the most predominant subtype of LUSC. Among the LUAD subtypes, EGFR sensitizing mutations were most prevalent in the invasive lepidic subtype. More than half of the patients with preinvasive adenocarcinoma in situ, minimally invasive, acinar, micropapillary and papillary subtypes were also EGFR-mutants. Patients with colloidal, invasive mucinous, and fetal subtypes had the least number of EGFR mutations. Moreover, KRAS mutations were prevalent in patients with invasive mucinous, colloid, enteric and solid subtypes. A total of 90% of the LUSC patients harbor mutations in TP53, wherein all patients except five with nonkeratinizing were TP53 mutants. PIK3CA amplifications were most prevalent in keratinizing, followed by basaloid and nonkeratinizing subtypes. CONCLUSION: These data suggest that the mutational profiles among the predominant histological subtypes were very distinct, which provided a reliable tool to improve treatment decisions.

[Corrigendum] ANXA1­derived peptides suppress gastric and colon cancer cell growth by targeting EphA2 degradation.

Following the publication of the above article, the authors have realized that one of the data panels featured in Fig. 5D was selected incorrectly. Specifically, the wrong image was selected for the A1 (28­30), HCT116 experiment. The authors have revisited their original sources to identify the correct data panel, and can confirm that the error arose unintentionally during the process of compiling the figure. The correct version of Fig. 5, featuring corrected data panel for Fig. 5D, is shown on the next page. The authors confirm that this error did not affect the conclusions reported in this study, and are grateful to the Editor of International Journal of Oncology for allowing them the opportunity to publish this corrigendum. Furthermore, the authors apologize to the readership of the Journal for any inconvenience caused. [the original article was published in International Journal of Oncology 57: 1203­1213, 2020; DOI: 10.3892/ijo.2020.5119].

Annexin A1-suppressed autophagy promotes nasopharyngeal carcinoma cell invasion and metastasis by PI3K/AKT signaling activation.

Annexin A1 (ANXA1) is dysregulated in the various tumors. However, the role and mechanism of ANXA1 in the cancers are poorly understood. In this study, we first showed a clinically positive correlation between ANXA1 and autophagy-associated protein SQSTM1 expression in nasopharyngeal carcinoma (NPC) and ANXA1-regulating SQSTM1 expression through autophagy, and further demonstrated that ANXA1 inhibited BECN1 and ATG5-dependent autophagy in the NPC cells. Using phospho-kinase antibody array to identify signaling through which ANXA1 regulated NPC cell autophagy, we found that ANXA1-suppressed autophagy was associated with PI3K/AKT signaling activation. We also showed that ANXA1 expression was significantly increased in the NPCs with metastasis relative to NPCs without metastasis and positively correlated with lymphonode and distant metastasis; high ANXA1 expression in the NPC cells promoted in vitro tumor cell migration and invasion and in vivo metastasis. Lastly, we showed that inhibition of autophagy restored the ability of tumor cell migration and invasion, epithelial-mesenchymal transition (EMT)-like alterations and in vivo metastasis in the ANXA1 knockdown NPC cells with autophagy activation; ANXA1-suppresed autophagy induced EMT-like alterations possibly by inhibiting autophagy-mediated degradation of Snail. Our data suggest that ANXA1-suppressed autophagy promotes NPC cell migration, invasion and metastasis by activating PI3K/AKT signaling pathway, highlighting that the activation of autophagy may inhibit metastasis of NPC with high ANXA1 expression.

Detection of immunoglobulin and T-cell receptor gene rearrangements in angioimmunoblastic T-cell lymphoma.

Objective: To assess the value of immunoglobulin and T-cell receptor gene rearrangements in the diagnosis and differential diagnosis of angioimmunoblastic T-cell lymphoma. Methods: We selected 55 cases of angioimmunoblastic T-cell lymphoma confirmed by histopathology and 15 cases of reactive lymph node hyperplasia. Using the IdentiClone gene rearrangement detection kit, BIOMED-2 primer system, and GeneScanning analysis, we tested for immunoglobulin and T-cell receptor gene rearrangements. Results: Among all 55 angioimmunoblastic T-cell lymphoma cases, 1 (2%) displayed the first type of angioimmunoblastic T-cell lymphoma, which has an intact lymphoid follicle structure. Five cases (9%) displayed the second type, which has an intact segmental lymphatic follicular structure. Forty-nine cases (89%) displayed the third type, which is characterized by a complete obliteration of the lymphatic follicular structure. Fifty-two cases (95%) had tumor cells that were positive for CD3, 50 cases (91%) were positive for CD4, 33 cases (60%) were positive for Bcl-6, 20 cases (36%) were positive for CD10, 44 cases (80%) were positive for CXCL13 to different degrees, and 53 cases (96%) showed a strong positive expression of CD21. Ki67 expression intensity was 30-80% in tumor T cells. Clonal gene rearrangements were identified in 48 of the 55 angioimmunoblastic T-cell lymphoma cases (87%), of which 30 (55%) displayed IG gene rearrangements, including IGHA (7 cases; 13%), IGHB (6 cases; 11%), IGHC (2 cases; 4%), IGKA (22 cases; 40%), IGKB (6 cases; 11%), and IGL (20 cases; 36%). TCR gene rearrangements were observed in 32 cases (58%), including TCRBA (6 cases; 11%), TCRBB (5 cases; 9%), TCRBC (10 cases; 18%), TCRD (7 cases; 13%), TCRGA (22 cases; 40%), and TCRGB (16 cases; 29%). IG and TCR gene rearrangements were concurrently observed in 14 cases (25%). Immunoglobulin or TCR clonal gene rearrangements were not detected in the 15 cases of reactive hyperplasia. Conclusions: Angioimmunoblastic T-cell lymphomas may be positive for immunoglobulin or T-cell receptor clone gene rearrangements or may express double rearrangements. The assessment of clonal gene rearrangements is valuable for the diagnosis and differential diagnosis of angioimmunoblastic T-cell lymphoma.

Asprellcosides B of Ilex asprella Inhibits Influenza A Virus Infection by Blocking the Hemagglutinin- Mediated Membrane Fusion.

Ilex asprella is routinely used in China as a traditional medicinal herb to treat influenza (Flu). However, its specific antiviral activity and underlying molecular mechanism have not yet been determined. In this study, we sought to determine the antiviral activity and mechanism of Asprellcosides B, an active component extracted from Ilex asprella, and used against the influenza A virus cell culture. We also performed a computer-assisted structural modeling analysis and carried out surface plasmon resonance (SPR) experiments in the hope of determining the viral target of Asprellcosides B. Results from our studies show that Asprellcosides B reduced virus replication by up to 63% with an IC50 of about 9 µM. It also decreased the low pH-induced and virus-mediated hemolysis by 71% in vitro. Molecular docking simulation analysis suggested a possible binding of Asprellcosides B to the hemagglutinin (HA), which was confirmed by a surface plasmon resonance (SPR) assay. Altogether, our findings demonstrate that Asprellcosides B inhibits the influenza A virus, through a specific binding to the HA, resulting in the blockade of the HA-mediated membrane fusion.

Lymphoepithelioma is a nonkeratinizing squamous cell carcinoma with Epstein-Barr virus infection in China.

OBJECTIVE: The objective of this study is to investigate the histogenesis of lymphoepithelial carcinoma (LEC) and its relationship with Epstein-Barr virus (EBV). MATERIALS AND METHODS: The expression of EBV was detected using in situ hybridization, and the CK5/6, p63, and p40 expression levels were detected using immunohistochemistry in 45 paraffin-embedded tissues from LEC. RESULTS: In 45 paraffin-embedded LEC tissues from 10 different samples, the positive CK5/6 signals were located in the cell membrane. The positive signals for p63 and p40 were located in the cell nucleus. In all LEC cases, the positive rates of CK5/6, p63, and p40 were 93.3% (42/45), 95.6% (43/45), and 93.3% (42/45), respectively. The positive EBV-encoded RNA (EBER) signals were located in the cell nucleus. In the 45 LEC cases, the expression of EBER was strongly positive with a positive rate of 100% (45/45). CONCLUSIONS: LEC is closely related to EBV, and EBV plays an important role in the development of LEC. LEC showed positive squamous cell markers, indicating that the samples contain squamous cell carcinoma (SQCC). LEC is EBV (+) with nonkeratinizing SQCC, and this name better reflects the nature of this disease.

The value of detecting immunoglobulin gene rearrangements in the diagnosis of B-cell lymphoma.

OBJECTIVE: To discuss the clinical value of immunoglobulin gene rearrangements in the diagnosis of B-cell lymphoma. METHODS: A total of 209 cases of B-cell lymphomas and 35 cases of reactive lymphoid hyperplasia were selected for DNA extraction and PCR amplification using the BIOMED-2 primer system. Gel electrophoresis of heteroduplexes was used to analyze immunoglobulin gene rearrangements. RESULTS: A total of 209 cases of B-cell lymphoma, including 69 extranodal marginal zone B-cell lymphomas of mucosa-associated lymphoid tissue, 63 diffuse large B-cell lymphomas, 39 follicular lymphomas, 15 small lymphocytic lymphomas, 6 plasmacytomas, 6 mantle cell lymphomas, 7 nodal marginal zone B-cell lymphomas, and 4 lymphoplasmacytoid lymphomas, were examined. Immunoglobulin gene rearrangements were found in all 209 cases, with 93 IGHA, 122 IGHB, 98 IGHC, 167 IGK, 100 IGL, 167 IGHA/B/C, 204 IGH/IGK, 209 IGH/IGK/IGL, 129 IGH+IGK, 81 IGH+IGL, 83 IGK+IGL and 68 IGH+IGK+IGL gene rearrangements. Immunoglobulin gene rearrangements were not found in the 35 cases of reactive lymphoid hyperplasia. IGH and IGK gene rearrangements were mainly found in mantle cell lymphomas, small lymphocytic lymphomas, extranodal marginal zone B-cell lymphomas of mucosa-associated lymphoid tissue and diffuse large B-cell lymphomas. The IGH gene rearrangement was mainly found in lymphoplasmacytoid lymphomas and follicular lymphomas. IGK and IGL gene rearrangements were mainly found in plasmocytoma, and the IGK gene rearrangement was mainly found in nodal marginal zone B-cell lymphomas. CONCLUSIONS: The BIOMED-2 standardized immunoglobulin gene rearrangement detection system is an important tool in B-cell lymphoma diagnosis. Analysis of IGH, IGK and IGL gene rearrangements is valuable in confirming the classification of B-cell NHL.

Luteolin restricts dengue virus replication through inhibition of the proprotein convertase furin.

In many countries afflicted with dengue fever, traditional medicines are widely used as panaceas for illness, and here we describe the systematic evaluation of a widely known natural product, luteolin, originating from the "heat clearing" class of herbs. We show that luteolin inhibits the replication of all four serotypes of dengue virus, but the selectivity of the inhibition was weak. In addition, ADE-mediated dengue virus infection of human cell lines and primary PBMCs was inhibited. In a time-of-drug-addition study, luteolin was found to reduce infectious virus particle formation, but not viral RNA synthesis, in Huh-7 cells. During the virus life cycle, the host protease furin cleaves the pr moiety from prM protein of immature virus particles in the trans-Golgi network to produce mature virions. Analysis of virus particles from luteolin-treated cells revealed that prM was not cleaved efficiently. Biochemical interrogation of human furin showed that luteolin inhibited the enzyme activity in an uncompetitive manner, with Ki value of 58.6 µM, suggesting that treatment may restrict the virion maturation process. Luteolin also exhibited in vivo antiviral activity in mice infected with DENV, causing reduced viremia. Given the mode of action of luteolin and its widespread source, it is possible that it can be tested in combination with other dengue virus inhibitors.

Molecular epidemiology demonstrates that imported and local strains circulated during the 2014 dengue outbreak in Guangzhou, China.

The dengue virus (DENV) is a vital global public health issue. The 2014 dengue epidemic in Guangzhou, China, caused approximately 40,000 cases of infection and five deaths. We carried out a comprehensive investigation aimed at identifying the transmission sources in this dengue epidemic. To analyze the phylogenetics of the 2014 dengue strains, the envelope (E) gene sequences from 17 viral strains isolated from 168 dengue patient serum samples were sequenced and a phylogenetic tree was reconstructed. All 17 strains were serotype I strains, including 8 genotype I and 9 genotype V strains. Additionally, 6 genotype I strains that were probably introduced to China from Thailand before 2009 were widely transmitted in the 2013 and 2014 epidemics, and they continued to circulate until 2015, with one affinis strain being found in Singapore. The other 2 genotype I strains were introduced from the Malaya Peninsula in 2014. The transmission source of the 9 genotype V strains was from Malaysia in 2014. DENVs of different serotypes and genotypes co-circulated in the 2014 dengue outbreak in Guangzhou. Moreover, not only had DENV been imported to Guangzhou, but it had also been gradually exported, as the viruses exhibited an enzootic transmission cycle in Guangzhou.

Comparison of small biopsy specimens and surgical specimens for the detection of EGFR mutations and EML4-ALK in non-small-cell lung cancer.

Epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) fusion genes represent novel oncogenes that are associated with non-small-cell lung cancers (NSCLC). The feasibility of detecting EGFR mutations and ALK fusion genes in small biopsy specimens or surgical specimens was determined. Of the 721 NSCLC patients, a total of 305 cases were positive for EGFR mutations (42.3%). The rate of EGFR mutations in women was significantly higher than that in men. Histologically, the EGFR mutation rate in adenocarcinomas was significantly higher than that in squamous cell carcinomas. No difference in the EGFR mutation rate was observed between surgical specimens (42.1%) and small biopsy specimens (42.4%), which indicated that the EGFR mutation ratios in surgical specimens and small biopsy specimens were not different. In 385 NSCLC patients, 26 cases were positive for EML4-ALK (6.8%). However, 11.7% of the surgical specimens were EML4-ALK-positive, whereas the positive proportion in the small biopsy specimens was only 4.7%, which indicated that EML4-ALK-positive rate in the surgical specimens was significantly higher than that in the small biopsy specimens. Detection of EGFR gene mutations was feasible in small biopsy specimens, and screening for EML4-ALK expression in small biopsy specimens can be used to guide clinical treatments.

Integrated analysis of the differential cellular and EBV miRNA expression profiles in microdissected nasopharyngeal carcinoma and non-cancerous nasopharyngeal tissues.

Nasopharyngeal carcinoma (NPC) is commonly diagnosed in southern Asia. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. Increasing evidence suggests that the dysregulation of miRNAs promotes NPC tumorigenesis. Epstein-Barr virus (EBV) infection and EBV-encoded miRNAs are also associated with the development of NPC. However, it is unclear how cellular and EBV miRNAs jointly regulate target genes and signaling pathways in NPC. In the present study, we analyzed the differential cellular and EBV miRNA expression profiles in 20 pooled NPC tissues using microarrays. We found that 19 cellular miRNAs and 9 EBV miRNAs were upregulated and 31 cellular miRNAs were downregulated in NPC tissues. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the 19 upregulated miRNAs target mainly the p53 signaling pathway in cancer, whereas the downregulated miRNAs regulate pathways related to cancer, focal adhesion and Erb, and MAPK signaling. In contrast, the upregulated EBV miRNAs target primarily the TGF-ß and Wnt signaling pathways. Data also suggested that cellular miR-34b, miR-34c, miR-18a, miR­200a/b, miR-449a, miR-31 and let-7 may be dysregulated in NPCs, and that the aberrant activation of their target genes in the p53 pathway and cell cycle enhance NPC cell survival and proliferation. In addition, EBV-miRNAs such as BART3 and BART5 target genes in the p53, TGF-ß and Wnt signaling pathways to modulate NPC apoptosis and transformation. To better elucidate the interaction between miRNAs and target genes, we constructed an anti-correlated cellular and EBV miRNA/target gene regulatory network. The current findings may help dissect the roles played by cellular and EBV miRNAs during NPC tumorigenesis, and also provide useful biomarkers for the diagnosis and treatment of NPCs.

MiRNA-203 Reduces Nasopharyngeal Carcinoma Radioresistance by Targeting IL8/AKT Signaling.

Radioresistance poses a major challenge in nasopharyngeal carcinoma (NPC) treatment, but little is known about how miRNA (miR) regulates this phenomenon. In this study, we investigated the function and mechanism of miR-203 in NPC radioresistance, one of downregulated miRs in the radioresistant NPC cells identified by our previous microarray analysis. We observed that miR-203 was frequently downregulated in the radioresistant NPC tissues compared with radiosensitive NPC tissues, and its decrement significantly correlated with NPC radioresistance and poor patient survival, and was an independent predictor for reduced patient survival. In vitro radioresponse assays showed that miR-203 mimic markedly decreased NPC cell radioresistance. In a mouse model, therapeutic administration of miR-203 agomir dramatically sensitized NPC xenografts to irradiation. Mechanistically, we confirmed that IL8 was a direct target of miR-203, and found that reduced miR-203 promoted NPC cell radioresistance by activating IL8/AKT signaling. Moreover, the levels of IL8 and phospho-AKT were significantly increased in the radioresistant NPC tissues compared with radiosensitive NPC tissues, and negatively associated with miR-203 level. Our data demonstrate that miR-203 is a critical determinant of NPC radioresponse, and its decrement enhances NPC radioresistance through targeting IL8/AKT signaling, highlighting the therapeutic potential of the miR-203/IL8/AKT signaling axis in NPC radiosensitization.