Hhex inhibits cell migration via regulating RHOA/CDC42-CFL1 axis in human lung cancer cells.

BACKGROUND: Hhex(human hematopoietically expressed homeobox), also known as PRH, is originally considered as a transcription factor to regulate gene expression due to its homebox domain. Increasing studies show that Hhex plays a significant role in development, including anterior-posterior axis formation, vascular development and HSCs self-renewal etc. Hhex is linked to many diseases such as cancers, leukemia, and type-2 diabetes. Although Hhex is reported to inhibit cell migration and invasion of breast and prostate epithelial cells by upregulating Endoglin expression, the effect and molecular mechanism for lung cancer cell motility regulation remains elusive. METHODS: Human non-small cell lung cancer cells and HEK293FT cells were used to investigate the molecular mechanism of Hhex regulating lung cancer cell migration by using Western blot, immunoprecipitation, wound-healing scratch assay, laser confocal. RESULTS: Our data indicated that Hhex could inhibit cell migration and cell protrusion formation in lung cancer cells. In addition, Hhex inhibited CFL1 phosphorylation to keep its F-actin-severing activity. RHOGDIA was involved in Hhex-induced CFL1 phosphorylation regulation. Hhex enhanced RHOGDIA interaction with RHOA/CDC42, thus maintaining RHOA/CDC42 at an inactive form. CONCLUSION: Collectively, these data indicate that Hhex inhibited the activation of RHOA/CDC42 by enhancing interaction of RHOGDIA with RHOA/CDC42, and then RHOA/ CDC42-p-CFL1 signaling pathway was blocked. Consequently, the formation of Filopodium and Lamellipodium on the cell surface was suppressed, and thus the ability of lung cancer cells to migrate was decreased accordingly. Our findings show Hhex plays an important role in regulating migration of lung cancer cells and may provide a potential target for lung cancer therapy. Video abstract.

Angio-associated migratory cell protein (AAMP) interacts with cell division cycle 42 (CDC42) and enhances migration and invasion in human non-small cell lung cancer cells.

Angio-associated migratory cell protein (AAMP) is considered a pro-tumor protein, which contributes to angiogenesis, proliferation, adhesion, and other biological activities. Although AAMP is known to facilitate the motility of breast cancer cells and smooth muscle cells by regulating ras homolog family member A (RHOA) activity, the function of AAMP in the metastasis of non-small cell lung cancer (NSCLC) cells still remains unknown. In the present study, AAMP was upregulated in non-small cell lung carcinoma, and was found to promote migration and invasion in NSCLC cells. Further experiments demonstrated that AAMP interacted with cell division cycle 42 (CDC42) and promoted its activation, resulting in the formation of cellular protrusions. Subsequently, we found that AAMP enhanced CDC42 activation by impairing the combination of rho GTPase activating protein 1 (ARHGAP1) and CDC42. Taken together, we revealed and elucidated the critical role of AAMP in the migration and invasion of NSCLC cells and presented a new potential target for lung cancer therapy.

Development and validation of a multiplex-PCR based assay for the detection of 18 pathogens in the cerebrospinal fluid of hospitalized children with viral encephalitis.

BACKGROUND: The Applied Biosystems 3500 Genetic Analyzer (ABI3500) allows for automated capillary electrophoresis on multiple targets. So far, the application of this method for detecting cerebrospinal fluid pathogens has hardly been reported. METHODS: To assess the performance of multiplex-PCR assay for 18 pathogens detection, 127 CSF samples from hospitalized children with suspected viral encephalitis were prospectively collected from April to November 2018. The Sanger sequencing was applied to verify this assay. RESULTS: All of the 18 target pathogens can be identified by multiplex-PCR assay at 104 copies (or CFU/mL) of each virus, bacterium and fungus. In contrast, 10 control microorganisms failed to be amplified. Approximately 68.5 % of the cases tested had positive results, the enterovirus accounted for the majority of the positive cases (63.8 %). Agreement between multiplex-PCR and sequencing was 91.49 %. CONCLUSIONS: Our findings suggest that the ABI3500-based multiplex-PCR detection kit could be a valuable diagnostic tool for pathogen detection in CSF of children with suspected viral encephalitis.

Inhibition of SIRT1/2 upregulates HSPA5 acetylation and induces pro-survival autophagy via ATF4-DDIT4-mTORC1 axis in human lung cancer cells.

Sirtuins have emerged as a promising novel class of anti-cancer drug targets. Inhibition of SIRT1 and SIRT2 induces apoptosis in cancer cells and they play multifaceted roles in regulating autophagy. In the present study, we found that salermide, a SIRT1/2-specific inhibitor or small interfering RNAs (siRNAs) to block SIRT1/2 expression could induce autophagy in human NSCLC cells. Moreover, SIRT1/2 inhibition increased the expression levels of ATF4 and DDIT4 and downregulated p-RPS6KB1 and p-EIF4EBP1, two downstream molecules of mTORC1. Moreover, ATF4 or DDIT4 knockdown attenuated salermide-induced autophagy, suggesting that SIRT1/2 inhibition induced autophagy through the ATF4-DDIT4-mTORC1 axis. Mechanistically, SIRT1/2 inhibition led to HSPA5 acetylation and dissociation from EIF2AK3, leading to ER stress response and followed by upregulation of ATF4 and DDIT4, triggering autophagy. Silencing of the autophagic gene ATG5 in lung cancer cells resulted in increased apoptotic cell death induced by SIRT1/2 inhibition. Our data show that inhibition of SIRT1/2 induces pro-survival autophagy via acetylation of HSPA5 and subsequent activation of ATF4 and DDIT4 to inhibit the mTOR signaling pathway in NSCLC cells. These findings suggest that combinatorial treatment with SIRT1/2 inhibitors and pharmacological autophagy inhibitors is an effective therapeutic strategy for cancer therapy.

Extracting the invariant model from the feedback paths of digital hearing aids.

Feedback whistling is a severe problem with hearing aids. A typical acoustical feedback path represents a wave propagation path from the receiver to the microphone and includes many complicated effects among which some are invariant or nearly invariant for all users and in all acoustical environments given a specific type of hearing aids. Based on this observation, a feedback path model that consists of an invariant model and a variant model is proposed. A common-acoustical-pole and zero model-based approach and an iterative least-square search-based approach are used to extract the invariant model from a set of impulse responses of the feedback paths. A hybrid approach combining the two methods is also proposed. The general properties of the three methods are studied using artificial datasets, and the methods are cross-validated using the measured feedback paths. The results show that the proposed hybrid method gives the best overall performance, and the extracted invariant model is effective in modeling the feedback path.

Using a reflection model for modeling the dynamic feedback path of digital hearing aids.

Feedback whistling is one of the severe problems with hearing aids, especially in dynamic situations when the users hug, pick up a telephone, etc. This paper investigates the properties of the dynamic feedback paths of digital hearing aids and proposes a model based on a reflection assumption. The model is compared with two existing models: a direct model and an initialization model, using the measured dynamic feedback paths. The comparison shows that the proposed approach is able to model the dynamic feedback paths more efficiently and accurately in terms of mean-square error and maximum stable gain. The method is also extended to dual-microphone hearing aids to assess the possibility of relating the two dynamic feedback paths through the reflection model. However, it is found that in a complicated acoustic environment, the relation between the two feedback paths can be very intricate and difficult to exploit to yield better modeling of the dynamic feedback paths.