• Based on strong research evidence (1), the prevalence of autism spectrum disorders (ASDs) has increased over the past decade, with a 2010 prevalence of 1:68 (1.5%) in children age 8 years. • Based on some research evidence as well as consensus (3), the most recent revision of the American Psychiatric Association's Diagnostic and Statistical Manual (DSM-V) identifies two core dimensions for the diagnosis of ASD: social (social communication and social interaction) and nonsocial (restricted, repetitive patterns of behaviors, interests, or activities). • Based on some research evidence as well as consensus (3) (31) (32) (33) (34), DSM-V identifies social pragmatic communication disorder (SPCD) as a dissociable dimension of language and communication ability that affects how individuals use language for social exchanges. SPCD is often found in children with language impairments and children with attention-deficit/hyperactivity disorder and other genetic/neurologic conditions. • Based on strong research evidence (2) (26) (27) (28), childhood language disorders affect 7.4% of kindergarteners, and 50% to 80% of these children experience persistent language, academic, and social-emotional difficulties into their adult years, despite having normal nonverbal cognitive abilities. • Based primarily on consensus due to lack of relevant clinical studies, differential diagnosis of autism and language disorders may require a multidisciplinary evaluation that takes into account a child’s overall development, including cognitive, communication, and social abilities. Monitoring the response to appropriate interventions and trajectory of development over time may improve the accuracy of diagnosis, especially in very young children.

Neural stem cell (NSC) proliferation and differentiation play a pivotal role in the development of brain, the plasticity of the brain network, and the repair for brain function in CNS diseases. The mechanisms regulating NSC behavior are not well elucidated. Previous studies showed porf-2 functions as a modulator in central nerve system development. We here show that porf-2, a conserved family of RhoGAPs, is highly and specifically expressed in NSCs. We also demonstrate that porf-2 inhibits the proliferation of NSCs in vivo and in vitro, but has no effect on NSC differentiation. We investigated which domain is required for the role of porf-2 on NSC proliferation. By using neurosphere formation and Edu assay we confirmed the GAP domain is necessary for its function. In addition, we surveyed a few classical pathways on NSC proliferation and found that porf-2 inhibits NSC proliferation by suppressing the β-catenin nuclear translocation. Taken together, we show for the first time that porf-2 inhibits NSC proliferation through Wnt/β-catenin pathway by its GAP domain.

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Non-small-cell lung cancer (NSCLC) is one of the most threatening malignant tumors to human health, with the overall 5-year survival rate being less than 30%. Regulatory T cells (Tregs), a functional subset of T cells, maintain immunologic immunological self-tolerance and homeostasis. Accumulating evidence has uncovered their implicated roles in various cancers in recent years. In NSCLC, they are associated with staging, therapeutic efficacy, and prognosis by infiltrating in tissues and thereby attenuating immunologic anticancer effects in patients. Tumor-associated Tregs display distinct immune signatures in NSCLC compared to thymus-derived Tregs, playing an important role in remodeling the tumor microenvironment (TME). Targeting Tregs has become a novel direction for NSCLC patients, such as disrupting their immune-suppressive functions, blocking their trafficking into tumors, and inhibiting their development and/or activation. This review is aimed at elucidating the molecular mechanisms of tumor-associated Tregs in NSCLC and providing therapeutic targets relevant to Tregs.

Endoplasmic reticulum (ER) stress has been identified as a primary factor involved in brain ischemia-reperfusion injury progression. p21-activated kinase 2 (Pak2) is a novel ER function regulator. The aim of our study is to explore the influence of Pak2 on ER stress and determine whether melatonin attenuates ER stress-mediated cell death by modulating Pak2 expression in vitro using N2a cells. The results of our study demonstrated that hypoxia-reoxygenation (HR) injury repressed the levels of Pak2, an effect that was accompanied by activation of ER stress. In addition, decreased Pak2 was associated with oxidative stress, calcium overload, and caspase-12-mediated apoptosis activation in HR-treated N2a cells. Interestingly, melatonin treatment reversed the decreased Pak2 expression under HR stress. Knockdown of Pak2 abolished the protective effects of melatonin on ER stress, oxidative stress, and caspase-12-related N2a cells death. Additionally, we found that Pak2 was regulated by melatonin via the AMPK pathway; inhibition of AMPK prevented melatonin-mediated Pak2 upregulation, a result that was accompanied by an increase in N2a cell death. Altogether, these results identify the AMPK-Pak2 axis as a new signaling pathway responsible for ER stress and N2a cell viability under HR injury. Modulation of the AMPK-Pak2 cascade via supplementation of melatonin might be considered an effective approach to attenuate reperfusion-mediated N2a cell damage via repression of ER stress.

Glioblastoma is a lethal brain tumor type, which is frequently resistant to radiotherapy. The aim of the present study was to explore the function of legumain pseudogene 1 (LGMNP1) on radioresistance in glioblastoma. Reverse transcription-quantitative PCR was used to detect the relative expression of LGMNP1 in glioma cell lines after radiotherapy. Ectopic expression of LGMNP1 was achieved by transfection of a lentiviral vector. A clonogenic assay was used to determine the colony formation ability following radiotherapy. A comet assay, flow cytometry and western blot analysis were applied to detect DNA damage, the apoptotic rate, and levels of apoptotic proteins, respectively. The results revealed that LGMNP1 was significantly upregulated in glioma cells after radiation. Glioma cells stably overexpressing LGMNP1 were successfully established. Overexpression of LGMNP1 in glioma cells reduced DNA damage processes and the percentage of apoptotic cells after radiotherapy. In addition, overexpression of LGMNP1 in glioblastoma multiforme cells decreased apoptotic protein expression after radiotherapy. The present results indicated that upregulation of LGMNP1 conferred radiotherapy resistance by increasing the ability of DNA damage protection and reducing the apoptotic population in glioma cells.

Spermatogenesis associated serine rich 2 (SPATS2) has been reported to be dysregulated in few types of cancer; however, no reports have investigated SPATS2 in liver cancer. The aim of the present study was to investigate SPATS2 expression in liver cancer and to analyze its association with the prognosis of liver cancer patients. We examined the differential expression of SPATS2 in liver cancer by exploring The Cancer Genome Atlas (TCGA) database. The diagnostic efficiency of SPATS2 was obtained by Receiver Operating Characteristic (ROC) curve. The Chi-Squared test was used to assess clinical relevance. Survival analysis and Cox regression model were used to detect the effect of SPATS2 on the survival of liver cancer patients. Gene Set Enrichment Analysis (GSEA) was used to identify signaling pathways related to SPATS2 expression. SPATS2 is highly expressed in liver cancer ( P < 2.2e-16) and has the high diagnostic ability (AUC = 0.964). Survival analysis showed that patients with high SPATS2 expression have an apparently shorter overall survival (OS, P < .0001) and relapse-free survival (RFS, P < .0001). Cox regression analysis showed that high SPATS2 expression might be an independent risk factor for liver cancer (OS, HR = 2.41, P = .000; RFS, HR = 1.90, P < .001). GSEA analysis identified 3 signaling pathways (Mitotic spindle, G2 M checkpoint, E2F targets) that were enriched in the presence of high SPATS2 expression. SPATS2 expression could be a novel diagnostic and prognostic biomarker in liver cancer.

Background Single‐cell transcriptomics has been used to investigate various tumors to elucidate the molecular distinction of all cell type compositions of a complex mix. Aims This study aimed to investigate malignant‐cell‐specific genes to explore diagnostic and therapeutic biomarkers using single‐cell transcriptomic data of lung adenocarcinoma. Materials & Methods 10X single‐cell RNA‐seq data of fourteen patients with lung adenocarcinoma were analyzed. Genes that expressed differentially and those with higher confidence to distinguish tumor cells from normal cells were picked out using the ROC curves. The LASSO regression method was used to select most markedly correlated genes to predict the malignancy of every single cell within a model. We also conducted further experiments to determine their roles in lung cancer in vitro. Results Twenty two thousand four hundred and ninety one tumor and 181 666 normal single cells were analyzed where 369 genes were found to be specifically expressed in single malignant cells. Seventy of them, encoding secreted or membrane‐bound proteins, showed involvement in cell‐to‐cell communications in tumor biology. KRT18 and the other six genes were identified as predictors to distinguish single malignant cells and were integrated to construct an accurate (96.1%) predicting model. Notably, IRX2, SPINK13, and CAPN8 outperformed the other four genes. Further experiments confirmed the upregulation of them in lung adenocarcinoma at both tissue and cell levels. Proliferative capacities of lung adenocarcinoma cells were attenuated by knocking‐down of either of them. However, targeting CAPN8, IRX2, or SPINK13 hardly exerted a cytotoxic effect on these cells. Discussion Apart from the current model, similar tools were still warranted using single‐cell RNA‐seq data of more types of tumors. The three genes identified as potential therapeutic targets in the present study still need to be validated in more in lung cancer. Conclusion Our model can aid the analyses of single‐cell sequencing data. CAPN8, IRX2, and SPINK13 may serve as novel targets of targeted and immune‐based therapies in lung adenocarcinoma.