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Background The cisplatin-resistance is still a main course for chemotherapy failure of lung cancer patients. Cisplatin-resistant cancer cells own higher malignance and exhibited increased metastatic ability, but the mechanism is not clear. In this study, we investigated the effects of Ataxia Telangiectasia Mutated (ATM) on lung cancer metastasis. Materials and methods Cisplatin-resistant A549CisR and H157CisR cell line were generated by long-term treating parental A549 and H157 cells (A549P and H157P) with cisplatin. Cell growth, cell migration and cell invasion were determined. Gene expressions were determined by Western Blot and qPCR. Tumor metastasis was investigated using a xenograft mouse model. Results The IC50 of the cisplatin-resistant cells (A549CisR and H157CisR cells) to cisplatin was 6–8 higher than parental cells. The A549CisR and H157CisR cells expressed lower level of E-cadherin and higher levels of N-cadherin, Vimentin and Snail compared to the parental A549P and H157P cells, and exhibited stronger capabilities of metastatic potential compared to the parental cells. The ATM expression was upregulated in A549CisR and H157CisR cells and cisplatin treatment also upregulated expression of ATM in parental cells, The inhibition of ATM by using specific ATM inhibitor CP466722 or knock-down ATM by siRNA suppressed Epithelial-to-Mesenchymal transition (EMT) and metastatic potential of A549CisR and H157CisR cells. These data suggest that ATM mediates the cisplatin-resistance in lung cancer cells. Expressions of JAK 1,2, 、 STAT 3 、PD-L1 and ATM were increased in A549CisR and H157CisR cells and could by induced by cisplatin in parental lung cancer cells. Interestedly, ATM upregulated PD-L1 expression via JAK 1,2 /STAT 3 pathway and inhibition of ATM decreased JAK/STAT3 signaling and decreased PD-L1 expression. The treatment of PD-L1 neutralizing Ab reduced EMT and cell invasion. Inhibition of JAK 1,2 /STAT 3 signaling by specific inhibitors suppressed ATM-induced PD-L1 expression, EMT and cell invasion. Importantly, inhibition of ATM suppressed EMT and tumor metastasis in cisplatin-resistant lung cancer cells in an orthotopic xenograft mouse model. Conclusions Our results show that ATM regulates PD-L1 expression through activation of JAK/STAT3 signaling in cisplatin-resistant cells. Overexpression of ATM contributes to cisplatin-resistance in lung cancer cells. Inhibition of ATM reversed EMT and inhibited cell invasion and tumor metastasis. Thus, ATM may be a potential target for the treatment of cisplatin-resistant lung cancer.

Long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) play vital roles in human diseases. We aimed to identify the effect of the lncRNA AGAP2 antisense RNA 1 (AGAP2-AS1)/miR-296/notch homolog protein 2 (NOTCH2) axis on the progression and radioresistance of lung cancer. Expression of AGAP2-AS1, miR-296, and NOTCH2 in lung cancer cells and tissues from radiosensitive and radioresistant patients was determined, and the predictive role of AGAP2-AS1 in the prognosis of patients was identified. THP-1 cells were induced and exosomes were extracted, and the lung cancer cells were respectively treated with silenced AGAP2-AS1, exosomes, and exosomes upregulating AGAP2-AS1 or downregulating miR-296. The cells were radiated under different doses, and the biological processes of cells were assessed. Moreover, the natural killing cell-mediated cytotoxicity on lung cancer cells was determined. The relationships between AGAP2-AS1 and miR-296, and between miR-296 and NOTCH2 were verified. AGAP2-AS1 and NOTCH2 increased while miR-296 decreased in radioresistant patients and lung cancer cells. The malignant behaviors of radioresistant cells were promoted compared with the parent cells. Inhibited AGAP2-AS1, macrophage-derived exosomes, and exosomes overexpressing AGAP2-AS1 or inhibiting miR-296 facilitated the malignant phenotypes of radioresistant lung cancer cells. Furthermore, AGAP2-AS1 negatively regulated miR-296, and NOTCH2 was targeted by miR-296. M2 macrophage-derived exosomal AGAP2-AS1 enhances radiotherapy immunity in lung cancer by reducing miR-296 and elevating NOTCH2. This study may be helpful for the investigation of radiotherapy of lung cancer.

Our aim was to validate and analyze the prognostic impact of the novel International Association for the Study of Lung Cancer (IASLC) Pathology Committee grading system for invasive pulmonary adenocarcinomas (IPAs) in Chinese patients and to evaluate its utility in predicting a survival benefit from adjuvant chemotherapy (ACT). In this multicenter, retrospective, cohort study, we included 926 Chinese patients with completely resected stage I IPAs and classified them into three groups (Grade 1, n = 119; Grade 2, n = 431; Grade 3, n = 376) according to the new grading system proposed by the IASLC. Recurrence-free survival (RFS) and overall survival (OS) were estimated by the Kaplan–Meier method, and prognostic factors were assessed using univariable and multivariable Cox proportional hazards models. All included cohorts were well stratified in terms of RFS and OS by the novel grading system. Furthermore, the proposed grading system was found to be independently associated with recurrence and death in the multivariable analysis. Among patients with stage IB IPA (N = 490), the proposed grading system identified patients who could benefit from ACT but who were undergraded by the adenocarcinoma (ADC) classification. The novel grading system not only demonstrated prognostic significance in stage I IPA in a multicenter Chinese cohort but also offered clinical value for directing therapeutic decisions regarding adjuvant chemotherapy.

When magnetic matching aided navigation is applied to an underwater vehicle, the magnetometer must be installed inside the vehicle, considering the navigation safety and concealment of the underwater vehicle. Then, the interference magnetic field will seriously affect the accuracy of geomagnetic field measurement, which directly affects the accuracy of geomagnetic matching aided navigation. Therefore, improving the accuracy of geomagnetic measurements inside the vehicle through error compensation has become one of the most difficult problems that requires an urgent solution in geomagnetic matching aided navigation. In order to solve this problem, this paper establishes the calculation model of the internal magnetic field of the underwater vehicle and the geomagnetic measurement error model of the ship-borne magnetometer. Then, a compensation method for the geomagnetic measurement error of the ship-borne magnetometer, based on the constrained total least square method, is proposed. To verify the effectiveness of the method proposed in this paper, a simulation experiment of geomagnetic measurement and compensation of a ship-borne three-axis magnetometer was constructed. Among them, to be closer to the real situation, a combination of the geomagnetism model, the elliptic shell model and the magnetic dipole model was used to simulate the internal magnetic field of the underwater vehicle. The experimental results indicated that the root mean square error of geomagnetic measurement in an underwater vehicle was less than 5 nT after compensation, and the accuracy of geomagnetic measurement met the requirements of geomagnetic matching aided navigation.

Background Nutritional assessment and quality of life (QOL) have become important indices for therapeutic efficacy in patients with malignancies. We aim to develop and validate an easy-to-use questionnaire with prognostic value to assess nutritional status in hospitalized cancer patients. Methods A comprehensive survey focused on patient-generated subjective global assessment (PG-SGA) and 30-item European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30 Chinese version) was performed in a cohort of 22,776 patients derived from the INSCOC study. Among them, 1948 patients were followed for 3 years after admission. An observational, retrospective, cross-sectional cohort study was conducted in accordance with TRIPOD statement. Breiman's random forest model was applied to calculate variable importance (VIMP) for items in PG-SGA and EORTC QLQ-C30 (Chinese version) for nutritional recommendation. Cox regression model was employed to construct Prognosis-Related Nutritional Score for Cancer Patients (PRNS). Kaplan–Meier Survival curve, ROC and DCA were calculated to evaluate prognostic value of nutritional status categorized by PRNS, and compared with PG-SGA. Results Nutritional status was classified into 4 levels by PRNS scores: well nourished (≤ 4.5 points), mild malnourished (5–7.5 points), moderate malnourished (8–14.5 points), and severe malnourished (≥ 15 points). Significant median overall survival differences were found among nutritional status groups stratified by the PRNS (all Ps < 0.05). Compared with PG-SGA, PRNS had better prognostic value for survival stratified by nutritional status. The external, internal validity, test–retest reliability and rater reliability were satisfactory. Conclusions We systematically developed and validated PRNS as a nutrition screening tool for cancer patients. Compared with PG-SGA, PRNS has better prognostic value and simpler operation. Trial registration Investigation on Nutrition Status and its Clinical Outcome of Common Cancers, ChiCTR1800020329. Registered 24 December 2018—Retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=31813

Background Lung cancer remains one of the most prevalent cancer types worldwide, with a high mortality rate. Upregulation of programmed cell death protein 1 (PD-1) and its ligand (PD-L1) may represent a key mechanism for evading immune surveillance. Immune checkpoint blockade (ICB) antibodies against PD-1 or PD-L1 are therefore widely used to treat patients with lung cancer. However, the mechanisms by which lung cancer and neutrophils in the microenvironment sustain PD-L1 expression and impart stronger inhibition of CD8 + T cell function remain unclear. Methods We investigated the role and underlying mechanism by which PD-L1 + lung cancer and PD-L1 + neutrophils impede the function of CD8 + T cells through magnetic bead cell sorting, quantitative real-time polymerase chain reaction (RT-PCR), western blotting, enzyme-linked immunosorbent assays, confocal immunofluorescence, gene silencing, flow cytometry, etc. In vivo efficacy and safety studies were conducted using (Non-obeseDiabetes/severe combined immune deficiency) SCID/NOD mice. Additionally, we collected clinical and prognostic data from 208 patients who underwent curative lung cancer resection between 2017 and 2018. Results We demonstrated that C-X-C motif chemokine ligand 5 (CXCL5) is markedly overexpressed in lung cancer cells and is positively correlated with a poor prognosis in patients with lung cancer. Mechanistically, CXCL5 activates the phosphorylation of the Paxillin/AKT signaling cascade, leading to upregulation of PD-L1 expression and the formation of a positive feedback loop. Moreover, CXCL5 attracts neutrophils, compromising CD8 + T cell-dependent antitumor immunity. These PD-L1 + neutrophils aggravate CD8 + T cell exhaustion following lung cancer domestication. Combined treatment with anti-CXCL5 and anti-PD-L1 antibodies significantly inhibits tumor growth in vivo. Conclusions Our findings collectively demonstrate that CXCL5 promotes immune escape through PD-L1 upregulation in lung cancer and neutrophils chemotaxis through autocrine and paracrine mechanisms. CXCL5 may serve as a potential therapeutic target in synergy with ICBs in lung cancer immunotherapy.

Adipose-derived stem cells (ASCs) are promising therapeutic cells for ischemic heart diseases, due to the ease and efficiency of acquisition, the potential of myocardial lineage differentiation, and the paracrine effects. Recently, many researchers have claimed that the ASC-based myocardial repair is mainly attributed to its paracrine effects, including the anti-apoptosis, pro-angiogenesis, anti-inflammation effects, and the inhibition of fibrosis, rather than the direct differentiation into cardiovascular lineage cells. However, the usage of ASCs comes with the problems of low cardiac retention and survival after transplantation, like other stem cells, which compromises the effectiveness of the therapy. To overcome these drawbacks, researchers have proposed various strategies for improving survival rate and ensuring sustained paracrine secretion. They also investigated the safety and efficacy of phase I and II clinical trials of ASC-based therapy for cardiovascular diseases. In this review, we will discuss the characterization and paracrine effects of ASCs on myocardial repair, followed by the strategies for stimulating the paracrine secretion of ASCs, and finally their clinical usage.

Background Small interfering RNA (siRNA) can be used to post-transcriptional gene regulation by knocking down targeted genes. In functional genomics, biomedical research and cancer therapeutics, siRNA design is a critical research topic. Various computational algorithms have been developed to select the most effective siRNA, whereas the efficacy prediction accuracy is not so satisfactory. Many existing computational methods are based on feature engineering, which may lead to biased and incomplete features. Deep learning utilizes non-linear mapping operations to detect potential feature pattern and has been considered perform better than existing machine learning method. Results In this paper, to further improve the prediction accuracy and facilitate gene functional studies, we developed a new powerful siRNA efficacy predictor based on a deep architecture. First, we extracted hidden feature patterns from two modalities, including sequence context features and thermodynamic property. Then, we constructed a deep architecture to implement the prediction. On the available largest siRNA database, the performance of our proposed method was measured with 0.725 PCC and 0.903 AUC value. The comparative experiment showed that our proposed architecture outperformed several siRNA prediction methods. Conclusions The results demonstrate that our deep architecture is stable and efficient to predict siRNA silencing efficacy. The method could help select candidate siRNA for targeted mRNA, and further promote the development of RNA interference.

Background A number of studies have indicated that Ubiquitin-conjugating enzyme E2T (UBE2T), as an oncogene, promotes progression and metastasis of lung cancer, including lung adenocarcinoma (LUAD), but it is completely unknown whether and how UBE2T is ubiquitylated and degraded, and by which E3 ligase. NEDD4L plays a critical role in the regulation of cellular processes of various cancers, most of which is attributed to its E3 ubiquitin ligase function. However, the relationship between NEDD4L and UBE2T in LUAD has not been elucidated. Methods The relationship between NEDD4L and UBE2T in LUAD tissues and cells was found by bioinformatic analyses and immunoblotting. Cell counting kit-8, colony formation assay, half-life analysis and the in vivo ubiquitylation assay, generation of xenograft model were performed to determine how NEDD4L regulates UBE2T and its downstream signaling pathway in vitro and in vivo. Results Bioinformatic analyses found that NEDD4L, as a potential correlation E3 ligase of UBE2T, was negatively correlated with UBE2T in LUAD. Consistently, UBE2T protein half-life was shortened or extended by NEDD4L overexpression or depletion, respectively. NEDD4L inhibited LUAD cell progression in vitro and in vivo via inducing the ubiquitination-mediated UBE2T degradation, which repressed PI3K-AKT signaling. Similarly, NEDD4L predicted a better patient survival, whereas UBE2T predicted a worse survival. Conclusions Collectively, our results reveal that NEDD4L is a novel E3 ligase of UBE2T, which can inhibit PI3K-AKT signaling by targeting for UBE2T ubiquitination and degradation, resulting in repression of LUAD cell progression.

In naval and civilian domains, meticulous ship classification and detection are paramount. Nevertheless, predominant research has gravitated toward leveraging Convolutional Neural Network (CNN)-centered methodologies, often overlooking the diverse granularity inherent in ship samples. In our pursuit to holistically extract features from ship images across varying granularities, we present a transformative architecture: the Vision Transformer and Multi-Grain Feature Vector Feature Pyramid Network (ViT-MGFV-FPN). This model synergistically melds the merits of MGFV-FPN with an augmented Vision Transformer (ViT) for a comprehensive image feature extraction. To cater to the extraction of broader image features whilst sidestepping the innate quadratic complexity of traditional ViT, we unveil an enhanced version christened the Global Swin Transformer. Concurrently, the MGFV-FPN is orchestrated to harness the prowess of CNNs in distilling intricate ship attributes. Rigorous empirical evaluations underscore our model's superiority in juxtaposition with extant CNN and transformer-based paradigms for nuanced ship categorization.