Our study aimed to establish a novel system for quantifying sialylation patterns and comprehensively analyze their relationship with immune cell infiltration (ICI) characterization, prognosis, and therapeutic sensitivity in small cell lung cancer (SCLC). We conducted a thorough assessment of the sialylation patterns in 100 patients diagnosed with SCLC. Our primary focus was on analyzing the expression levels of 7 prognostic sialylation-related genes. To evaluate and quantify these sialylation patterns, we devised a sialylation score (SS) using principal component analysis algorithms. Prognostic value and therapeutic sensitivities were then evaluated using multiple methods. The GSE176307 was used to verify the predictive ability of SS for immunotherapy. Our study identified 2 distinct clusters based on sialylation patterns. Sialylation cluster B exhibited a lower level of induced ICI therapy and immune-related signaling enrichment, which was associated with a poorer prognosis. Furthermore, there were significant differences in prognosis, response to targeted inhibitors, and immunotherapy between the high and low SS groups. Patients with high SS were characterized by decreased immune cell infiltration, chemokine and immune checkpoint expression, and poorer response to immunotherapy, while the low SS group was more likely to benefit from immunotherapy. This work showed that the evaluation of sialylation subtypes will help to gain insight into the heterogeneity of SCLC. The quantification of sialylation patterns played a non-negligible role in the prediction of ICI characterization, prognosis and individualized therapy strategies.

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with clinical and pathological heterogeneity. Recent studies have identified cuproptosis as a novel cell death mechanism. However, the role of cuproptosis-related genes in the pathogenesis of IPF is still unclear. Two IPF datasets of the Gene Expression Omnibus database were studied. Mann-Whitney U test, correlation analysis, functional enrichment analyses, single-sample gene set enrichment analysis, CIBERSORT, unsupervised clustering, weighted gene co-expression network analysis, and receiver operating characteristic curve analysis were used to conduct our research. The dysregulated cuproptosis-related genes and immune responses were identified between IPF patients and controls. Two cuproptosis-related molecular clusters were established in IPF, the high immune score group (C1) and the low immune score group (C2). Significant heterogeneity in immunity between clusters was revealed by functional analyses results. The module genes with the strongest correlation to the 2 clusters were identified by weighted gene co-expression network analysis results. Seven hub genes were found using the Cytoscape software. Ultimately, 2 validated diagnostic biomarkers of IPF, CDKN2A and NEDD4, were obtained. Subsequently, the results were validated in GSE47460. Our investigation illustrates that CDKN2A and NEDD4 may be valid biomarkers that were useful for IPF diagnosis and copper-related clustering.

Abstract Background S100A16 belongs to the S100 protein family, exhibiting different expression levels across several human tumors. S100A16 upregulation in many malignancies suggests its potential role in malignant transformation. However, the specific involvement of S100A16 in lung adenocarcinoma (LUAD) remains unclear. Methods This study utilized RNA sequencing and protein expression data from the Cancer Genome Atlas (TCGA) and the Human Protein Atlas (THPA) databases to scrutinize the expression of S100A16 and its associations with patients’ prognosis, clinicopathological characteristics, tumor microenvironment (TME), immune cell infiltration, expression of immune checkpoint genes, and relevant signaling pathways in LUAD. Employing ESTIMATE and CIBERSORT algorithms alongside Gene Set Enrichment Analysis (GSEA), we investigated the underlying mechanisms by which LUAD is involved in the TME. Additionally, we used single-cell sequencing to measure the role of S100A16 at the cellular level and dissect the effect on treatment response in LUAD. Results S100A16 was highly expressed in LUAD. As an independent prognostic marker, S100A16 expression was correlated with adverse outcomes. Its expression levels were positively correlated with the clinical TN stage and LUAD grade. GO and KEGG analyses revealed the predominance of molecules positively associated with S100A16 expression in LUAD, concentrating on pathways related to cellular signaling, motility, morphology, and cell interactions. The high S100A16 group showed a significantly higher TME score compared with the low S100A16 expression group. Immune cells, including M1 macrophages, memory B cells, activated NK cells, plasma cells, and naive B cells, were positively associated with S100A16 expression in LUAD. Furthermore, a positive correlation was observed between S100A16 and the expression of most immune checkpoint genes. Patients with high S100A16 expression demonstrated lower IC50 values for drugs such as 5-fluorouracil, bortezomib, cisplatin, cytarabine, docetaxel, doxorubicin, etoposide, and vinorelbine, suggesting that S100A16 overexpression increased sensitivity to these treatments in LUAD. This study provides novel insights into the role of S100A16 in LUAD and associated signaling pathways. Conclusions S100A16 is an independent prognostic marker in LUAD, intricately linked to the TME, immune cell infiltration, immune checkpoint expression, and response to treatment. This study underscores the potential of S100A16 as a prognostic marker in LUAD, advancing cancer treatment.

Abstract Background Small cell lung carcinoma (SCLC) is characterized by -poor prognosis, -high predilection for -metastasis, -proliferation, and -absence of newer therapeutic options. Elucidation of newer pathways characterizing the disease may allow for development of targeted therapies and consequently favorable outcomes. Methods The current study explored the combinatorial action of arsenic trioxide (ATO) and apatinib (APA) in vitro and in vivo. In vitro models were tested using -H446 and -H196 SCLC cell lines. The ability of drugs to reduce -metastasis, -cell proliferation, and -migration were assessed. Using bioinformatic analysis, differentially expressed genes were determined. Gene regulation was assessed using gene knock down models and confirmed using Western blots. The in vivo models were used to confirm the resolution of pathognomic features in the presence of the drugs. Growth factor receptor bound protein (GRB) 10 expression levels of human small cell lung cancer tissues and adjacent tissues were detected by IHC. Results In combination, ATO and APA were found to significantly reduce -cell proliferation, -migration, and -metastasis in both the cell lines. Cell proliferation was found to be inhibited by activation of Caspase-3, -7 pathway. In the presence of drugs, it was found that expression of GRB10 was stabilized. The silencing of GRB10 was found to negatively regulate the VEGFR2/Akt/mTOR and Akt/GSK-3β/c-Myc signaling pathway. Concurrently, absence of metastasis and reduction of tumor volume were confirmed in vivo. The immunohistochemical results confirmed that the expression level of GRB10 in adjacent tissues was significantly higher than that in human small cell lung cancer tissues. Conclusions Synergistically, ATO and APA have a more significant impact on inhibiting cell proliferation than each drug independently. ATO and APA may be mediating its action through the stabilization of GRB10 thus acting as a tumor suppressor. We thus, preliminarily report the impact of GRB10 stability as a target for SCLC treatment.

Background With the rapid advances of genetic and genomic technologies, the pathophysiological mechanisms of idiopathic pulmonary fibrosis (IPF) were gradually becoming clear, however, the prognosis of IPF was still poor. This study aimed to systematically explore the ferroptosis-related genes model associated with prognosis in IPF patients. Methods Datasets were collected from the Gene Expression Omnibus (GEO). The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to create a multi-gene predicted model from patients with IPF in the Freiburg cohort of the GSE70866 dataset. The Siena cohort and the Leuven cohort were used for validation. Results Nineteen differentially expressed genes (DEGs) between the patients with IPF and control were associated with poor prognosis based on the univariate Cox regression analysis (all P < 0.05). According to the median value of the risk score derived from an 8-ferroptosis-related genes signature, the three cohorts’ patients were stratified into two risk groups. Prognosis of high-risk group (high risk score) was significantly poorer compared with low-risk group in the three cohorts. According to multivariate Cox regression analyses, the risk score was an independently predictor for poor prognosis in the three cohorts. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) confirmed the signature's predictive value in the three cohorts. According to functional analysis, inflammation- and immune-related pathways and biological process could participate in the progression of IPF. Conclusions These results imply that the 8-ferroptosis-related genes signature in the bronchoalveolar lavage samples might be an effective model to predict the poor prognosis of IPF.

Background: This retrospective study aimed to evaluate the value of D-dimer to platelets ratio (DPR) in predicting the in-hospital prognosis of patients with acute pulmonary embolism (APE). Methods: We retrospectively reviewed the medical records of 237 patients with APE admitted from January 2016 to August 2020. The associations between the DPR and other predictors and serious adverse events were analyzed with univariate and multivariate analyses. Results : A total of 134 (56.5%) patients were categorized into the low DPR group (DPR <4.55) and 103 (43.5%) in the high DPR group (DPR ≥4.55) according to the cut-off value for the DPR of 4.55 with a sensitivity of 87.5% and a specificity of 62.0%, respectively. The model that included DPR revealed a significant improvement in the accuracy of the predictive value compared with the sPESI score alone (AUC: 0.721 [95% CI: 0.636-0.807]; P <0.001 vs AUC: 0.607 [95% CI: 0.496-0.718]; P=0.085; respectively. Multivariate analysis showed that DPR (P=0.001) and the pulmonary embolus position (P=0.011) were independent factors of serious adverse events (SAEs) of APE inpatients. The in-hospital SAEs rate was significantly higher in the high DPR group compared with the low DPR group. Conclusion: Our findings showed that DPR is seemed to be a novel marker of risk stratification in patients with APE. This parameter may be used to identify these patients at higher risk for clinical adverse events, and individualization of therapeutic interventions should be timely considered.

Background The Coronavirus Disease 2019 (COVID-19) had become a Public Health Emergency of International Concern with more than 90 million confirmed cases worldwide. Therefore, this study aims to establish a predictive score model of progression to severe type in patients with COVID-19. Methods This is a retrospective cohort study of 151 patients with COVID-19 diagnosed by nucleic acid test or specific serum antibodies from February 13, 2020, to March 14, 2020, hospitalized in a COVID-19-designed hospital in Wuhan, China. Results Of the 151 patients with average age of 63 years, 64 patients were male (42.4%), and 29 patients (19.2%) were classified as severe group. Multivariate analysis showed that age > 65 years (odds ratio [OR] = 9.72, 95%CI: 2.92–32.31, P < 0.001), lymphocyte count ≤ 1.1 × 109/L (OR = 3.42, 95%CI: 1.24–9.41, P = 0.017) and AST > 35 U/L (OR = 3.19, 95%CI: 1.11–9.19, P = 0.032) were independent risk factors for the disease severity. The area under curve (AUC) of receiver operating characteristic curve of the probabilities of the composite continuous variable (age + lymphocyte + AST) is 0.796. Finally, a predictive score model called ALA was established, and its AUC was 0.83 (95%CI: 0.75–0.92). Using a cutoff value of 9.5 points, the positive and negative predictive values were 54.1% (38–70.1%) and 92.1% (87.2–97.1%), respectively. Conclusion The ALA score model can quickly identify severe patients with COVID-19, so as to help clinicians to better choose accurate management strategy.

Background SLC15A family members are known as electrogenic transporters that take up peptides into cells through the proton-motive force. Accumulating evidence indicates that aberrant expression of SLC15A family members may play crucial roles in tumorigenesis and tumor progression in various cancers, as they participate in tumor metabolism. However, the exact prognostic role of each member of the SLC15A family in human lung cancer has not yet been elucidated. Materials and Methods We investigated the SLC15A family members in lung cancer through accumulated data from TCGA and other available online databases by integrated bioinformatics analysis to reveal the prognostic value, potential clinical application and underlying molecular mechanisms of SLC15A family members in lung cancer. Results Although all family members exhibited an association with the clinical outcomes of patients with NSCLC, we found that none of them could be used for squamous cell carcinoma of the lung and that SLC15A2 and SLC15A4 could serve as biomarkers for lung adenocarcinoma. In addition, we further investigated SLC15A4-related genes and regulatory networks, revealing its core molecular pathways in lung adenocarcinoma. Moreover, the IHC staining pattern of SLC15A4 in lung adenocarcinoma may help clinicians predict clinical outcomes. Conclusion SLC15A4 could be used as a survival prediction biomarker for lung adenocarcinoma due to its potential role in cell division regulation. However, more studies including large patient cohorts are required to validate the clinical utility of SLC15A4 in lung adenocarcinoma.

目的 旨在探索包括高血压在内的影响新型冠状病毒肺炎预后的危险因素.方法 收集2020年2月13日～2020年3月4日来自武汉市冠状病毒定点医院的151例患者的电子病历信息.结果 151例新型冠状病毒感染者中,平均年龄为64岁,64例(42.4％)为男性患者.结果显示在重症肺炎与非重症患者中,年龄(P＜0.001)、白细胞(P=0.003)、淋巴细胞(P＜0.01)、白蛋白(P =0.001)、乳酸脱氢酶水平(P=0.001)等具有显著性差异.而高血压和非高血压SARS-CoV-2感染患者在重症肺炎的发生率、死亡率等方面无显著性差异(P＞0.05).结论 高龄、高乳酸脱氢酶、低淋巴细胞可能是冠状病毒肺炎重症及死亡的危险因素,而是否患有高血压与冠状病毒肺炎严重程度和死亡无明显相关性.

The Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a public health emergency of international concern. The current study aims to explore whether the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are associated with the development of death in patients with COVID-19. A total of 131 patients diagnosed with COVID-19 from 13 February 2020 to 14 March 2020 in a hospital in Wuhan designated for treating COVID-19 were enrolled in the current study. These 131 patients had a median age of 64 years old (interquartile range: 56-71 years old). Furthermore, among these patients, 111 (91.8%) patients were discharged and 12 (9.2%) patients died in the hospital. The pooled analysis revealed that the NLR at admission was significantly elevated for non-survivors, when compared to survivors (P< 0.001). The NLR of 3.338 was associated with all-cause mortality, with a sensitivity of 100.0% and a specificity of 84.0% (area under the curve (AUC): 0.963, 95% confidence interval (CI) 0.911-1.000;P< 0.001). In view of the small number of deaths (n= 12) in the current study, NLR of 2.306 might have potential value for helping clinicians to identify patients with severe COVID-19, with a sensitivity of 100.0% and a specificity of 56.7% (AUC: 0.729, 95% CI 0.563-0.892;P= 0.063). The NLR was significantly associated with the development of death in patients with COVID-19. Hence, NLR is a useful biomarker to predict the all-cause mortality of COVID-19.

Background: Coronavirus disease 2019 (COVID-19) has become a global emerging infectious disease. Objectives: To analyze the initial clinical characteristics of COVID-19 suspected and confirmed patients on admission in order to find out which kinds may be more likely to get positive nucleic acid testing results, and to explore the risk factors associated with all-cause death. Methods: Medical records from 309 highly suspected cases with pneumonia were collected from February 13, 2020, to March 14, 2020, in a COVID-19-designated hospital of Wuhan. The majority of the clinical data were collected on the first day of hospital admission. Results: Of 309 patients with median age 64 years (interquartile ranges [IQR], 53–72 years), 111 patients (35.9%) were confirmed by nucleic acid testing (median age 64 years, IQR: 56–71 years; 48 males). Of those 111 patients, 13 (11.7%) patients died. In multivariate analysis, factors associated with positive testing included fatigue (odds ratios [OR] = 3.14; 95% confidence interval [CI]: 1.88–5.24, p < 0.001), cough (OR = 0.55; 95% CI: 0.32–0.95, p = 0.032), no less than 1 comorbidity (OR = 1.77; 95% CI: 1.06–2.98, p = 0.030), and severe pneumonia (OR = 2.67; 95% CI: 1.20–5.97, p = 0.016). Furthermore, age, dyspnea, noneffective antibiotic treatment, white blood cell, lymphocyte, platelets, and organ dysfunction (e.g., higher lactate dehydrogenase) were significantly associated with all-cause in-hospital death in patients with COVID-19. Conclusion: Patients with severe forms of this disease were more likely to get positive results. Age and organ dysfunction were associated with a greater risk of death.

Interstitial lung diseases (ILDs), a diverse group of diffuse lung diseases, mainly affect the lung parenchyma. The low-throughput ‘omics’ technologies (genomics, transcriptomics, proteomics) and relative drug information have begun to reshaped our understanding of ILDs, whereas, these data are scattered among massive references and are difficult to be fully exploited. Therefore, we manually mined and summarized these data at a database (ILDGDB, http://ildgdb.org/ ) and will continue to update it in the future. The current version of ILDGDB incorporates 2018 entries representing 20 ILDs and over 600 genes obtained from over 3000 articles in four species. Each entry contains detailed information, including species, disease type, detailed description of gene (e.g. official symbol of gene), and the original reference etc. ILDGDB is free, and provides a user-friendly web page. Users can easily search for genes of interest, view their expression pattern and detailed information, manage genes sets and submit novel ILDs-gene association. The main principle behind ILDGDB’s design is to provide an exploratory platform, with minimum filtering and interpretation, while making the presentation of the data very accessible, which will provide great help for researchers to decipher gene mechanisms and improve the prevention, diagnosis and therapy of ILDs.

Pulmonary embolism (PE) is gradually considered to be the third most common disease in the vascular disease category. Lung cancer is the most frequently diagnosed cancer and the leading cause of cancer death among males worldwide. Although initially appearing as distinct entities, lung cancer is a great risk factor for the development of PE. Pulmonary embolism is common in lung cancer patients, with a pooled incidence of 3.7%, and unsuspected pulmonary embolism (UPE) is also non-negligible with a rough rate ranging from 29.4% to 63%. Many risk factors of PE have been detected and could be classified into three categories: lung cancer-related, patient-related, and treatment-related factors. Decreased mean survival time could be significantly observed in lung cancer patients with PE or UPE compared to those only, but suspected PE has higher mortality than UPE. Prophylactic anticoagulant therapy benefit might be highest in patients with stage IV non-small cell lung cancer (NSCLC) or limited small cell lung cancer (SCLC), and heparin seems superior to warfarin for thrombotic prophylaxis. Periodically reassessing the risk-benefit ratio of anticoagulant treatment will be an efficient treatment strategy in lung cancer patients with PE.

Allograft rejection is an important issue post cardiac transplantation. In order to investigate the effect of combined treatment with simvastatin and rapamycin on allograft rejection, a cardiac transplantation rat model was employed in the present study. The survival time of rats following cardiac transplantation was recorded, while histopathological alterations were assessed by hematoxylin and eosin staining. The levels of transcription factors were measured by reverse transcription-quantitative polymerase chain reaction. In addition, the levels of CD4+ interleukin (IL)-17+ cells and CD4+ forkhead box P3 (FOXP3)+ cells in the allografts and CD4+ T cells and CD8+ T cells in the spleens were detected by flow cytometry. The results of the current study demonstrated that, following treatment with simvastatin and rapamycin, the survival time of model rats was prolonged, and the histopathological damage was attenuated. Treatment with simvastatin and rapamycin also led to decreased retinoic acid receptor-related orphan receptor γt (RORγt) level, increased FOXP3 level, reduced levels of CD4+IL-17+, CD4+ T and CD8+ T cells, and increased level of CD4+FOXP3+ cells. In conclusion, the current study observed that simvastatin and rapamycin performed a synergistic effect to reduce cardiac transplantation rejection. Thus, combined therapy of simvastatin and rapamycin may be a promising adjuvant therapy to reduce rejection post cardiac transplantation.

Objective To study the clinical efficacy of non-invasive mechanical ventilation in the treatment of chronic obstructive pulmonary disease(COPD) patients with type Ⅱ respiratory failure.Methods Two hundred and seven patients with COPD with type Ⅱ respiratory failure were divided into the treatment group(104 cases) and control group(103 cases).Anti-infection,eliminating phlegm,relieving asthma and oxygen therapy were given to both groups and the treatment group was treated with bi-level positive airway pressure(BiPAP) ventilation in addition to above routine treatment.Dyspnea relieving degree,the artery blood gas were obtained at the 4 h,48 h.Average length of stay and hospital mortality were observed before and after the treatment.Results PaO2 and PaCO2 changed more significantly in treatment group than that in the control group(P0.05).Conclusion BiPAP is definitely valuable for treatment of COPD patients with type Ⅱ respiratory failure and can shorten the mean hospital time and reduce hospital mortality.