Combined treatment with endostar can improve the response rate for NSCLC patients without increasing the risk of developing severe adverse event.

Background: The rarity of pulmonary sarcomatoid carcinoma (PSC) and the lack of prospective clinical trials have led to limited knowledge of its clinical characteristics. This study aimed to evaluate the survival and prognostic factors of PSC and to build a nomogram for clinical practice. Methods: Eligible patients diagnosed from 2010 to 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. We compared the clinical characteristics and survival times of PSC patients with those of lung adenocarcinoma (LADC) and lung squamous cell carcinoma (LSCC) patients. We also used univariate and multivariable Cox regression to estimate mortality hazard ratios among patients with PSC, while a visual nomogram was established to judge the prognosis. Discrimination, calibration, clinical utility, and reproducibility were validated by Harrell's concordance index (C-index), the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Results: A total of 400 PSC patients (0.42%) were identified in the SEER database, whereas 58 474 and 33 637 patients were diagnosed with LADC and LSCC, respectively. Age, T stage, grade, surgery, and radiation were shown to be significant prognostic factors in the Cox regression analyses and were included in the nomogram as predictors. The C-index of the nomogram in the validation set was 0.759. The AUC also demonstrated the good performance of the nomogram, and DCA demonstrated its good clinical applicability. Conclusion: We established a novel nomogram to predict the prognosis of PSC, which can help clinicians make tailored decisions and adjust follow-up management strategies, and can provide accurate and individualized survival predictions.

Long non-coding RNAs (lncRNAs) serve a crucial role in every aspect of cell biological functions as well as in a variety of diseases, including cardiovascular disease, cancer and nervous system disease. However, the differential expression profiles of lncRNAs in Marfan syndrome (MFS) have not been reported. The aim of the present study was to identify potential target genes behind the pathogenesis of MFS by analyzing microarray profiles of lncRNA in aortic tissues from individuals with MFS and normal aortas (NA). The differentially expressed lncRNA profiles between MFS (n=3) and NA (n=4) tissues were analyzed using microarrays. Bioinformatics analyses were used to further investigate the candidate lncRNAs. Reverse transcription-quantitative (RT-qPCR) was applied to validate the results. In total, the present study identified 294 lncRNAs (245 upregulated and 49 downregulated) and 644 mRNAs (455 upregulated and 189 downregulated) which were differential expressed between MFS and NA tissues (fold change ≥1.5; P<0.05). Gene Ontology enrichment analysis indicated that the differentially expressed mRNAs were involved in cell adhesion, elastic fiber assembly, extracellular matrix (ECM) organization, the response to virus and the inflammatory response. Kyoto Encyclopedia of Gene and Genomes pathway analysis indicated that the differentially expressed mRNAs were mainly associated with focal adhesion, the ECM-receptor interaction, the mitogen-activated protein kinase signaling pathway and the tumor necrosis factor signaling pathway. The lncRNA-mRNA coexpression network analysis further elucidated the interaction between the lncRNAs and mRNAs. A total of five lncRNAs (uc003jka.1, uc003jox.1, X-inactive specific transcript, linc-lysophosphatidic acid receptor 1 and linc-peptidylprolyl isomerase domain and WD repeat containing 1) with the highest degree of coexpression were selected and confirmed using RT-qPCR. In the present study, expression profiles of lncRNA and mRNA in MFS were revealed using microarray analysis. These results provided novel candidates for further investigation of the molecular mechanisms and effective targeted therapies for MFS.

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Lung large cell neuroendocrine carcinoma (LCNEC) is a rare and highly aggressive malignancy with a dismal prognosis. This study was designed to depict patterns of distant organ metastatic and to analyze prognosis of LCNEC patients. We gathered data from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. We conducted the Kaplan–Meier method to calculate overall survival (OS) and compare different variables. Cox proportional hazards regression models in univariate and multivariate analyses were employed to further explore prognostic factors. A total of 1335 LCNEC patients were eventually selected from the SEER database, of which 348 patients (26.0%) had single organ metastasis and 197 patients (14.8%) had multiple metastases. Our study indicates that patients with single organ metastasis generally have a poor prognosis, with a median OS of 8 months for both lung and brain metastasis with 1-year survival rates of 33% and 29% respectively. Patients with multiple metastases exhibited the worst prognosis, with a median OS of only 4 months and a 1-year OS of 8%. Multivariate analysis revealed that age, T stage, N stage, chemotherapy and radiation in metastatic patients were independently associated with OS. In conclusion, LCNEC exhibits a high metastatic rate when diagnosed. The most common metastatic organ is the brain in single-site metastatic patients. Patients with single or multiple metastases exhibit a significantly worse prognosis than those with non-organ metastases. In the group of single organ metastases, patients with brain and lung metastases had a better prognosis than those with bone and liver metastases.