The antineoplastic drugs pingyangmycin ( PYM ) and adriamycin ( ADM ) and biological response modifier thymosin were tested for the effects on concanavalin A ( Con-A ) induced interleukin-2 ( IL-2 ) production by MTT colorimetric assay. When the drug was added to splenocytes of BALB/c mice in the presence of suboptimal dose of Con-A for 24h ,PYM increased IL-2 release over a wide range of doses, and this effect was achieved when using less than 0.01mg/L PYM. However, 10mg/L PYM inhibited IL-2 activity in the supernatant of cultures. ADM was able to enhance the production of IL-2, and thymosin enhance production of IL-2 too.When PYM or ADM applied with thymosin, the additive effects were shown. The activity of IL-2 was increased significantly.

Objective Based on data mining technology, we discussed the correlation of different gene mutation, fusion or amplification in advanced lung cancer patients. Methods 630 cases in our hospital were collected and the drug database was established by Excel 2016. Frequency analysis and association rules were used for statistical analysis, and statistical analysis was performed on SPSS22.0 and SPSSModerler statistical software.Results There were 26 high frequency genes, such as EGFR-19 mutation, ALK fusion, RET mutation, EGFRL858 R-21 mutation, ALK mutation, and the first 6 cases of T790M mutation. The first 26 were NRAS-G12 D mutation and BRAF-G466 V mutation, MYC-R450 W mutation and CYP2D6 mutation, GATA3 M423 fs mutation and ESR1 mutation, abrupt mutation, mutation and sudden process. The variable classification values are associated with each other. The minimum value of gene association analysis was 50％ and support was 10％. After Apriori module analysis, EGFR-19 mutation and 14 genes were not found (confidence degree 46.667％) , EGFR-19 mutation and T790 M mutation (confidence degree 40％) , EGFR-19 mutation and TP53 mutation (confidence degree 13.333％) , ROS1 fusion and MET amplification (confidence 47.619％) , MET amplification and ROS1 melting (confidence level 50％) , T790 M mutation and EGFR amplification (confidence level 57.895％) , EGFR-19 mutation and EGFR amplification (confidence 42.105％). Cluster analysis BRAF-G466 V and NRAS-G12D, MYC-R450 W and CYP2 D6, GATA3 M423 fs and SRC, PIK3 CA amplification and PIK3CA, Pten and EGFEL861 Q-21, KRAS G12A and blending. Conclusion There are correlations between different genes and mutation, fusion, lack and amplification of lung cancer.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths, patients with non-small cell lung cancer (NSCLC) usually have distant metastases, such as bone metastasis, brain metastasis, and lung metastasis. The purpose of this study was to explore the risk factors for bone metastasis in NSCLC patients. METHODS: A total of 176 cases of NSCLC were selected from May 2009 to May 2011, and patients were divided into two groups, namely the bone metastasis group and non-bone metastasis group. The general clinicopathological data of the two groups and analyzing the independent risk factors of bone metastasis were compared. RESULTS: In the general clinicopathological data of NSCLC patients. The thrombus or not and tumor-node-metastasis (TNM) stage were closely related to the occurrence of bone metastasis, and were statistically significant (all P<0.01). Prothrombin time, activated partial thromboplastin time, Fibrinogen, thrombin time, blood platelet, D-Dimer and alkaline phosphatase have significantly difference between the two groups (all P<0.05). Logistic regression analysis showed that fibrinogen, activated partial thromboplast in time, alkaline phosphatase, T4 phase, N3 phase and d-dimer were independent risk factors for bone metastasis in NSCLC patients. CONCLUSIONS Fibrinogen, alkaline phosphatase, T3, N2 stage and D-Dimer is the independent risk factors of bone metastases in patients with NSCLC.
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Aged ; Bone Neoplasms ; diagnosis ; secondary ; Carcinoma, Non-Small-Cell Lung ; pathology ; therapy ; Female ; Follow-Up Studies ; Humans ; Lung Neoplasms ; pathology ; therapy ; Male ; Middle Aged ; Multivariate Analysis ; Neoplasm Staging ; Prognosis ; Risk Factors