Comparison of monocyte-derived dendritic cells from colorectal cancer patients, non-small-cell-lung-cancer patients and healthy donors

Vaccine ◽  
2009 ◽  
Vol 28 (2) ◽  
pp. 542-547 ◽  
Author(s):  
P. Kvistborg ◽  
C.M. Bechmann ◽  
A.W. Pedersen ◽  
H.C. Toh ◽  
M.H. Claesson ◽  
...  
2019 ◽  
Vol 70 (2) ◽  
pp. 109-114 ◽  
Author(s):  
Plamen Minkov ◽  
Maya Gulubova ◽  
Koni Ivanova ◽  
Evelin Obretenov ◽  
Julian Ananiev

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 21014-21014
Author(s):  
L. Chen ◽  
Y. Wang ◽  
Z. Yu

21014 Objective: To detect the hypermethylation status of RASSF1A promoter in serum DNA of lung cancer patients and to analyze its correlation with clinicopathological features. Methods: Serum DNA was extracted from peripheral blood from 80 primary lung cancer patients, 35 benign pulmonary disease patients and 15 healthy donors. The methylation status of RASSF1A promoter was determined using methylation-specific PCR technique, and the correlation between methylation profiles and clinicopathological parameters was statistically analyzed. Results: Aberrant methylation of RASSF1A was detected in 27 of the 80 (33.8%) patients with lung cancer but no benign pulmonary disease patients or healthy donors (p<0.001). RASSF1A was preferentially observed in small cell lung cancer (p=0.042), while no statistical difference was found among methylation frequencies of different subtypes of non-small cell lung cancer. The methylation status was also found to be associated with relative poor differentiation (p=0.009) and late stage (p=0.013), but not with gender, age or treatment. Conclusion: RASSF1A promoter is frequently hypermethylated in serum DNA of primary lung cancer patients, and RASSF1A is a promising novel biomarker for lung cancer diagnosis. No significant financial relationships to disclose.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhou Jie ◽  
Zeng Zhiying ◽  
Li Li

AbstractUsing the method of meta-analysis to systematically evaluate the consistency of treatment schemes between Watson for Oncology (WFO) and Multidisciplinary Team (MDT), and to provide references for the practical application of artificial intelligence clinical decision-support system in cancer treatment. We systematically searched articles about the clinical applications of Watson for Oncology in the databases and conducted meta-analysis using RevMan 5.3 software. A total of 9 studies were identified, including 2463 patients. When the MDT is consistent with WFO at the ‘Recommended’ or the ‘For consideration’ level, the overall concordance rate is 81.52%. Among them, breast cancer was the highest and gastric cancer was the lowest. The concordance rate in stage I–III cancer is higher than that in stage IV, but the result of lung cancer is opposite (P < 0.05).Similar results were obtained when MDT was only consistent with WFO at the "recommended" level. Moreover, the consistency of estrogen and progesterone receptor negative breast cancer patients, colorectal cancer patients under 70 years old or ECOG 0, and small cell lung cancer patients is higher than that of estrogen and progesterone positive breast cancer patients, colorectal cancer patients over 70 years old or ECOG 1–2, and non-small cell lung cancer patients, with statistical significance (P < 0.05). Treatment recommendations made by WFO and MDT were highly concordant for cancer cases examined, but this system still needs further improvement. Owing to relatively small sample size of the included studies, more well-designed, and large sample size studies are still needed.


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