Author contributions: P.-J.H. participated in the data collection and coordination and analyzed the clinical data. L.-E.Y. participated in the data collection. W.-M.K. and Z.-G. Q. conceived the study, participated in its design and coordination, and analyzed the clinical data. All authors helped draft the manuscript. Patient consent: Written consent for publication was obtained from the patients.

Long non-coding RNAs (lncRNAs) serve comprehensive roles in various diseases, including cancer. lncRNA upregulated in bladder cancer 1 (linc-UBC1) is a notable biomarker of prognosis in certain cancer types; however, its involvement in the progression of colorectal cancer (CRC) remains unknown. The present study aimed to investigate the expression of linc-UBC1 in patients with CRC and to investigate its effect on CRC cells. The expression levels of linc-UBC1 were estimated by reverse transcription-quantitative polymerase chain reaction in clinical CRC specimens and matched adjacent non-tumor mucosa from 96 cases of CRC, as well as in a number of CRC cell lines. In addition, the biological roles of linc-UBC1 were examined using a cell counting kit-8 assay, flow cytometry, and migration and invasion assays following the downregulation of linc-UBC1 by small interfering RNA. The results revealed that linc-UBC1 was significantly overexpressed in CRC tissues and the majority of CRC cell lines compared with the matched non-tumor mucosa and normal intestinal epithelial cells. Furthermore, high expression levels of linc-UBC1 were significantly associated with large tumor size, greater tumor depth, lymph node metastasis, and advanced tumor-node-metastasis stages. Patients with abnormal expression of linc-UBC1 had poorer overall survival times according to Kaplan–Meier analyses. Furthermore, multivariate Cox regression analysis indicated that linc-UBC1 was a significant independent prognostic factor. The results also revealed that reducing the expression of linc-UBC1 led to the inhibition of migration, invasion, and proliferation of CRC cells in vitro. Taken together, the results of the present study suggest that overexpression of linc-UBC1 promotes proliferation and metastasis in CRC, and may be considered as a novel diagnostic marker of CRC.

Background. Lung cancer has been one of the most deadly illnesses all over the world, and radiotherapy can be an effective approach for treating lung cancer. Now, mathematical model has been extended to many biomedical fields to give a hand for analysis, evaluation, prediction, and optimization. Methods. In this paper, we propose a multicomponent mathematical model for simulating the lung cancer growth as well as radiotherapy treatment for lung cancer. The model is digitalized and coded for computer simulation, and the model parameters are fitted with many research and clinical data to provide accordant results along with the growth of lung cancer cells in vitro. Results. Some typical radiotherapy plans such as stereotactic body radiotherapy, conventional fractional radiotherapy, and accelerated hypofractionated radiotherapy are simulated, analyzed, and discussed. The results show that our mathematical model can perform the basic work for analysis and evaluation of the radiotherapy plan. Conclusion. It will be expected that in the near future, mathematical model will be a valuable tool for optimization in personalized medical treatment.

Objective To setup a three‐component tumor growth mathematical model and discuss its basic application in tumor fractional radiotherapy with computer simulation. Method First, our three‐component tumor growth model extended from the classical Gompertz tumor model was formulated and applied to a fractional radiotherapy with a series of proper parameters. With the computer simulation of our model, the impact of some parameters such as fractional dose, amount of quiescent tumor cells, and α/β value to the effect of radiotherapy was also analyzed, respectively. Results With several optimal technologies, the model could run stably and output a series of convergent results. The simulation results showed that the fractional radiotherapy dose could impact the effect of radiotherapy significantly, while the amount of quiescent tumor cells and α/β value did that to a certain extent. Conclusions Supported with some proper parameters, our model can simulate and analyze the tumor radiotherapy program as well as give some theoretical instruction to radiotherapy personalized optimization.

Although the prognostic value of nodal metastases in differentiated thyroid cancer remains controversial, it is of interest to evaluate and understand the different characteristics of predictive outcomes.A multicenter retrospective study was conducted in 215 untreated patients with differentiated thyroid cancer from July 1997 to July 2015 in 4 medical centers of Guangdong Province. A total of 107 patients with nodal metastases (group A) were compared to 108 patients without metastases (group B). The 5-year disease-free survival (DFS), overall survival (OS), and postoperative complications in both groups were calculated. Variables predictive of DFS and OS were evaluated in group A.The group A had lower 5-year DFS (69.16%, 11 months) and shorter median time of recurrence than those in group B (87.96%, 8.5 months, respectively, P < 0.001). The incidence of temporary hypoparathyroidism in group A is lower; whereas higher incidence of temporary unilateral vocal cord palsy, permanent hypoparathyroidism, permanent unilateral vocal cord palsy, and bilateral vocal cord palsy in group A were observed. Both univariate and multivariate analyses in group A revealed that age, pathological tumor node metastasis (pTNM) stage, and histology were related to DFS (P < 0.05); while pTNM stage and histology were related to OS only in univariate analyses.Positive nodal metastases have significant prognostic value in patients with differentiated thyroid cancer in Guangdong, China and primarily reduce DFS. Moreover, patients with positive nodal metastases who are >45 years and have higher pTNM stage or follicular histology tend to have poor prognosis. Selective lymph node dissection with appropriate postoperative treatment and frequent follow-up should be accorded to these vulnerable groups of patients.

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Background: Lung cancer has been one of the most deadly illnesses all over the world and radiotherapy can be an effective approach for treating lung cancer. Now, mathematical model has been extended to many biomedical fields to give a hand for analysis, evaluation, prediction and optimization. Methods: In this paper, we propose a multi-component mathematical model for simulating the lung cancer growth as well as radiotherapy treatment for lung cancer. The model is digitalized and coded for computer simulation and the model parameters are fitted with many research and clinical data to provide accordant results along with the growth of lung cancer cells in vitro. Results: Some typical radiotherapy plans such as stereotactic body radiotherapy, conventional fractional radiotherapy and accelerated hypo-fractionated radiotherapy are simulated, analyzed and discussed. The results show that our mathematical model can perform the basic work for analysis and evaluation of the radiotherapy plan. Conclusion: It will be expected that in the near future, mathematical model will be a valuable tool for optimization in personalized medical treatment.