Sentence examples for model of recurrence from inspiring English sources

Analysis of INMT and TRIP13 expression combined as a model of recurrence did not significantly improve the prediction capability over using INMT alone.

These selected genes were used to develop a gene expression-based prediction model of recurrence risk using the supervised principal component method of E. Bair and R. Tibshirani [ 14].

This may be the case for 2379, which also showed overexpression of c-Myc protein; interestingly, amplification of the c-Myc gene has been observed in a model of recurrence after de-induction of the doxycycline-dependent oncogene [ 14].

Using an in vitro model of recurrence after exposure of ovarian cancer cells to supra-pharmacological doses of cisplatin and paclitaxel, and for clinically relevant exposure times, we demonstrated that a clinically relevant dose of the synthetic steroid mifepristone significantly improves treatment efficacy by reducing the number and clonogenic survival capacity of escape cells.

Expression microarrays have also been used to identify profiles characteristic of metastasic disease [ 1], prostate intraepithelial neoplasia (PIN) [ 2], and subgroups of tumors with distinct outcomes [ 3], including a 5-gene model predictive of recurrence [ 4].

The spontaneous development of mesenchymal tumors after epithelial cell regression has been proposed as a model of tumor recurrence [9].

In the mouse model of infection, recurrence of disease and late mortality has also been observed to occur in 40-60% of mice treated with vancomycin [ 24, 30].

Furthermore, the spontaneous development of mesenchymal tumour after regression of the epithelial compartment has been proposed as a model of tumour recurrence (Moody et al, 2005).

In this study, we applied global gene expression profiling on samples of a well-established mouse model of tumor recurrence, and identified differentially expressed candidate genes some of which have been described previously in the context of HNSCC development or tumor recurrence, such as mucins, kallikreins, tryptase alpha/beta 1, claudin-10 and lactotransferrin [ 15- 20].

Using established methods [ 30], we developed several models predictive of recurrence independent of chemotherapy response, although future development would naturally focus on the smaller, simpler models (for example, the five miRNA profile; Figure 2H).

A linear mixed-model regression of recurrence rate, probability and site type on AMUA response strength shows that all three variables and their interactions are statistically significant factors in explaining the observed variation (Table 1), and therefore confirms the patterns described above.