Development of an innovative nomogram of risk factors to predict postoperative recurrence of gastrointestinal stromal tumors

BACKGROUND

There are many staging systems for gastrointestinal stromal tumors (GISTs), and the risk indicators selected are also different; thus, it is not possible to quantify the risk of recurrence among individual patients.

AIM

To develop and internally validate a model to identify the risk factors for GIST recurrence after surgery.

METHODS

The least absolute shrinkage and selection operator (LASSO) regression model was performed to identify the optimum clinical features for the GIST recurrence risk model. Multivariable logistic regression analysis was used to develop a prediction model that incorporated the possible factors selected by the LASSO regression model. The index of concordance (C-index), calibration curve, receiver operating characteristic curve (ROC), and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the predictive model. Internal validation of the clinical predictive capability was also evaluated by bootstrapping validation.

RESULTS

The nomogram included tumor site, lesion size, mitotic rate/50 high power fields, Ki-67 index, intracranial necrosis, and age as predictors. The model presented perfect discrimination with a reliable C-index of 0.836 (95%CI: 0.712-0.960), and a high C-index value of 0.714 was also confirmed by interval validation. The area under the curve value of this prediction nomogram was 0.704, and the ROC result indicated good predictive value. Decision curve analysis showed that the predicting recurrence nomogram was clinically feasible when the recurrence rate exceeded 5% after surgery.

CONCLUSION

This recurrence nomogram combines tumor site, lesion size, mitotic rate, Ki-67 index, intracranial necrosis, and age and can easily predict patient prognosis.

Bifidobacteria Expressing Tumstatin Protein for Antitumor Therapy in Tumor-Bearing Mice

Tumstatin (Tum) is a powerful angiostatin that inhibits proliferation and induces apoptosis of tumorous vascular endothelial cells. A nonpathogenic and anaerobic bacterium, Bifidobacterium longum (BL), selectively localizes to and proliferates in the hypoxia location within solid tumor. The aims of this study were to develop a novel delivery system for Tum using engineered Bifidobacterium and to investigate the inhibitory effect of Tum on tumor in mice. A vector that enabled the expression of Tum under the control of the pBBADs promoter of BL was constructed and transformed into BL NCC2705 by electroporation. The mouse colon carcinoma cells CT26 (1 × 10(7)/mL) were subcutaneously inserted in the left armpit of BALB/c mice. The tumor-bearing mice were treated with Tum-transformed BL, and green fluorescent protein (GFP)-transformed BL was used as a negative control. The microvessel density (MVD) in the transplanted tumor was determined, and terminal deoxynucleotidyl transferase-mediated 2'-deoxyuridine 5'-triphosphate nick end labeling was used to detect apoptosis of vascular endothelial cells in transplanted tumor. The in vitro expression of Tum was examined in BL after l-arabinose induction. Bifidobacterium longum with pBBAD-Tum (BL-Tum) showed significant antitumor effect in tumor-bearing mice. The weight, volume, growth, and MVD, as well as the percentage of apoptotic vascular endothelial cells of transplanted tumors in the tumor-bearing mice treated with Tum-transformed BL were all significantly lower than those in the GFP negative control group. Intragastric administration, injection in tumor and vena caudalis injection of Tum-transformed BL exerted marked antitumor effects in tumor-bearing mice. This is the first demonstration of the utilization of Tum-transformed BL as a specific gene delivery system for treating tumor.