Magnetic resonance imaging-based lymph node radiomics for predicting the metastasis of evaluable lymph nodes in rectal cancer.

BACKGROUND: Lymph node (LN) staging in rectal cancer (RC) affects treatment decisions and patient prognosis. For radiologists, the traditional preoperative assessment of LN metastasis (LNM) using magnetic resonance imaging (MRI) poses a challenge. AIM: To explore the value of a nomogram model that combines Conventional MRI and radiomics features from the LNs of RC in assessing the preoperative metastasis of evaluable LNs. METHODS: In this retrospective study, 270 LNs (158 nonmetastatic, 112 metastatic) were randomly split into training (n = 189) and validation sets (n = 81). LNs were classified based on pathology-MRI matching. Conventional MRI features [size, shape, margin, T2-weighted imaging (T2WI) appearance, and CE-T1-weighted imaging (T1WI) enhancement] were evaluated. Three radiomics models used 3D features from T1WI and T2WI images. Additionally, a nomogram model combining conventional MRI and radiomics features was developed. The model used univariate analysis and multivariable logistic regression. Evaluation employed the receiver operating characteristic curve, with DeLong test for comparing diagnostic performance. Nomogram performance was assessed using calibration and decision curve analysis. RESULTS: The nomogram model outperformed conventional MRI and single radiomics models in evaluating LNM. In the training set, the nomogram model achieved an area under the curve (AUC) of 0.92, which was significantly higher than the AUCs of 0.82 (P < 0.001) and 0.89 (P < 0.001) of the conventional MRI and radiomics models, respectively. In the validation set, the nomogram model achieved an AUC of 0.91, significantly surpassing 0.80 (P < 0.001) and 0.86 (P < 0.001), respectively. CONCLUSION: The nomogram model showed the best performance in predicting metastasis of evaluable LNs.

Focal adhesion kinase: important to prostaglandin E2-mediated adhesion, migration and invasion in hepatocellular carcinoma cells.

Prostaglandin E2 has been implicated in cell growth and metastasis in many types of cancers. However, the effects of PGE2 and its mechanism on cell adhesion, migration, and invasion have not been clarified yet. In this study, we found PGE2 treatment significantly increased the cell adhesion, migration, and invasion in hepatocellular carcinoma (HCC) cells. In addition, the effects of PGE2 were found to be associated with focal adhesion kinase (FAK). PGE2 treatment increased the phosphorylation and synthesis of FAK in a dose-dependent manner. RNA interference targeting FAK suppressed PGE2-mediated cell adhesion and migration. Furthermore, the downstream proteins of FAK, paxillin and Erk2, were also activated by PGE2. PGE2 treatment increased the phosphorylation and synthesis of paxillin in a dose-dependent manner. PGE2 treatment also induced the phosphorylation of Erk2. PD98059, the specific inhibitor of MEK, suppressed PGE2-mediated cell adhesion and migration. However, it had no effect on PGE2-induced activation and synthesis of FAK. These results demonstrated that PGE2 greatly induced HCC cell adhesion, migration, and invasion by activating FAK/paxillin/Erk pathway.