Cyclooxygenase-2 expression as a predictor of para-aortic lymph node recurrence in uterine cervical cancer

Development of machine learning models integrating PET/CT radiomic and immunohistochemical pathomic features for treatment strategy choice of cervical cancer with negative pelvic lymph node by mediating COX-2 expression

Objectives: We aimed to establish machine learning models based on texture analysis predicting pelvic lymph node metastasis (PLNM) and expression of cyclooxygenase-2 (COX-2) in cervical cancer with PET/CT negative pelvic lymph node (PLN).

Methods: Eight hundred and thirty-seven texture features were extracted from PET/CT images of 148 early-stage cervical cancer patients with negative PLN. The machine learning models were established by logistic regression from selected features and evaluated by the area under the curve (AUC). The correlation of selected PET/CT texture features predicting PLNM or COX-2 expression and the corresponding immunohistochemical (IHC) texture features was analyzed by the Spearman test.

Results: Fourteen texture features were reserved to calculate the Rad-score for PLNM and COX-2. The PLNM model predicting PLNM showed good prediction accuracy in the training and testing dataset (AUC = 0.817, p < 0.001; AUC = 0.786, p < 0.001, respectively). The COX-2 model also behaved well for predicting COX-2 expression levels in the training and testing dataset (AUC = 0.814, p < 0.001; AUC = 0.748, p = 0.001). The wavelet-LHH-GLCM ClusterShade of the PET image selected to predict PLNM was slightly correlated with the corresponding feature of the IHC image (r = −0.165, p < 0.05). There was a weak correlation of wavelet-LLL-GLRLM LongRunEmphasis of the PET image selected to predict COX-2 correlated with the corresponding feature of the IHC image (r = 0.238, p < 0.05). The correlation between PET image selected to predict COX-2 and the corresponding feature of the IHC image based on wavelet-LLL-GLRLM LongRunEmphasis is considered weak positive (r = 0.238, p=<0.05).

Conclusion: This study underlined the significant application of the machine learning models based on PET/CT texture analysis for predicting PLNM and COX-2 expression, which could be a novel tool to assist the clinical management of cervical cancer with negative PLN on PET/CT images.

Prognostic significance of cyclooxygenase-2 in cervical cancer: a meta-analysis

Published data on the prognostic value of cyclooxygenase-2 (COX-2) overexpression in cervical cancer are conflicting and heterogeneous. We performed a meta-analysis to more precisely estimate its prognostic significance. The pooled hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were used to estimate the effects. Twenty-three studies with 1,477 cervical cancer patients were selected to evaluate the association between COX-2 and overall survival (OS), disease-free survival (DFS), response to chemoradiation (RC) and clinicopathological parameters. High COX-2 expression predicted poor OS (HR: 2.53, 95% CI: 1.54-4.18), DFS (HR: 2.41, 95% CI: 1.58-3.69) and RC (OR: 3.03, 95% CI: 1.97-4.64). Subgroup analyses showed that COX-2 overexpression was related significantly with poor OS in patients treated by chemoradiation or surgery, and in patients with squamous cell carcinoma, respectively. Besides, COX-2 overexpression was related significantly with poor DFS in chemoradiation subgroup. Furthermore, COX-2 overexpression was associated with poor RC in patients who received "FP" regimen or "P" regimen. Additionally, there were significant associations between COX-2 expression and all clinicopathological parameters except tumor grade. The pooled ORs (95% CI) were as follows: 1.49 (1.09-2.04) for age, 1.77 (1.22-2.56) for lymph node metastasis, 1.04 (0.74-1.47) for tumor grade, 1.71 (1.12-2.64) for tumor size, 2.38 (1.28-4.45) for FIGO stage, 3.96 (2.32-6.77) for histological type, 2.45(1.10-5.42) for parametrical involvement. This meta-analysis indicated that COX-2 overexpression might be an unfavorable prognostic and a chemoradiation resistance predictive factor for cervical cancer; it could potentially help to stratify patients further in clinical treatment.

siRNA-mediated downregulation of COX-2 gene expression alters the proliferation of hepatocellular carcinoma HepG2 cells

AIM: To explore the effects of siRNA-mediated downregulation of COX-2 gene expression on the proliferation of hepatocellular carcinoma HepG2 cells.

METHODS: HepG2 cells were divided into four groups: COX-2 siRNA intervention group, control siRNA intervention group, empty liposome group and blank control group. COX-2 siRNA was transfected into HepG2 cells by lipofection. Cell proliferation inhibition was measured at 24, 48 and 72 h after transfection by MTT (thiazolyl blue) assay. The changes in cell cycle distribution were detected at 24 h after transfection by flow cytometry. The expression levels of COX-2 and ERK1/2 mRNAs and proteins were detected at 24 h after transfection by semiquantitative RT-PCR and Western blot, respectively.

RESULTS: The proliferation inhibition rate achieved in the COX-2 siRNA intervention group was higher than those in the control siRNA intervention group and empty liposome group (67.08% vs 2.45% and 1.56%, both P < 0.01). The percentage of HepG2 cells arrested at G₁ phase (DNA presynthetic phase) was increased in the COX-2 siRNA intervention group as compared to the control siRNA intervention group, empty liposome group and blank control group (72.80% vs 50.27%, 50.97% and 53.13%, all P < 0.05). Semiquantitative RT-PCR analysis showed that the expression levels of COX-2, ERK1 and ERK2 mRNAs in the COX-2 siRNA intervention group were significantly decreased as compared to the control siRNA intervention group, empty liposome group and blank control group (0.58 vs 0.83, 0.89 and 0.93; 0.32 vs 0.71, 0.64 and 0.76; 0.48 vs 0.65, 0.67 and 0.72; all P < 0.05). Similar results were obtained for protein expression as revealed by Western blot analysis.

CONCLUSION: siRNA can downregulate the expression of COX-2 gene in hepatocellular carcinoma HepG2 cells and inhibit their proliferation. COX-2 promotes the development of primary hepatic carcinoma perhaps through regulation of ERK1/2 pathway.