C14ORF166 overexpression is associated with pelvic lymph node metastasis and poor prognosis in uterine cervical cancer

A Novel Ultrasound-Based Radiomics Model for the Preoperative Prediction of Lymph Node Metastasis in Cervical Cancer

OBJECTIVE

The purpose of this retrospective study was to establish a combined model based on ultrasound (US)-radiomics and clinical factors to predict preoperative lymph node metastasis (LNM) in cervical cancer (CC) patients non-invasively.

METHODS

A total of 131 CC patients who had cervical lesions found by transvaginal sonography (TVS) from the First Affiliated Hospital of Anhui Medical University (Hefei, China) were retrospectively analyzed. The clinical independent predictors were selected using univariate and multivariate logistic regression analysis. US-radiomics features were extracted from US images; after selecting the most significant features by univariate analysis, Spearman's correlation analysis, and the least absolute shrinkage and selection operator (LASSO) algorithm; four machine-learning classification algorithms were used to build the US-radiomics model. Fivefold cross-validation was then used to test the performance of the model and compare the ability of the clinical, US-radiomics and combined models to predict LNM in CC patients.

RESULTS

Red blood cell, platelet and squamous cell carcinoma-associated antigen were independent clinical predictors of LNM (+) in CC patients. eXtreme Gradient Boosting performed the best among the four machine-learning classification algorithms. Fivefold cross-validation confirmed that eXtreme Gradient Boosting indeed performs the best, with average area under the curve values in the training and validation sets of 0.897 and 0.898. In the three prediction models, both the US-radiomics model and the combined model showed good predictive efficacy, with average area under the curve values in the training and validation sets of 0.897, 0.898 and 0.912, 0.905, respectively.

CONCLUSION

US-radiomics features combined with clinical factors can preoperatively predict LNM in CC patients non-invasively.

Study on the preoperative value of serum SCC-Ag in predicting the stromal invasion of cervical squamous cell carcinoma

OBJECTIVE

To investigate the preoperative value of serum SCC-Ag in predicting the stromal invasion of cervical squamous cell carcinoma.

METHODS

This study retrospectively analyzed 78 patients with early cervical squamous cell carcinoma who underwent surgery as initial treatment at the Senior Department of Obstetrics and Gynecology, the Seventh Medical Center of PLA General Hospital from January 2018 to September 2022 was implemented. The clinicopathological characteristics were statistically compared. The ROC curve was drawn to determine the optimal critical level of  preoperative serum SCC-Ag value for predicting cervical stromal invasion.

RESULTS

The depth of myometrial invasion was not related to the age of diagnosis and HPV infection (p > 0.05), while it was related to tumor size, staging, tissue differentiation, LVSI, lymph node metastasis (LNM) and preoperative serum SCC-Ag value (p < 0.05).The area under the curve (AUC) of serum SCC-Ag value was 0.894 (p = 0.000, 95% CI 0.824-0.964), and preoperative serum SCC-Ag value 1.65 ng/ml was the best cutoff for predicting cervical stromal invasion in cervical squamous cell carcinoma. The sensitivity and specificity of diagnosis were 92.3% and 78.8%, respectively.

CONCLUSION

If the preoperative serum SCC-Ag leval more than 1.65 ng/ml in patients with cervical squamous cell carcinoma, the risk of cervical stromal invasion will increase, which can provide a reference for clinical treatment.

An in silico prediction of interaction models of influenza A virus PA and human C14orf166 protein from yeast-two-hybrid screening data

The human C14orf166 protein, also known as RNA transcription, translation, and transport factor, shows positive modulatory activity on the cellular RNA polymerase II enzyme. This protein is a component of the tRNA-splicing ligase complex and is involved in RNA metabolism. It also functions in the nucleo-cytoplasmic transport of RNA molecules. The C14orf166 protein has been reported to be associated with some types of cancer. It has been shown that the C14orf166 protein binds to the influenza A virus RNA polymerase PA subunit and has a stimulating effect on viral replication. In this study, candidate interactor proteins for influenza A virus PA protein were screened with a Y2H assay using HEK293 Matchmaker cDNA. The C14orf166 protein fragments in different sizes were found to interact with the PA. The three-dimensional structures of the viral PA and C14orf166 proteins interacting with the PA were generated using the I-TASSER algorithm. The interaction models between these proteins were predicted with the ClusPro protein docking algorithm and analyzed with PyMol software. The results revealed that the carboxy-terminal end of the C14orf166 protein is involved in this interaction, and it is highly possible that it binds to the carboxy-terminal of the PA protein. Although amino acid residues in the interaction area of the PA protein with the C14orf166 showed distribution from 450th to 700th position, the intense interaction region was revealed to be at amino acid positions 610-630.

Development and validation of a nomogram for predicting pelvic lymph node metastasis and prognosis in patients with cervical cancer

Objective

Cervical cancer (CC) is one of the main causes of death among gynecological malignancies. Patients with CC with lymph node metastasis (LNM) have poor prognoses. We investigated the risk factors and prognosis of LNM in patients with CC patients using data from the SEER database.

Methods

We collected the information of cervical cancer patients registered in SEER database from 2010 to 2015. The dataset was divided into a training set and a validation set at a 7:3 ratio. LASSO regression analysis was used to evaluate risk factors for LNM in patients with CC. Using the results, we established a nomogram prediction model. C-index, ROC curves, calibration curves, decision curve analysis, and clinical impact curves were used to evaluate the prediction performance of the model.

Results

We included 14,356 patients with CC in the analysis. Among these, 3997 patients were diagnosed with LNM. A training set (10,050 cases) and a validation set (4306 cases) were used for the following analysis. We established nomogram LNM prediction models for the patients with T_1-2-stage CC. The C-indices for the internal and external validations of the prediction models were 0.758 and 0.744, respectively. In addition, we established a prognostic nomogram for all CC patients with LNM, and the internal and external validation C-indices were 0.763 and 0.737.

Conclusion

We constructed a quantitative and visual predictive nomogram that predicted prognosis of patients with LNM in CC to provide clinicians with a reference for diagnosis and treatment.

Non-coding RNAs related to angiogenesis in gynecological cancer

Gynecological cancer affects the female reproductive system, including ovarian, uterine, endometrial, cervical, vulvar, and vaginal tumors. Non-coding RNAs (ncRNAs), and in particular microRNAs, function as regulatory molecules, which can control gene expression in a post-transcriptional manner. Normal physiological processes like cellular proliferation, differentiation, and apoptosis, and pathological processes such as oncogenesis and metastasis are regulated by microRNAs. Numerous reports have shown a direct role of microRNAs in the modulation of angiogenesis in gynecological cancer, via targeting pro-angiogenic factors and signaling pathways. Understanding the molecular mechanism involved in the regulation of angiogenesis by microRNAs may lead to new treatment options. Recently the regulatory role of some long non-coding RNAs in gynecological cancer has also been explored, but the information on this function is more limited. The aim of this article is to explore the pathways responsible for angiogenesis, and to what extent ncRNAs may be employed as biomarkers or therapeutic targets in gynecological cancer.

Assessment of p16 and Ki67 Immunohistochemistry Expression in Squamous Intraepithelial Lesion with Cytohistomorphological Correlation

BACKGROUND & OBJECTIVE

Cervical cancer is the most common cancer in women worldwide with high mortality, necessitating quicker diagnostic methods. We wish to enhance the existing cervical biopsies of Squamous Intraepithelial Lesions (SIL) using p16 and Ki67 as surrogate markers to assess correlation between its positivity and histological grade of the lesion.

METHODS

Analysis of p16 and Ki67 expression was done on 31 histopathologically diagnosed cases of SILs. Positive expression of p16 was assessed based on a scoring system and compared with histology and cytology. Ki67 expression was studied and the correlation was observed with degree of dysplasia. Twenty cases of chronic cervicitis was assigned to the control group for comparison.

RESULTS

Cases of HSIL showed greater expression of p16 as compared to LSIL. Sensitivity of p16 for HSIL was higher than that for LSIL. The specificity for HSIL and LSIL was 100%. Ki67 expression correlated well with the degree and level of dysplasia with a significant P-value of 0.002.

CONCLUSION

p16 and Ki67 positivity of SILs should point towards further evaluation. The expressions of p16 and Ki67 are useful markers for confirmation of SILs and in predicting HPV infection which can be further confirmed by HPV DNA testing.

Development and Validation of a Deep Learning Radiomics Model Predicting Lymph Node Status in Operable Cervical Cancer

Aim: To develop and validate a deep learning radiomics model, which could predict the lymph node metastases preoperatively in cervical cancer patients. Patients and methods: We included a cohort of 226 pathological proven operable cervical cancer patients in two academic medical institutions from December 2014 to November 2017. Then this dataset was split into training set (n = 176) and independent testing set (n = 50) randomly. Five radiomic features were selected and a radiomic signature was established. We then combined these five radiomic features with the preoperative tumor histology and grade of these patients together. Baseline logistic regression model (LRM) and support vector machine model (SVM) were established for the comparison. We then explored the performance of a deep neural network (DNN), which is a popular deep learning model nowadays. Finally, performance of this DNN was validated in another independent test set including 50 cases of operable cervical cancer patients. Results: One thousand forty-five radiomic features were extracted for each patient. Twenty-eight features were found to be significantly correlated with the lymph node status in these patients (P < 0.05). Five radiomic features were further selected for further study due to their higher predictive powers. Baseline LRM incorporating these five radiomic and two clinicopathological features was established, which had an area under receiver operating characteristic curve (ROC) of 0.7372 and an accuracy of 89.20%. The established DNN model had four neural layers, in which layer there were 10 neurons. Adagrad optimizer and 1,500 iterations were used in training. The trained DNN had an area under curve (AUC) of 0.99 and an accuracy of 97.16% in the internal validation. To exclude the overfitting, independent external validation was also performed. AUC and accuracy in test set could still retain 0.90 and 92.00% respectively. Conclusion: This study used deep learning method to provide a comprehensive predictive model using preoperative CT images, tumor histology, and grade in cervical cancer patients. This model showed an acceptable accuracy in the prediction of lymph node status in cervical cancer. Our model may help identifying those patients who could benefit a lot from radiation therapy rather than primary hysterectomy surgery if this model could resist strict testing of future randomized controlled trials (RCTs).

Down-regulation of long non-coding RNA ANRIL inhibits the proliferation, migration and invasion of cervical cancer cells

OBJECTIVES

Cervical cancer (CC) is a common malignant tumor in the female reproductive system that is characterized by a high metastatic potential. LncRNA ANRIL has been found to be a cancer oncogene in multiple tumors. In our study, we altered the expression of ANRIL in CC cells and evaluated its ability on influencing proliferation, migration and invasion of CC cells and associated mechanism.

METHODS

Differentially expressed lncRNAs in CC were identified by microarray and TCGA analyses. CC tissues and adjacent tissues were collected in order to extract CC cells. The expression of ANRIL was determined by RT-qPCR. The CC cells were transfected with siRNA or si-NC against ANRIL to find out whether ANRIL can influence the expression of Cyclin D1, CDK4, CDK6, E-cadherin, vimentin and N-cadherin, as well as affect cell proliferation, cell apoptosis, cell migration and cell invasion of CC cells.

RESULTS

Based on TCGA and microarray analyses, ANRIL was predicted to be highly expressed in CC and CC with migration. Then further verification was obtained by means of RT-qPCR that ANRIL was highly expressed in CC tissues. In addition, high expression of ANRIL was related to increased E-cadherin expression, high migration of CC as well as decreased cell apoptosis rate. On the other hand, inhibition of ANRIL expression led to decreased expressions of Cyclin D1, CDK4, CDK6, N-cadherin and Vimentin, along with attenuated cell proliferation, migration and invasion of CC cells.

CONCLUSION

The key findings of our study demonstrated that the inhibition of lncRNA ANRIL reduces the proliferation, migration and invasion capabilities of CC cells. Down-regulation of ANRIL may serve as a potential therapeutic target in the treatment of CC.

LncRNA LINC01305 silencing inhibits cell epithelial-mesenchymal transition in cervical cancer by inhibiting TNXB-mediated PI3K/Akt signalling pathway

Cervical cancer (CC) remains one of the leading malignancies afflicting females worldwide, with its aetiology associated with long‐term papillomavirus infection. Recent studies have shifted their focus and research attention to the relationship between long non‐coding RNAs (lncRNAs) and CC therapeutic. Thus, the aim of the current study was to investigate the underlying mechanism of lncRNA LINC01305 on the cell invasion, migration and epithelial‐mesenchymal transition (EMT) of CC cells via modulation of the PI3K/Akt signalling pathway by targeting tenascin‐X B (TNXB). The expressions of LINC01305, TNXB, MMP2, MMP9, E‐cadherin, vimentin, PI3K, Akt, p‐PI3K, p‐Akt and TNXB were detected in this study. After which, the cell invasion and migration abilities of the CC cells were determined respectively. Bioinformatics and the application of a dual luciferase reporter gene assay provided verification indicating that TNXB is the target gene of lncRNA LINC01305. Reverse transcription quantitative polymerase chain reaction (RT‐qPCR) and western blot analysis methods revealed that the expressions of MMP2, MMP9, vimentin, PI3K, Akt, p‐PI3K and p‐Akt were decreased following the down‐regulation of LncRNA LINC01305 or overexpression of TNXB. LncRNA LINC01305 silencing or TNXB overexpression was noted to decrease the migration and invasion of SiHa cells. Taken together, the key findings of the current study present evidence suggesting that lncRNA LINC01305 silencing suppresses EMT, invasion and migration via repressing the PI3K/Akt signalling pathway by means of targeting TNXB in CC cells, which ultimately provides novel insight and identification of potential therapeutic targets for CC.

Upregulation of microRNA-129-5p inhibits cell invasion, migration and tumor angiogenesis by inhibiting ZIC2 via downregulation of the Hedgehog signaling pathway in cervical cancer

Recently, some studies have placed additional research focus on microRNAs (miRNAs) in a bid to discover novel therapeutic approaches for cervical cancer (CC), which is one of the most common female reproductive tract malignancies with high rates of morbidity and mortality. Hence, the aim of the present study was to evaluate the ability of miR-129-5p to influence cell angiogenesis, invasion and migration by targeting ZIC2 through the Hedgehog signaling pathway in CC. Both CC and adjacent normal tissues were extracted from 87 eligible participating patients with CC. Measurements of the levels of miR-129-5p, mRNA and protein levels of ZIC2, sonic Hedgehog (Shh), Gli1, and Gli2 and levels of CXCL1, VEGF and Ang2 were determined accordingly. An angiogenesis assay was performed to evaluate cell angiogenesis in vitro, while a scratch test and transwell assay were adopted for cell invasion and migration determination. Lastly, tumor formation within nude mice was performed in order to analyze angiogenesis and tumor growth among the nude mice in vivo. The findings revealed that upregulation of miR-129-5p resulted in the decrease in the mRNA and protein levels of ZIC2, Shh, Gli1, Gli2, as well as reduced levels of CXCL1, VEGF and Ang2. Moreover, up-regulation of miR-129-5p was determined to inhibit CC cell angiogenesis ability in vitro, in addition to the processes of cell migration, and invasion. Finally, up-regulation of miR-129-5p was observed to inhibit the tumor growth and angiogenesis ability of nude mice in vivo. The results of the present study provided evidence suggesting that overexpressed miR-129-5p prevents angiogenesis and inhibits cell migration and invasion by means of negatively targeting ZIC2 through suppression of the Hedgehog signaling pathway in CC. Thus, highlighting the promise of miR-129-5p as a novel target for treating CC is promising.

Overexpressed C14orf166 associates with disease progression and poor prognosis in non-small-cell lung cancer

Chromosome 14 ORF 166 (C14orf166), a protein involved in the regulation of RNA transcription and translation, has been reported to possess the potency to promote tumorigenesis; however, the role of C14orf166 in non-small-cell lung cancer (NSCLC) remains unknown. The purpose of the present study was to assess C14orf166 expression and its clinical significance in NSCLC. Immunohistochemical staining, quantitative real-time PCR (qRT-PCR), and Western blotting were used to detect the C14orf166 protein and mRNA expression levels in NSCLC tissues compared with adjacent normal tissues, as well as in NSCLC cells lines compared with normal human bronchial epithelial cells (HBE). Then, the correlations between the C14orf166 expression levels and the clinicopathological features of NSCLC were analyzed. Additionally, the Cox proportional hazard model was used to evaluate the prognostic significance of C14orf166. We found that C14orf166 expression increased in carcinoma tissues compared with their adjacent normal tissues at the protein (P<0.001) and mRNA levels (P<0.001). High expression of C14orf166 was significantly associated with the T stage (P=0.006), lymph node metastasis (P=0.001), advanced TNM stage (P<0.001), and chemotherapy (P<0.001). Moreover, according to the survival analysis, patients with overexpressed C14orf166 were inclined to experience a shorter overall survival and disease-free survival time (P<0.001). Multivariate COX analysis implied that C14orf166 was an independent prognostic biomarker. Taken together, our findings indicate that the overexpression of C14orf166 may contribute to the disease progression of NSCLC, represent a novel prognostic predictor and help high-risk patients make better decisions for subsequent therapy.

Correlations of MicroRNA-21 Gene Polymorphisms With Chemosensitivity and Prognosis of Cervical Cancer

BACKGROUND

We investigated correlations of miR-21 gene polymorphisms including rs1292037 (A > G) and rs13137 (A > T) with the chemosensitivity to cisplatin plus paclitaxel, and prognosis before cervical cancer (CC) surgery, which may provide a novel target for prevention and treatment of CC.

MATERIALS AND METHODS

A total of 165 patients with CC were divided into 2 groups, a sensitive group and resistance group. Gene polymorphisms of rs1292037 (A > G) and rs13137 (A > T) were detected respectively. Logistic and Cox multivariate regression analyses were used to explore factors that influence resistance to cisplatin plus paclitaxel.

RESULTS

rs1292037 (A > G) locus AG, GG, AG + GG and G allele in miR-21 gene may increase chemoresistance to cisplatin plus paclitaxel in CC. The risk factors of prognosis included rs1292037 (A > G) locus, tumor stage, maximum lesion diameter and lymph node metastasis (hazard ratio [HR] = 1.819, 95% CI = 1.127-2.935; HR = 1.504, 95% CI = 1.070-2.114; HR = 1.671, 95% CI = 1.038-2.689; HR = 3.043, 95% CI = 1.783-5.193). The influencing factors of resistance to cisplatin plus paclitaxel included maximum lesion diameter, tumor stage, lymph node metastasis and rs1292037 (odds ratio [OR] = 14.047, 95% CI = 5.694-34.653; OR = 5.873, 95% CI = 3.104-11.110; OR = 3.574, 95% CI = 1.554-8.216; OR = 2.449, 95% CI = 1.052-5.705).

CONCLUSIONS

rs1292037 (A > G) locus are associated with the chemoresistance to cisplatin plus paclitaxel and prognosis of patients with CC. In addition to that, the G allele at rs1292037 (A > G) locus increases the risk of preoperative chemoresistance to cisplatin plus paclitaxel and is a poor prognostic factor for patients with CC.

Identification of clinical tumor stages related mRNAs and miRNAs in cervical squamous cell carcinoma

OBJECTIVES

The aim of this study is to identify the clinical tumor stage related mRNAs and miRNAs, shedding light on the potential molecular mechanisms of cervical squamous cell carcinoma (CSCC).

METHODS

Firstly, the mRNA and miRNA next-generation sequencing data were downloaded. Secondly, clinical tumor stage correlation analysis of mRNAs and miRNA was performed, followed by the functional enrichment analysis of all clinical tumor stage related mRNAs. Thirdly, differentially expression analysis of mRNAs and miRNA between different clinical tumor stages was performed, followed by target gene prediction of these differentially expressed miRNAs.

RESULTS

3 mRNAs (PER1, PRKAB1 and PMM2) and 5 miRNAs (hsa-mir-486, hsa-mir-451, hsa-mir-424, hsa-mir-144 and hsa-mir-450a-2) were overlapped from stage 1, stage 2, stage 3 and stage 4.

CONCLUSIONS

Alterations of differentially expressed mRNAs and miRNAs may offer important insights into the molecular mechanisms in the pathology of CSCC.

Expression and clinical significance of C14orf166 in esophageal squamous cell carcinoma

C14orf166, a 28 kD protein regulating RNA transcription and translation, may serve a critical role in oncogenesis. The aim of the current study was to explore the association between C14orf166 expression and esophageal squamous cell carcinoma (ESCC) and to draw attention to the association between C14orf166 and the initiation, progression and prognosis of ESCC. C14orf166 expression in ESCC and paired normal tissues was detected by immunohistochemical staining, western blotting and reverse transcription-quantitative polymerase chain reaction, and the association between C14orf166 expression and clinicopathological characters of ESCC was analyzed. Survival analysis was used to assess the prognostic significance of C14orf166 and it was observed that C14orf166 expression was higher in the ESCC tissues when compared with adjacent non-cancerous tissues at protein (P<0.001) and mRNA levels (P<0.001). There was a significant difference in T stage, lymph node metastasis and TNM stage in patients categorized according to different C14orf166 expression levels. The overexpression of C14orf166 was associated with a shorter overall survival and disease-free survival, and multivariate analysis indicated that C14orf166 was an independent prognostic indicator. The present study indicates that the expression of C14orf166 is elevated in ESCC, and is potentially a valuable prognostic predictor for ESCC.

High Expression of KIF20A Is Associated with Poor Overall Survival and Tumor Progression in Early-Stage Cervical Squamous Cell Carcinoma

Background

The kinesin family member 20a (KIF20A) protein has been implicated in the development and progression of many human cancers; however, its precise function and role in cervical cancer remain largely unclear. This study aimed to investigate the expression profile and prognostic value of KIF20A in patients with early-stage cervical squamous cell carcinoma.

Methods

We examined the mRNA and protein levels of KIF20A in eight cervical cancer cell lines and eight paired cervical cancer samples, compared with normal cervical epithelial cells and adjacent normal cervical tissues, respectively. Immunohistochemistry was performed to detect the expression of KIF20A in paraffin-embedded specimens from 169 early-stage cervical squamous cell carcinoma patients. Statistical analyses were applied to analyze the association between KIF20A expression and clinical variables, as well with patient survival.

Results

The mRNA and protein expression levels of KIF20A were significantly elevated in cervical cancer cell lines and lesions compared with normal cells and corresponding normal tissues (P < 0.05). Immunohistochemistry analysis in 169 cervical cancer cases revealed that increased KIF20A expression was strongly associated with human papillomavirus (HPV) infection (P = 0.008), clinical stage (P = 0.001), tumor recurrence (P = 0.016), vital status (P < 0.001), the property of the surgical margin (P = 0.032), the lymphovascular space involvement (P = 0.014), and pelvic lymph node metastasis (P = 0.001). The overall survival and disease-free survival of patients with high levels of KIF20A expression were significantly poorer than those with low KIF20A expression. KIF20A was an independent survival prognostic factor, as evidenced by univariate and multivariate analysis.

Conclusions

Our results illustrate that elevated KIF20A expression correlates with HPV infection, clinical stage, tumor recurrence, lymphovascular space involvement, pelvic lymph node metastasis, and poor outcome in early-stage cervical squamous cell carcinoma patients. KIF20A aberrant expression is a novel independent unfavorable prognostic factor and may present a potential therapeutic target for cervical cancer.

C14orf166 is a high-risk biomarker for bladder cancer and promotes bladder cancer cell proliferation

BACKGROUND

C14orf166 (chromosome 14 open reading frame 166) plays a crucial role in some tumors, but its role in bladder cancer hasn't been explored.

METHOD

We determined C14orf166 expression in uroepithelial cell, bladder cancer cells, normal bladder tissues and bladder cancer tissues using quantitative RT-PCR and western blot, we then analyzed the correlation between C14orf166 expression and clinicopathologic characteristics in a cohort of 149 patients with bladder cancer. Finally we downregulated C14orf166 and determined its role in the proliferation of bladder cancer cell lines using MTT assay, colony formation assay and cell cycle assay.

RESULTS

We demonstrated C14orf166 was upregulated in bladder cancer cells and tissues, C14orf166 expression was significantly correlated with larger tumor size (P = 0.001), lymph node involvement (P < 0.001), histological differentiation (P < 0.001), survival time and vital states, and high C14orf166 expression correlated with poor survival, these results suggested C14orf166 served as a high-risk marker for bladder cancer. Knockdown of C14orf166 decreased the proliferation rate and colony formation ability of bladder cancer cells, and arrested cell cycle in G1/S transition. Further analysis showed that C14orf166 knockdown caused abnormal expression of key proteins for G1/S transition, such as Cyclin D1, P21, P27 and Rb phosphorylation.

CONCLUSIONS

This study demonstrates that C14orf166 promotes bladder cancer cell proliferation and can be a novel prognostic biomarker for patients with bladder cancer.

B3GNT3 Expression Is a Novel Marker Correlated with Pelvic Lymph Node Metastasis and Poor Clinical Outcome in Early-Stage Cervical Cancer

BACKGROUND

The β1,3-N-acetylglucosaminyltransferase-3 gene (B3GNT3) encodes a member of the B3GNT family that functions as the backbone structure of dimeric sialyl-Lewis A and is involved in L-selectin ligand biosynthesis, lymphocyte homing and lymphocyte trafficking. B3GNT3 has been implicated as an important element in the development of certain cancers. However, the characteristics of B3GNT3 in the development and progression of cancer remain largely unknown. Thus, our study aimed to investigate the expression pattern and the prognostic value of B3GNT3 in patients with early-stage cervical cancer.

METHODS

The mRNA and protein levels of B3GNT3 expression were examined in eight cervical cancer cell lines and ten paired cervical cancer tumors, using real-time PCR and western blotting, respectively. Immunohistochemistry (IHC) was used to analyze B3GNT3 protein expression in paraffin-embedded tissues from 196 early-stage cervical cancer patients. Statistical analyses were applied to evaluate the association between B3GNT3 expression scores and clinical parameters, as well as patient survival.

RESULTS

B3GNT3 expression was significantly upregulated in cervical cancer cell lines and lesions compared with normal cells and adjacent noncancerous cervical tissues. In the 196 cases of tested early-stage cervical cancer samples, the B3GNT3 protein level was positively correlated with high risk TYPES of human papillomavirus (HPV) infection (P = 0.026), FIGO stage (P < 0.001), tumor size (P = 0.025), tumor recurrence (P = 0.004), vital status (P < 0.001), concurrent chemotherapy and radiotherapy (P = 0.016), lymphovascular space involvement (P = 0.003) and most importantly, lymph node metastasis (P = 0.003). Patients with high B3GNT3 expression had a shorter overall survival (OS) and disease-free survival (DFS) compared with those with low expression of this protein. Multivariate analysis suggested that B3GNT3 expression is an independent prognostic indicator for cervical cancer patients.

CONCLUSIONS

Our study demonstrated that elevated B3GNT3 expression is associated with pelvic lymph node metastasis and poor outcome in early-stage cervical cancer patients. B3GNT3 may be a novel prognostic marker and therapeutic target for the treatment of cervical cancer.