Risk of parametrial invasion in women with early stage cervical cancer: a meta-analysis

Development and Validation of Radiomics-Based Models for Predicting the Parametrial Invasion in Stage IB1 to IIA2 Cervical Cancer

Objective

To develop an early warning system that enables accurate parametrial invasion (PMI) risk prediction in cervical cancer patients with early-stage.

Methods

We retrospectively collected 218 early-stage cervical cancer patients who were treated in Jingzhou Central Hospital from January 31, 2015, to January 31, 2023, and diagnosed with early stage cervical cancer by pathology. The prediction model training is achieved by randomly dividing 70% of the training queue population, with the remaining 30% used as the testing queue. Then, a prediction model based on machine learning algorithms (including random forest, generalized linear regression, decision tree, support vector machine, and artificial neural network) is constructed to predict the risk of PMI occurrence. Ultimately, the analysis of receiver operating characteristic curve (ROC) and decision curve analysis (DCA) is used to evaluate the predictive ability of various prediction models.

Results

We finally included radiomics-based candidate variables that can be used for PMI model. Multivariate logistic regression analysis showed that energy, correlation, sum entropy (SUE), entropy, mean sum (MES), variance of differences (DIV), and inverse difference (IND) were independent risk factors for PMI occurrence. The predictive performance AUC of five types of machine learning ranges from 0.747 to 0.895 in the training set and can also reach a high accuracy of 0.905 in the testing set, indicating that the predictive model has ideal robustness.

Conclusion

Our ML-based model incorporating GLCM parameters can predict PMI in cervical cancer patients with stage IB1 to IIA2, particularly the RFM, which could contribute to distinguishing PMI before surgery, especially in assisting decision-making on surgical scope.

Prediction of recurrence risk factors in patients with early-stage cervical cancers by nomogram based on MRI handcrafted radiomics features and deep learning features: a dual-center study

PURPOSE

To establish and validate a deep learning radiomics nomogram (DLRN) based on intratumoral and peritumoral regions of MR images and clinical characteristics to predict recurrence risk factors in early-stage cervical cancer and to clarify whether DLRN could be applied for risk stratification.

METHODS

Two hundred and twenty five pathologically confirmed early-stage cervical cancers were enrolled and made up the training cohort and internal validation cohort, and 40 patients from another center were enrolled into the external validation cohort. On the basis of region of interest (ROI) of intratumoral and different peritumoral regions, two sets of features representing deep learning and handcrafted radiomics features were created using combined images of T2-weighted MRI (T2WI) and diffusion-weighted imaging (DWI). The signature subset with the best discriminant features was chosen, and deep learning and handcrafted signatures were created using logistic regression. Integrated with independent clinical factors, a DLRN was built. The discrimination and calibration of DLNR were applied to assess its therapeutic utility.

RESULTS

The DLRN demonstrated satisfactory performance for predicting recurrence risk factors, with AUCs of 0.944 (95% confidence interval 0.896-0.992) and 0.885 (95% confidence interval 0.834-0.937) in the internal and external validation cohorts. Furthermore, decision curve analysis revealed that the DLRN outperformed the clinical model, deep learning signature, and radiomics signature in terms of net benefit.

CONCLUSION

A DLRN based on intratumoral and peritumoral regions had the potential to predict and stratify recurrence risk factors for early-stage cervical cancers and enhance the value of individualized precision treatment.

Oncological and reproductive outcomes of conization combined with pelvic node evaluation in patients with early-stage cervical cancer: a systematic review and meta-analysis

Objective

This study aims to preliminarily assess the oncological and reproductive outcomes of fertility preservation treatment using conization combined with pelvic node evaluation in young patients with early-stage cervical cancer (ECC) through meta-analysis.

Methods

In this meta-analysis, we analyzed studies published in PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), International Clinical Trials Registry Platform (ICTRP), and Clinical Trials. gov that appeared in our search from inception to 0 7/02/2023.

Results

There were 17 relevant studies with a total of 620 patients included, of which 444 patients received conization combined with pelvic node evaluation. The combined pregnancy rate was 45.4% (95% CI: 0.34-0.57), the combined live birth rate was 33.9% (95% CI: 0.26-0.42), the combined miscarriage rate was 4.8% (95% CI: 0.02-0.092), the combined preterm delivery rate was 5.1% (95% CI: 0.02-0.092), and the combined recurrence rate was 1.9% (95% CI: 0.006-0.035), which did not significantly differ from that of patients who received radical surgery (OR: 0.689, 95% CI: 0.506-0.938).

Conclusion

Cervical conization combined with pelvic lymph node evaluation for fertility preservation in young ECC patients can achieve oncological outcomes similar to radical surgery while improving pregnancy success rates and preserving postoperative fertility. In summary, fertility preservation treatment using cervical conization combined with pelvic lymph node evaluation may be considered as a viable option for young ECC patients with strong fertility preservation desire, resulting in better pregnancy and live birth outcomes.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/#myprospero, identifier PROSPERO (CRD42023423432).

What are the determinants of parametrial invasion in patients with early stage cervical cancer: A cross sectional study

Introduction

There was an increase in number of patients presented with early-stage cervical cancer (CC). Tumors with favorable pathological features might be candidates for less radical surgery.

Methods

We retrospectively reviewed 700 patients with histologically confirmed CC between January 2011 and March 2020. Chi-square, Fisher's exact tests and multivariate logistic regression analysis were used to assess relations between parametrial involvement (PI) and clinic-pathological variables.

Results

Total number of 132 patients with stage IA to IIA were eligible to participate. Squamous cell carcinoma was reported in 100 (75.8%) patients, adenocarcinoma and other tumor pathologies were found in 24(18.2%) and 8(6.1%), respectively. Considering the 2018 FIGO stage, 11 (8.4%) patients had IA, 111 (83%%) IB and 10 (7.6%) IIA. Nine patients (6.8%) had PI on permanent pathologic report. Univariate analysis demonstrated that following variables were statistically different between patients with and without PI: age ≥50, tumor size ≥ 3 cm, lower segment involvement, poorly differentiated pathology, deep stromal invasion, pelvic lymph node, lympho-vascular involvement and positive surgical margin (all p values < 0.05). Among these variables only tumor size ≥3 cm (OR: 2.1, 95% CI: 1.11–4.16, p value: 0.02), deep stromal invasion (OR: 2.2, 95% CI: 1.9–7.43, p value: 0.02) and positive surgical margin (OR: 5.1, 95% CI: 3.97–11.15, p value: 0.008) were independent risk factor of PI in multivariate analysis.

Conclusions

Early stage CC might be surgically approached in a more conservative manner if patients have tumor size <3 cm and do not have deep stromal invasion in conization.

•

The parametrium was resected, in order to remove occult disease at the time of extirpation of the primary cervical lesion.

•

This study revealed, tumor size, deep stromal invasion and surgical margin were independent risk factors for parametrial invasion.

•

Selected patients in early stages of cervical cancer are possible candidates to undergo a more conservative approach.

The Effect of Surgeon Volume on the Outcome of Laser Vaporization: A Single-Center Retrospective Study

Although laser vaporization is a popular minimally invasive treatment for cervical intraepithelial neoplasia (CIN), factors influencing CIN recurrence are understudied. Moreover, the effect of surgeon volume on patients’ prognosis after laser vaporization for CIN is unknown. This single-center retrospective study evaluated the predictive value of surgeon volume and patient characteristics for laser vaporization outcomes in women with pathologically confirmed CIN2. Histologically confirmed CIN2 or higher grade after laser vaporization was defined as persistent or recurrent. Various patient characteristics were compared between women with and those without recurrence to examine the predictive factors for laser vaporization. There were 270 patients with a median age of 36 (18–60) years. The median follow-up period was 25 (6–75.5) months and the median period between treatment and persistence or recurrence was 17 (1.5–69) months. The median annual number of procedures for all seven surgeons was 7.8. There were 38 patients (14.1%) with persistent or recurrent lesions—24 had CIN2, 13 had CIN3, and one had adenocarcinoma in situ. Patient age, body mass index, surgeon volume, and history of prior CIN treatment or invasive cervical cancer were not significantly correlated with lesion persistence or recurrence. In conclusion, laser vaporization has comparable success rates and is a feasible treatment for both low- and high-volume surgeons.

Nomogram Predicting Parametrial Involvement Based on the Radical Hysterectomy Specimens in the Early-Stage Cervical Cancer

Objective: Radical hysterectomy (RH) is the surgical standard for the treatment of the early-stage cervical cancer (CC). However, this procedure is associated with a high rate of adverse impact on the quality of the life of the patient. Since the rate of parametrial involvement (PI) is low for the patients with the early-stage CC, some authors believe that the patients with the early-stage CC may benefit from the less radical surgery. This study aims to estimate the incidence of the PI in the patients with the early-stage CC and establish a simple nomogram to identify a cohort of the patients with low risk of the PI who may benefit from the less radical surgery.

Methods: All the patients who underwent the RH and pelvic lymphadenectomy were included from 2013 to 2018. The significant independent predictors were identified through the Cox regression analysis and then incorporated into a nomogram to predicate the PI. The calibration plots and receiver operating characteristic (ROC) curves were used to assess the predictive accuracy of the nomogram.

Results: A total of 4,533 patients met the inclusion criteria and 441 women (9.7%) had the PI. The positive PI rate in the ≤2 cm group (1.2%) was significantly lower compared to >2– ≤4 cm (6.2%) or >4 cm (22.4%) groups. The multivariate analyses revealed that tumor size (p = 0.002), lymphovascular space invasion (LVSI) (p = 0.001), vaginal involvement (VI) (p < 0.001), status of the pelvic lymph nodes (PLNs) (p = 0.001), and depth of stromal invasion (DSI) (p < 0.001) were the independent prognostic factors of the PI. Finally, the five variables were combined to construct the nomogram model. The concordance indexes (C-indexes) of the PI were 0.756 (95% CI 0.726–0.786) for the internal validation and 0.729 (95% CI 0.678–0.780) for the external validation. The calibration plots further showed good consistency between the nomogram prediction and the actual observation.

Conclusion: This study confirmed that the patients with tumor size 2 cm or smaller were at very low risk for the PI. If other variables such as negative LVSI, DSI <50%, no VI, and negative PLN were limited, the risk would reduce significantly. Meanwhile, a simple nomogram based on the significant clinicopathological characteristics could be used as a tool for the clinicians to predict the PI among the patients with the early-stage CC, who might benefit from a less radical surgery.

IL-17 and CCR9+α4β7- Th17 Cells Promote Salivary Gland Inflammation, Dysfunction, and Cell Death in Sjögren's Syndrome

Previous studies have evaluated the roles of T and B cells in the pathogenesis of Sjögren's syndrome (SS); however, their relationships with age-dependent and metabolic abnormalities remain unclear. We examined the impacts of changes associated with aging or metabolic abnormalities on populations of T and B cells and SS disease severity. We detected increased populations of IL-17-producing T and B cells, which regulate inflammation, in the salivary glands of NOD/ShiLtJ mice. Inflammation-induced human submandibular gland cell death, determined based on p-MLKL and RIPK3 expression levels, was significantly increased by IL-17 treatment. Among IL-17-expressing cells in the salivary gland, peripheral blood, and spleen, the α4β7 (gut-homing integrin)-negative population was significantly increased in aged NOD/ShiLtJ mice. The α4β7-positive population markedly increased in the intestines of aged NOD/ShiLtJ mice following retinoic acid (RA) treatment. A significant increase in α4β7-negative IL-17-expressing cells in salivary glands may be involved in the onset and progression of SS. These results suggest the potential therapeutic utility of RA in SS treatment.

iPMI: Machine Learning-Aided Identification of Parametrial Invasion in Women with Early-Stage Cervical Cancer

Radical hysterectomy is a recommended treatment for early-stage cervical cancer. However, the procedure is associated with significant morbidities resulting from the removal of the parametrium. Parametrial cancer invasion (PMI) is found in a minority of patients but the efficient system used to predict it is lacking. In this study, we develop a novel machine learning (ML)-based predictive model based on a random forest model (called iPMI) for the practical identification of PMI in women. Data of 1112 stage IA-IIA cervical cancer patients who underwent primary surgery were collected and considered as the training dataset, while data from an independent cohort of 116 consecutive patients were used as the independent test dataset. Based on these datasets, iPMI-Econ was then developed by using basic clinicopathological data available prior to surgery, while iPMI-Power was also introduced by adding pelvic node metastasis and uterine corpus invasion to the iPMI-Econ. Both 10-fold cross-validations and independent test results showed that iPMI-Power outperformed other well-known ML classifiers (e.g., logistic regression, decision tree, k-nearest neighbor, multi-layer perceptron, naive Bayes, support vector machine, and extreme gradient boosting). Upon comparison, it was found that iPMI-Power was effective and had a superior performance to other well-known ML classifiers in predicting PMI. It is anticipated that the proposed iPMI may serve as a cost-effective and rapid approach to guide important clinical decision-making.

Retrospective analysis of the incidence and predictive factors of parametrial involvement in FIGO IB1 cervical cancer

BACKGROUND AND OBJECTIVES

Radical surgery is the standard primary treatment for patients with stage IB1 (FIGO 2009 staging) cervical cancer due to latent parametrial involvement. Recent studies suggested that less radical surgery was applicable for patients with no or low risk of parametrial involvement. In this study, we aimed to determine the incidence and possible predictive factors of parametrial involvement in patients with stage IB1 cervical cancer so as to evaluate whether less radical surgery was suitable for selected patients.

METHODS

Clinical data of patients who underwent type C radical hysterectomy with pelvic lymphadenectomy and diagnosed as stage IB1 cervical cancer at Union Hospital, Wuhan, China from October 2014 to December 2017 were collected and analysed retrospectively. The incidence of parametrial involvement was calculated and the risk factors for parametrial involvement were evaluated by univariate and multivariate logistic regression.

RESULTS

Among 282 eligible patients, 33 (11.7%) had parametrial involvement. Postmenopause, lymphovascular space invasion (LVSI), lymph node metastasis (LNM), deep stromal invasion (outer 1/3) and tumor size larger than 2 cm were statistically associated with parametrial involvement. Multivariate analysis showed that LNM (OR = 11.431; 95%CI: 3.455 - 37.821), deep stromal invasion (OR = 6.080; 95%CI: 1.814 - 20.382) and LVSI (OR = 7.147; 95%CI: 1.863-27.411) remained as independent risk factors for parametrial involvement in patients with stage IB1 cervical cancer.

CONCLUSIONS

The incidence of parametrial involvement in stage IB1 cervical cancer is non-negligible. Only LNM, LVSI and deep stromal invasion were independent predictors, which were not easy to evaluate accurately before surgery. Less radical surgery requires modified pre-treatment evaluation methods and prospective data support.

Radical trachelectomy

Radical trachelectomy is the 'cornerstone' of fertility-sparing surgery in patients with early-stage cervical cancer wishing to preserve fertility. Growing evidence has demonstrated the oncologic safety and subsequent favorable pregnancy outcomes in well-selected cases. In the absence of prospective trials, the decision on the appropriate surgical approach (vaginal, open, or minimally invasive surgery) should be based on local resources and surgeons' preferences. Radical trachelectomy has the potential to preserve fertility in a large proportion of women with early-stage cervical cancer. However, prematurity and premature rupture of membranes are common obstetric complications after radical trachelectomy for cervical cancer. A multidisciplinary approach is crucial to optimize the balance between oncologic and obstetric outcomes. The purpose of this review is to provide an updated overview of the technical, oncologic, and obstetric aspects of radical trachelectomy.

Elevated microRNA-130b-5p or silenced ELK1 inhibits self-renewal ability, proliferation, migration, and invasion abilities, and promotes apoptosis of cervical cancer stem cells

Cervical cancer (CC) is the most familiar gynecological malignancy. With the poor prognosis of CC patients, this study explored the effect of microRNA (miR)-130b-5p targeting ELK1 expression on self-renewal ability and stemness of CC stem cells. The tissues of patients with CC or cervical benign lesions were collected. MiR-130b-5p and ELK1 expression was detected by reverse transcription quantitative polymerase chain reaction and western blot analysis. Human CC cell line Hela was cultured and the induced CC stem cells were introduced with miR-130b-5p mimic or silenced ELK1 to figure their roles in self-renewal ability, stemness, colony formation, proliferation, migration, invasion abilities, and apoptosis of CC stem cells. Tumor growth was detected in nude mice in vivo. The targeting relationship between miR-130b-5p and ELK1 was analyzed using bioinformatic prediction and dual luciferase reporter gene assay. Decreased miR-130b-5p and elevated ELK1 existed in CC tissues of patients. Up-regulated miR-130b-5p decreased ELK1 expression in CC stem cells. Elevated miR-130b-5p or silenced ELK1 inhibited self-renewal ability and stemness, colony formation, proliferation, migration and invasion abilities, promoted apoptosis of CC stem cells, as well as decreased the weight and volume of tumor in nude mice. ELK1 was found to be targeted by miR-130b-5p. Overexpression ELK1 effectively reversed the cellular phenotypic changes and tumor formation in vivo caused by up-regulation of miR-130b-5p. We conclude that up-regulated miR-130b-5p or silenced ELK1 inhibits CC stem cell growth.

Down-regulation of lncRNA PCGEM1 inhibits cervical carcinoma by modulating the miR-642a-5p/LGMN axis

LncRNA PCGEM1 (PCGEM1) has been reported to exert essential effects on the development and progress of various tumors, while the detailed effects and possible mechanisms of PCGEM1 in cervical carcinoma remain unknown. In the present study, PCGEM1 was over-expressed in cervical carcinoma cells as evidenced by real-time quantitative polymerase chain reaction (RT-qPCR) assay. Knockdown of PCGEM1 significantly repressed proliferation, migration, and invasion, while induced G1 arrest in cervical carcinoma cells. In addition, PCGEM1 was predicted to target miR-642a-5p by bioinformatics software, which was further confirmed by luciferase reporter assay. Besides, RT-qPCR assay indicated that miR-642a-5p expression was decreased in cervical carcinoma cells and knockdown of PCGEM1 could accelerate miR-642a-5p expression. Moreover, inhibition of miR-642a-5p partly abolished the functions of PCGEM1 knockdown on proliferation, cell cycle, migration and invasion of cervical carcinoma cells. Furthermore, miR-642a-5p could bind to the 3'-UTR of LGMN, which was over-expressed in the cervical carcinoma cells. Suppression of LGMN partly restored the functions of miR-642a-5p inhibitor on proliferation, cell cycle distribution, migration and invasion in the cervical carcinoma cells treated with the PCGEM1 shRNA. Taken together, our data indicated that knockdown of PCGEM1 inhibited proliferation, migration and invasion in cervical carcinoma by modulating the miR-642a-5p/ LGMN axis.

Preoperative prediction of parametrial invasion in early-stage cervical cancer with MRI-based radiomics nomogram

PURPOSE

To develop and identify a MRI-based radiomics nomogram for the preoperative prediction of parametrial invasion (PMI) in patients with early-stage cervical cancer (ECC).

MATERIALS AND METHODS

All 137 patients with ECC (FIGO stages IB-IIA) underwent T2WI and DWI scans before radical hysterectomy surgery. The radiomics signatures were calculated with the radiomics features which were extracted from T2WI and DWI and selected by the least absolute shrinkage and selection operation regression. The support vector machine (SVM) models were built using radiomics signatures derived from T2WI and joint T2WI and DWI respectively to evaluate the performance of radiomics signatures for distinguishing patients with PMI. A radiomics nomogram was drawn based on the radiomics signatures with a better performance, patient's age, and pathological grade; its discrimination and calibration performances were estimated.

RESULTS

For T2WI and joint T2WI and DWI, the radiomics signatures yielded an AUC of 0.797 (95% CI, 0.682-0.911) vs 0.946 (95% CI, 0.899-0.994), and 0.780 (95% CI, 0.641-0.920) vs 0.921 (95% CI, 0.832-1) respectively in the primary and validation cohorts. The radiomics nomogram, integrating the radiomics signatures from joint T2WI and DWI, patient's age, and pathological grade, showed excellent discrimination, with C-index values of 0.969 (95% CI, 0.933-1) and 0.941 (95% CI, 0.868-1) in the primary and validation cohorts, respectively. The calibration curve showed a good agreement.

CONCLUSIONS

The radiomics nomogram performed well for the preoperative prediction of PMI in patients with ECC and may be used as a supplementary tool to provide individualized treatment plans for patients with ECC.

KEY POINTS

• No previously reported study that has utilized radiomics nomogram to preoperatively predict PMI for patients with ECC. • Radiomics model involves radiomics features extracted from joint T2WI and DWI which characterize the heterogeneity between tumors in patients with ECC. • Radiomics nomogram can assist clinicians with individualized treatment decision-making for patients with ECC.

iTRAQ-based quantitative proteomic analysis of the inhibition of cervical cancer cell invasion and migration by metformin

In recent years the anti-diabetic drug metformin has been shown to inhibit tumor growth, but the underlying mechanism is unclear. Our previous results showed that metformin can destroy the sponge effect of long-chain non-coding RNA MALAT1/miR-142-3p and inhibit the proliferation of cervical cancer cells. Metformin can inhibit the PI3K/Akt signaling pathway and synergizes with Nelfinavir to inhibit the proliferation and invasion of cervical cancer cells. In this study, we used iTRAQ-based proteomics, mass spectrometry-based targeted proteomics, immunoblotting, and bioinformatics to analyze the molecular mechanism by which metformin inhibits the proliferation and invasion of cervical cancer cells. We found that 53 proteins were differentially expressed in cervical cancer cells after metformin treatment, of which 20 were up-regulated and 33 were down-regulated. Bioinformatics analysis showed that the 53 differentially expressed proteins are negative regulators of receptor signaling that inhibit cell growth and are mainly enriched in cell growth and apoptosis signaling pathways. We performed PRM verification on 11 of the differentially expressed proteins and found that they were all associated with apoptosis. We also found that metformin up-regulated the expression of the tumor suppressor IGFBP7 to inhibit the proliferation and invasion of cervical cancer cells. Our results indicate that metformin mainly regulates the insulin signaling pathway and interferes with cell proliferation and apoptosis to inhibit proliferation and invasion of cervical cancer cells. These differentially expressed proteins may become new targets for the treatment of cervical cancer.

Which factors predict parametrial involvement in early stage cervical cancer? A Turkish multicenter study

OBJECTIVE

To evaluate the clinical and pathological factors for predicting the parametrial involvement (PI) in early stage cervical cancer.

STUDY DESIGN

This study included 406 patients with type III radical hysterectomy + pelvic ± para-aortic lymphadenectomy and FIGO stage I and II cervical adenocarcinoma, squamous type, and adenosquamous type cervical cancer.

RESULTS

The entire cohort of patients had lymphadenectomy performed. Early stage cervical cancer patients were evaluated. FIGO 2014 stage, uterine invasion, LVSI, surgical border involvement, vaginal metastasis, stromal invasion and lymph node metastasis were found to be effective for PI on univariate analyses. However; age, tumor type and tumor size did not determine the parametrial invasion. LVSI (HR: 4.438, 95%CI: 1.771-11.121; p = 0.001), lymph node metastases (HR: 2.418, 95%CI: 1.207-4.847; p = 0.013) and vaginal involvement (HR: 4.109, 95%CI: 1.674-10.087; p = 0.02) are independent prognostic factors on multivariate analysis.

CONCLUSION

Lymph node metastases, LVSI and surgical border involvement are independent prognostic factors for PI in early stage cervical cancer patients. Therefore, less radical surgical approaches for early stage tumors with no nodal spread, negative LVSI and no surgical border involvement are applicable.

CD36 promotes the epithelial-mesenchymal transition and metastasis in cervical cancer by interacting with TGF-β

Background

Accumulating evidence indicates that CD36 initiates metastasis and correlates with an unfavorable prognosis in cancers. However, there are few reports regarding the roles of CD36 in initiation and metastasis of cervical cancer.

Methods

Using immunohistochemistry, we analyzed 133 cervical cancer samples for CD36 protein expression levels, and then investigated the correlation between changes in its expression and clinicopathologic parameters. The effect of CD36 expression on the epithelial–mesenchymal transition (EMT) in cervical cancer cells was evaluated by Western immunoblotting analysis. In vitro invasion and in vivo metastasis assays were also used to evaluate the role of CD36 in cervical cancer metastasis.

Results

In the present study, we confirmed that CD36 was highly expressed in cervical cancer samples relative to normal cervical tissues. Moreover, overexpression of CD36 promoted invasiveness and metastasis of cervical cancer cells in vitro and in vivo, while CD36 knockdown suppressed proliferation, migration, and invasiveness. We demonstrated that TGF-β treatment attenuated E-cadherin expression and enhanced the expression levels of CD36, vimentin, slug, snail, and twist in si-SiHa, si-HeLa, and C33a–CD36 cells, suggesting that TGF-β synergized with CD36 on EMT via active CD36 expression. We also observed that the expression levels of TGF-β in si-SiHa cells and si-HeLa cells were down-regulated, whereas the expression levels of TGF-β were up-regulated in C33a–CD36 cells. These results imply that CD36 and TGF-β interact with each other to promote the EMT in cervical cancer.

Conclusions

Our findings suggest that CD36 is likely to be an effective target for guiding individualized clinical therapy of cervical cancer.