Lymph node assessment in cervical cancer: prognostic and therapeutic implications

High M2-TAM Infiltration and STAT3/NF-κB Signaling Pathway as a Predictive Factor for Tumor Progression and Death in Cervical Cancer

INTRODUCTION

The tumor microenvironment (TME) plays a crucial role in the progression, invasion, and metastasis of cervical carcinoma (CC). Tumor-associated macrophages (TAMs) are significant components of the CC TME, but studies on their correlation with CC progression are still controversial. This study aimed to investigate the relationship between TAM infiltration, the STAT3/NF-κB signaling pathway, and Overall Survival (OS) in CC patients.

METHODS

In a retrospective study, 691 CC patients who had received a definitive histopathologic diagnosis of CC scored by the FIGO staging system and not undergone preoperative treatment were selected from a database. The effect of TAM infiltration on tumor progression biomarkers using Tissue Microarray (TMA) and immunohistochemistry was evaluated. Furthermore, the impact of the expression of these biomarkers and clinical-pathological parameters on recurrence-free (RF) and OS using Kaplan-Meier and multivariable Cox regression methods was also analyzed.

RESULTS

High stromal CD163 + 204 + TAMs density and via STAT3 and NF-κB pathways was relevant to the expression of E-cadherin, Vimentin, MMP9, VEGFα, Bcl-2, Ki-67, CD25, MIF, FOXP3, and IL-17 (all p < 0.0001). In addition, elevated TNM staging IV had a strong association correlation with STAT3 and NF-κB pathways (p < 0.0001), CD25 (p < 0.001), VEGFα (p < 0.001), MIF (p < 0.0001), and Ki-67 (p < 0.0001). On the other hand, overall and recurrence survival was shown to be strongly influenced by the expression of SNAIL (HR = 1.52), E-cadherin (HR = 1.78), and Ki-67 (HR = 1.44).

CONCLUSION

M2-TAM and via STAT3/NF-κB pathways had a strong effect on CC tumor progression which reverberated in the severity of clinicopathological findings, becoming an important factor of poor prognosis.

Association between body mass index and lymph node metastasis among women with cervical cancer: a systematic review and network meta-analysis

PURPOSE

Lymph node status is a determinant of survival in patients with early-stage cervical cancer. However, the relationship between obesity and lymph node status remains unclear. Therefore, this systematic review aims to evaluate the correlation between body mass index (BMI) and lymph node metastasis in cervical cancer.

METHODS

Cohort studies through six databases were reviewed until December 2021. Odds ratios (ORs) for lymphatic metastasis were estimated using random-effects models and network meta-analysis. BMI groups for lymph node metastasis were ranked. Heterogeneities were assessed using I2. Subgroup analyses were performed to determine possible sources of heterogeneity.

RESULTS

No significant difference was found between obese (BMI ≥ 25) and non-obese patients (BMI < 25) (OR = 1.01; 95% CI 0.69-1.47; P = 0.97). In subgroup analyses, obesity was associated with higher risk among the Americans and advanced-stage patients. The grouping analysis based on BMI and the rankogram values revealed that the '35 ≤ BMI' group had the highest risk of lymph node metastasis.

CONCLUSION

Although there were no significant differences in lymph node metastasis between obese and non-obese cervical cancer patients in overall analysis, patients with BMI ≥ 35 were at significantly higher risk of lymph node metastasis.

An interpretable clinical ultrasound-radiomics combined model for diagnosis of stage I 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 patients with stage I cervical cancer (CC) before surgery.

Materials and methods

A total of 209 CC patients who had cervical lesions found by transvaginal sonography (TVS) from the First Affiliated Hospital of Anhui Medical University were retrospectively reviewed, patients were divided into the training set (n = 146) and internal validation set (n = 63), and 52 CC patients from Anhui Provincial Maternity and Child Health Hospital and Nanchong Central Hospital were taken as the external validation set. The clinical independent predictors were selected by univariate and multivariate logistic regression analyses. 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, six machine learning (ML) algorithms were used to build the radiomics model. Next, the ability of the clinical, US-radiomics, and clinical US-radiomics combined model was compared to diagnose stage I CC. Finally, the Shapley additive explanations (SHAP) method was used to explain the contribution of each feature.

Results

Long diameter of the cervical lesion (L) and squamous cell carcinoma-associated antigen (SCCa) were independent clinical predictors of stage I CC. The eXtreme Gradient Boosting (Xgboost) model performed the best among the six ML radiomics models, with area under the curve (AUC) values in the training, internal validation, and external validation sets being 0.778, 0.751, and 0.751, respectively. In the final three models, the combined model based on clinical features and rad-score showed good discriminative power, with AUC values in the training, internal validation, and external validation sets being 0.837, 0.828, and 0.839, respectively. The decision curve analysis validated the clinical utility of the combined nomogram. The SHAP algorithm illustrates the contribution of each feature in the combined model.

Conclusion

We established an interpretable combined model to predict stage I CC. This non-invasive prediction method may be used for the preoperative identification of patients with stage I CC.

Significance of tumor size and number of positive nodes in patients with FIGO 2018 stage IIIC1 cervical cancer

OBJECTIVE

This study aimed to investigate the prognostic significance of tumor size and number of positive pelvic lymph nodes (PLN) in International Federation of Gynecology and Obstetrics (FIGO) 2018 stage IIIC1 cervical cancer patients.

METHODS

Clinical data from 626 women with cervical cancer treated at Osaka International Cancer Center in 2010-2020 were retrospectively reviewed. Using the cutoff value obtained on the receiver operating characteristic analysis, the prognostic significance of tumor size and number of positive PLN in stage IIIC1 patients was first evaluated via uni- and multivariate analyses. Then, the impact of incorporating tumor size and number of positive PLN into the FIGO staging system was investigated using the Kaplan-Meier method.

RESULTS

Among 196 women with Stage IIIC1 disease, larger tumors (>4 cm) and multiple PLN metastases (≥4) were independent predictors of progression-free survival (PFS) in patients with stage IIIC1 cervical cancer. The PFS of patients with stage IIIC1 disease was inversely associated with the number of risk factors. Although patients with stage IIIC1 disease had significantly increased survival rates compared to those with stage IIIA or IIIB disease in the original FIGO 2018 staging system, this reversal phenomenon was resolved by incorporating larger tumors (>4 cm) and multiple PLN metastases (≥4) into the revised staging system.

CONCLUSIONS

Incorporating tumor size and number of metastatic lymph nodes into the FIGO staging system allows additional risk stratification for women with stage IIIC1 cervical cancer and improves survival prediction performance.

Prediction of lymph node status in patients with early-stage cervical cancer based on radiomic features of magnetic resonance imaging (MRI) images

BACKGROUND

Lymph node metastasis is an important factor affecting the treatment and prognosis of patients with cervical cancer. However, the comparison of different algorithms and features to predict lymph node metastasis is not well understood. This study aimed to construct a non-invasive model for predicting lymph node metastasis in patients with cervical cancer based on clinical features combined with the radiomic features of magnetic resonance imaging (MRI) images.

METHODS

A total of 180 cervical cancer patients were divided into the training set (n = 126) and testing set (n = 54). In this cross-sectional study, radiomic features of MRI images and clinical features of patients were collected. The least absolute shrinkage and selection operator (LASSO) regression was used to filter the features. Seven machine learning methods, including eXtreme Gradient Boosting (XGBoost), Logistic Regression, Multinomial Naive Bayes (MNB), Support Vector Machine (SVM), Decision Tree, Random Forest, and Gradient Boosting Decision Tree (GBDT) are used to build the models. Receiver operating characteristics (ROC) curve and area under the curve (AUC), accuracy, sensitivity, and specificity were calculated to assess the performance of the models.

RESULTS

Of these 180 patients, 49 (27.22%) patients had lymph node metastases. Five of the 122 radiomic features and 3 clinical features were used to build predictive models. Compared with other models, the MNB model was the most robust, with its AUC, specificity, and accuracy on the testing set of 0.745 (95%CI: 0.740-0.750), 0.900 (95%CI: 0.807-0.993), and 0.778 (95%CI: 0.667-0.889), respectively. Furthermore, the AUCs of the MNB models with clinical features only, radiomic features only, and combined features were 0.698 (95%CI: 0.692-0.704), 0.632 (95%CI: 0.627-0.637), and 0.745 (95%CI: 0.740-0.750), respectively.

CONCLUSION

The MNB model, which combines the radiomic features of MRI images with the clinical features of the patient, can be used as a non-invasive tool for the preoperative assessment of lymph node metastasis.

Prognostic analysis of patients with stage IIIC1p cervical cancer treated by surgery

BACKGROUND

Cervical cancer (CC) is one of the most common gynaecologic malignancies. The prognosis of stage IIIC1p cervical cancer patients treated by surgery is heterogeneous. Therefore, the aim of this study was to analyse the factors influencing the prognosis in such patients.

METHODS

From January 2012 to December 2017, 102 patients with cervical cancer who underwent surgical treatment in the Department of Gynaecology and Tumours, Changzhou Maternal and Child Health Hospital, and had pelvic lymph node metastasis confirmed by pathology were analysed retrospectively. All patients underwent radical hysterectomy with/without oophorectomy with pelvic lymphadenectomy with/without para-aortic lymphadenectomy. Clinical data was collected including age, surgical method, ovarian status, intraoperative blood loss, perioperative complications, tumour size, pathological type, depth of stromal invasion (DSI), whether the lymphatic vascular space was infiltrated, number of pelvic lymph node metastases, location of pelvic lymph node metastases, total number of lymph nodes resected, lymph node ratio (LNR), nature of vaginal margin, whether parametrium was involved, postoperative adjuvant therapy, preoperative neutrophil-lymphocyte ratio (NLR) and prognostic information of patients. Survival curves for overall survival (OS) and disease-free survival (DFS) were plotted using the Kaplan-Meier method, and the difference between the survival curves was tested using the log-rank test. Univariate and multivariate COX regression models were used to assess the factors associated with overall survival and disease-free survival in patients with stage IIIC1p cervical cancer. Nomogram plots were constructed to predict OS and DFS, and the predictive accuracy of the nomograms was measured by Harrell's C-index and calibration curves.

RESULTS

A total of 102 patients with stage IIIC1p cervical cancer were included in the study, and the median follow-up time was 63 months (range from 6 to 130 months). The 5-year OS was 64.7%, and the 5-year DFS was 62.7%. Multivariate analysis showed that no postoperative adjuvant therapy, LNR > 0.3 and NLR > 3.8 were independent risk factors for OS and DFS in patients with stage IIIC1p cervical cancer.

CONCLUSIONS

Patients with stage IIIC1p cervical cancer have a poor prognosis. Lower OS and DFS were associated with no postoperative adjuvant therapy, LNR > 0.3 and NLR > 3.8.

Developing a nomogram for preoperative prediction of cervical cancer lymph node metastasis by multiplex immunofluorescence

BACKGROUND

Most traditional procedures can destroy tissue natural structure, and the information on spatial distribution and temporal distribution of immune milieu in situ would be lost. We aimed to explore the potential mechanism of pelvic lymph node (pLN) metastasis of cervical cancer (CC) by multiplex immunofluorescence (mIF) and construct a nomogram for preoperative prediction of pLN metastasis in patients with CC.

METHODS

Patients (180 IB1-IIA2 CC patients of 2009 FIGO (International Federation of Gynecology and Obstetrics)) were divided into two groups based on pLN status. Tissue microarray (TMA) was prepared and tumor-infiltrating immune markers were assessed by mIF. Multivariable logistic regression analysis and nomogram were used to develop the predicting model.

RESULTS

Multivariable logistic regression analysis constructs a predictive model and the area under the curve (AUC) can reach 0.843. By internal validation with the remaining 40% of cases, a new ROC curve has emerged and the AUC reached 0.888.

CONCLUSIONS

This study presents an immune nomogram, which can be conveniently used to facilitate the preoperative individualized prediction of LN metastasis in patients with CC.

Intra- and peri-tumoral MRI radiomics features for preoperative lymph node metastasis prediction in early-stage cervical cancer

BACKGROUND

Noninvasive and accurate prediction of lymph node metastasis (LNM) is very important for patients with early-stage cervical cancer (ECC). Our study aimed to investigate the accuracy and sensitivity of radiomics models with features extracted from both intra- and peritumoral regions in magnetic resonance imaging (MRI) with T2 weighted imaging (T2WI) and diffusion weighted imaging (DWI) for predicting LNM.

METHODS

A total of 247 ECC patients with confirmed lymph node status were enrolled retrospectively and randomly divided into training (n = 172) and testing sets (n = 75). Radiomics features were extracted from both intra- and peritumoral regions with different expansion dimensions (3, 5, and 7 mm) in T2WI and DWI. Radiomics signature and combined radiomics models were constructed with selected features. A nomogram was also constructed by combining radiomics model with clinical factors for predicting LNM.

RESULTS

The area under curves (AUCs) of radiomics signature with features from tumors in T2WI and DWI were 0.841 vs. 0.791 and 0.820 vs. 0.771 in the training and testing sets, respectively. Combining radiomics features from tumors in the T2WI, DWI and peritumoral 3 mm expansion in T2WI achieved the best performance with an AUC of 0.868 and 0.846 in the training and testing sets, respectively. A nomogram combining age and maximum tumor diameter (MTD) with radiomics signature achieved a C-index of 0.884 in the prediction of LNM for ECC.

CONCLUSIONS

 Radiomics features extracted from both intra- and peritumoral regions in T2WI and DWI are feasible and promising for the preoperative prediction of LNM for patients with ECC.

Treatment for Locally Resectable Stage IIIC1 Cervical Cancer: A Retrospective, Single-Institution Study

According to the revision of the FIGO 2018 staging system, cervical cancer with pelvic lymph node metastases was changed to stage IIIC1. We retrospectively analyzed the prognosis and complications of locally resectable (classified as T1/T2 by TNM classification of the Union for International Cancer Control) stage IIIC1 cervical cancer. A total of 43 patients were divided into three groups: surgery with chemotherapy (CT) (ope+CT group) (T1; n = 7, T2; n = 16), surgery followed by concurrent chemoradiotherapy (CCRT), or radiotherapy (RT) (ope+RT group) (T1; n = 5, T2; n = 9), and CCRT or RT alone (RT group) (T1; n = 0, T2; n = 6). In T1 patients, recurrence was observed in three patients, but there was no difference among the treatment groups, and no patients died. In contrast, in T2 patients, recurrence and death were observed in nine patients (8 in ope+CT; 1 in ope+RT), and recurrence-free survival and overall survival were lower in the ope+CT group (p = 0.02 and 0.04, respectively). Lymphedema and dysuria were more common in the ope+RT group. A randomized controlled trial comparing CT and CCRT as an adjuvant therapy after surgery in T1/T2 patients, including those with pelvic lymph node metastases, is currently underway. However, our data suggest that performing CT alone after surgery in T2N1 patients is likely to worsen the prognosis.

Recent Advances in Cervical Cancer Management: A Review on Novel Prognostic Factors in Primary and Recurrent Tumors

BACKGROUND

Several pathological parameters, including tumor size, depth of stromal invasion, lympho-vascular space invasion and lymph node status, have been proposed as prognostic predictors in cervical cancer. However, given the high mortality and recurrence rate of cervical cancer, novel parameters that are able to provide additional prognostic information are needed in order to allow a better prognostic stratification of cervical cancer patients.

METHODS

A search was conducted on PubMed to identify relevant literature data regarding prognostic factors in cervical cancer. The key words "cervical cancer", "prognostic factors", "pathology", and "outcome" were used.

RESULTS

The novel pathological grading system based on tumor budding and cell nest size appeared the most relevant prognostic factor in primary neoplasms. Moreover, other potentially useful prognostic factors were tumor size, depth of stromal invasion, lympho-vascular space invasion, perineural invasion, tumor-free distance and tumor-infiltrating lymphocytes. Prognostic factors related to advanced-stage cervical cancer, including lymph-nodes status, endometrial and cervical involvement as well as distant metastases, were also taken into consideration.

CONCLUSIONS

According to our findings, tumor budding and cell nest size grading system, depth of stromal invasion, lympho-vascular space invasion, perineural invasion, tumor-free distance and tumor-infiltrating lymphocytes appeared the most relevant factors included in the pathology report.

Integrated single-cell transcriptome analysis of the tumor ecosystems underlying cervical cancer metastasis

Cervical cancer (CC) is one of the most frequent female malignancies worldwide. However, the molecular mechanism of lymph node metastasis in CC remains unclear. In this study, we investigated the transcriptome profile of 51,507 single cells from primary tumors, positive lymph nodes (P-LN), and negative lymph nodes (N-LN) using single-cell sequencing. Validation experiments were performed using bulk transcriptomic datasets and immunohistochemical assays. Our results indicated that epithelial cells in metastatic LN were associated with cell- cycle-related signaling pathways, such as E2F targets, and mitotic spindle, and immune response-related signaling pathways, such as allograft rejection, IL2_STAT5_signaling, and inflammatory response. However, epithelial cells in primary tumors exhibited high enrichment of epithelial-mesenchymal translation (EMT), oxidative phosphorylation, and interferon alpha response. Our analysis then indicated that metastasis LN exhibited an early activated tumor microenvironment (TME) characterized by the decrease of naive T cells and an increase of cytotoxicity CD8 T cells, NK cells, FOXP3+ Treg cells compared with normal LN. By comparing the differently expressed gene of macrophages between tumor and metastatic LN, we discovered that C1QA+ MRC1^low macrophages were enriched in a tumor, whereas C1QA+ MRC1^high macrophages were enriched in metastatic LN. Finally, we demonstrated that cancer-associated fibroblasts (CAFs) in P-LN were associated with immune regulation, while CAFs in tumor underwent EMT. Our findings offered novel insights into the mechanisms of research, diagnosis, and therapy of CC metastasis.

Diagnostic performance of ADC values and MRI-based radiomics analysis for detecting lymph node metastasis in patients with cervical cancer: A systematic review and meta-analysis

OBJECTIVE

To evaluate and compare the diagnostic performance of apparent diffusion coefficient (ADC) values and MRI-based radiomics analysis for lymph node metastasis (LNM) detection in patients with cervical cancer (CC).

METHODS

We searched relevant databases for studies on ADC values and MRI-based radiomics analysis for LNM detection in CC between January 2001 and December 2021. Methodological quality assessment of risk of bias using Quality Assessment of Diagnostic Accuracy Studies 2 and radiomics quality score (RQS) of the studies was conducted. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated. Diagnostic performance was compared between the two quantitative analyses using a two-sample Z-test.

RESULTS

In total, 22 studies including 2314 patients were included. Unclear risk of bias was observed in 4.5-36.4% of the studies. The 8 radiomics studies exhibited a median (interquartile range) RQS of 13.5 (5.5-15.75). The pooled sensitivity, specificity, LR+, LR-, DOR, and AUC of the ADC values vs radiomics analysis were 0.86 vs 0.84, 0.85 vs 0.73, 5.7 vs 3.1, 0.17 vs 0.22, 34 vs 14, and 0.91 vs 0.86, respectively. There was no threshold effect or publication bias, but significant heterogeneity existed among the studies. No significant difference was detected in the diagnostic performance of the two quantitative analyses using the Z-test.

CONCLUSION

ADC values are more clinically promising because they are more easily accessible and widely applied, and exhibit a non-statistically significant trend to outperform radiomics analysis.

Identification of novel genetic and epigenetic regulators of different tissue types of cervical cancer

OBJECTIVES

The study aimed to find differential gene mutations, DNA methylation, and expression profiles among different categories of cervical cancer samples.

METHODS

The study was based on freely available gene mutations, promoter methylation, and gene expression status of The Cancer Genome Atlas (TCGA) cervical cancer samples and adjacent normal tissues in the Genomic Data Commons (GDC) portal. The association of CpG island methylation with gene expression was determined through negative correlation analysis.

RESULTS

We identified that the ErbB signaling pathway and proteoglycans pathway was significantly associated with adenocarcinoma cervical cancers patients. In these pathways, missense mutation especially S310F in the ERBB2 gene as well as G12D and A146T in the KRAS gene were significantly associated with adenocarcinoma cases. Furthermore, a comparison of SCC cases with adjacent control tissues revealed differential hypermethylation of two CpG positions of the KAAG1 gene and differential downregulation of NPY1R and NPY5R genes in cervical squamous cell carcinoma compared to cervical adenocarcinoma cases and adjacent normal tissues. Specifically, the hypermethylation of the promoter region of the KAAG1 gene might be responsible for the carcinogenesis of cervical squamous cells exclusively and methylation marks can be reversible by the widely used drug, azacytidine. In contrast, adenocarcinoma cervical cancer cases may be treated with floxuridine which is successfully utilized for other tissue-specific adenocarcinoma cases.

CONCLUSIONS

These results provide valuable insight into the differential molecular markers among the categories of cervical cancer, which helps our ability to classify these cancers and for targeted therapy.

Impact of examined lymph node number on lymph node status and prognosis in FIGO stage IB-IIA cervical squamous cell carcinoma: A population-based study

Objective

We aimed to investigate the association of examined lymph node (ELN) number with lymph node status and long-term survival in FIGO stage IB-IIA cervical squamous cell carcinoma(CSCC) and to determine the minimum number of ELN associated with survival improvement.

Method

Data from the Surveillance, Epidemiology, and End Results Program (SEER) database of FIGO stage IB-IIA CSCC patients undergoing hysterectomy and pelvic lymphadenectomy in 2004-2016 were analyzed to explore the relationship between ELN number and lymph node status and overall survival (OS) by using the multivariable approach. The estimated probability of falsely identifying a patient as node-negative and the hazard ratios (HRs) for each ELN was fitted with a LOWESS smoother, and the structural breakpoints were determined. X-tile software was used to determine the optimal cutoff value for ELNs.

Results

A total of 2627 patients were analyzed. The optimal cutoff value of the ELN number was identified as 7 based on the results of X-tile software. The structural breakpoints according to the associations between the number of ELNs and the estimated risk of false-negative lymph node dissection and HRs for overall survival were 9 and 8, respectively. The multivariate analysis indicated that ELN number was an independent prognostic factor for OS, both as a continuous or categorical variable. To further explore the effect of more ELNs on survival, another cutoff value of 17 was chosen to compare the survival curves of patients. The multivariate-adjusted COX model showed that patients with ELN<8 had a significantly higher risk of death than those with ELN8-17 (HR=1.447, 95% CI =1.075-1.947, p=0.015), but there was no significant difference in overall survival between patients with ELN>17 and patients with ELN8-17 (HR=0.822, 95%CI =0.665-1.016, p=0.070).

Conclusion

A sufficient number of ELNs was associated with better long-term survival in FIGO stage IB-IIA CSCC. At least 8 ELNs need to be examined for prognostic stratification. Excessive lymph node dissection (ELN>17) may not confer additional survival benefits.

Clinical outcome of FIGO 2018 stage IB3/IIA2 cervical cancer treated by neoadjuvant chemotherapy followed by radical surgery due to lack of radiotherapy equipment: A retrospective comparison with concurrent chemoradiotherapy

This study aimed to assess neoadjuvant chemotherapy’s clinical outcomes such as efficacy, toxicity, and survival outcomes followed by radical hysterectomy ((NACT-RS) among women with cervical cancer stage IB3 and IIA2, by comparing concurrent chemoradiotherapy (CCRT) and NACT-RS. The study retrospectively reviewed patients with (2018 FIGO) stage IB3 and IIA2 cervical cancer who received preoperative neoadjuvant chemotherapy followed by NACT-RS or concurrent chemoradiotherapy (CCRT). The outcome measures were the 5-year survival and complication rates between the two groups. The median follow-up was 75 months. In total, 218 patients had stage IIA2, 136 patients had stage IB3, 201 patients received CCRT, and 153 patients received preoperative NACT-RS. In the CCRT group, the incidence of early complications (myelosuppression, gastrointestinal and urinary) was higher compared with that in the NACT-RS group (76.1 vs. 26.1%; p < 0.001, respectively). There was no significant difference between the two study groups concerning late complications. Five-year PFS was 79.9% and 85.5% in the NACT-RS and CCRT groups, respectively (p = 0.093). Five-year OS was 86.9% and 85.5% in the NACT-RS and CCRT groups, respectively (p = 0.97). In the multivariate clinicopathologic characteristics analysis for OS, initial tumor size > 4.3 cm (HR 5.11; p < 0.001), AC/ASC (HR 1.89; p = 0.02), histologic grade 2–3 (HR 2.25; p = 0.04), and 2018 FIGO stage IIA2 (HR 8.67; p < 0.001) were independent risk factors. The survival of patients with stage IB3 and IIA2 cervical cancer treated with NACT-RS was similar to that of patients treated with CCRT without increasing side effects.

Treatment Strategies and Prognostic Factors of 2018 FIGO Stage IIIC Cervical Cancer: A Review

Cervical cancer is the fourth most common malignant tumor globally in terms of morbidity and mortality. The presence of lymph node metastasis (LNM) is an independent prognostic factor for progression-free survival (PFS) and overall survival (OS) in cervical cancer patients. The International Federation of Gynecology and Obstetrics (FIGO) staging system was revised in 2018. An important revision designates patients with regional LNM as stage IIIC, pelvic LNM only as stage IIIC1, and para-aortic LNM as stage IIIC2. However, the current staging system is only based on the anatomical location of metastatic lymph nodes (LNs). It does not consider other LN status parameters, which may limit its prognostic significance to a certain extent and needs further exploration and confirmation in the future. The purpose of this review is to summarize the choice of treatment for stage IIIC cervical cancer and the effect of different LN status parameters on prognosis.

MRI-based peritumoral radiomics analysis for preoperative prediction of lymph node metastasis in early-stage cervical cancer: A multi-center study

PURPOSE

To evaluate intra- and preitumoral radiomics on the contrast-enhanced T1-weighted (CE-T1) and T2-weighted (T2W) MRI for predicting the LNM, and develop a nomogram for potential clinical uses.

METHODS

We enrolled 169 cervical cancer cases who underwent CE-T1 and T2W MR scans from two hospitals between Dec. 2015 and Sep. 2021. Intra- and peritumoral features were extracted separately and selected by the least absolute shrinkage and selection operator (LASSO) regression. Radiomics signatures were built using the selected features from different regions. Clinical parameters were evaluated by statistical analysis. The nomogram was developed combining the multi-regional radiomics signature and the most predictive clinical parameters.

RESULTS

Five radiomics features were finally selected from the peritumoral regions with 1 and 3 mm distances in the CE-T1 and T2W MRI, respectively. The nomogram incorporating multi-regional combined radiomics signature, MR-reported LN status and tumor diameter achieved the highest AUCs in the training (nomogram vs. combined radiomics signature vs. clinical model, 0.891 vs. 0.830 vs. 0.812), internal validation (nomogram vs. combined radiomics signature vs. clinical model, 0.863 vs. 0.853 vs. 0.816) and external validation (nomogram vs. combined radiomics signature vs. clinical model, 0.804 vs. 0.701 vs. 0.787) cohort. DCA suggested good clinical usefulness of our developed models.

CONCLUSION

The current work suggested clinical potential for intra- and peritumoral radiomics with multi-modal MRI for preoperative predicting LNM.

Deep learning nomogram for predicting lymph node metastasis using computed tomography image in cervical cancer

BACKGROUND

Deep learning (DL) has been used on medical images to grade, differentiate, and predict prognosis in many tumors.

PURPOSE

To explore the effect of computed tomography (CT)-based deep learning nomogram (DLN) for predicting cervical cancer lymph node metastasis (LNM) before surgery.

MATERIAL AND METHODS

In total, 418 patients with stage IB-IIB cervical cancer were retrospectively enrolled for model exploration (n = 296) and internal validation (n = 122); 62 patients from another independent institution were enrolled for external validation. A convolutional neural network (CNN) was used for DL features extracting from all lesions. The least absolute shrinkage and selection operator (Lasso) logistic regression was used to develop a deep learning signature (DLS). A DLN incorporating the DLS and clinical risk factors was proposed to predict LNM individually. The performance of the DLN was evaluated on internal and external validation cohorts.

RESULTS

Stage, CT-reported pelvic lymph node status, and DLS were found to be independent predictors and could be used to construct the DLN. The combination showed a better performance than the clinical model and DLS. The proposed DLN had an area under the curve (AUC) of 0.925 in the training cohort, 0.771 in the internal validation cohort, and 0.790 in the external validation cohort. Decision curve analysis and stratification analysis suggested that the DLN has potential ability to generate a personalized probability of LNM in cervical cancer.

CONCLUSION

The proposed CT-based DLN could be used as a personalized non-invasive tool for preoperative prediction of LNM in cervical cancer, which could facilitate the choice of clinical treatment methods.

Heart Rate Variability is an Independent Predictor of Lymph Node Metastasis in Patients with Cervical Cancer

Purpose

Heart rate variability (HRV) has been reported as a useful biomarker for prognostic factors in a variety of cancers. The purpose of this study was to explore the predictive value of preoperative HRV for lymph node metastasis (LNM) in patients with cervical cancer (CC).

Patients and Methods

A total of 77 patients with CC were included, including 18 LNM and 59 non-LNM patients. A five-minute resting electrocardiogram (ECG) was collected before surgery for the analysis of HRV time domain, frequency domain and Poincaré plot parameters (ie, SDNN, RMSSD, LF, HF, LF/HF, SD1, SD2 and SD2/SD1). Student’s t-tests and logistic regression were performed to determine the relationship between HRV and LNM.

Results

The LNM group had significantly lower SDNN, LF, and SD2 than the non-LNM group (all p < 0.05; all Cohen’s d > 0.5). Binary logistic regression analysis indicated that SDNN, LF and SD2 were still significantly associated with LNM. Specifically, for each 1 ms decrease in SDNN and SD2 and each 1 logarithmic unit decrease in ln (LF), the odds of LNM increased by 12%, 9%, and 86%, respectively (all p < 0.05).

Conclusion

These findings suggest an association between HRV and CC LNM, and HRV could be a potential noninvasive biomarker for the prediction of LNM in CC patients.

Association between single nucleotide polymorphisms of VEGF gene and pelvic lymph node metastasis in patients with early-stage cervical cancer

Cervical cancer patients in early-stage cervical cancer (ECC) were divided into pelvic lymph node (PLN) metastasis and non-PLN metastasis group. Single nucleotide polymorphism (SNP) genotyping for the VEGF gene was conducted and plasma VEGF levels were measured. Multivariate analysis was performed to assess the correlation between SNPs of the VEGF gene and PLN metastasis. We found that SNP of the VEGF rs2010963 was independently associated with PLN metastasis. GG and CG genotype had increased susceptibility to PLN metastasis compared with CC genotype, and moreover, OR was higher in GG genotype than in CG genotype. Plasma VEGF levels were lowest in CC genotype, intermediate in GC genotype and highest in GG genotype. In summary, the SNP of the VEGF rs2010963 affected susceptibility to PLN metastasis in patients with ECC, and GG and CG genotype had increased susceptibility compared with CC genotype. The potential mechanism was associated with elevated plasma VEGF levels.Impact StatementWhat is already known on this subject? The positive expression of vascular endothelial growth factor (VEGF) is correlated with higher risk of lymph node metastasis among cervical cancer patients, and VEGF levels of patients with pelvic lymph node (PLN) metastasis are significantly higher than those without PLN metastasis. Additionally, single nucleotide polymorphisms (SNPs) of the VEGF gene have been indicated to be correlated with individual susceptibility to tumours and expression and protein production of VEGF.What do the results of this study add? The SNP of the VEGF rs2010963 was independently associated with PLN metastasis in patients with early-stage cervical cancer (ECC). The GG and CG genotype of the VEGF rs2010963 had increased susceptibility to PLN metastasis compared with CC genotype. Plasma VEGF levels were lowest in the CC genotype, intermediate in the GC genotype and highest in the GG genotype.What are the implications of these findings for clinical practice and/or further research? The SNP of the VEGF rs2010963 affected susceptibility to PLN metastasis in patients with ECC, and the potential mechanism was associated with elevated plasma VEGF levels.

Radiomic models for lymph node metastasis prediction in cervical cancer: can we think beyond sentinel lymph node?

Liu and colleagues performed a retrospective study to validate a computed tomography (CT) scan-based radiomic model to detect lymph node metastasis in cervical cancer. The proposed model incorporating the arterial and venous phase CT-scan features represented a non-invasive method exhibiting high sensitivity in the prediction of lymph node metastasis. It is well established that lymph node metastasis is one of the most significant prognostic factors in cervical cancer. For this reason, management of cervical cancer is strictly related to lymph node status, with international guidelines recommending definitive chemo-radiation in case of metastatic lymph node. More and more evidence supports the use of sentinel lymph node in early-stage cervical cancer but its frozen section analysis may result in false negative results; in locally-advanced stages staging para-aortic lymphadenectomy is proposed by many Authors to tailor chemoradiotherapy treatment, with potential intra-and post-operative related complications. The use of a validated radiomic model able to predict lymph node metastases in radiologically normal lymph nodes may represent an essential tool to possibly spare lympadenectomy related morbidity.

MRI-based radiomics: promise for locally advanced cervical cancer treated with a tailored integrated therapeutic approach

OBJECTIVE

To assess prognostic factors by analyzing clinical and radiomic data of patients with locally advanced cervical cancer (LACC) treated with definitive concurrent cisplatin-based chemoradiotherapy (CCRT) using magnetic resonance imaging (MRI).

METHODS

We analyzed radiomic features from MRI in 60 women with FIGO (International Federation of Gynecology and Obstetrics) stage IB2-IVA cervical cancer who underwent definitive CCRT 45-50.4 Gy (in 25-28 fractions). Thirty-nine (65.0%) received EBRT sequential boost (4-20 Gy) on primary tumor site and 56 (93.3%) received high-dose-rate brachytherapy boost (6-28 Gy) (daily fractions of 5-7 Gy). Moreover, 71.7% of patients received dose-dense neoadjuvant chemotherapy for 6 cycles. The gross tumor volume was defined on T2-weighted sequences and 29 features were extracted from each MRI performed before and after CCRT, using dedicated software, and their prognostic value was correlated with clinical information.

RESULTS

In univariate analysis, age ⩾60 years and FIGO stage IB2-IIB had significantly better progression-free survival (PFS) (p = 0.022 and p = 0.009, respectively). There was a trend for significance for worse overall survival (OS) in patients with positive nodes (p = 0.062). In multivariate analysis, only age ⩾60 years and FIGO stage IB2-IIB reached significantly better PFS (p = 0.020 and p = 0.053, respectively). In radiomic dataset, in multivariate analysis, pregray level p75 was significantly associated with PFS (p = 0.047), pre-D3D value with OS (p = 0.049), and preinformation measure of correlation value with local control (p = 0.031).

CONCLUSION

The combination of clinical and radiomics features can provide information to predict behavior and prognosis of LACC and to make more accurate treatment decisions.

Computed tomography-based radiomic model at node level for the prediction of normal-sized lymph node metastasis in cervical cancer

•

The metastatic status of lymph nodes in cervical cancer patients can be predicted.

•

Computed tomography-based radiomic model can identify the status of the normal-sized lymph node singly.

•

The model may help doctors to make staging and clinical decision, and realize individualized treatment.

Purpose

Radiomic models have been demonstrated to have acceptable discrimination capability for detecting lymph node metastasis (LNM). We aimed to develop a computed tomography–based radiomic model and validate its usefulness in the prediction of normal-sized LNM at node level in cervical cancer.

Methods

A total of 273 LNs of 219 patients from 10 centers were evaluated in this study. We randomly divided the LNs from the 2 centers with the largest number of LNs into the training and internal validation cohorts, and the rest as the external validation cohort. Radiomic features were extracted from the arterial and venous phase images. We trained an artificial neural network (ANN) to develop two single-phase models. A radiomic model reflecting the features of two-phase images was also built for directly predicting LNM in cervical cancer. Moreover, four state-of-the-art methods were used for comparison. The performance of all models was assessed using the area under the receiver operating characteristic curve (AUC).

Results

Among the models we built, the models combining the features of two phases surpassed the single-phase models, and the models generated by ANN had better performance than the others. We found that the radiomic model achieved the highest AUCs of 0.912 and 0.859 in the training and internal validation cohorts, respectively. In the external validation cohort, the AUC of the radiomic model was 0.800.

Conclusion

We constructed a radiomic model that exhibited great ability in the prediction of LNM. The application of the model could optimize clinical staging and decision-making.

Nomograms predicting the overall survival and cancer-specific survival of patients with stage IIIC1 cervical cancer

BACKGROUND

To explore the factors that affect the prognosis of overall survival (OS) and cancer-specific survival (CSS) of patients with stage IIIC1 cervical cancer and establish nomogram models to predict this prognosis.

METHODS

Data from patients in the Surveil-lance, Epidemiology, and End Results (SEER) programme meeting the inclusion criteria were classified into a training group, and validation data were obtained from the First Affiliated Hospital of Anhui Medical University from 2010 to 2019. The incidence, Kaplan-Meier curves, OS and CSS of patients with stage IIIC1 cervical cancer in the training group were evaluated. Nomograms were established according to the results of univariate and multivariate Cox regression models. Harrell's C-index, calibration plots, receiver operating characteristic (ROC) curves and decision-curve analysis (DCA) were calculated to validate the prediction models.

RESULTS

The incidence of pelvic lymph node metastasis, a high-risk factor for the prognosis of cervical cancer, decreased slightly over time. Eight independent prognostic variables were identified for OS, including age, race, marriage status, histology, extension range, tumour size, radiotherapy and surgery, but only seven were identified for CSS, with marriage status excluded. Nomograms of OS and CSS were established based on the results. The C-indexes for the nomograms of OS and CSS were 0.687 and 0.692, respectively, using random sampling of SEER data sets and 0.701 and 0.735, respectively, using random sampling of external data sets. The AUCs for the nomogram of OS were 0.708 and 0.705 for the SEER data sets and 0.750 and 0.750 for the external data sets, respectively. In addition, AUCs of 0.707 and 0.709 were obtained for the nomogram of CSS when validated using SEER data sets, and 0.788 and 0.785 when validated using external data sets. Calibration plots for the nomograms were almost identical to the actual observations. The DCA also indicated the value of the two models.

CONCLUSIONS

Eight independent prognostic variables were identified for OS. The same factors predicted CSS, with the exception of the marriage status. Both OS and CSS nomograms had good predictive and clinical application value after validation. Notably, tumour size had the largest contribution to the OS and CSS nomograms.

Family with sequence similarity 83 member A promotes tumor cell proliferation and metastasis and predicts poor prognosis in cervical cancer

Family with sequence similarity 83 member A (FAM83A) is a member of the FAM83 family and is proven to have oncogenic properties in several cancers. However, the mechanisms of FAM83A in human cervical cancer (CC) progression are unknown. Here, we found that FAM83A is highly expressed in CC tissues and cell lines through western blot and qRT-PCR. We utilized GEO datasets to assess FAM83A expression in CC in comparison to the normal cervical tissue (NCT) (GSE6791), and similarly, in lymph node positive CC compared to the lymph node negative CC (GSE26511). Immunohistochemistry (IHC) was used to quantify FAM83A expression in 20 NCT and 105 CC patient samples. FAM83A expression is upregulated in early-stage CC and correlates with aggressive clinicopathologic features. Moreover, both our hospital's and TCGA datasets revealed that patients of early-stage CC with higher FAM83A expression had a poorer prognosis. Subsequently, CCK-8 and transwell assays verified that FAM83A promotes proliferation, migration, and invasion of CC cells. Additionally, Gene Set Enrichment Analysis (GSEA) revealed that FAM83A is not only involved in cell development, differentiation, and proliferation but is also correlated with cell junction assembly and cell matrix adhesion. It might also be affiliated with the regulation of tumor necrosis factor-mediated signaling pathway and the regulation of the ErbB signaling pathway in CC. These results indicate that FAM83A promotes tumor cell proliferation, migration, and metastasis. Our study provides novel evidence FAM83A may act as a promising therapeutic target for CC.

PET/MR imaging for the evaluation of cervical cancer during pregnancy

BACKGROUND

Malignancy during pregnancy is increasing, and the most common type of malignancy is uterine cervical cancer. When planning the treatment of cervical cancer, it is important to look for signs of metastasis before surgery, especially metastasis to the lymph nodes. In this report, we assessed the diagnostic value of positron emission tomography/magnetic resonance imaging (PET/MRI) for evaluating cervical cancer propagation before surgery, with a focus on pregnant women.

CASE PRESENTATION

¹⁸F Fluorodeoxyglucose (FDG)-PET/MRI was performed in seven pregnant cervical cancer patients (28-34 years old) at 9-18 gestational weeks. In case #5, a second PET/MRI was performed at 24 gestational weeks. Of seven FDG-PET/MRI examination series in six cases (cases #1-6), FDG-PET/MR imaging could detect cervical tumors with abnormal FDG accumulation; these tumors were confirmed with a standardized uptake value max (SUV max) titer of 4.5-16. A second PET/MRI examination in case #5 revealed the same SUV max titer as the first examination. In these six imaging series (cases #1-5), there were no signs of cancer metastasis to the parametrium and lymph nodes. However, in case #6, abnormal FDG accumulation in the left parametrial lymph nodes was also detectable. Pathological examination showed lymph node metastasis in case #6. In case #7, PET/MRI could not detect any abnormal FDG accumulation in the cervix and other sites. Cone biopsy demonstrated only micro-invasive squamous cell carcinoma. After treatment for cervical cancer, all seven patients have had no recurrence of disease within the follow-up period (2.8-5.6 years), and their children have developed appropriately.

CONCLUSION

PET/MRI is an effective imaging tool to evaluate cervical cancer progression in pregnancy.

Recurrence pattern and prognostic factors for survival in cervical cancer with lymph node metastasis

AIM

The aim of this study is to evaluate the recurrence pattern and oncological outcomes in cervical cancer (CC) patients with lymph node metastasis.

METHODS

This study included 224 International Federation of Gynecology and Obstetrics (FIGO) 2009 stage IB1-IIIB CC patients with pathologically proven lymph node metastasis. Surgical intervention was grouped as hysterectomy performed/not performed. Adjuvant therapy decision was made by the tumor board. Radiotherapy was applied to all patients with lymph node metastasis.

RESULTS

Only paraaortic lymph node metastasis was determined as an independent prognostic factor for recurrence. Presence of paraaortic lymph node metastasis increased the risk of recurrence more than two times (odds ratio: 2.129; 95% confidence interval: 1.011-4.485; p = 0.047). An independent prognostic factor for death because of disease was age only. Risk of death was nearly doubled with younger age (odds ratio: 2.693; 95% confidence interval: 1.064-6.184; p = 0.037).

CONCLUSION

The most of recurrences were located at distant sites and multiple regions. Paraaortic lymph node metastasis was the only independent prognostic factor for recurrence, in spite of that age was an independent predictor for risk of death in patients with early stage or locally advanced CC and also with surgically proven metastatic lymph nodes. Furthermore, the presence of the paraaortic lymph node metastasis was significantly associated with distant recurrence. Therefore, more appropriate and individualized therapy strategy focusing on intenser systemic chemotherapy options in addition to radiotherapy should be taken into consideration according to paraaortic lymph node metastasis and age.

A novel 2-deoxy-2-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT)-based nomogram to predict lymph node metastasis in early stage uterine cervical squamous cell cancer

Background

We aimed to establish an effective 2-deoxy-2-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) based nomogram for pelvic lymph node (PLN) metastasis prediction in early-stage uterine cervical squamous cell cancer.

Methods

A predictive model was developed in a cohort that consisted of 351 patients with stage IB-IIA [International Federation of Gynecology and Obstetrics (FIGO) 2009] uterine cervical squamous cell cancer. All patients underwent a preoperative PET/CT scan and subsequent radical surgery between 2010 and 2017, with 241 and 110 patients allotted into training and external validation cohorts. The chi-square (χ²) test and the logistic regression analysis were used to compare the clinical and PET/CT parameters with PLN metastasis. A nomogram was developed and validated by internal and external validation.

Results

In the training cohort, 82 (34.0%) patients had positive PLNs identified in the preoperative PET/CT scan. Among them, 46 (56.1%) were pathologically confirmed. There were 30 (18.9%) PET/CT scan-negative patients found to have PLN metastasis. The χ² test and logistic regression showed that only the squamous cell carcinoma antigen (SCCA) level (P=0.039) and maximum standardized uptake value (SUVmax) of PLN (nSUVmax, P=0.001) were independent predictors for PLN metastasis. A predictive nomogram based on these 2 parameters was developed with a C-index [95% confidence interval (CI)] of 0.854 (0.772-0.937) on internal validation and 0.836 (0.723-0.948) on the external validation. Compared to nSUVmax alone, our nomogram showed elevated sensitivity (70.5%, 73.1% vs. 60.5%), specificity (94.4%, 86.4% vs. 78.2%), and positive predictive value (PPV) (93.9%, 86.4% vs. 56.1%) in both the training and validation cohorts.

Conclusions

We successfully developed a noninvasive and convenient nomogram for preoperative identification of PLN metastasis in early-stage squamous cell cervical cancer.

Histopathologic Validation of the Sentinel Node Technique for Early-Stage Cervical Cancer Patients

BACKGROUND

The sentinel lymph node (SLN) biopsy may be an alternative to systematic lymphadenectomy in early cervical cancer. The SLN biopsy is less morbid and has been shown to have high sensitivity for metastasis detection. However, the sensitivity of the SLN technique might be overevaluated because SLNs are examined with ultra-staging, and non-sentinel nodes usually are examined only with routine techniques. This study aimed to validate the negative predictive value (NPV) of the SLN technique by the ultra-staging of SLNs and non-sentinel nodes (NSLNs).

METHODS

The SENTICOL 1 study data published in 2011 were used. All nodes (i.e., SLNs and NSLNs) were secondarily subjected to ultra-staging. The ultra-staging consisted of sectioning every 200 µm, in addition to immunohistochemistry. Moreover, the positive slides and 10% of the negative slides were reviewed.

RESULTS

The study enrolled 139 patients, and SLNs were detected in 136 (97.8%) of these patiets. Bilateral SLNs were detected in 104 (76.5%) of the 136 patients. A total of 2056 NSLNs were identified (median, 13 NSLNs per patient; range 1-54). Of the 136 patients with SLNs, 23 were shown to have positive SLNs after serial sectioning and immunohistochemical staining. The NSLNs were metastatic in six patients. In the case of bilateral SLN detection, the NPV was 100%, with no false-negatives (FNs).

CONCLUSIONS

The pelvic SLN technique is safe and trustworthy for determining the nodal status of patients with early-stage cervical cancer. In the case of optimal mapping with bilateral detection, the NPV was found to be 100%.

Comparison of different lymph node staging systems in patients with node-positive cervical squamous cell carcinoma following radical surgery

Objective: We compared the prognostic accuracy of four lymph node (LN) staging systems - the 2018 International Federation of Gynecology and Obstetrics (FIGO) stage, number of positive lymph node (PLN), metastatic lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) systems - in patients with node-positive cervical squamous cell carcinoma (CSCC) following radical surgery and explored the optimal choice for clinical applications. Materials and methods: Data were retrospectively collected from 928 node-positive CSCC patients who underwent radical surgery between 2006 and 2014 in our center. Tree-based recursive partitioning was applied to split variables (PLN, LNR, and LODDS) into low-risk and high-risk groups. The log-rank test was used to compare survival curves, and Cox regression analysis was performed to identify prognostic factors. The relative discriminative abilities of the different staging systems were assessed using Harrell's concordance index (C index) and the Akaike information criterion (AIC). Results: The mean number of PLNs was 3.8 (range: 1-44 nodes). According to the 2018 FIGO staging system, 831 patients had stage IIIC1, and 97 had stage IIIC2. For the PLN system, 761 patients were included in the low-risk group, and 167 were included in the high-risk group. For the LNR system, 658 patients were included in the low-risk group, and 270 were included in the high-risk group. The low-risk LODDS group included 694 patients, while the high-risk LODDS group included 234 patients. All four staging systems had a significant influence on patients' progression-free survival (PFS, P < 0.001) and overall survival (OS, P < 0.001). Univariate analysis and multivariate Cox analysis adjusted for significant factors indicated that the four staging systems were significant prognostic factors for PFS and OS. Among them, the PLN system was noted to have the best prognostic performance for both PFS (C index: 0.582; AIC: 8213.33) and OS (C index: 0.624; AIC: 8433.80). Conclusion: The PLN system seemed to be the most accurate LN staging method for predicting node-positive CSCC following radical surgery.

Radiomics Analysis of Multiparametric MRI for the Preoperative Prediction of Lymph Node Metastasis in Cervical Cancer

Objective: To develop and validate a radiomics predictive model based on multiparameter MR imaging features and clinical features to predict lymph node metastasis (LNM) in patients with cervical cancer.

Material and Methods: A total of 168 consecutive patients with cervical cancer from two centers were enrolled in our retrospective study. A total of 3,930 imaging features were extracted from T2-weighted (T2W), ADC, and contrast-enhanced T1-weighted (cT1W) images for each patient. Four-step procedures, mainly minimum redundancy maximum relevance (MRMR) and least absolute shrinkage and selection operator (LASSO) regression, were applied for feature selection and radiomics signature building in the training set from center I (n = 115). Combining clinical risk factors, a radiomics nomogram was then constructed. The models were then validated in the external validation set comprising 53 patients from center II. The predictive performance was determined by its calibration, discrimination, and clinical usefulness.

Results: The radiomics signature derived from the combination of T2W, ADC, and cT1W images, composed of six LN-status-related features, was significantly associated with LNM and showed better predictive performance than signatures derived from either of them alone in both sets. Encouragingly, the radiomics signature also showed good discrimination in the MRI-reported LN-negative subgroup, with AUC of 0.825 (95% CI: 0.732–0.919). The radiomics nomogram that incorporated radiomics signature and MRI-reported LN status also showed good calibration and discrimination in both sets, with AUCs of 0.865 (95% CI: 0.794–0.936) and 0.861 (95% CI: 0.733–0.990), respectively. Decision curve analysis confirmed its clinical usefulness.

Conclusion: The proposed MRI-based radiomics nomogram has good performance for predicting LN metastasis in cervical cancer and may be useful for improving clinical decision making.

Revised FIGO Staging for Cervical Cancer - A New Role for MRI

Cervical cancer is still the fourth most common malignancy in women worldwide and has a high mortality rate. The prognosis as well as the therapy depends largely on the extent of the tumor at the time of initial diagnosis. This shows the importance of correct staging of cervical cancer. In order to promote a globally uniform approach, staging of cervical cancer in the past was based on widespread examinations such as exam under anesthesia, histology from cervical conization or biopsy, systematic lymphadenectomy, cystoscopy, proctoscopy, i. v.-pyelogram and chest X-ray. However, as the primary tumor stage was often underestimated, the 2018 revised FIGO classification now permits cross-sectional imaging techniques and pathological findings to be incorporated into disease staging or an already existing stage to be adapted based on radiological findings. Thanks to its excellent soft tissue contrast, magnetic resonance imaging (MRI) is the method of choice for local-regional staging of cervical cancer, evaluating the response to treatment, detecting tumor recurrence and for follow-up examinations. It is important that radiologists interpreting pelvic MRI in case of suspected cervical cancer are familiar with the current FIGO staging system. This is the only way to determine the tumor stage as precisely as possible and thus lay the foundation for the success of therapy for patients. The aim of this review is to present the changes of the revised FIGO classification as well as to show the importance of MRI as the method of choice for local-regional tumor staging as a complement to clinical examination. KEY POINTS::   · Cervical cancer is still the world's fourth most common female cancer and has a high mortality rate.. · The FIGO classification for staging cervical cancer in the past was based on clinical and widespread examinations.. · The primary tumor stage has often been underestimated with the FIGO staging system since 2018.. · Since 2018, cross-sectional imaging techniques have been incorporated into disease staging.. · MRI is the method of choice for local-regional tumor staging, evaluation of the response to treatment, detection of tumor recurrence and possible complications.. CITATION FORMAT: · Merz J, Bossart M, Bamberg F et al. Revised FIGO Staging for Cervical Cancer - A New Role for MRI. Fortschr Röntgenstr 2020; 192: 937 - 944.

Clinicopathological risk factors in the light of the revised 2018 International Federation of Gynecology and Obstetrics staging system for early cervical cancer with staging IB: A single center retrospective study

To validate the revised 2018 International Federation of Gynecology and Obstetrics (FIGO) staging system for cervical cancer on the survival of patients who underwent radical hysterectomy for 2009 FIGO stage IB carcinomas.We retrospectively identified and reviewed 251 patients treated with radical hysterectomy for 2009 FIGO stage IB cervical carcinomas from January 2011 to December 2016. The re-staged IB cohort consisted of 2018 FIGO stage IB1 (tumor size <2 cm), IB2 (2-3.9 cm), IB3 (≥4 cm), and IIIC1p (any pelvic nodal metastasis) cervical cancer. The univariate log-rank test and multivariate Cox regression models were performed for all potential clinic pathological risk factors based on cancer stage.On re-staging the 251 patients with 2009 FIGO stage IB using the 2018 FIGO staging system, 96 patients (38.2%) had stage IB1, 109 patients (43.4%) had stage IB2, 28 patients (11.2%) had stage IB3, and 18 patients (7.2%) had stage IIIC1p. The 5-year overall survival (OS) rates of patients with 2018 FIGO stage IB1, IB2, IB3, and IIIC1p were 97.9%, 92.7%, 78.6%, and 61.1%, respectively. The 5-year progression-free survival rates were 97.9%, 92.7%,63.7%, and 20.8%, respectively. Factors significantly affecting OS and disease-free survival were 2018 FIGO stage≥IB3, histologic grade 2-3, and lymph node involvement.The revised 2018 FIGO staging system seemed to accurately reflect the survival rate, with a distinct statistical tendency for poorer 5-year disease-free survival and OS rates with increasing stage. Women with positive lymph nodes in this classification were classified as having stage IIIC disease, which can achieve more realistic survival results than the previous staging system. The prognostic discrimination of histologic grade should be considered when revising the staging system in the future.

Multiparametric MRI-Based Radiomics Nomogram for Predicting Lymph Node Metastasis in Early-Stage Cervical Cancer

BACKGROUND

Lymph node metastasis (LNM) is a critical risk factor affecting treatment strategy and prognosis in patients with early-stage cervical cancer.

PURPOSE

To establish a multiparametric MRI (mpMRI)-based radiomics nomogram for preoperatively predicting LNM status.

STUDY TYPE

Retrospective.

POPULATION

Among 233 consecutive patients, 155 patients were randomly allocated to the primary cohort and 78 patients to the validation cohort.

FIELD STRENGTH

Radiomic features were extracted from a 1.5T mpMRI scan (T₁ -weighted imaging [T₁ WI], fat-saturated T₂ -weighted imaging [FS-T₂ WI], contrast-enhanced [CE], diffusion-weighted imaging [DWI], and apparent diffusion coefficient [ADC] maps).

ASSESSMENT

The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. The area under the receiver operating characteristics curve (ROC AUC), accuracy, sensitivity, and specificity were also calculated.

STATISTICAL TESTS

The least absolute shrinkage and selection operator (LASSO) method was used for dimension reduction, feature selection, and radiomics signature building. Multivariable logistic regression analysis was used to develop the radiomics nomogram. An independent sample t-test and chi-squared test were used to compare the differences in continuous and categorical variables, respectively.

RESULTS

The radiomic signature allowed a good discrimination between the LNM and non-LNM groups, with a C-index of 0.856 (95% confidence interval [CI], 0.794-0.918) in the primary cohort and 0.883 (95% CI, 0.809-0.957) in the validation cohort. Additionally, the radiomics nomogram also had a good discriminating performance and yielded good calibration both in the primary and validation cohorts (C-index, 0.882 [95% CI, 0.827-0.937], C-index, 0.893 [95% CI, 0.822-0.964], respectively). Decision curve analysis demonstrated that the radiomics nomogram was clinically useful.

DATA CONCLUSION

A radiomics nomogram was developed by incorporating the radiomics signature with the MRI-reported LN status and FIGO stage. This nomogram might be used to facilitate the individualized prediction of LNM in patients with early-stage cervical cancer.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:885-896.

Noninvasive prediction of lymph node status for patients with early-stage cervical cancer based on radiomics features from ultrasound images

OBJECTIVE

To investigate the feasibility of a noninvasive detection of lymph node metastasis (LNM) for early-stage cervical cancer (ECC) patients with radiomics methods based on the textural features from ultrasound images.

METHODS

One hundred seventy-two ECC patients between January 2014 and September 2018 with pathologically confirmed lymph node status (LNS) and preoperative ultrasound images were retrospectively reviewed. Regions of interest (ROIs) were delineated by a senior radiologist in the ultrasound images. LIFEx was applied to extract textural features for radiomics study. Least absolute shrinkage and selection operator (LASSO) regression was applied for dimension reduction and for selection of key features. A multivariable logistic regression analysis was adopted to build the radiomics signature. The Mann-Whitney U test was applied to investigate the correlation between radiomics and LNS for both training and validation cohorts. Receiver operating characteristic (ROC) curves were applied to evaluate the accuracy of the radiomics prediction models.

RESULTS

A total of 152 radiomics features were extracted from ultrasound images, in which 6 features were significantly associated with LNS (p < 0.05). The radiomics signatures demonstrated a good discrimination between patients with LNM and non-LNM groups. The best radiomics performance model achieved an area under the curve (AUC) of 0.79 (95% confidence interval (CI), 0.71-0.88) in the training cohort and 0.77 (95% CI, 0.65-0.88) in the validation cohort.

CONCLUSIONS

The feasibility of radiomics features from ultrasound images for the prediction of LNM in ECC was investigated. This noninvasive prediction method may be used to facilitate preoperative identification of LNS in patients with ECC.

KEY POINTS

• Few studied had investigated the feasibility of radiomics based on ultrasound images for cervical cancer, even though it is the most common practice for gynecological cancer diagnosis and treatment. • The radiomics signatures based on ultrasound images demonstrated a good discrimination between patients with and without lymph node metastasis with an area under the curve (AUC) of 0.79 and 0.77 in the training and validation cohorts, respectively. • The radiomics model based on preoperative ultrasound images has the potential ability to predict lymph node status noninvasively in patients with early-state cervical cancer, so as to reduce the impact of invasive examination and to optimize the treatment choices.

Preoperative prediction of pelvic lymph nodes metastasis in early-stage cervical cancer using radiomics nomogram developed based on T2-weighted MRI and diffusion-weighted imaging

OBJECTIVE

To explore an MRI-based radiomics nomogram for preoperatively predicting of pelvic lymph node (PLN) metastasis in patients with early-stage cervical cancer (ECC).

METHODS

Ninety-six patients with ECC were enrolled in this study. All patients underwent T2WI and DWI scans before radical hysterectomy with PLN dissection surgery. Radiomics features extracted from T2WI and DWI were selected by least absolute shrinkage and selection operation regression for further radimoics signature calculation. The discrimination of this radiomics signature for PLN metastasis was then assessed using a support vector machine (SVM) model. Subsequently, a radiomics nomogram was constructed based on the radiomics signature and clinicopathologic risk factors using a multivariable logistic regression method. The performance of the radiomics nomogram for the preoperative prediction of PLN metastasis was evaluated for discrimination and calibration.

RESULTS

The radiomics signatures demonstrated a good discrimination for PLN metastasis. A radiomics signature derived from joint T2WI and DWI yielded higher AUC than the signatures derived from T2WI or DWI alone. The radiomics nomogram integrating the radiomics signature with clinicopathologic risk factors showed a significant improvement over the nomogram based only on clinicopathologic risk factors in the primary cohort(C-index, 0.893 vs. 0.616; P = 4.311×10^-5) and validation cohort(C-index, 0.922 vs. 0.799; P = 3.412 ×10^-2).The calibration curves also showed good agreement.

CONCLUSIONS

The radiomics nomogram based on joint T2WI and DWI demonstrated an improved prediction ability for PLN metastasis in ECC. This noninvasive and convenient tool may be used to facilitate preoperative identification of PLN metastasis in patients with ECC.

Neo-adjuvant treatment of adenocarcinoma and squamous cell carcinoma of the cervix results in significantly different pathological complete response rates

Background

Previous studies on cervical cancer reported a worse outcome for adenocarcinoma (AC) compared with squamous cell carcinoma (SCC). Nevertheless, standard treatment remains identical. Insight in the impact of histological types on biological behavior and pathological complete response rates might result in a treatment paradigm shift.

Methods

Clinicopathological characteristics, survival rates and relapse patterns were compared between AC (n = 36) and SCC (n = 143) cervical cancer patients. Pathological response to treatment was evaluated in the patient subgroup treated with neo-adjuvant chemoradiation followed by surgery (NA-CRT group; n = 84).

Results

In the entire cohort, 5y Disease Specific Survival (DSS) was 97.1 and 84% for AC and SCC respectively (p = 0.150). In the NA-CRT group 5y DSS was 100 and 75.5% for AC and SCC respectively (p = 0.059). Relapse patterns did not differ significantly between AC and SCC in the entire cohort, or in the NA-CRT group. Adenocarcinoma patients treated with NA-CRT showed significantly less pathological complete response compared with SCC patients (AC = 7%, SCC = 43%, p = 0.027).

Conclusions

There were no statistically significant differences regarding relapse and DSS rates between SCC and AC in the entire cohort, or the NA-CRT group. However, a trend to better 5y DSS of AC in the NA-CRT group was observed. This analysis showed significant differences in treatment responses after NA-CRT: patients with AC responded remarkably less to chemoradiation, resulting in a significantly lower pathological complete response rate. These findings imply a need for a paradigm shift in the treatment of cervical AC patients.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5007-0) contains supplementary material, which is available to authorized users.

Progress in the Study of Lymph Node Metastasis in Early-stage Cervical Cancer

Spread into regional lymph node is the major route of metastasis in cervical cancer. Although lymph node status is not involved in the International Federation of Gynecology and Obstetrics staging system of uterine cervical cancer, the presence or absence of lymph node metastasis provides important information for prognosis and treatment. In this review, we have attempted to focus on the incidence and patterns of lymph node metastasis, and the issues surrounding surgical assessment of lymph nodes. In addition, the preoperative prediction of lymph node status, as well as the intraoperative assessment by sentinel nodes will be reviewed. Finally, lymph node micrometastasis also will be discussed.

Isolated para-aortic lymph node metastasis in FIGO stage IA2-IB2 carcinoma of the cervix: Revisiting the role of surgical assessment

OBJECTIVES

To investigate the utility of para-aortic lymph node dissection among women undergoing radical hysterectomy and pelvic lymph adenectomy for FIGO Stage IA2-IB2 cervical cancer using the National Cancer Database (NCDB).

METHODS

We identified patients with stage IA2-IB2 squamous cell, adenosquamous, or adenocarcinoma of the cervix diagnosed 2011-2014 in the NCDB. The primary outcome was the negative predictive value of histologically assessed pelvic lymph node status for para-aortic lymph node status among women undergoing pelvic and para-aortic lymph node dissection. We calculated probability of para-aortic lymph node metastasis conditional on pelvic lymph node status. Finally, we compared overall survival between patients undergoing para-aortic lymph node dissection and those in whom this procedure was omitted.

RESULTS

A total of 3212 patients met study inclusion criteria, of whom 994 (30.9%) underwent para-aortic lymph node dissection. In this group, the risk of isolated para-aortic metastasis was 0.11%. The negative predictive value of surgically assessed pelvic lymph nodes to predict para-aortic lymph node status was 99.9% (95% CI 99.9-99.9). Among 93 patients with pelvic lymph node metastasis, 18 (19.4%) had concurrent para-aortic lymph node metastasis. There was no difference in overall survival between women undergoing pelvic and para-aortic lymph node dissection compared with those undergoing pelvic lymphadenectomy only (p = 0.69).

CONCLUSIONS

In patients undergoing radical hysterectomy and pelvic lymphadenectomy for stage IA2-IB2 cervical cancer, para-aortic lymph node dissection is not warranted based on the low risk of isolated metastatic disease, and lack of survival benefit associated with the procedure.

Identification of lncRNAs by microarray analysis reveals the potential role of lncRNAs in cervical cancer pathogenesis

Long non-coding RNAs (lncRNAs) have been acknowledged to serve a significant role in cancer biology and abnormal expression in tumors is frequently observed. However, their mechanisms in cervical cancer remain unclear. With a genome-wide analysis of lncRNA expression in cervical cancer tissues, the present study aimed to identify lncRNA targets for the further study of cervical cancer. To elucidate the specific role of lncRNAs in the pathogenesis of this type of cancer, 6 cervical cancer samples paired with normal cervical tissues were obtained. Expression profiles of lncRNAs and mRNAs were constructed through microarray analysis and confirmed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) methods. Gene Ontology and pathway enrichment analyses were performed with computational methods. On the basis of correlations between the differential expression levels of lncRNAs and mRNAs, a coding-non-coding gene co-expression network (CNC network) was established. The differential expression of 5,844 lncRNAs and 4,436 mRNAs were discovered in cervical cancer samples compared with normal cervical tissues. Among the differentially expressed lncRNAs, 14 were chosen at random and validated by RT-qPCR; the majority of the results measured were consistent with the microarray results. Furthermore, the lncRNA ENST00000551152 was found to be upregulated and TCO. NS_00001368 lncRNA was downregulated in cervical cancer cell lines. The CNC network included 592 network nodes and 934 associations between 12 lncRNAs and 580 protein-coding genes, indicating that one lncRNA could act on a maximum of 141 coding genes, and that one coding gene may corresponded with a maximum of 5 lncRNAs. Overall, the present study has provided a complete expression profile of lncRNAs and mRNAs in cervical cancer, which may now be used to establish a solid foundation for cervical cancer research. These results may provide significant information for improving the understanding of the pathogenesis of cervical cancer and indicate potential therapeutic targets.

Development and validation of a surgical-pathologic staging and scoring system for cervical cancer

Background

Most cervical cancer patients worldwide receive surgical treatments, and yet the current International Federation of Gynecology and Obstetrics (FIGO) staging system do not consider surgical-pathologic data. We propose a more comprehensive and prognostically valuable surgical-pathologic staging and scoring system (SPSs).

Methods

Records from 4,220 eligible cervical cancer cases (Cohort 1) were screened for surgical-pathologic risk factors. We constructed a surgical-pathologic staging and SPSs, which was subsequently validated in a prospective study of 1,104 cervical cancer patients (Cohort 2).

Results

In Cohort 1, seven independent risk factors were associated with patient outcome: lymph node metastasis (LNM), parametrial involvement, histological type, grade, tumor size, stromal invasion, and lymph-vascular space invasion (LVSI). The FIGO staging system was revised and expanded into a surgical-pathologic staging system by including additional criteria of LNM, stromal invasion, and LVSI. LNM was subdivided into three categories based on number and location of metastases. Inclusion of all seven prognostic risk factors improves practical applicability. Patients were stratified into three SPSs risk categories: zero-, low-, and high-score with scores of 0, 1 to 3, and ≥4 (P=1.08E-45; P=6.15E-55). In Cohort 2, 5-year overall survival (OS) and disease-free survival (DFS) outcomes decreased with increased SPSs scores (P=9.04E-15; P=3.23E-16), validating the approach. Surgical-pathologic staging and SPSs show greater homogeneity and discriminatory utility than FIGO staging.

Conclusions

Surgical-pathologic staging and SPSs improve characterization of tumor severity and disease invasion, which may more accurately predict outcome and guide postoperative therapy.

Predictive factors of para-aortic lymph nodes metastasis in cervical cancer patients: a retrospective analysis based on 723 para-aortic lymphadenectomy cases

Para-aortic lymph node (PALN) dissection is optional and controversial in patients with stage IB1-IIA2 cervical cancer. This retrospective study investigated PALN involvement patterns and evaluated preoperative clinical factors. A total of 723 consecutive FIGO stage IB1-IIA2 cervical cancer patients were included in the study. All patients underwent radical hysterectomy/radical trachelectomy, pelvic lymph node dissection, and PALN dissection. PALN metastasis was found in 101 (14.0%) patients, and the positive PALN rates of stage IB1, IB2, IIA1, and IIA2 were 8.4%, 11.1%, 17.2% and 21.7%, respectively. A multivariate model suggested age > 46 years (OR: 1.67, 95% confidence interval (CI): 1.08-2.58), tumor size > 3.5 cm (OR: 1.79, 95% CI: 1.12-2.87), and FIGO stage IIA (vs. IB) (OR: 1.97, 95% CI: 1.25-3.11) all positively correlated with PALN metastasis. When squamous cervical cancer cases were categorically analyzed, a multivariate model indicated age > 46 years (OR: 1.67, 95% CI: 1.00-2.80), FIGO stage IIA (vs. IB) (OR: 1.76, 95% CI: 1.02-3.02), and squamous cell carcinoma antigen (SCCA) > 6.5 ng/ml (OR: 5.20, 95% CI: 3.07-8.81) all positively correlated with PALN metastasis. Age, tumor size, and FIGO stage correlated with PALN metastasis in cervical cancer, while age, FIGO stage, and SCCA level were predictive in squamous cell carcinoma.

Classical and non-classical HLA class I aberrations in primary cervical squamous- and adenocarcinomas and paired lymph node metastases

Background

Tumors avoid destruction by cytotoxic T cells (CTL) and natural killer (NK) cells by downregulation of classical human leukocyte antigens (HLA) and overexpression of non-classical HLA. This is the first study to investigate HLA expression in relation to histology (squamous cell carcinoma (SCC) vs. adenocarcinoma (AC)), clinicopathological parameters and survival in a large cervical cancer patient cohort.

Methods

Classical (HLA-A and HLA-B/C)- and non-classical HLA molecules (HLA-E and HLA-G) were studied on primary tumors and paired lymph node (LN) metastases from cervical cancer patients (n = 136) by immunohistochemistry. The Chi² test was used for the comparison of clinicopathological characteristics between SCC and AC patients. The Related-Samples Wilcoxon Signed Rank test was used to compare HLA expression between the primary tumor and metastasis in LN. Patient survival rates were analyzed by Kaplan-Meier curves and Log Rank test. The Mann-Whitney U Test was used to compare the distribution of HLA class I expression between SCC and AC.

Results

Decreased expression of HLA-A (SCC P < 0.001), HLA-B/C (SCC P < 0.01; AC P < 0.01) and total classical HLA (SCC P < 0.001; AC P = 0.02) was apparent in metastatic tumor cells compared to the primary tumor. In primary SCC, there was a clear trend towards complete loss of HLA-A (P = 0.05). SCC metastases showed more complete loss of HLA-A, while AC metastases showed more complete loss of HLA-B/C (P = 0.04). In addition, tumor size and parametrium involvement were also related to aberrant HLA class I expression. No significant associations between HLA expression and disease-specific (DSS) or disease-free survival (DFS) were found in this advanced disease cohort. However, in the SCC group, samples showing loss of HLA-A or loss of total classical HLA but positive for HLA-G were linked to poor patient survival (DSS P = 0.001 and P = 0.01; DFS P = 0.003 and P = 0.01, for HLA-A and total classical HLA, respectively).

Conclusion

These results strengthen the idea of tumor immune escape variants leading to metastasis. Moreover, SCC tumors showing downregulation of HLA-A or total classical HLA in combination with HLA-G expression had poor prognosis. Our findings warrant further analysis of HLA expression as a biomarker for patient selection for CTL- and NK- cell based immunotherapeutic intervention.

Electronic supplementary material

The online version of this article (doi:10.1186/s40425-016-0184-3) contains supplementary material, which is available to authorized users.

Tripartite motif containing 62 is a novel prognostic marker and suppresses tumor metastasis via c-Jun/Slug signaling-mediated epithelial-mesenchymal transition in cervical cancer

Background

TRIM62 (tripartite motif containing 62) has been found to act as a tumor suppressor of several cancers. However, its precise biological role and related mechanism remain unknown in cervical cancer (CC).

Methods

Quantitative Real-time PCR and western blot were adopted to detect the mRNA and protein expression level of TRIM62 in both human CC cell lines and tissues. Immunohistochemistry was used to measure the TRIM62 expression in 30 normal cervical and 189 CC tissues. Univariate and multivariate Cox regression analyses and Kaplan–Meier survival analyses performed to investigate the association between TRIM62 expression and CC patients’ prognosis. The effect of TRIM62 on CC growth and metastasis was studied in vitro and in vivo. Multi-pathway reporter array were utilized to identify the potential signaling manipulated by TRIM62.

Results

TRIM62 was frequently down-regulated in both human CC cells and tissues. Low expression of TRIM62 in CC tissues was associated with aggressive clinicopathological features of CC patients. In addition, TRIM62 was also an independent poor prognostic factor for overall and disease-free survival of CC patients after surgery. Moreover, enforced expression of TRIM62 in CC cells significantly inhibited their abilities of proliferation, migration and invasion in vitro. Besides, subcutaneous xenograft tumor model and xenograft mouse metastatic model respectively displayed that TRIM62 impeded the growth and metastasis of CC in vivo. Furthermore, mechanism study exhibited that TRIM62 could suppress epithelial-mesenchymal transition (EMT) by inhibiting c-Jun/Slug signaling. The inhibitory role of TRIM62 in tumor proliferation might be through regulating cell cycle related proteins CyclinD1 and P27 by targeting c-Jun.

Conclusion

TRIM62 is a potential prognostic biomarker in CC and suppresses metastasis of CC via inhibiting c-Jun/Slug signaling-mediated EMT.

Electronic supplementary material

The online version of this article (doi:10.1186/s13046-016-0445-5) contains supplementary material, which is available to authorized users.

Metastasis-Associated in Colon Cancer-1 Associates With Poor Prognosis and Promotes Cell Invasion and Angiogenesis in Human Cervical Cancer

Supplemental digital content is available in the text.

Objective

The aim of this study is to investigate the clinicopathologic significance and potential role of metastasis-associated in colon cancer-1 (MACC1) in the progression of cervical cancer.

Methods

MACC1 expression was examined in cervical cancer cell lines, 6 matched cervical cancer tissues, and adjacent noncancerous tissues using Western blotting and real-time reverse transcriptase polymerase chain reaction. MACC1 protein expression and localization were determined in 181 paraffin-embedded archived cervical cancer samples using immunohistochemistry. Statistical analyses were applied to evaluate the clinicopathologic significance. The effects of MACC1 on cell migration, invasion, and angiogenesis were examined using migration assay, wound healing assay, 3-dimensional morphogenesis assay, and chicken chorioallantoic membrane assay. Western blotting was performed to examine the impact of MACC1 on the Akt and nuclear factor κB signaling pathways.

Results

Both protein and messenger RNA levels of MACC1 was up-regulated in cervical cancer cell lines and cervical cancer tissues, as compared with normal tissues. High MACC1 expression was detected in 96 (53%) of 181 of the cervical cancer tissues. In addition, high MACC1 expression correlated significantly with aggressiveness of cervical cancer, including International Federation of Gynecology and Obstetric stage (P = 0.001), pelvic lymph node metastasis (P = 0.004), recurrence (P = 0.037), and poor survival (P = 0.001). Moreover, enforced expression of MACC1 in cervical cancer cell lines significantly enhanced cell migration, invasion, and angiogenesis. Conversely, knockdown of MACC1 caused an inhibition of cell migration, invasion, and angiogenesis. Up-regulation of MACC1 increased, but knockdown of MACC1 decreased the expression of matrix metalloproteinase-2 and matrix metalloproteinase-9. Furthermore, enforced expression of MACC1 could enhance, but knockdown of MACC1 could reduce AKT and nuclear factor κB pathway activity.

Conclusions

Our findings suggest that MACC1 protein, as a valuable marker of cervical cancer prognosis, plays an important role in the progression of human cervical cancer cells.

Nonsurgical management of cervical cancer: locally advanced, recurrent, and metastatic disease, survivorship, and beyond

Despite the declining incidence of cervical cancer as a result of the introduction of screening programs, globally it remains a leading cause of cancer-related death in women. Outcomes for patients who are diagnosed with anything but early-stage disease remain poor. Here we examine emerging strategies to improve the treatment of locally advanced disease. We discuss emerging biologic data, which are informing our investigation of new therapeutic interventions in persistent, recurrent, and metastatic cervical cancer. We recognize the importance of interventions to improve quality of life and to prevent long-term sequelae in women undergoing treatment. Finally, and perhaps most importantly, we recognize the need for global collaboration and advocacy to improve the outcome for all women at risk of and diagnosed with this disease.