Adenocarcinoma histology is a poor prognostic factor in locally advanced cervical cancer

Computed tomography-based radiomics modeling to predict patient overall survival in cervical cancer with intensity-modulated radiotherapy combined with concurrent chemotherapy

ObjectiveThe objective of this study was to develop a predictive model combining radiomic characteristics and clinical features to forecast overall survival in cervical cancer patients treated with intensity-modulated radiotherapy and concurrent chemotherapy.MethodsIn this retrospective observational study, 159 patients were divided into a training group (n = 95) and a validation group (n = 64). Radiomic characteristics were extracted from contrast-enhanced computed tomography scans. The least absolute shrinkage and selection operator regression analysis was used to filter the extracted radiomic characteristics and reduce the dimensionality of the data. A radiomic score was calculated from the selected features, and multivariate Cox regression models were established to analyze overall survival. A nomogram combining radiomic score and clinical features was developed, and its reliability was assessed using the area under the receiver operating characteristic curve.ResultsFour radiomic characteristics and two clinical features were extracted for overall survival analysis. A nomogram combining these factors was developed and validated, showing good performance with a high C-index. Patients were categorized as low-risk or high-risk for overall survival based on a cut-off value.ConclusionsOur model combining computed tomography-extracted radiomic characteristics and clinical features shows good potential for evaluating overall survival in cervical cancer patients treated with intensity-modulated radiotherapy and concurrent chemotherapy.

Prognostic Factors for Cervical Cancer in Asian Populations: A Scoping Review of Research From 2013 to 2023

Cervical cancer is the fourth most common cancer among women worldwide, with particularly high incidence and mortality rates in low- and middle-income countries, with Asia reporting the highest number of cases in 2022. Despite this significant burden, the prognostic factors specific to Asian populations remain underexplored. This scoping review aimed to identify and evaluate prognostic factors associated with cervical cancer outcomes in Asia, focusing on clinical, socio-demographic, and treatment-related variables. The review followed the Arksey and O'Malley framework and included 44 studies published between 2013 and 2023. The majority of research was concentrated in East Asia, particularly in China, Japan, and South Korea. Key prognostic factors affecting overall survival and disease-free survival included tumor size, histology, age, lymphovascular invasion, and lymph node metastasis. Non-squamous cell carcinoma histology, especially adenocarcinoma, was consistently linked to poorer outcomes. Older age and medical comorbidities, such as anemia and diabetes, also negatively impacted survival. Treatment-related factors, though less frequently reported, demonstrated the significance of adjuvant therapy, chemotherapy, and treatment intensity in improving outcomes. This review underscores the complexity of cervical cancer prognosis in Asian populations and highlights the need for targeted research and region-specific interventions to address the rising incidence of cervical cancer. It also highlights the scarcity of research on cervical cancer prognostic factors in West, Central, and South Asian countries. Future research should aim to address the gaps in understanding treatment-related factors and explore the potential for region-specific interventions to improve outcomes in cervical cancer across Asia.

Survival disparities in non-Hispanic Black and White cervical cancer patients vary by histology and are largely explained by modifiable factors

PURPOSE

We investigated racial disparities in survival by histology in cervical cancer and examined the factors contributing to these disparities.

METHODS

Non-Hispanic Black and non-Hispanic White (hereafter known as Black and White) patients with stage I-IV cervical carcinoma diagnosed between 2004 and 2017 in the National Cancer Database were studied. Survival differences were compared using Cox modeling to estimate hazard ratio (HR) or adjusted HR (AHR) and 95% confidence interval (CI). The contribution of demographic, socioeconomic and clinical factors to the Black vs White differences in survival was estimated after applying propensity score weighting in patients with squamous cell carcinoma (SCC) or adenocarcinoma (AC).

RESULTS

This study included 10,111 Black and 43,252 White patients with cervical cancer. Black patients had worse survival than White cervical cancer patients (HR = 1.40, 95% CI = 1.35-1.45). Survival disparities between Black and White patients varied significantly by histology (HR = 1.20, 95% CI = 1.15-1.24 for SCC; HR = 2.32, 95% CI = 2.12-2.54 for AC, interaction p < 0.0001). After balancing the selected demographic, socioeconomic and clinical factors, survival in Black vs. White patients was no longer different in those with SCC (AHR = 1.01, 95% CI 0.97-1.06) or AC (AHR = 1.09, 95% CI = 0.96-1.24). In SCC, the largest contributors to survival disparities were neighborhood income and insurance. In AC, age was the most significant contributor followed by neighborhood income, insurance, and stage. Diagnosis of AC (but not SCC) at ≥65 years old was more common in Black vs. White patients (26% vs. 13%, respectively).

CONCLUSIONS

Histology matters in survival disparities and diagnosis at ≥65 years old between Black and White cervical cancer patients. These disparities were largely explained by modifiable factors.

PAX1 hypomethylation as a prognostic biomarker for radioresistance of cervical cancer

BACKGROUND

PAX1 gene methylation plays an important role in the development of cervical cancer. However, its prognostic value after radiotherapy for locally advanced cervical cancer is unknown, so this study aimed to investigate the value of PAX1 gene methylation for predicting the sensitivity of radiotherapy for cervical cancer.

METHODS

We selected 125 patients with primary cervical cancer who underwent concurrent chemo-radiotherapy as the study population, quantitative methylation-specific polymerase chain reaction (QMSP) was used for detecting PAX1 methylation status of cervical exfoliated cells. Logistic regression model was used to analyze the risk factors associated with the short-term efficacy and to establish a prediction model of radiotherapy sensitivity based on PAX1 gene methylation. Cell viability after radiation of Hela and SiHa cells transfected with PAX1 or control vector was evaluated by CCK8. Furthermore, RNA-Seq analyses identified different expressed genes (DEGs) in PAX1 overexpressed SiHa cells. Gene Ontology (GO) and pathway enrichment analysis was carried out to determine the biological function of DEGs.

RESULTS

PAX1 methylation level was associated with HPV16/18-positive rate. PAX1 hypomethylation was found to be a risk factor for tumor residual after chemo-radiotherapy. A nomogram containing the risk factors for PAX1 methylation status, lymph node metastasis, pathological type and tumor size was further constructed to predict the probability of tumor residual after chemo-radiotherapy (AUC = 0.823, 95% CI 0.736-0.910). High PAX1 protein level was more likely to cause radioresistance in both Hela and SiHa cells. Transcriptomic sequencing of PAX1 overexpressed and control cells identified 615 differentially expressed genes, and GO enrichment analysis suggested that PAX1 may be involved in the regulation of signaling receptor activity and response to viruses.

CONCLUSION

PAX1 hypomethylation status could be used as a promising biomarker to predict radioresistance in cervical cancer. This further provides a new idea for the individualized treatment strategy of simultaneous radiotherapy for cervical cancer.

Racial and Ethnic Disparities in Cervical Cancer Incidence, Survival, and Mortality by Histologic Subtype

PURPOSE

We conducted an integrated population-based analysis of histologic subtype-specific cervical cancer incidence, survival, and incidence-based mortality by race and ethnicity, with correction for hysterectomy prevalence.

METHODS

Using the SEER 21 and 18 registries, we selected primary cases of malignant cervical cancer diagnosed among women ≥ 15 years. We evaluated age-adjusted incidence rates among cases diagnosed between 2000 and 2018 (SEER21) and incidence-based mortality rates among deaths from 2005 to 2018 (SEER18), per 100,000 person-years. Rates were stratified by histologic subtype and race/ethnicity (incidence and mortality), and stage, age at diagnosis, and county-level measures of social determinants of health (incidence only). Incidence and mortality rates were corrected for hysterectomy using data from the Behavioral Risk Factor Surveillance System. We estimated 5-year relative survival by histologic subtype and stratified by stage at diagnosis.

RESULTS

Incidence rates of cervical squamous cell carcinoma were highest in Black and Hispanic women, while incidence rates of cervical adenocarcinoma (ADC) were highest among Hispanic and White women, particularly for localized ADC. County-level income and education variables were inversely associated with squamous cell carcinoma incidence rates in all racial and ethnic groups but had less influence on ADC incidence rates. Black women had the highest overall mortality rates and lowest 5-year relative survival, irrespective of subtype and stage. Disparities in survival were particularly pronounced for Black women with regional and distant ADC, compared with other racial/ethnic groups.

CONCLUSION

Although Black women are less likely to be diagnosed with ADC compared with all other racial/ethnic groups, they experience the highest mortality rates for this subtype, likely attributed to the poor survival observed for Black women with regional and distant ADC.

Identification and validation of serum tumor-markers based nomogram to predict the prognostic value of patients with cervical adenocarcinoma

Unlike cervical squamous cell carcinoma (CSCC), no uniform standard has been implemented to identify serum biomarkers for adenocarcinoma of the cervix (ADC). In the present study, we aimed to determine whether pretreatment serum tumor markers were of prognostic value in patients with ADC and constructed and validated the novel accurate nomogram for stratifying the risk groups. Patients with ADC who underwent curative hysterectomy or definitive radiotherapy from January 2011 to December 2016 were included. Significant factors independently predicting prognosis were selected by univariate multivariate Cox proportional hazard regression models and adopted for constructing the overall survival (OS) and progression-free survival (PFS) prediction nomograms. The receiver operating characteristic (ROC) curve and concordance index (C-index) with calibration curve was used to determine the accuracy of the nomogram in the prediction and determination of performance. We enrolled a total of 295 samples and randomized them as the training set (n = 207) or validation set (n = 88). Federation of Gynecology and Obstetrics Staging Guidelines (FIGO) stage, para-aortic lymph node (PALN), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), and HCG-β were assessed as the common factors independently predicting OS and PFS. For our constructed nomograms, its C-index values in OS and PFS prediction were 0.896 (95% CI, 0.879-0.913) and 0.895 (95% CI, 0.878-0.912) in training set, whereas 0.845 (95% CI:0.796-0.894) and 0.846 (95% CI:0.797-0.895) in validation set. ROC and calibration curves for our constructed nomograms predicted the excellent consistency of nomogram-predicted values with real measurements of 1-, 3-, and 5-year OS. We explored novel prognostic serum tumor markers of ADC and constructed effective nomograms comprising NSE, HCG-β, FIGO stage, PALN, and CEA, which could estimate OS and PFS for patients with ADC. These nomograms performed well in predicting patient prognosis, which was a potentially useful approach for stratifying ADC risk, thus contributing to clinical decision-making and individualized follow-up planning.

Tumor histology is an independent prognostic factor in locally advanced cervical carcinoma: A retrospective study

Background

Even with different histologic origins, squamous cell carcinoma (SCC) and adenocarcinoma (AC) are considered a single entity, and the first-line treatment is the same. Locally advanced disease at the diagnosis of cervical cancer is the most important prognostic factor, the recurrence rate is high, making it necessary to evaluate prognostic factors other than clinical or radiological staging; histology could be one of them but continues to be controversial. The aim of this study was to evaluate tumor histology as a prognostic factor in terms of treatment outcomes, disease-free survival (DFS) and overall survival (OS) in a retrospective cohort of patients with Locally Advanced Cervical Carcinoma (LACC).

Methods

The records of 1291patients with LACC were reviewed, all of them were treated with 45–50 Gy of external beam radiotherapy with concurrent chemotherapy and brachytherapy. A descriptive and comparative analysis was conducted. Treatment response was analyzed by the chi-square test; DFS and OS were calculated for each histology with the Kaplan–Meier method and compared with the log-rank test; and the Cox model was applied for the multivariate analysis.

Results

We included 1291 patients with LACC treated from 2005 to 2014, of which 1154 (89·4%) had SCC and 137 (10·6%) had AC. Complete response to treatment was achieved in 933 (80·8%) patients with SCC and 113 (82·5%) patients with AC. Recurrence of the disease was reported in 29·9% of SCC patients and 31·9% of AC patients. Five-year DFS was 70% for SCC and 62·2% for AC. The five-year OS rates were 74·3% and 60% for SCC and AC, respectively. The mean DFS was 48·8 months for SCC vs 46·10 for AC (p = 0·043), the mean OS was 50·8 for SCC and 47·0 for AC (p = 0·002).

Conclusion

Our findings support the hypothesis that SCC and AC are different clinical entities.

Trial Registration

NCT04537273.

A Combination Analysis of IVIM-DWI Biomarkers and T2WI-Based Texture Features for Tumor Differentiation Grade of Cervical Squamous Cell Carcinoma

Purpose

To explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and texture analysis on T2-weighted imaging (T2WI) for evaluating pathological differentiation of cervical squamous cell carcinoma.

Method

This retrospective study included a total of 138 patients with pathologically confirmed poor/moderate/well-differentiated (71/49/18) who underwent conventional MRI and IVIM-DWI scans. The values of ADC, D, D ∗ , and f and 58 T2WI-based texture features (18 histogram features, 24 gray-level co-occurrence matrix features, and 16 gray-level run length matrix features) were obtained. Multiple comparison, correlation, and regression analyses were used.

Results

For IVIM-DWI, the ADC, D, D ∗ , and f were significantly different among the three groups (p < 0.05). ADC, D, and D ∗ were positively correlated with pathological differentiation (r = 0.262, 0.401, 0.401; p < 0.05), while the correlation was negative for f (r = -0.221; p < 0.05). The comparison of 52 parameters of texture analysis on T2WI reached statistically significant levels (p < 0.05). Multivariate logistic regression analysis incorporated significant IVIM-DWI, and texture features on T2WI showed good diagnostic performance both in the four differentiation groups (poorly vs. moderately, area under the curve(AUC) = 0.797; moderately vs. well, AUC = 0.954; poorly vs. moderately and well, AUC = 0.795; and well vs. moderately and poorly, AUC = 0.952). The AUCs of each parameters alone were smaller than that of each regression model (0.503∼0.684, 0.547∼0.805, 0.511∼0.712, and 0.636∼0.792, respectively; pairwise comparison of ROC curves between regression model and individual variables, p < 0.05).

Conclusions

IVIM-DWI biomarkers and T2WI-based texture features had potential to evaluate the pathological differentiation of cervical squamous cell carcinoma. The combination of IVIM-DWI with texture analysis improved the predictive performance.

A novel lncRNA-mRNA-miRNA signature predicts recurrence and disease-free survival in cervical cancer

Cervical cancer (CC) patients have a poor prognosis due to the high recurrence rate. However, there are still no effective molecular signatures to predict the recurrence and survival rates for CC patients. Here, we aimed to identify a novel signature based on three types of RNAs [messenger RNA (mRNAs), microRNA (miRNAs), and long non-coding RNAs (lncRNAs)]. A total of 763 differentially expressed mRNAs (DEMs), 46 lncRNAs (DELs), and 22 miRNAs (DEMis) were identified between recurrent and non-recurrent CC patients using the datasets collected from the Gene Expression Omnibus (GSE44001; training) and The Cancer Genome Atlas (RNA- and miRNA-sequencing; testing) databases. A competing endogenous RNA network was constructed based on 23 DELs, 15 DEMis, and 426 DEMs, in which 15 DELs, 13 DEMis, and 390 DEMs were significantly associated with disease-free survival (DFS). A prognostic signature, containing two DELs (CD27-AS1, LINC00683), three DEMis (hsa-miR-146b, hsa-miR-1238, hsa-miR-4648), and seven DEMs (ARMC7, ATRX, FBLN5, GHR, MYLIP, OXCT1, RAB39A), was developed after LASSO analysis. The built risk score could effectively separate the recurrence rate and DFS of patients in the high- and low-risk groups. The accuracy of this risk score model for DFS prediction was better than that of the FIGO (International Federation of Gynecology and Obstetrics) staging (the area under receiver operating characteristic curve: training, 0.954 vs 0.501; testing, 0.882 vs 0.656; and C-index: training, 0.855 vs 0.539; testing, 0.711 vs 0.508). In conclusion, the high predictive accuracy of our signature for DFS indicated its potential clinical application value for CC patients.

Does adenocarcinoma have a worse prognosis than squamous cell carcinoma in patients with cervical cancer? A real-world study with a propensity score matching analysis

Objective

To compare survival outcomes between cervical adenocarcinoma (ADC) and squamous cell carcinoma (SCC) using a propensity score matching (PSM) analysis based on the Surveillance, Epidemiology, and End Results (SEER) Program.

Methods

Patients diagnosed with cervical cancer between 1998 and 2016 were identified from the SEER database. The Kaplan-Meier method and Cox regression analysis were used to analyze survival. A subgroup analysis of overall survival (OS) between patients with ADC and SCC was performed after the 1:1 PSM analysis.

Results

Of the 33,148 patients, 24,591 (79.19%) had SCC and 8,557 (25.81%) had ADC. In the unmatched cohort, after adjustment in multivariate analysis, patients with ADC had a worse prognosis than patients with SCC (hazard ratio [HR]=1.12; 95% confidence interval [CI]=1.07–1.18; p<0.001). In the propensity matched cohort, Kaplan-Meier analysis and subgroup analysis showed that ADC was associated with a worse prognosis than SCC (p=0.001). An analysis stratified by SEER stage revealed a worse prognosis for patients with ADC patients presenting with a regional disease than patients with SCC (HR=1.24; 95% CI=1.14–1.36 p<0.001), but no statistically significant differences were observed between the localized disease (HR=0.97; 95% CI=0.86–1.10; p=0.664) and distant disease (HR=1.09; 95% CI=0.97–1.22; p=0.162) subgroups.

Conclusion

The significant differences in survival outcomes between patients with cervical ADC and SCC were only observed in the regional disease subgroup, but not in the localized disease and distant disease subgroups.

Post-radiotherapy hysterectomy does not benefit females with cervical adenocarcinoma

Cervical adenocarcinoma is associated with a poor prognosis, which may be caused by the infiltrative growth pattern and metastasis of tumor cells. There is a lack of consensus on hysterectomy after radiotherapy for the improvement of selected cases. The present study aimed to assess the oncological outcome of post-radiotherapy hysterectomy in females with cervical adenocarcinoma. A total of 39 females with cervical adenocarcinoma at stages IB1 to IIIB, managed primarily with radiotherapy with complete response, and underwent extrafascial hysterectomy as consolidation therapy between 1988 to 2015 were studied. Surgery complications and residual disease were evaluated. A comparison group was constructed, comprising 41 females with cervical adenocarcinoma managed with exclusive radiotherapy or chemoradiotherapy demonstrating complete response, without surgery. Descriptive and survival analysis was performed. The groups were comparable in terms of age, cancer stage, radiotherapy (dose and duration) and follow-up, although 67% of hysterectomies were performed prior to 2002 and 46% of the radiotherapy group received chemoradiation. Late complications were similar. There were nine recurrences (23%) in the case series and 10 recurrences (24%) in the radiotherapy group. Residual disease was detected in 56% (22/39) of uterine specimens, of which 12 were up to 10 mm. Residual disease was associated with recurrence (31% vs. 6%, P=0.028). The overall survival rate was 75% for the case series vs. 88% for the radiotherapy group (P=0.579), and the disease-free survival rate was 79-80% for both. Removal of residual disease by hysterectomy did not improve the overall survival rate (P=0.283) and disease-free survival rate (P=0.072). Post-radiotherapy hysterectomy in cervical adenocarcinoma is a feasible procedure with acceptable complications, however, it did not bring relevant benefits in recurrences, disease-free survival, and overall survival rates.

Calculating the overall survival probability in patients with cervical cancer: a nomogram and decision curve analysis-based study

BACKGROUND

Cervical cancer has long been a common malignance troubling women. However, there are few studies developing nomogram with comprehensive factors for the prognosis of cervical cancer. Hence, we aimed to build a nomogram to calculate the overall survival (OS) probability in patients with cervical cancer.

METHODS

Data of 9876 female patients in SEER database and diagnosed as cervical cancer during 2010-2015, was retrospectively analyzed. Univariate and multivariate Cox proportional hazard regression model were applied to select predicted factors and a nomogram was developed to visualize the prediction model. The nomogram was compared with the FIGO stage prediction model. Harrell's C-index, receiver operating curve, calibration plot and decision curve analysis were used to assess the discrimination, accuracy, calibration and clinical utility of the prediction models.

RESULT

Eleven independent prognostic variables, including age at diagnosis, race, marital status at diagnosis, grade, histology, tumor size, FIGO stage, primary site surgery, regional lymph node surgery, radiotherapy and chemotherapy, were used to build the nomogram. The C-index of the nomogram was 0.826 (95% CI: 0.818 to 0.834), which was better than that of the FIGO stage prediction model (C-index: 0.785, 95% CI: 0.776 to 0.793). Calibration plot of the nomogram was well fitted in 3-year overall OS prediction, but overfitting in 5-year OS prediction. The net benefit of the nomogram was higher than the FIGO prediction model.

CONCLUSION

A clinical useful nomogram for calculating the overall survival probability in cervical cancer patients was developed. It performed better than the FIGO stage prediction model and could help clinicians to choose optimal treatments and precisely predict prognosis in clinical care and research.

A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction

Aims. This study is aimed at identifying a prognostic signature for cervical cancer. Main Methods. The gene expression data and clinical information of cervical cancer and normal cervical tissues were acquired from The Cancer Genome Atlas and from three datasets of the Gene Expression Omnibus database. DESeq2 and Limma were employed to screen differentially expressed genes (DEGs). The overlapping DEGs among all datasets were considered the final DEGs. Then, the functional enrichment analysis was performed. Moreover, the Cox proportional hazards regression was performed to establish a prognostic signature of the DEGs. The Kaplan-Meier analysis was applied to test the model. Relationships between gene expression and clinicopathological parameters in cervical cancer, including age, HPV status, histology, stage, and lymph node metastasis, were analysed by the chi-square test. The somatic mutations of these prognostic genes were assessed through cBioPortal. The robustness of the model was verified in another two independent validation cohorts. Key Findings. In total, 169 overlapping upregulated genes and 29 overlapping downregulated genes were identified in cervical cancer compared with normal cervical tissues. Functional enrichment analysis indicated that the DEGs were mainly enriched in DNA replication, the cell cycle, and the p53 signalling pathway. Finally, a 5-gene- (ITM2A, DSG2, SPP1, EFNA1, and MMP1) based prognostic signature was built. According to this model, each patient was given a prognostic-related risk value. The Kaplan-Meier analysis showed that a higher risk was related to worse overall survival in cervical cancer, with an area under the receiver operating characteristic curve of 0.811 for 15 years. The validity of this model in the prediction of cervical cancer outcome was verified in another two independent datasets. In addition, our study also found that the low expression of ITM2A was associated with cervical adenocarcinoma. Interestingly, DSG2 was associated with the HPV status of cervical cancer. Significance. Our study constructed a prognostic model in cervical cancer and discovered two novel genes, ITM2A and DSG2, associated with cervical carcinogenesis and survival.