Disparities in Diagnosis and Treatment of Cervical Adenocarcinoma Compared With Squamous Cell Carcinoma: An Analysis of the National Cancer Database, 2004-2017

Radiomics-based machine learning models for differentiating pathological subtypes in cervical cancer: a multicenter study

Purpose

This study was designed to determine the diagnostic performance of fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) radiomics-based machine learning (ML) in the classification of cervical adenocarcinoma (AC) and squamous cell carcinoma (SCC).

Methods

Pretreatment 18F-FDG PET/CT data were retrospectively collected from patients who were diagnosed with locally advanced cervical cancer at two centers. Radiomics features were extracted and selected by the Pearson correlation coefficient and least absolute shrinkage and selection operator regression analysis. Six ML algorithms were then applied to establish models, and the best-performing classifier was selected based on accuracy, sensitivity, specificity, and area under the curve (AUC). The performance of different model was assessed and compared using the DeLong test.

Results

A total of 227 patients with locally advanced cervical cancer were enrolled in this study (N=136 for the training cohort, N=59 for the internal validation cohort, and N=32 for the external validation cohort). The PET radiomics model constructed based on the lightGBM algorithm had an accuracy of 0.915 and an AUC of 0.851 (95% confidence interval [CI], 0.715-0.986) in the internal validation cohort, which were higher than those of the CT radiomics model (accuracy: 0.661; AUC: 0.513 [95% CI, 0.339-0.688]). The DeLong test revealed no significant difference in AUC between the combined radiomics model and the PET radiomics model in either the training cohort (z=0.940, P=0.347) or the internal validation cohort (z=0.285, P=0.776). In the external validation cohort, the lightGBM-based PET radiomics model achieved good discrimination between SCC and AC (AUC = 0.730).

Conclusions

The lightGBM-based PET radiomics model had great potential to predict the fine histological subtypes of locally advanced cervical cancer and might serve as a promising noninvasive approach for the diagnosis and management of locally advanced cervical cancer.

Stratified Prognostic Comparison Between Stage IIB-IVA Cervical Adenocarcinoma and Squamous Cell Carcinoma: A SEER Database-Based Study

Objective

In current most observational studies, the prognosis of cervical adenocarcinoma is worse than that of cervical squamous cell carcinoma. However, most of the current studies are holistic and lack more detailed staging and grouping analysis of the prognosis of the two types of cervical tumors.

Patients and Methods

Inclusion from the SEER database of stage IIB-IVA cervical squamous cell carcinoma and cervical adenocarcinoma patients who did not undergo surgery from 2000 to 2019, underwent radiotherapy/chemotherapy/radiotherapy and chemotherapy/no treatment, and then propensity score matching (PSM) was performed to eliminate confounding factors between cervical squamous cell carcinoma and cervical adenocarcinoma patients with the same stage and treatment method. After matching the original data and propensity score, logarithmic rank test and chi square test were used to evaluate the survival benefits of different stages and treatment methods for patients using Kaplan Meier curve. The prognosis of two types of cervical tumors under the same treatment method was compared, and factors that may cause poor prognosis were analyzed, excluding confounding factors.

Results

A total of 10,057 patients were included in this study, and survival analysis showed a significant correlation between the treatment method used and patient prognosis (P<0.05). However, for patients who received radiotherapy or no special treatment, OS and CSS were only related to tumor stage and not to tumor type. In patients undergoing radiotherapy and chemotherapy, the OS and CSS of stage IIIA and IVA patients are not related to tumor pathological characteristics, while the OS of stage IIB patients is not related to tumor properties after PSM.

Conclusion

In patients undergoing radiotherapy and chemotherapy, the OS and CSS of stage IIIA and IVA patients were not related to histological type, while the OS of stage IIB patients was not related to histological type after PSM.

Disparities in Survival Outcomes Between Locally Advanced Cervical Squamous Cell Carcinoma and Adenocarcinoma Treated with Chemoradiotherapy

Purpose

To determine the disparities in survival outcomes between stage IIB-IVA cervical squamous cell carcinoma (SCC) and adenocarcinoma (AC) treated with chemoradiotherapy.

Methods

Patients diagnosed between 2004 and 2015 were retrospectively included from the Surveillance, Epidemiology, and End Results databases. Propensity score matching (PSM) was used in this study. The primary endpoints were cervical cancer-specific survival (CCSS) and overall survival (OS).

Results

A total of 2752 patients were identified, including 87.5% (n=2408) were SCC and 12.5% (n=344) were AC. Patients with AC had inferior 5-year CCSS (67.5% vs 54.8%, P<0.001) and OS (58.4% vs 47.2%, P<0.001) compared to those with the SCC subtype. The hazard curve of cervical cancer-related death in AC peaked at 2 years (19%) and still small peaks in the 7 and 11 years of follow-up. Regarding SCC, cervical cancer-related deaths peaked at 2 years (15%) and the hazard rate was 2.0% during the six years of follow-up. The multivariate Cox regression analyses indicated that histology was an independent prognostic factor associated with survival outcomes. Patients with AC had significantly poor CCSS (P<0.001) and OS (P<0.001). Similar results were found after PSM.

Conclusion

Our study demonstrates a significantly better prognosis for cervical SCC patients compared to those with cervical AC undergoing chemoradiotherapy. These results highlight the importance of histological subtyping in predicting treatment outcomes and tailoring therapeutic strategies.

KLF5 inhibits the migration and invasion in cervical cancer cell lines by regulating SNAI1

BACKGROUND

Epithelial-mesenchymal transition (EMT) is an important biological process by which malignant tumor cells to acquire migration and invasion abilities. This study explored the role of KLF5 in the EMT process of in cervical cancer cell lines.

OBJECTIVE

Krüpple-like factor 5 (KLF5) is a basic transcriptional factor that plays a key role in cell-cycle arrest and inhibition of apoptosis. However, the molecular mechanism by which KLF5 mediates the biological functions of cervical cancer cell lines has not been elucidated. Here, we focus on the potential function of ELF5 in regulating the EMT process in in vitro model of cervical cancer cell lines.

METHOD

Western-blot and real-time quantitative PCR were used to detect the expression of EMT-related genes in HeLa cells. MTT assays, cell scratch and Transwell assays were used to assess HeLa cells proliferation and invasion capability. Using the bioinformatics tool JASPAR, we identified a high-scoring KLF5-like binding sequence in the SNAI1 gene promoter. Luciferase reporter assays was used to detect transcriptional activity for different SNAI1 promoter truncates.

RESULT

After overexpressing the KLF5 gene in HeLa cells, KLF5 not only significantly inhibited the invasion and migration of HeLa cells, but also increased the expression of E-cadherin and decreased the expression of N-cadherin and MMP9. In addition, the mRNA expression of upstream regulators of E-cadherin, such as SNAI1, SLUG, ZEB1/2 and TWIST1 was also decreased. Furthermore, KLF5 inhibiting the expression of the SNAI1 gene via binding its promoter region, and the EMT of Hela cells was promoted after overexpression of the SNAI1 gene.

CONCLUSION

These results indicate that KLF5 can downregulate the EMT process of HeLa cells by decreasing the expression of the SNAI1 gene, thereby inhibiting the migration and invasion of HeLa cervical cancer cells.

Targeting PARP for the optimal immunotherapy efficiency in gynecologic malignancies

Gynecologic cancer, which includes ovarian, cervical, endometrial, vulvar, and vaginal cancer, is a major health concern for women all over the world. Despite the availability of various treatment options, many patients eventually progress to advanced stages and face high mortality rates. PARPi (poly (ADP-ribose) polymerase inhibitor) and immune checkpoint inhibitor (ICI) have both shown significant efficacy in the treatment of advanced and metastatic gynecologic cancer. However, both treatments have limitations, including inevitable resistance and a narrow therapeutic window, making PARPi and ICI combination therapy a promising approach to treating gynecologic malignancies. Preclinical and clinical trials have looked into the combination therapy of PARPi and ICI. PARPi improves ICI efficacy by inducing DNA damage and increasing tumor immunogenicity, resulting in a stronger immune response against cancer cells. ICI, conversly, can increase PARPi sensitivity by priming and activating immune cells, consequently prompting immune cytotoxic effect. Several clinical trials in gynecologic cancer patients have investigated the combination therapy of PARPi and ICI. When compared to monotherapy, the combination of PARPi and ICI increased progression-free survival and overall survival in ovarian cancer patients. The combination therapy has also been studied in other types of gynecologic cancer, including endometrial and cervical cancer, with promising results. Finally, the combination therapeutic strategy of PARPi and ICI is a promising approach in the treatment of gynecologic cancer, particularly advanced and metastatic stages. Preclinical studies and clinical trials have demonstrated the safety and efficacy of this combination therapy in improving patient outcomes and quality of life.

Differentially Expressed Genes and Molecular Susceptibility to Human Age-Related Diseases

Mainstream transcriptome profiling of susceptibility versus resistance to age-related diseases (ARDs) is focused on differentially expressed genes (DEGs) specific to gender, age, and pathogeneses. This approach fits in well with predictive, preventive, personalized, participatory medicine and helps understand how, why, when, and what ARDs one can develop depending on their genetic background. Within this mainstream paradigm, we wanted to find out whether the known ARD-linked DEGs available in PubMed can reveal a molecular marker that will serve the purpose in anyone's any tissue at any time. We sequenced the periaqueductal gray (PAG) transcriptome of tame versus aggressive rats, identified rat-behavior-related DEGs, and compared them with their known homologous animal ARD-linked DEGs. This analysis yielded statistically significant correlations between behavior-related and ARD-susceptibility-related fold changes (log₂ values) in the expression of these DEG homologs. We found principal components, PC1 and PC2, corresponding to the half-sum and the half-difference of these log₂ values, respectively. With the DEGs linked to ARD susceptibility and ARD resistance in humans used as controls, we verified these principal components. This yielded only one statistically significant common molecular marker for ARDs: an excess of Fcγ receptor IIb suppressing immune cell hyperactivation.