Predicting the risk of the distant recurrence of cervical cancer after concurrent chemoradiation: A validation study of the Korean Gynecologic Oncologic Group (KGOG)-1024 model

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.

Predicting the Recurrence of Operable Cervical Cancer Patients Based on Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score and Classical Clinicopathological Parameters

Objective

The purpose of this study was to evaluate the prognostic value of hemoglobin, albumin, lymphocyte, and platelet (HALP) score in patients with operable cervical cancer, and on this basis, combined with classical clinicopathological parameters to predict the recurrence of patients.

Methods

A total of 1580 patients with stage IA-IIA cervical cancer were randomly divided into training cohort (n=1054) and validation cohort (n=526) according to the predefined ratio of 2:1. In the training cohort, the receiver operating characteristic (ROC) curve and Youden index were used to determine the optimal threshold of HALP score for predicting cervical cancer recurrence. On this basis, the independent related factors with cervical cancer recurrence were screened through univariate and multivariate Cox regression analysis, and then a nomogram model was further established. The internal and external validation of the model was carried out in the training cohort and the validation cohort respectively through the consistency index (C-index) and calibration curve.

Results

ROC curve and Youden index showed that the optimal threshold of HALP score for predicting cervical cancer recurrence was 39.50. Multivariate analysis confirmed that HALP score and some other classic clinicopathological parameters were independently associated with cervical cancer recurrence. Based on the results of multivariate analysis, a nomogram model for predicting cervical cancer recurrence was successfully constructed. The internal and external calibration curves showed that the fitting degree of the model was good, and the C-index (the C-index of the training cohort and the validation cohort were 0.862 and 0.847, respectively) showed that the prediction accuracy of the model proposed in this study was better than other similar models.

Conclusion

HALP score may be a novel predictor for predicting the cervical cancer recurrence. Nomogram model based on HALP score and classical clinicopathological parameters can better predict the recurrence of cervical cancer.