The Incorporation of Immunotherapy and Targeted Therapy Into Chemoradiation for Cervical Cancer: A Focused Review

A Cellular Senescence-Related Signature Predicts Cervical Cancer Patient Outcome and Immunotherapy Sensitivity

Cervical cancer (CC) is one of the most prevalent gynecological malignancies. The rate of mortality and morbidity among patients with CC is high. Cellular senescence is involved in tumorigenesis as well as in the cancer progression. However, the involvement of cellular senescence in CC development is still unclear and requires further investigation. In this study, we retrieved data on cellular senescence-related genes (CSRGs) from the "CellAge" Database. We used the TCGA-CESC and CGCI-HTMCP-CC datasets as the training and validation sets, respectively. Finally, a signature was constructed using "univariate" and "Least Absolute Shrinkage and Selection Operator" (LASSO) Cox regression analysis, which contains eight CSRGs. Using this signature, we calculated the risk scores of all patients in the training and validation cohorts and categorized them into the low-risk group (LR-G) and the high-risk group (HR-G). Results showed that, compared to patients in the HR-G, those in the LR-G demonstrated a more positive clinical prognosis, more abundant immune cell infiltrations, and a more active immune response. The signature could also modulate the expression of SASP factors. In vitro studies showed an increased expression of SERPINE1 and IL-1α genes included in the signature in CC cells and tissues. Our findings help to deepen our insights into the etiology of CC, which could be beneficial for prognostic prediction and immunotherapy in clinical practice.

A Cellular Senescence-Related Signature Predicts Cervical Cancer Patient Outcome and Immunotherapy Sensitivity

Cervical cancer (CC) is among the most prevalent gynaecological malignancy. The rate of mortality and morbidity of patients with CC is high. Cellular senescence is involved in tumorigenesis as well as cancer progression. However, the involvement of cellular senescence in CC development is still unclear and requires further investigation. We retrieved data on cellular senescence-related genes (CSRGs) from the "CellAge" Database. We used TCGA-CESC and the CGCI-HTMCP-CC datasets as the training and validation sets, respectively. Eight CSRGs signatures based on the data extracted from these sets were constructed using "univariate" and "Least Absolute Shrinkage and Selection Operator Cox regression analyses". Using this model, we calculated the risk scores of all patients in the training and validation cohort and categorised these patients into the low-risk group (LR-G) and the high-risk group (HR-G). Finally, compared to patients in the HR-G, CC patients in the LR-G demonstrated a more positive clinical prognosis; the expression of senescence-associated secretory phenotype (SASP) markers and immune cell infiltration was higher, and these patients had more active immune responses. In vitro studies showed increased SERPINE1 and IL-1α ((genes included in the signature) expression in CC cells and tissues. The eight-gene prognostic signatures could modulate the expression of SASP factors and the tumour immune micro-environment (TIME). It could be used as a reliable biomarker for predicting the patient's prognosis and response to immunotherapy in CC.

Immune infiltration and a necroptosis-related gene signature for predicting the prognosis of patients with cervical cancer

Background: Cervical cancer (CC), the fourth most common cancer among women worldwide, has high morbidity and mortality. Necroptosis is a newly discovered form of cell death that plays an important role in cancer development, progression, and metastasis. However, the expression of necroptosis-related genes (NRGs) in CC and their relationship with CC prognosis remain unclear. Therefore, we screened the signature NRGs in CC and constructed a risk prognostic model. Methods: We downloaded gene data and clinical information of patients with cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) from The Cancer Genome Atlas (TCGA) database. We performed functional enrichment analysis on the differentially expressed NRGs (DENRGs). We constructed prognostic models and evaluated them by Cox and LASSO regressions for DENRGs, and validated them using the International Cancer Genome Consortium (ICGC) dataset. We used the obtained risk score to classify patients into high- and low-risk groups. We employed the ESTIMATE and single sample gene set enrichment analysis (ssGSEA) algorithms to explore the relationship between the risk score and the clinical phenotype and the tumor immune microenvironment. Results: With LASSO regression, we established a prognostic model of CC including 16 signature DENRGs (TMP3, CHMP4C, EEF1A1, FASN, TNF, S100A10, IL1A, H1.2, SLC25A5, GLTP, IFNG, H2AC13, TUBB4B, AKNA, TYK2, and H1.5). The risk score was associated with poor prognosis in CC. Survival was lower in the high-risk group than the low-risk group. The nomogram based on the risk score, T stage, and N stage showed good prognostic predictive power. We found significant differences in immune scores, immune infiltration analysis, and immune checkpoints between the high- and low-risk groups (p < 0.05). Conclusion: We screened for DENRGs based on the TCGA database by using bioinformatics methods, and constructed prognostic models based on the signature DENRGs, which we confirmed as possibly having important biological functions in CC. Our study provides a new perspective on CC prognosis and immunity, and offers a series of new targets for future treatment.

Diagnostic, prognostic, and immunological roles of CD177 in cervical cancer

BACKGROUND

CD177, an indicator of prognosis in diverse cancers, is involved in the physiological processes of various tumor cells, and acts as an immune molecule with novel functions in cancer pathogenesis. However, the diagnostic, prognostic, and immunological role of CD177 in cervical cancer remains unclear.

METHODS

Utilizing publicly available databases and integrating several bioinformatics analysis methods, we evaluated the expression level of CD177 in cervical cancer by GENT2, HPA, and GEO databases. And the experiments of western blot and immunohistochemical staining were used to test the hypothesis. The Kaplan-Meier Plotter database, Xena Shiny, and the constructed nomogram were clearly demonstrated its prognostic value for patients. Gene set enrichment analysis explored the relationship between CD177 and cervical cancer immune responses and immune cells infiltration level. In addition, we investigated the association between CD177 expression and stromal score, immune score, immune checkpoint, and drug sensitivity by TCGA RNA-seq data.

RESULTS

CD177 was apparently expressed at low levels in cervical cancer and predicted a poor survival rate for patients. CD177 significantly activated immune-related signaling pathways and had a positive relationship with immune cell infiltration level. The high CD177 expression group possessed the high stromal score and immune score. CD177 had potential interactions with CTLA4, CD27, BLTA, CD200R1, CD80, NRP1, TNFRSF25, TIGIT, ICOS, and TNFSF9 checkpoint markers. And CD177 expression was positively relevant with drug sensitivity for Lapatinib, Belinostat, ATRA, Gefitinib, Navitoclax, and Tamoxifen.

SIGNIFICANCE

These findings may shed light on the vital role of CD177 in cervical cancer diagnosis, prognosis, and immunological functions, and it may be a promising predictor and potential factor for cervical cancer patients.

Identification of a necroptosis-related prognostic gene signature associated with tumor immune microenvironment in cervical carcinoma and experimental verification

Cervical carcinoma (CC) has been associated with high morbidity, poor prognosis, and high intratumor heterogeneity. Necroptosis is the significant cellular signal pathway in tumors which may overcome tumor cells’ apoptosis resistance. To investigate the relationship between CC and necroptosis, we established a prognostic model based on necroptosis-related genes for predicting the overall survival (OS) of CC patients. The gene expression data and clinical information of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients were obtained from The Cancer Genome Atlas (TCGA). We identified 43 differentially expressed necroptosis-related genes (NRGs) in CESC by examining differential gene expression between CESC tumors and normal tissues, and 159 NRGs from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Gene ontology (GO) and KEGG enrichment analysis illustrated that the genes identified were mainly related to cell necrosis, extrinsic apoptosis, Influenza A, I − kappaB kinase/NF − kappaB, NOD − like receptor, and other signaling pathways. Subsequently, least absolute shrinkage and selection operator (LASSO) regression and univariate and multivariate Cox regression analyses were used to screen for NRGs that were correlated with patient prognosis. A prognostic signature that includes CAMK2A, CYBB, IL1A, IL1B, SLC25A5, and TICAM2 was established. Based on the prognostic model, patients were stratified into either the high-risk or low-risk subgroups with distinct survival. Receiver operating characteristic (ROC) curve analysis was used to identify the predictive accuracy of the model. In relation to different clinical variables, stratification analyses were performed to demonstrate the associations between the expression levels of the six identified NRGs and the clinical variables in CESC. Immunohistochemical (IHC) validation experiments explored abnormal expressions of these six NRGs in CESC. We also explored the relationship between risk score of this necroptosis signature and expression levels of some driver genes in TCGA CESC database and Gene Expression Omnibus (GEO) datasets. Significant relationships between the six prognostic NRGs and immune-cell infiltration, chemokines, tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoints in CESC were discovered. In conclusion, we successfully constructed and validated a novel NRG signature for predicting the prognosis of CC patients and might also play a crucial role in the progression and immune microenvironment in CC.

Recent progress of the tumor microenvironmental metabolism in cervical cancer radioresistance

Radiotherapy is widely used as an indispensable treatment option for cervical cancer patients. However, radioresistance always occurs and has become a big obstacle to treatment efficacy. The reason for radioresistance is mainly attributed to the high repair ability of tumor cells that overcome the DNA damage caused by radiotherapy, and the increased self-healing ability of cancer stem cells (CSCs). Accumulating findings have demonstrated that the tumor microenvironment (TME) is closely related to cervical cancer radioresistance in many aspects, especially in the metabolic processes. In this review, we discuss radiotherapy in cervical cancer radioresistance, and focus on recent research progress of the TME metabolism that affects radioresistance in cervical cancer. Understanding the mechanism of metabolism in cervical cancer radioresistance may help identify useful therapeutic targets for developing novel therapy, overcome radioresistance and improve the efficacy of radiotherapy in clinics and quality of life of patients.

Review of the Standard and Advanced Screening, Staging Systems and Treatment Modalities for Cervical Cancer

Simple Summary

This review discusses the timeline and development of the recommended screening tests, diagnosis system, and therapeutics implemented in clinics for precancer and cancer of the uterine cervix. The incorporation of the latest automation, machine learning modules, and state-of-the-art technologies into these aspects are also discussed.

Abstract

Cancer arising from the uterine cervix is the fourth most common cause of cancer death among women worldwide. Almost 90% of cervical cancer mortality has occurred in low- and middle-income countries. One of the major aetiologies contributing to cervical cancer is the persistent infection by the cancer-causing types of the human papillomavirus. The disease is preventable if the premalignant lesion is detected early and managed effectively. In this review, we outlined the standard guidelines that have been introduced and implemented worldwide for decades, including the cytology, the HPV detection and genotyping, and the immunostaining of surrogate markers. In addition, the staging system used to classify the premalignancy and malignancy of the uterine cervix, as well as the safety and efficacy of the various treatment modalities in clinical trials for cervical cancers, are also discussed. In this millennial world, the advancements in computer-aided technology, including robotic modules and artificial intelligence (AI), are also incorporated into the screening, diagnostic, and treatment platforms. These innovations reduce the dependence on specialists and technologists, as well as the work burden and time incurred for sample processing. However, concerns over the practicality of these advancements remain, due to the high cost, lack of flexibility, and the judgment of a trained professional that is currently not replaceable by a machine.

KCNN4 is a Potential Biomarker for Predicting Cancer Prognosis and an Essential Molecule that Remodels Various Components in the Tumor Microenvironment: A Pan-Cancer Study

Objectives: Potassium Calcium-Activated Channel Subfamily N Member 4 (KCNN4) is a member of the KCNN family. Studies have revealed that KCNN4 is implicated in various physiological processes as well as promotes the malignant phenotypes of cancer cells. However, little is known about its associations with survival outcomes across varying cancer types.

Methods: Herein, we systematically explored the prognostic value of KCNN4 in the pan-cancer dataset retrieved from multiple databases. Next, we performed correlation analysis of KCNN4 expression with tumor mutational burden (TMB) and microsatellite instability (MSI), and immune checkpoint genes (ICGs) to assess its potential as a predictor of immunotherapy efficacy. Afterwards, patients were divided into increased-risk group and decreased-risk group based on the contrasting survival outcomes in various cancer types. Furthermore, the underlying mechanisms of the distinctive effects were analyzed using ESTIMATE, CIBERSORT algorithms, and Gene Set Enrichment Analysis (GSEA) analysis.

Results: KCNN4 expression levels were aberrant in transcriptomic and proteomic levels between cancer and normal control tissues in pan-cancer datasets, further survival analysis elucidated that KCNN4 expression was correlated to multiple survival data, and clinical annotations. Besides, KCNN4 expression was correlated to TMB and MSI levels in 14 types and 12 types of pan-cancers, respectively. Meanwhile, different types of cancer have specific tumor-infiltrating immune cell (TICs) profiles.

Conclusions: Our results revealed that KCNN4 could be an essential biomarker for remodeling components in the tumor microenvironment (TME), and a robust indicator for predicting prognosis as well as immunotherapy response in pan-cancer patients.

A Review of the Effects of Cervical Cancer Standard Treatment on Immune Parameters in Peripheral Blood, Tumor Draining Lymph Nodes, and Local Tumor Microenvironment

Cervical cancer remains a public health concern despite all the efforts to implement vaccination and screening programs. Conventional treatment for locally advanced cervical cancer consists of surgery, radiotherapy (with concurrent brachytherapy), combined with chemotherapy, or hyperthermia. The response rate to combination approaches involving immunomodulatory agents and conventional treatment modalities have been explored but remain dismal in patients with locally advanced disease. Studies exploring the immunological effects exerted by combination treatment modalities at the different levels of the immune system (peripheral blood (PB), tumor-draining lymph nodes (TDLN), and the local tumor microenvironment (TME)) are scarce. In this systemic review, we aim to define immunomodulatory and immunosuppressive effects induced by conventional treatment in cervical cancer patients to identify the optimal time point for immunotherapy administration. Radiotherapy (RT) and chemoradiation (CRT) induce an immunosuppressive state characterized by a long-lasting reduction in peripheral CD3, CD4, CD8 T cells and NK cells. At the TDLN level, CRT induced a reduction in Nrp1+Treg stability and number, naïve CD4 and CD8 T cell numbers, and an accompanying increase in IFNγ-producing CD4 helper T cells, CD8 T cells, and NK cells. Potentiation of the T-cell anti-tumor response was particularly observed in patients receiving low irradiation dosage. At the level of the TME, CRT induced a rebound effect characterized by a reduction of the T-cell anti-tumor response followed by stable radioresistant OX40 and FoxP3 Treg cell numbers. However, the effects induced by CRT were very heterogeneous across studies. Neoadjuvant chemotherapy (NACT) containing both paclitaxel and cisplatin induced a reduction in stromal FoxP3 Treg numbers and an increase in stromal and intratumoral CD8 T cells. Both CRT and NACT induced an increase in PD-L1 expression. Although there was no association between pre-treatment PD-L1 expression and treatment outcome, the data hint at an association with pro-inflammatory immune signatures, overall and disease-specific survival (OS, DSS). When considering NACT, we propose that posterior immunotherapy might further reduce immunosuppression and chemoresistance. This review points at differential effects induced by conventional treatment modalities at different immune compartments, thus, the compartmentalization of the immune responses as well as individual patient's treatment plans should be carefully considered when designing immunotherapy treatment regimens.

Plasma Exosome-Derived SENP1 May Be a Potential Prognostic Predictor for Melanoma

Objective

To evaluate plasma exosome-derived SUMO-specific protease (SENP)1 levels and assess their prognostic value in melanoma.

Patients and Methods

We extracted exosomes from the plasma of 126 melanoma patients, and identified them with transmission electron microscopy, nanoparticle tracking analysis and western blotting. The plasma exosome-derived SENP1 levels of melanoma patients and healthy controls were detected with ELISA.

Results

Plasma exosome-derived SENP1 levels in melanoma patients were significantly upregulated than in healthy controls (P < 0.001). Plasma exosome-derived SENP1 levels in melanoma patients with tumor size >10 cm, located in the mucosa or viscera, with Clark level IV/V, with lymph node metastasis, and TNM stages IIb-IV were significantly higher than in patients in with tumor size <10 cm, located in the skin, with Clark level I-III, without lymph node metastasis, and TNM stages IIb-IV (all P < 0.05). Disease-free survival (DFS) and overall survival (OS) were worse in melanoma patients who had higher plasma exosome-derived SENP1 levels than lower plasma exosome-derived SENP1 levels (both P < 0.001). Area under the receiver operating characteristic curve (AUROC) of plasma exosome-derived SENP1 for predicting 3-year DFS of melanoma patients was 0.82 [95% confidence interval (CI): 0.74-0.88], with a sensitivity of 81.2% (95% CI: 69.9-89.6%) and specificity of 75.4% (95% CI: 62.2-85.9%). The AUROC of plasma exosome-derived SENP1 for predicting 3-year OS of melanoma patients was 0.76 (95% CI: 0.67-0.83), with a sensitivity of 95.7% (95% CI: 85.5-99.5%) and specificity of 62.0% (95% CI: 50.4-72.7%).

Conclusions

Melanoma patients with higher plasma exosome-derived SENP1 levels had worse DFS and OS. The plasma exosome-derived SENP1 levels may be a potential prognostic predictor for 3-year DFS and 3-year OS of melanoma.