Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer.

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

Corrigendum: The research progress on radiation resistance of cervical cancer.

[This corrects the article DOI: 10.3389/fonc.2024.1380448.].

The research progress on radiation resistance of cervical cancer.

Cervical carcinoma is the most prevalent gynecology malignant tumor and ranks as the fourth most common cancer worldwide, thus posing a significant threat to the lives and health of women. Advanced and early-stage cervical carcinoma patients with high-risk factors require adjuvant treatment following surgery, with radiotherapy being the primary approach. However, the tolerance of cervical cancer to radiotherapy has become a major obstacle in its treatment. Recent studies have demonstrated that radiation resistance in cervical cancer is closely associated with DNA damage repair pathways, the tumor microenvironment, tumor stem cells, hypoxia, cell cycle arrest, and epigenetic mechanisms, among other factors. The development of tumor radiation resistance involves complex interactions between multiple genes, pathways, and mechanisms, wherein each factor interacts through one or more signaling pathways. This paper provides an overview of research progress on an understanding of the mechanism underlying radiation resistance in cervical cancer.

A novel immune-related risk-scoring system associated with the prognosis and response of cervical cancer patients treated with radiation therapy.

Objective: The tumor microenvironment plays a critical role in the radiotherapy and immunotherapy response of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Radioresistance is a key factor in treatment failure among patients who receive radical radiotherapy. Thus, new immune-related biomarkers associated with radiotherapy response in CESC are needed. Methods: In this study, the CIBERSORT and ESTIMATE methods were applied to determine the percentage of tumor-infiltrating cells and the number of immune components in 103 CESCs treated with radiotherapy from The Cancer Genome Atlas (TCGA) database. The main dysregulated genes were subjected to multivariate and univariate analyses. The prognostic value of this system was studied via receiver operating characteristic curve and survival analysis. For further confirmation, the biomarkers' expression levels and predictive value were validated by immunohistochemistry (IHC) and qRT-PCR. The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in cervical cancer patients treated with radiation therapy. Results: Data for 17 radioresistant and 86 radiosensitive tumors were obtained from the The Cancer Genome Atlas database. 53 immune-related DEGs were identified. GO and KEGG analyses revealed that the DEGs were enriched in protein kinase B signaling, growth factors in cytokines, the MAPK pathway and the PI3K-Akt pathway. Then, 14 key immune-related genes built a risk scoring model were deemed prognostic in CESC with radiotherapy. The area under the curve (AUC) of the model was 0.723, and the high-risk group presented worse outcomes than the low-risk group. In addition, the high-risk group tended to have persistent tumors (p = 0.001). The high expression of WT1 and SPOUYT4 were associated with relapse, the high expression of Angiotensinogen and MIEN1 were associated with nonrelapse. Analysis of the immune microenvironment indicated that M0 macrophages, M2 macrophages, activated mast cells and resting memory CD4+ T cells were positively correlated with the risk score (p < 0.05). Conclusion: The novel immune-related risk scoring system has some advantages in predicting the prognosis and treatment response of cervical cancer patients treated with radiotherapy. Moreover, it might provide novel clues for providing targeted immune therapy to these patients.

Association of the LEP gene with immune infiltration as a diagnostic biomarker in preeclampsia.

Objective: Preeclampsia (PE) is a serious condition in pregnant women and hence an important topic in obstetrics. The current research aimed to recognize the potential and significant immune-related diagnostic biomarkers for PE. Methods: From the Gene Expression Omnibus (GEO) data sets, three public gene expression profiles (GSE24129, GSE54618, and GSE60438) from the placental samples of PE and normotensive pregnancy were downloaded. Differentially expressed genes (DEGs) were selected and determined among 73 PE and 85 normotensive control pregnancy samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO) enrichment analysis, and Gene Set Enrichment Analysis (GSEA). The candidate biomarkers were identified by the least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analysis. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the expression levels and diagnostic value of biomarkers in PE were verified in the GSE75010 data set (80 PE and 77 controls) and validated by qRT-RCR, Western blot, and immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in PE. Results: In total, 15 DEGs were recognized. The GO and KEGG analyses revealed that the DEGs were enriched in the steroid metabolic process, receptor ligand activity, GnRH secretion, and neuroactive ligand-receptor interaction. The recognized DEGs were primarily implicated in cell-type benign neoplasm, kidney failure, infertility, and PE. Gene sets related to hormone activity, glycosylation, multicellular organism process, and response to BMP were activated in PE. The LEP gene was distinguished as a diagnostic biomarker of PE (AUC = 0.712) and further certified in the GSE75010 data set (AUC = 0.850). The high expression of LEP was associated with PE in clinical samples. In addition, the analysis of the immune microenvironment showed that gamma delta T cells, memory B cells, M0 macrophages, and regulatory T cells were positively correlated with LEP expression (P < 0.05). Conclusion: LEP expression can be considered to be a diagnostic biomarker of PE and can offer a novel perspective for future studies regarding the occurrence and molecular mechanisms of PE.

DPP6 and MFAP5 are associated with immune infiltration as diagnostic biomarkers in distinguishing uterine leiomyosarcoma from leiomyoma.

Objective: Uterine leiomyosarcoma (ULMS) is the most common subtype of uterine sarcoma and is difficult to discern from uterine leiomyoma (ULM) preoperatively. The aim of the study was to determine the potential and significance of immune-related diagnostic biomarkers in distinguishing ULMS from ULM. Methods: Two public gene expression profiles (GSE36610 and GSE64763) from the GEO datasets containing ULMS and ULM samples were downloaded. Differentially expressed genes (DEGs) were selected and determined among 37 ULMS and 25 ULM control samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Disease Ontology (DO) enrichment analyses as well as gene set enrichment analysis (GSEA). The candidate biomarkers were identified by least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analyses. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the biomarker expression levels and diagnostic value in ULMS were verified in the GSE9511 and GSE68295 datasets (12 ULMS and 10 ULM), and validated by immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in ULMS. Result: In total, 55 DEGs were recognized via GO analysis, and KEGG analyses revealed that the DEGs were enriched in nuclear division, and cell cycle. The recognized DEGs were primarily implicated in non-small cell lung carcinoma and breast carcinoma. Gene sets related to the cell cycle and DNA replication were activated in ULMS. DPP6 and MFAP5 were distinguished as diagnostic biomarkers of ULMS (AUC = 0.957, AUC = 0.899, respectively), and they were verified in the GSE9511 and GSE68295 datasets (AUC = 0.983, AUC = 0.942, respectively). The low expression of DPP6 and MFAP5 were associated with ULMS. In addition, the analysis of the immune microenvironment indicated that resting mast cells were positively correlated with DPP6 and MFAP5 expression and that eosinophils and M0 macrophages were negatively correlated with DPP6 expression (P<0.05). Conclusion: These findings indicated that DPP6 and MFAP5 are diagnostic biomarkers of ULMS, thereby offering a novel perspective for future studies on the occurrence, function and molecular mechanisms of ULMS.

PRKCI Mediates Radiosensitivity via the Hedgehog/GLI1 Pathway in Cervical Cancer.

Objective: Insensitivity to radiotherapy accounts for the majority of therapeutic failures in cervical cancer (CC) patients who undergo radical radiotherapy. We aimed to elucidate the molecular mechanisms underlying radiosensitivity to identify methods to improve the overall 5-year survival rate. The atypical protein kinase C iota (aPKCι) gene PRKCI exhibits tumor-specific copy number amplification (CNA) in CC. We investigated how PRKCI decreases radiosensitivity in CC and assessed the interplay between PRKCI and the Hedgehog (Hh)/GLI1 pathway in the present research. Methods: The biological functions of PRKCI in CC radiosensitivity were explored through immunohistochemistry, colony formation, Cell Counting Kit-8 (CCK-8), cell cycle, apoptosis assays, and xenograft models. qRT-PCR, Western blotting analysis, and immunofluorescence assays were utilized to evaluate the interplay between PRKCI and the Hh/GLI1 pathway and its mechanism in PRKCI-decreased radiosensitivity in CC. Furthermore, the effect of auranofin (AF), a selective inhibitor of PKCι, on CC cells was explored through biochemical assays in vitro and in vivo. Results: We found that high PRKCI expression was responsible for decreased survival in CC. PRKCI was intimately associated with radiation-triggered alterations in proliferation, the cell cycle, apoptosis, and xenograft growth. The Hh/GLI1 pathway was activated when PRKCI expression was altered. PRKCI functions downstream of the Hh/GLI1 pathway to phosphorylate and activate the transcription factor GLI1. AF acts as a radiosensitizer and showed biological effects in vitro and in vivo. Conclusions: PRKCI is a therapeutic target for regulating radiosensitivity in CC. This molecule regulates radiosensitivity by modulating GLI1 relocalization and phosphorylation in CC via the Hh/GLI1 pathway.

Prognostic value of preoperative soluble interleukin 2 receptor α as a novel immune biomarker in epithelial ovarian cancer.

PURPOSE: Epithelial ovarian cancer (EOC) is regarded as the deadliest gynecological cancer, and the demand for novel noninvasive prognostic biomarkers remains significant. This study aimed to investigate the prognostic value of preoperative blood biomarkers in EOC patients. METHODS: In total, 73 patients who had undergone ovarian mass resection were enrolled. Serum concentration of biomarkers, including soluble interleukin 2 receptor α (sIL-2R), was measured 1-2 weeks before surgery. Independent prognostic factors for progression-free survival (PFS) were investigated with multivariate Cox regression analysis. A prognostic model was subsequently developed and evaluated by discrimination, calibration and clinical net benefit. Furthermore, transcriptome data of 376 EOC cases from The Cancer Genome Atlas (TCGA) were analyzed with ESTIMATE, CIBERSORT and Maftools algorithm to evaluate the correlation of IL2RA expression with tumor immune microenvironment and immunotherapeutic response. RESULTS: High sIL-2R concentration was found to be the only significant prognostic blood biomarker for PFS by multivariate Cox regression analysis in our center. A prognostic nomogram was developed with satisfactory discrimination, calibration and clinical net benefit. In addition, higher IL2RA expression was significantly associated with higher immune scores, activated CD4+ T cells, M2 macrophages and resting dendritic cells in TCGA data. Furthermore, IL2RA expression was closely related to TMB scores. CONCLUSIONS: sIL-2R is a potential prognostic immune biomarker for EOC patients, and a comprehensive prognostic model comprising sIL-2R with satisfactory discrimination and clinical appliance was developed. Therefore, we recommend routine sIL-2R testing in EOC patients.

Wogonoside inhibits tumor growth and metastasis in endometrial cancer via ER stress-Hippo signaling axis.

Wogonoside, a bioactive flavonoid component derived from Scutellaria baicalensis Georgi, has been reported to inhibit tumor growth in mice bearing various types of cancer cells such as breast cancer, lung cancer, and leukemia cells. However, whether wogonoside could inhibit tumor growth of endometrial cancer has not been elucidated. In this study, we explored the function of wogonoside on tumor growth and the underlying mechanism on endometrial cancer. Firstly, we investigated the effect of wogonoside on endometrial cancer cells and found that wogonoside could significantly decrease cell proliferation and metastasis. Mechanistically, wogonoside could aggravate the extent of ER stress and upregulate the phosphorylation level of Mammalian Ste20-like kinase 1, leading to the activation of the Hippo signaling pathway. Taken together, in vitro and in vivo data demonstrated that wogonoside could be a potent inducer of ER stress and could be further developed into a promising therapy for endometrial cancer.

Aldehyde dehydrogenase 1 (ALDH1) positivity correlates with poor prognosis in cervical cancer.

OBJECTIVE: To analyse the associations between aldehyde dehydrogenase 1 (ALDH1) tumour immunopositivity and disease-free survival in cervical carcinoma. METHODS: ALDH1 immunohistochemistry was performed on formalin-fixed, paraffin wax-embedded cervical tumour tissue samples obtained from hospital archives. Data regarding disease-free survival were obtained. Kaplan-Meier survival analyses and Cox proportional hazards regression models were performed. RESULTS: Patients with ALDH1-positive tumours (n = 31) had significantly shorter disease-free survival than those with ALDH1-negative tumours (n = 167; 41.99 ± 0.90 vs 53.64 ± 2.67 months). ALDH1 positivity was associated with poor prognosis (relative risk 2.727; 95% confidence intervals 1.253, 5.914). CONCLUSIONS: ALDH1 positivity is associated with poor prognosis of cervical carcinoma, and may be an independent predictor of prognosis.