Cervical, Ovarian and Endometrial Tumor Markers: Potential Clinical Value

LASSO and Bioinformatics Analysis in the Identification of Key Genes for Prognostic Genes of Gynecologic Cancer

The aim of this study is to identify potential biomarkers for early diagnosis of gynecologic cancer in order to improve survival. Cervical cancer (CC) and endometrial cancer (EC) are the most common malignant tumors of gynecologic cancer among women in the world. As the underlying molecular mechanisms in both cervical and endometrial cancer remain unclear, a comprehensive and systematic bioinformatics analysis is required. In our study, gene expression profiles of GSE9750, GES7803, GES63514, GES17025, GES115810, and GES36389 downloaded from Gene Expression Omnibus (GEO) were utilized to analyze differential gene expression between cancer and normal tissues. A total of 78 differentially expressed genes (DEGs) common to CC and EC were identified to perform the functional enrichment analyses, including gene ontology and pathway analysis. KEGG pathway analysis of 78 DEGs indicated that three main types of pathway participate in the mechanism of gynecologic cancer such as drug metabolism, signal transduction, and tumorigenesis and development. Furthermore, 20 diagnostic signatures were confirmed using the least absolute shrink and selection operator (LASSO) regression with 10-fold cross validation. Finally, we used the GEPIA2 online tool to verify the expression of 20 genes selected by the LASSO regression model. Among them, the expression of PAMR1 and SLC24A3 in tumor tissues was downregulated significantly compared to the normal tissue, and found to be statistically significant in survival rates between the CC and EC of patients (p < 0.05). The two genes have their function: (1.) PAMR1 is a tumor suppressor gene, and many studies have proven that overexpression of the gene markedly suppresses cell growth, especially in breast cancer and polycystic ovary syndrome; (2.) SLC24A3 is a sodium–calcium regulator of cells, and high SLC24A3 levels are associated with poor prognosis. In our study, the gene signatures can be used to predict CC and EC prognosis, which could provide novel clinical evidence to serve as a potential biomarker for future diagnosis and treatment.

Single-cell transcriptomics reveals the landscape of intra-tumoral heterogeneity and transcriptional activities of ECs in CC

Cervical cancer (CC) is the fourth leading cause of deaths in gynecological malignancies. Although the etiology of CC has been extensively investigated, the exact pathogenesis of CC remains incomplete. Recently, single-cell technologies demonstrated advantages in exploring intra-tumoral diversification among various tumor cells. However, single-cell transcriptome analysis (single-cell RNA sequencing [scRNA-seq]) of CC cells and microenvironment has not been conducted. In this study, a total of 20,938 cells from CC and adjacent normal tissues were examined by scRNA-seq. We identified four tumor cell subpopulations in tumor cells, which had specific signature genes with different biological functions and presented different prognoses. Among them, we identified a subset of cancer stem cells (CSCs) that was related to the developmental hierarchy of tumor progression. Then, we compared the expressive differences between tumor-derived endothelial cells (TECs) and normal ECs (NECs) and revealed higher expression of several metabolism-related genes in TECs. Then, we explored the potential biological function of ECs in vascularization and found several marker genes, which played a prior role in connections between cancer cells and ECs. Our findings provide valuable resources for deciphering the intra-tumoral heterogeneity of CC and uncover the developmental procedure of ECs, which paves the way for CC therapy.

Diagnosis of cancer at early stages based on the multiplex detection of tumor markers using metal nanoclusters

Traditional cancer diagnosis strategies are not considered by most people until the last resort, which delays many cancer treatments leading to advanced stages. Tumor marker sensors show great potential for detecting cancer because of its cost-effective and harmless checking procedures. Normally, one tumor marker is detected each time by using one type of sensor, but the accuracy to declare cancer is not always satisfied. Metal nanoclusters are ultra-small nanomaterials with low toxicity, distinct optical properties, catalytic activities, and cost-effective performance. Some metal nanoclusters have been designed to detect more than one tumor marker in a single step. The consideration of combined parameters using such facile sensing strategies has the potential to simplify the test procedure, and increase the diagnostic accuracy of early cancer. Therefore, various sensing strategies for the multiplex detection of tumor markers using metal nanoclusters are summarized.

Predictive Ki-67 Proliferation Index of Cervical Squamous Cell Carcinoma Based on IVIM-DWI Combined with Texture Features

Purpose

This study aims to determine whether IVIM-DWI combined with texture features based on preoperative IVIM-DWI could be used to predict the Ki-67 PI, which is a widely used cell proliferation biomarker in CSCC.

Methods

A total of 70 patients were included. Among these patients, 16 patients were divided into the Ki-67 PI <50% group and 54 patients were divided into the Ki-67 PI ≥50% group based on the retrospective surgical evaluation. All patients were examined using a 3.0T MRI unit with one standard protocol, including an IVIM-DWI sequence with 10 b values (0–1,500 sec/mm²). The maximum level of CSCC with a b value of 800 sec/mm² was selected. The parameters (diffusion coefficient (D), microvascular volume fraction (f), and pseudodiffusion coefficient (D^∗)) were calculated with the ADW 4.6 workstation, and the texture features based on IVIM-DWI were measured using GE AK quantitative texture analysis software. The texture features included the first order, GLCM, GLSZM, GLRLM, and wavelet transform features. The differences in IVIM-DWI parameters and texture features between the two groups were compared, and the ROC curve was performed for parameters with group differences, and in combination.

Results

The D value in the Ki-67 PI ≥50% group was lower than that in the Ki-67 PI <50% group (P < 0.05). A total of 1,050 texture features were obtained using AK software. Through univariate logistic regression, mPMR feature selection, and multivariate logistic regression, three texture features were obtained: wavelet_HHL_GLRLM_ LRHGLE, lbp_3D_k_ firstorder_IR, and wavelet_HLH_GLCM_IMC1. The AUC of the prediction model based on the three texture features was 0.816, and the combined D value and three texture features was 0.834.

Conclusions

Texture analysis on IVIM-DWI and its parameters was helpful for predicting Ki-67 PI and may provide a noninvasive method to investigate important imaging biomarkers for CSCC.

FAM83A exerts tumor‑suppressive roles in cervical cancer by regulating integrins

Family with sequence similarity 83 member A (FAM83A) has been recently observed to be upregulated in various types of cancer and hypothesized to be serve as an oncogene. The present study aimed to determine the functional roles and the underlying molecular mechanism of FAM83A in cervical cancer. The results demonstrated that although FAM83A expression was increased in cervical cancer compared with normal tissues, the expression levels of FAM83A were decreased in patients with advanced FIGO stage, deep stromal invasion, poor differentiation and/or lymph node metastasis and negatively associated with short survival time of patients with cervical cancer. FAM83A knockdown promoted cell proliferative, migratory and invasive abilities of CaSki and HeLa cells. A mouse xenograft model demonstrated that FAM83A knockdown promoted tumor growth in vivo. Mechanistically, RNA sequencing results revealed that knockdown of FAM83A increased the transcription of genes mainly associated with oncogenesis-associated pathways. In addition, FAM83A knockdown increased the protein levels of α1, α3, α5, β4 and β5 integrins in vitro and in vivo, and the expression of FAM83A was also negatively associated with the levels of these proteins in human cervical cancer tissue samples. In conclusion, the results of the present study suggested that FAM83A may exert a tumor-suppressive role in cervical cancer by suppressing the expression of integrins, which may offer new insight into the biological basis of cervical cancer.

Diagnostic Value of Albumin to Fibrinogen Ratio in Cervical Cancer

BACKGROUND

Albumin to fibrinogen ratio (AFR) play a crucial role in the progression and prognosis of many malignant tumors. This study aimed to comprehensively assess the diagnostic value of AFR as single markers or in combination with squamous cell carcinoma antigen (SCC-Ag), cancer antigen 125 (CA-125) in cervical cancer.

METHODS

A total of 323 cervical cancer inpatients, 143 patients with cervical intraepithelial neoplasia (CIN) and 317 healthy controls were analyzed. Differences in laboratory parameters and clinicopathological features were calculated using the Mann-Whitney U or Kruskal-Wallis H test. The receiver operating characteristic (ROC) curve was used to evaluate the predicted value of AFR, alone or combined with SCC-Ag, CA-125 for the diagnosis of cervical cancer.

RESULTS

The levels of AFR in patients with cervical cancer were significantly lower than those in the CIN patients and the control subjects. AFR were not only negatively correlated with the tumor stage, but also related to histology typing, lymph node metastasis, distant metastasis, depth of stromal infiltration, tumor size, and tumor stage; however, it was not associated with the blood group. AFR combined with SCC-Ag possessed a larger area under the curve (AUC; AUC_AFR+SCC-Ag = 0.924, 95% confidence interval (CI) 0.900, 0.944) than AFR (P < 0.001), SCC-Ag (P < 0.001), or CA-125 (P < 0.001) did alone.

CONCLUSIONS

The pretreatment levels of AFR, alone or combined with SCC-Ag, CA-125 could improve the diagnostic efficiency of cervical cancer.

Circular RNAs and their emerging roles as diagnostic and prognostic biomarkers in ovarian cancer

Ovarian cancer (OC), one of the gynecologic malignancies with high invasive and metastatic potential, has a low survival rate in females. Although cytoreductive surgery combined with chemotherapy is the principal treatment for OC, the prognosis remains poor, and the recurrence rate of OC remains high. It is urgent to explore novel biomarkers for the diagnosis and prognosis of OC, as well as therapeutic targets. Circular RNAs (circRNAs) are a class of highly conserved, stable and abundant noncoding RNAs (ncRNAs). Recent studies have shown that circRNAs participate in OC progression by regulating various processes, including cell proliferation, migration, invasion and apoptosis. In addition, circRNAs are potential biomarkers for OC diagnosis and prognosis. This review provides an overview of recent findings on circRNAs in OC, including their functions and molecular mechanisms, and discusses their potential roles as diagnostic and prognostic biomarkers, as well as therapeutic targets for OC.