Chunbo Li

Cervical cancer (CC) represents a leading malignant threat to women’s health globally. Patients with advanced-stage CC frequently encounter limited t

Background: This study aims to investigate the epidemiological data and trends of male infertility aged 20–49 years in Asia from 1990 to 2021. Methods: Data for this study was obtained from the Global Burden of Disease (GBD) 2021 public database. Trends in prevalence, years lived with disability (YLDs), age‐standardized prevalence rate (ASPR), and age‐standardized YLD rate (ASYR), along with their correlation with the sociodemographic index (SDI), were analyzed. A join‐point regression model was developed to assess trends across different time segments. In addition, an autoregressive integrated moving average (ARIMA) model was employed for predictions extending to 2040. Results: From 1990 to 2021, the burden of male infertility among individuals aged 20–49 years increased both globally and across all Asian regions. In East Asia, the burden was the highest in 1990 and had an initial rapid escalation through the early 1990s, then declined steadily since 1995. South and Southeast Asia experienced significantly accelerating upward trends, with South Asia saw the steepest increases. High‐income Asia Pacific and Central Asia sustained relatively low disease burdens and stable trends throughout the study period. Conclusion: The disease burden in East Asia, South Asia, and Southeast Asia remains significant, with a notable upward trend observed in South Asia and Southeast Asia. Targeted interventions and policies are needed based on the epidemiological characteristics and changing trends of different Asian regions.

Background: The high molecular phenotype heterogeneity of cervical cancer (CC) is the main focus of individualized therapy. Molecular classification may lead to personal treatment and new drug discovery. We summarized the molecular features by establishing a new classification of metabolism-related gene expression profiles. Methods: Clinical information and messenger ribonucleic acid (mRNA) expression were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Twenty-two immune cells were detected by CIBERSORT method. K-means clustering algorithm based on 258 metabolism-related genes was used for CC classification. Univariate and multivariate Cox regression analyses were carried out to find out the optimal metabolism-related genes. A predictive model was established to evaluate the overall survival (OS) of patients. Then, a nomogram model was established to predict the OS of patients based on independent prognostic factors. Results: Based on the expression profiles of 258 survival-related metabolic genes, we identified two metabolism-related subtypes of CC. Cluster_A subtype was characterized with significant glucose metabolism, and had a poor prognosis; and cluster_B subtype exhibited high enrichment of lipid metabolism-related and immune-related signaling pathways. Then, seven metabolism-related genes (CYP4F12, NPL, CH25H, NOS2, SDR16C5, PGK1 and LYZ) were used to establish a metabolism-related risk signature. Patients in high risk groups had a worse prognosis than those in low risk group. Multivariate Cox regression analysis indicted that the metabolism-related risk signature could predict OS as an independent prognostic factor. Conclusions: Our study provides new insight into the metabolic heterogeneity of CC and its relationship with immune landscape. The novel metabolism-related gene signature is an effective potential prognostic signature in the individualized prognosis prediction of CC.

Objective: This study aimed to investigate the role of acellular amniotic membrane (AAM) loaded with adipose-derived mesenchymal stem cells (ADSCs) for the treatment of intrauterine adhesion. Methods: One hundred twenty female Spargue-Dawley rats were randomly divided into four groups: sham operation group (the uterus was picked out and incised without treatment), intrauterine adhesion group, the experimental group treated with AAM, and experimental group treated with AAM loaded with ADSCs. Histological and immunohistochemical analysis were performed on 3, 7, and 14 days after surgery to evaluate the degree of uterine fibrosis and regeneration of injured endometrium. RNA sequencing and real-time PCR were used to explore the potential mechanism by which ADSCs modulated immune response and promoted endometrial regeneration. Results: On 14 days after surgery, the endometrial thickness, number of glands, and degree of fibrosis reduction in the ADSCs/AAM group was higher than those in the AAM group, and similar to the sham operation group. RNA sequencing analysis showed that ADSCs can modulate local immune responses and promote the formation of functional endometrium. Meanwhile, we found that ADSCs significantly decreased the levels of pro-inflammatory cytokines (TNF-α and IL-1β) and increased the levels of anti-inflammatory cytokines (bFGF and IL-6). Conclusion: Our results demonstrated that AAM loaded with ADSCs can result in the regeneration of injured endometrium and fibrosis reduction. Meanwhile, ADSCs also regulated the immune microenvironment, which was beneficial to functional endometrial recovery.

Objective: Due to the information-rich nature of positron emission tomography/computed tomography (PET/CT) images, the authors hope to explore radiomics features that could distinguish metastatic lymph nodes (LNs) from hypermetabolic benign LNs, in addition to conventional indicators. Methods: PET/CT images of 106 patients with early-stage cervical cancer from 2019 to 2021 were retrospectively analyzed. The tumor lesions and LN regions of PET/CT images were outlined with SeeIt, and then radiomics features were extracted. The least absolute shrinkage and selection operator (LASSO) was used to select features. The final selected radiomics features of LNs were used as predictors to construct a machine learning model to predict LN metastasis. Results: The authors determined two morphological coefficient characteristics of cervical lesions (shape – major axis length and shape – mesh volume), one first order characteristics of LNs (first order – 10 percentile) and two gray-level co-occurrence matrix (GLCM) characteristics of LNs (GLCM – id and GLCM – inverse variance) were closely related to LN metastasis. Finally, a neural network was constructed based on the radiomic features of the LNs. The area under the curve of receiver operating characteristic (AUC-ROC) of the model was 0.983 in the training set and 0.860 in the test set. Conclusion: The authors constructed and demonstrated a neural network based on radiomics features of PET/CT to evaluate the risk of single LN metastasis in early-stage cervical cancer.

Cervical squamous cell carcinoma (SCC) and adenocarcinoma (AD) are the main histological types of human papillomavirus‐related cervical cancer. However, there are few reports on cell type‐specific molecular differences between SCC and AD. Here, we used unbiased droplet‐based single‐cell RNA sequencing to elucidate the cellular differences between SCC and AD in tumor heterogeneity, and tumor microenvironment (TME). A total of 61 723 cells from three SCC and three AD patients, were collected and divided into nine cell types. Epithelial cells exhibited high intra‐ and interpatient heterogeneity and functional diversity. Signaling pathways, such as epithelial‐to‐mesenchymal‐transition (EMT), hypoxia and inflammatory response were upregulated in SCC, while cell cycle‐related signaling pathways were highly enriched in AD. SCC was associated with high infiltration of cytotoxicity CD8 T, effector memory CD8 T, proliferative natural killer (NK), and CD160+ NK cells as well as tumor‐associated macrophages (TAMs) with high major histocompatibility complex‐II genes. AD exhibited a high proportion of naive CD8 T, naive CD4 T, Treg CD4, central memory CD8, and TAMs with immunomodulatory functions. Additionally, we also observed that the majority of cancer‐associated fibroblasts (CAFs) were from AD, and participated in inflammation regulation, while SCC‐derived CAFs exhibited similar functions to tumor cells, such as EMT and hypoxia. This study revealed the widespread reprogramming of multiple cell populations in SCC and AD, dissected the cellular heterogeneity and characteristics in TME, and proposed potential therapeutic strategies for CC, such as targeted therapy and immunotherapy.

LINC02532 and miR-362-5p modulates gastric cancer (GC) cell activities. Herein, we elucidated the role of LINC02532 targeting miR-362-5p to mediate p-AKT in GC cells, aiming to provide a theoretical basis for clinical treatment. Human GC cells were treated with si-LINC02532, si-NC, LINC02532+miR-362-5p inhibitor and p-AKT inhibitor. LINC02532 and miR-362-5p expression was determined by RT-qPCR and p-AKT expression was detected. Transwell assay assessed cell invasion and migration upon treatment and the targeting relationship of LINC02532 and miR-362-5p was evaluated. A positive expression of LINC02532 and miR-362-5p was detected in each group of GC cells. The expression of LINC02532 was up-regulated (2.95 ± 0.23) and miR-362-5p was down-regulated (0.35 ± 0.08). Silence of LINC02532 significantly suppressed GC cell behaviors and inhibited migration speed of cancer cells, while p-AKT inhibitor treatment resulted in a decrease in the number of invaded and migrated cells. Combination of LINC02532 and miR-362-5p inhibitor was not effective as previous two treatments, but still decreased cell migration and invasion (p < 0.05). The luciferase experiment indicated LINC02532 targeted miR-362-5p. Down-regulation of LINC02532 also reduced p-AKT protein expression. p-AKT inhibitor group had a lower level of p-AKT protein, followed by LINC02532+miR-362-5p inhibitor group, and si-NC group. In conclusion, silence of LINC02532 reduces miR-362-5p and p-AKT protein expression in GC cells to suppress GC cell growth through inhibition of p-AKT signaling pathway.

Cervical cancer (CC) is the fourth most gynecological malignancy in the world. The identification of predictive markers can provide a basis for personalized treatment and prognostic evaluation. Our aim was to identify a new predictive marker of epiregulin (EREG) gene and explore its functional characteristics of CC and other cancer types. Differentially highly expressed genes were obtained from Gene Expression Omnibus (GEO) databases. Key genes can be verified by the Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) data, and the functions of these genes were investigated through gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Survival analysis were performed to determine the key genes (EREG) related to the prognosis of CC. Then, the expression difference of EREG between tumor and normal tissue was evaluated by real-time polymerase chain reaction (PCR), western blotting, and immunohistochemistry. The relationship between EREG and prognosis of patients, immune microenvironment, immune checkpoint, immune therapy and angiogenesis was discussed in 33 tumor types. Finally, the regulatory mechanism of EREG on human umbilical vein endothelial cells (HUVECs) was also explored. The differential analysis results from multiple databases showed that EREG was significantly highly expressed in CC, which was further verified in Hela and Siha cell lines. Then, Survival analysis revealed that EREG was associated with the prognosis of CC and other tumor types, and high EREG expression was significantly associated with poor prognosis. In addition, in almost all tumor types, the expression of EREG was related to immune cells infiltration, immune checkpoint genes expression and immunotherapy. Further analysis exhibited that high EREG expression can promote the high expression of angiogenesis related genes. The experimental data demonstrated that EREG could promote the proliferative, migration, invasive and tube formation of HUVECs by interacting with receptors, such as epidermal growth factor receptor (EGFR and ERBB4). EREG may be an independent prognostic marker for predicting tumor prognosis and immunotherapy response of various cancers, and may be a potential target of tumor anti-angiogenic therapy in CC.