BACKGROUND

Early-stage endometrial cancer often presents with favorable survival rates, but high-risk factors, including TP53 mutations and high-grade serous pathology, can lead to recurrence and poor prognosis. The standard primary treatment for endometrial cancer is surgical staging, and lymph node metastases significantly impact adjuvant therapy decisions. The subgroup of p53-abnormal (p53abn) indicates the worst prognosis and potential benefits from adjuvant chemotherapy. Molecular classification, while recommended, faces practical challenges due to resource constraints.

OBJECTIVES

The study aimed to assess the incidence of p53 abnormal expression in clinical stage 1 endometrial cancer cases that underwent surgery at a government tertiary hospital, and assess its relationship with clinicopathologic factors and pelvic and paraaortic lymph node metastasis (LNM).

METHODS

A cross-sectional retrospective analysis was conducted on clinical early-stage endometrial cancer cases that underwent surgical primary treatment between January 2018 and December 2022. Patient records were reviewed to gather demographics, surgical information, and pathological evaluations. Preoperative clinical staging was determined through imaging, and surgical staging involved comprehensive lymphadenectomy. Immunohistochemistry studies for p53 were carried out on formalin-fixed paraffin-embedded tissue samples.

RESULTS

A total of 233 endometrial cancer cases were included. The mean age at diagnosis was 53.7 years. Common comorbidities included hypertension (47.2%) and dyslipidemia (20.6%). Most cases were endometrioid histology (82.8%) and low-grade tumors (85.8%). Tumor grade (p=0.010), myometrial invasion (p<0.001) and lymphovascular space invasion (p<0.001) significantly correlated with lymph node metastasis. However, tumor size and p53abn were not significantly associated with lymph node metastasis. p53abn overexpression was significantly associated with non-endometrioid histology at 33% and Grade 3 tumors at 23%. Preoperative grading demonstrated moderate reliability (0.51) with postoperative grading, with an agreement of 65.4%.

CONCLUSION

Tumor grade, myometrial invasion, and LVSI were all significantly associated with lymph node involvement. While p53 immunohistochemical stains show promise in predicting metastasis and has been associated with tumor aggressiveness, this should still be correlated with clinicopathological parameters to carry out a more accurate risk stratification of early-stage patients.

Therapeutics ; Survival Rate ; Risk Factors ; Recurrence ; Prognosis ; Pathology ; Endometrial Neoplasms ; Immunohistochemistry ; Tumor Suppressor Protein P53 ; Lymph Node Excision ; Risk Assessment

OBJECTIVES: Ovarian cancer is a common gynecologic malignancy, with poor prognosis in advanced stages. This study aimed to identify differentially expressed long noncoding RNA (lncRNA) associated with ovarian cancer prognosis and to explore the effects of lncRNA RP11-499E18.1 on the malignant biological behavior of ovarian cancer cells. METHODS: Ovarian cancer-related lncRNA datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed and prognostically relevant tumor-suppressive lncRNAs were screened using lncRNA sequencing combined with clinical data. Reverse transcription PCR (RT-PCR) was used to detect the expression of lncRNA RP11-499E18.1 in ovarian cancer tissues, adjacent normal tissues, the IOSE80 normal ovarian epithelial cell line, and various ovarian cancer cell lines. Fluorescence in situ hybridization (FISH) was performed to determine its subcellular localization. Ovarian cancer cell lines CaOV3 and SKOV3 were divided into 3 groups: a negative control (NC) group, a knockdown (si-RP11-499E18.1) group, and a overexpression (pcDNA-RP11-499E18.1) group. Methyl thiazolyl tetrazolium (MTT) and Transwell assays were used to assess the effects of lncRNA RP11-499E18.1 on cell proliferation and migration. Western blotting was used to evaluate its effect on epithelial-mesenchymal transition (EMT)-related molecules. BALB/c nude mice were injected with CaOV3 cells transfected with pcDNA-RP11-499E18.1 (experimental group) or empty vector (control group), and tumor growth was monitored. Immunohistochemistry was used to assess the expression of Caspase 3 and Ki67 in tumor tissues. RESULTS: LncRNA sequencing identified RP11-499E18.1 as a differentially expressed and associated with prognosis. GEO data analysis showed that low RP11-499E18.1 expression was correlated with shorter overall and progression-free survival (both P<0.05). Its expression was significantly lower in ovarian cancer tissues and cell lines compared to normal controls (P<0.05 or P<0.001), and it was localized in both the nucleus and cytoplasm. In CaOV3 and SKOV3 cells, proliferation rates increased significantly in the si-RP11-499E18.1 group and decreased in the pcDNA-RP11-499E18.1 group (P<0.05 or P<0.001). Cell migration was enhanced in the si-RP11-499E18.1 group and suppressed in the pcDNA-RP11-499E18.1 group. Overexpression increased E-cadherin and decreased vimentin expression, while knockdown had the opposite effect. Tumor volume in the mouse model was significantly smaller in the experimental group (P<0.001), with increased Caspase 3 and decreased Ki67 expression in tumor tissues (both P<0.05). CONCLUSIONS LncRNA RP11-499E18.1 inhibits proliferation, migration, and EMT of ovarian cancer cells, and its low expression is associated with poor prognosis.
Female ; Humans ; RNA, Long Noncoding/physiology* ; Ovarian Neoplasms/pathology* ; Cell Line, Tumor ; Animals ; Mice ; Mice, Nude ; Cell Proliferation ; Prognosis ; Mice, Inbred BALB C ; Gene Expression Regulation, Neoplastic ; Cell Movement ; Epithelial-Mesenchymal Transition

OBJECTIVES: Wild-caught Microtus fortis (M. fortis) at the age of 9-15 months can develop epithelial ovarian cancers similar to human epithelial ovarian cancers under natural conditions during experimental animal breeding, but its pathological types and biological characteristics remain unclear. This study aims to analyze the biological characteristics of spontaneous ovarian cancer in M. fortis, intending to develop M. fortis as an animal model for human epithelial ovarian cancer. METHODS: The female M. fortis (9-15 months old) with spontaneous ovarian cancer were selected as the experimental group, and healthy M. fortis from the same litter were selected as the control group. The ovarian pathological changes of the two groups were observed by dissection. Blood routine and biochemical indicators were measured by biochemical analysis. Hematoxylin and eosin (HE) staining was performed to observe the pathological changes in the ovarian cancer tissue of M. fortis. Immunohistochemical staining was used to detect the protein expression of common ovarian cancer markers, and real-time RT-PCR was used to analyze the transcription levels of ovarian cancer-related genes. RESULTS: Spontaneous ovarian cancer in M. fortis mainly affects both ovaries, with tumors appearing solid or cystic. HE staining and histopathological analysis confirmed that the ovarian tumors originated from ovarian surface epithelium. Compared to the control group, the experimental group showed significantly decreased hemoglobin (P<0.01), hematocrit (P<0.05), albumin (P<0.05), and blood glucose levels (P<0.01), while lymphocyte percentage (P<0.05), monocyte percentage (P<0.05), cholesterol (P<0.01), and progesterone (P<0.01) levels were significantly increased. Expression of ovarian cancer-related genes, including ID3, CDC42, RHOA, RB1CC1, NF1, PIN1, MIB1, PDS5A, MCM7, and MLH1, was significantly downregulated (all P<0.05), while PAX8 gene expression was significantly upregulated (P<0.05). Immunohistochemical results showed that Wilms' tumor gene 1 (WT1) protein was mainly distributed throughout the cell, with significantly higher expression in ovarian cancer M. fortis. Tumor protein 53 (TP53) was expressed in both healthy and ovarian cancer M. fortis and was distributed throughout the cell. Hepatocyte nuclear factor 1 beta (HNF1B) and progesterone receptor (PR) protein were highly expressed in the ovarian tissue of healthy M. fortis but were significantly reduced in the ovarian cancer M. fortis, though both were located in the cytoplasm. CONCLUSIONS Spontaneous ovarian cancer in M. fortis is serous ovarian cancer. Compared to healthy M. fortis, significant differences were observed in ovarian tissue morphology, biochemical indicators, ovarian cancer-related gene expression, and protein expression, which show similarity to the biological characteristics of human serous ovarian cancer. This suggests that M. fortis could be an ideal animal model for studying human serous ovarian cancer.
Female ; Ovarian Neoplasms/metabolism* ; Animals ; Carcinoma, Ovarian Epithelial ; Disease Models, Animal ; Humans ; Neoplasms, Glandular and Epithelial/metabolism* ; Ovary/pathology*

Atypical placental site nodules (APSN) are a rare form of trophoblastic disease in pregnancy. There is limited research on APSN, and treatment methods are controversial, with unclear prognosis. This study collected clinical and prognostic data of 5 patients diagnosed with APSN at Xiangya Hospital of Central South University from June 2008 to June 2023, aiming to provide a better understanding of the prognosis of APSN patients and offer scientific evidence for clinical treatment. The average age of the 5 APSN patients was 32.60 years, and all patients underwent dilation and curettage or hysteroscopic surgery or hysteroscopic surgery without hysterectomy. Except for one patient who was lost to follow-up after 30 days, the remaining 4 patients were followed up for 1.36 to 4.61 years. During the follow-up, gynecological ultrasound did not show abnormalities, and serum human chorionic gonadotropin (HCG) tests were negative, with no evidence of malignancy. A search of both English and Chinese databases yielded 8 articles reporting the diagnosis, treatment, and follow-up outcomes of APSN, with 37 cases cumulatively followed up. Among them, 2 (5.41%) cases developed epithelial trophoblastic tumors or placental site trophoblastic tumors during follow-up, but there is insufficient evidence to determine whether these tumors directly originated from APSN or were secondary to APSN. Currently, there is no direct evidence suggesting that APSN has the potential for malignant transformation. Patients with APSN who have completed their childbearing may consider preserving their uterus, but close follow-up is needed to further evaluate the prognosis.
Humans ; Female ; Pregnancy ; Adult ; Trophoblastic Tumor, Placental Site/pathology* ; Uterine Neoplasms/diagnosis* ; Prognosis ; Dilatation and Curettage ; Chorionic Gonadotropin/blood*

OBJECTIVES: Esophageal squamous cell carcinoma (ESCC) is characterized by complex pathogenesis and poor prognosis. In recent years, epithelial-mesenchymal transition (EMT) in tumor initiation and progression has attracted increasing attention. Enhancer of zeste homolog 2 (EZH2), which is aberrantly expressed in various tumors, may be closely related to the EMT process. This study aims to examine the expression and correlation of EZH2 and EMT markers in ESCC cells and tissues, evaluate the effects of EZH2 knockdown on ESCC cell proliferation, invasion, and migration, and explore how EZH2 contributes to the malignant biological behavior of ESCC. METHODS: Bioinformatics analyses were used to assess EZH2 expression levels in ESCC. Small interfering RNA was used to knock down EZH2 in ESCC cell lines EC109 and EC9706. Cell proliferation, invasion, and migration were evaluated using cell counting kit-8 (CCK-8), wound healing, and Transwell assays. Protein and mRNA expression levels of EZH2, E-cadherin (E-cad), and vimentin (Vim) were detected by Western blotting and real time fluorogenic quantitative PCR (RT-qPCR), respectively. Immunohistochemical (IHC) staining was performed on 70 ESCC tissue samples and 40 paired adjacent normal tissues collected from the First Affiliated Hospital of Shihezi University between 2010 and 2016 to assess the expression of EZH2, E-cad, and Vim, and to analyze their associations with clinicopathological feature and patient prognosis. RESULTS: Bioinformatics analysis showed that EZH2 was highly expressed in ESCC (P<0.001), and high EZH2 expression was associated with worse prognosis (P<0.001). CCK-8, wound healing, and Transwell assays demonstrated that EZH2 knockdown significantly suppressed the proliferation, invasion, and migration of ESCC cells (P<0.001). In addition, Vim expression was significantly reduced, while E-cad expression was significantly increased at both protein and mRNA levels in EZH2-silenced cells (all P<0.05). IHC staining analysis revealed higher expression of EZH2 and Vim and lower expression of E-cad in ESCC tissues compared to adjacent normal tissues. Kaplan-Meier survival analysis showed that low expression of EZH2 and Vim and high expression of E-cad were associated with longer survival (all P<0.05). CONCLUSIONS EZH2 promotes malignant biological behavior in ESCC by mediating EMT. Elevated EZH2 expression is associated with poor prognosis in ESCC patients.
Humans ; Enhancer of Zeste Homolog 2 Protein/physiology* ; Esophageal Squamous Cell Carcinoma/pathology* ; Epithelial-Mesenchymal Transition/genetics* ; Esophageal Neoplasms/metabolism* ; Cell Proliferation ; Cell Line, Tumor ; Cell Movement ; Cadherins/genetics* ; Vimentin/genetics* ; Male ; Female ; Middle Aged ; Neoplasm Invasiveness ; Prognosis ; RNA, Small Interfering/genetics* ; Gene Expression Regulation, Neoplastic

OBJECTIVES: Hepatocellular carcinoma is one of the most common primary malignant tumors with the third highest mortality rate worldwide. This study aims to identify key genes associated with hepatocellular carcinoma prognosis using the Gene Expression Omnibus (GEO) database and provide a theoretical basis for discovering novel prognostic biomarkers for hepatocellular carcinoma. METHODS: Hepatocellular carcinoma-related datasets were retrieved from the GEO database. Differentially expressed genes (DEGs) were identified using the GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and key genes were identified using Cytoscape software. The University of Alabama at Birmingham Cancer Data Analysis Resource (UALCAN) was used to analyze the expression levels of key genes in normal and hepatocellular carcinoma tissues, as well as their associations with pathological grade, clinical stage, and patient survival. The Human Protein Atlas (THPA) was used to further validate the impact of key genes on overall survival. Expression levels of key genes in the blood of hepatocellular carcinoma patients were evaluated using the expression atlas of blood-based biomarkers in the early diagnosis of cancers (BBCancer). RESULTS: A total of 78 DEGs were identified from the GEO database. GO and KEGG analyses indicated that these genes may contribute to hepatocellular carcinoma progression by promoting cell division and regulating protein kinase activity. Sixteen key genes were screened via Cytoscape and validated using UALCAN and THPA. These genes were overexpressed in hepatocellular carcinoma tissues and were associated with disease progression and poor prognosis. Finally, BBCancer analysis showed that ASPM and NCAPG were also elevated in the blood of hepatocellular carcinoma patients. CONCLUSIONS This study identified 16 key genes as potential prognostic biomarkers for hepatocellular carcinoma, among which ASPM and NCAPG may serve as promising blood-based markers for hepatocellular carcinoma.
Humans ; Carcinoma, Hepatocellular/mortality* ; Liver Neoplasms/pathology* ; Prognosis ; Computational Biology/methods* ; Protein Interaction Maps/genetics* ; Biomarkers, Tumor/genetics* ; Gene Expression Regulation, Neoplastic ; Gene Expression Profiling ; Gene Ontology ; Databases, Genetic

OBJECTIVES: In recent years, the incidence and detection rate of pancreatic cystic lesions (PCLs) have increased significantly. Endoscopic ultrasound (EUS) plays an indispensable role in the diagnosis and differential diagnosis of PCLs. However, evidence comparing the diagnostic performance of EUS-guided fine-needle aspiration (EUS-FNA) and fine-needle biopsy (FNB) remains limited. This study aims to compare the diagnostic yield, adequacy of tissue acquisition, and safety between EUS-FNA and EUS-FNB in evaluating PCLs to inform clinical practice. METHODS: A retrospective review was conducted on patients with PCLs who underwent either EUS-FNA or EUS-FNB between January 2014 and August 2021. The diagnostic yield, tissue acquisition adequacy, and incidence of adverse events were compared between the 2 groups. RESULTS: A total of 90 patients with PCLs were included (52 in the FNA group and 38 in the FNB group). The diagnostic yield was similar between the FNA and FNB groups (94.2% vs 94.7%, P>0.05). The adequacy of tissue acquisition was 71.2% in the FNA group and 81.6% in the FNB group (P>0.05). No statistically significant difference was observed in the incidence of adverse events between the 2 groups (P>0.05). CONCLUSIONS Both EUS-FNA and EUS-FNB demonstrate equally high diagnostic yields and tissue adequacy in PCLs, with excellent safety profiles. Both methods are safe and effective diagnostic tools for evaluating PCLs.
Humans ; Endoscopic Ultrasound-Guided Fine Needle Aspiration/adverse effects* ; Retrospective Studies ; Female ; Male ; Pancreatic Cyst/diagnostic imaging* ; Middle Aged ; Biopsy, Fine-Needle/adverse effects* ; Aged ; Pancreatic Neoplasms/diagnosis* ; Adult ; Endosonography/methods* ; Pancreas/pathology* ; Diagnosis, Differential

OBJECTIVES: Verrucous epidermal nevus (VEN), seborrheic keratosis (SK), verruca plana (VP), verruca vulgaris (VV), and nevus sebaceous (NS) are common verrucous proliferative skin diseases with similar clinical appearances, often posing diagnostic challenges. Dermoscopy and reflectance confocal microscopy (RCM) can aid in their differentiation, yet their specific features under these tools have not been systematically described. This study aims to summarize and analyze the dermoscopic and RCM features of VEN, SK, VP, VV, and NS. METHODS: A total of 121 patients with histopathologically confirmed verrucous proliferative skin diseases were enrolled. Dermoscopy and RCM imaging was used to observe and analyze the microscopic features of these conditions. RESULTS: Under dermoscopy, the 5 diseases displayed distinct characteristics: VEN typically showed gyriform structures; SK was characterized by gyriform structures, comedo-like openings, and milia-like cysts; VP and VV featured dotted vessels and frogspawn-like structures; NS presented as brownish-yellow globules. RCM revealed shared features such as hyperkeratosis and acanthosis across all 5 diseases. Specific features included gyriform structures and elongated rete ridges in VEN; pseudocysts and gyriform structures in SK; evenly distributed ring-like structures in VP; vacuolated cells and papillomatous proliferation in VV; and frogspawn-like structures in NS. CONCLUSIONS These 5 verrucous proliferative skin conditions exhibit distinguishable features under both dermoscopy and RCM. The combination of these 2 noninvasive imaging modalities holds significant clinical value for the differential diagnosis of verrucous proliferative skin diseases.
Humans ; Dermoscopy/methods* ; Diagnosis, Differential ; Microscopy, Confocal/methods* ; Male ; Female ; Adult ; Middle Aged ; Adolescent ; Keratosis, Seborrheic/pathology* ; Young Adult ; Warts/diagnosis* ; Child ; Aged ; Skin Diseases/pathology* ; Nevus, Sebaceous of Jadassohn/diagnosis* ; Skin Neoplasms/diagnosis* ; Child, Preschool

OBJECTIVES: Lymph node metastasis in papillary thyroid cancer (PTC) is closely associated with tumor recurrence and patient survival. However, current technologies have limited sensitivity in detecting occult cervical lymph node metastases. Identifying accurate molecular markers for predicting PTC metastasis holds significant clinical value. This study aims to analyze WNT10A expression in PTC and its clinical significance, and to explore the role of WNT10A gene knockdown in PTC cell proliferation, invasion, and metastasis. METHODS: The expression of WNT10A in thyroid carcinoma was analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) and University of Alabama at Birminghara Cancer data analysis Portal (UALCAN) databases. Real-time RT-PCR was used to measure WNT10A mRNA levels in tumor and adjacent normal tissues from 32 PTC patients. Immunohistochemistry was conducted on 158 PTC specimens to assess WNT10A protein expression and its correlation with clinicopathological features. In vitro experiments were performed using K1 and TPC-1 cell lines. Cell proliferation was assessed using the Celigo system and methyl thiazolyl tetrazolium (MTT) assays; apoptosis was measured via flow cytometry; invasion and metastasis were evaluated using scratch and Transwell assays. A xenograft model was established in nude mice to observe tumor growth, and tumor weight and volume were compared between cell lines. Differentially expressed genes regulated by WNT10A were identified via mRNA sequencing, followed by Gene Ontology (GO) and ingenuity pathway analysis (IPA). Real-time PCR and Western blotting were used to validate the effects of WNT10A on key downstream mRNA and protein in the Tec kinase signaling pathway. RESULTS: WNT10A mRNA expression was significantly higher in thyroid cancer tissues compared to adjacent normal tissues according to GEPIA and UALCAN (both P<0.01). The real-time RT-PCR result showed that WNT10A mRNA expression in PTC tissues was high than that in adjacent tissues (P<0.01). Immunohistochemistry revealed significantly higher WNT10A protein expression in PTC tissues compared to adjacent tissues (P<0.01), and its expression correlated with multifocality, extrathyroidal invasion, and lymph node metastasis. WNT10A knockdown significantly inhibited proliferation, altered cell cycle distribution, and increased apoptosis in K1 and TPC-1 cells (all P<0.01). WNT10A silencing also reduced migration and invasion abilities in both cell lines. In vivo, WNT10A knockdown in TPC-1 cells suppressed tumor formation in nude mice. GO analysis and IPA suggested that the Tec kinase signaling pathway was a key downstream target of WNT10A. RT-PCR and Western blotting confirmed that WNT10A knockdown downregulated the expression of key genes (STAT3, MAPK8, TNFRSF21, and AKT2) in this pathway. CONCLUSIONS WNT10A is highly expressed in PTC and is associated with tumor proliferation, invasion, and metastasis. Its tumor-promoting effects may be mediated through suppression of the Tec kinase signaling pathway.
Humans ; Cell Proliferation ; Thyroid Cancer, Papillary/pathology* ; Thyroid Neoplasms/metabolism* ; Animals ; Wnt Proteins/metabolism* ; Neoplasm Invasiveness ; Mice ; Cell Line, Tumor ; Female ; Male ; Mice, Nude ; Apoptosis ; Lymphatic Metastasis ; Middle Aged ; Cell Movement ; Adult

OBJECTIVES: Renal cell carcinoma (RCC) is a malignant renal tumor that poses a significant threat to patient health. Accurate preoperative pathological grading plays a crucial role in determining the appropriate treatment for this disease. Currently, deep learning technology has become an important method for pathological grading of RCC. However, existing methods primarily rely on single-phase computed tomography (CT) imaging for analysis and prediction, which has limitations such as missing small lesions, one-sided evaluation, and local focusing issues. Therefore, this study proposes a multi-modal deep learning algorithm that integrates multi-phase enhanced CT images with clinical variable data, aiming to provide a basis for predicting the pathological grading of RCC. METHODS: First, the algorithm took four-phase enhanced CT images from the plain scan, arterial phase, venous phase, and delayed phase, along with clinical variables, as inputs. Then, an embedding encoding module was used to extract heterogeneous information from the clinical variables, and a 3-dimensional (3D) ResNet50 model was employed to capture spatial information from the multi-phase enhanced CT image data. Finally, a Fusion module deeply integrated the feature information from clinical variables and each phase's CT image features, further utilizing a cross-self-attention mechanism to achieve multi-phase feature fusion. This approach comprehensively captures the deep semantic information from the patient data, fully leveraging the complementary advantages of multi-modal and multi-phase data. To validate the effectiveness of the proposed method, a total of 1 229 RCC patients were approved by ethics review were included to train the model. RESULTS: Experimental results demonstrated superior performance compared to traditional radiomics and state-of-the-art deep learning methods, achieving an accuracy of 83.87%, a recall rate of 95.04%, and an F1-score of 82.23%. CONCLUSIONS The proposed algorithm exhibits strong stability and sensitivity, significantly enhancing the predictive performance of RCC pathological grading. It offers a novel approach for accurate RCC diagnosis and personalized treatment planning.
Humans ; Carcinoma, Renal Cell/pathology* ; Deep Learning ; Kidney Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed/methods* ; Algorithms ; Neoplasm Grading ; Male ; Female ; Middle Aged