Machine learning constructs a T cell-related signature for predicting prognosis and drug sensitivity in ovarian cancer.

BACKGROUND: The leading cause of death related to gynecologic cancer is ovarian cancer, which typically has a poor prognosis. T cells are referred to as key mediators of immunosurveillance and tumor eradication, and unbalanced regulation or lack of T cells in tumors result in immunotherapy resistance. METHODS: The identification of T cell related markers depended on single-cell RNA-seq analysis. Using data from multiple datasets, including TCGA, GSE14764, GSE26193, GSE26712, and GSE140082, we constructed a prognostic signature called TRS (T cell-related signature) using 10 different machine learning algorithms. The correlation between TRS and drug sensitivity were analyzed using the data from GSE91061 and IMvigor210 dataset. RESULTS: PlsRcox method based TRS was as a risk factor for the clinical outcome of ovarian cancer patients. In comparison with stage, grade and many prognostic signatures, the performance of our TRS in evaluating the clinical outcome was better in ovarian cancer. TRS-based risk score showed distinct association with the level of ESTIMATE score, immune-related function score and immune cells. Moreover, TRS could be used to predict the immunotherapy response and chemotherapy response in ovarian cancer. CONCLUSION: In conclusion, we constructed a powerful TRS in ovarian cancer, which could accurately predict the clinical outcome of patients and be used to predict the immunotherapy response and chemotherapy response.

Preoperative sST2 levels relate to myocardial remodeling and cardiac function improvement after cardiac valve surgery.

AIMS: We aim to investigate the correlation between preoperative soluble suppression of tumourigenicity 2 (sST2) and postoperative myocardial remodelling and cardiac function in patients with valvular heart disease. METHODS AND RESULTS: This retrospective study included patients who underwent heart valve surgery at the General Hospital of Northern Theatre Command from July 2019 to June 2020. Preoperative, early postoperative, and 1-month postoperative cardiac ultrasound data were collected. Multivariable linear regression was used to analyse the factors associated with preoperative sST2 and postoperative cardiac function parameters. A receiver operator characteristic curve analysis was used to analyse the predictive value of sST2 for left ventricular ejection fraction (LVEF) reduction at 1 month after surgery. This study included 156 patients. Left ventricular end-systolic volume (b = 0.125, P = 0.004), atrial fibrillation (b = 7.933, P = 0.003), and coronary artery disease (b = 5.826, P = 0.043) were correlated with the preoperative sST2 levels. Preoperative sST2 was independently associated with early postoperative left ventricular end-systolic volume (b = -0.136, P = 0.035), left ventricular end-diastolic volume (b = -0.225, P = 0.036), and LVEF (b = 0.056, P = 0.008). At 1 month after surgery, LVEF (r = -0.234, P = 0.023) and reduction in LVEF (r = -0.316, P = 0.002) were negatively correlated with preoperative sST2. The area under the receiver operator characteristic curve of preoperative sST2 in predicting LVEF reduction at 1 month was 0.646, with a sensitivity of 0.357 and a specificity of 0.918. CONCLUSIONS: Preoperative sST2 levels are related to early postoperative myocardial remodelling and have a predictive value for the improvement of cardiac function 1 month after surgery.

USP43 impairs cisplatin sensitivity in epithelial ovarian cancer through HDAC2-dependent regulation of Wnt/ß-catenin signaling pathway.

Epithelial ovarian cancer (EOC) is the leading cause of cancer death all over the world. USP43 functions as a tumor promoter in various malignant cancers. Nevertheless, the biological roles and mechanisms of USP43 in EOC remain unknown. In this study, USP43 was highly expressed in EOC tissues and cells, and high expression of USP43 were associated with a poor prognosis of EOC. USP43 overexpression promoted EOC cell proliferation, enhanced the ability of migration and invasion, decreased cisplatin sensitivity and inhibited apoptosis. Knockdown of USP43 in vitro effectively retarded above malignant progression of EOC. In vivo xenograft tumors, silencing USP43 slowed tumor growth and enhanced cisplatin sensitivity. Mechanistically, USP43 inhibited HDAC2 degradation and enhanced HDAC2 protein stability through its deubiquitylation function. USP43 diminished the sensitivity of EOC cells to cisplatin through activation of the Wnt/ß-catenin signaling pathway mediated by HDAC2. Taken together, the data in this study revealed the functions of USP43 in proliferation, migration, invasion, chemoresistance of EOC cells, and the mechanism of HDAC2-mediated Wnt/ß-catenin signaling pathway. Thus, USP43 might serve as a potential target for the control of ovarian cancer progression.

A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning.

BACKGROUND: Ovarian cancer ranks the leading cause of gynecologic cancer-related death in the United States and the fifth most common cause of cancer-related mortality among American women. Increasing evidences have highlighted the vital role of macrophages M2/M1 proportion in tumor progression, prognosis and immunotherapy. METHODS: Weighted gene co-expression network analysis (WGCNA) was performed to identify macrophages related markers. Integrative procedure including 10 machine learning algorithms were performed to develop a prognostic macrophage related signature (MRS) with TCGA, GSE14764, GSE140082 datasets. The role of MRS in tumor microenvironment (TME) and therapy response was evaluated with the data of CIBERSORT, MCPcounter, QUANTISEQ, XCELL, CIBERSORT-ABS, TIMER and EPIC, GSE91061 and IMvigor210 dataset. RESULTS: The optimal MRS developed by the combination of CoxBoost and StepCox[forward] algorithm served as an independent risk factor in ovarian cancer. Compared with stage, grade and other established prognostic signatures, the current MRS had a better performance in predicting the overall survival rate of ovarian cancer patients. Low risk score indicated a higher TME score, higher level of immune cells, higher immunophenoscore, higher tumor mutational burden, lower TIDE score and lower IC50 value in ovarian cancer. The survival prediction nomogram had a good potential for clinical application in predicting the 1-, 3-, and 5-year overall survival rate of ovarian cancer patients. CONCLUSION: All in all, the current study constructed a powerful prognostic MRS for ovarian cancer patients using 10 machine learning algorithms. This MRS could predict the prognosis and drug sensitivity in ovarian cancer.

Comprehensive Analysis of the Expression and Prognosis for MCM4 in Uterine Corpus Endometrial Carcinoma.

Background: Mini chromosome maintenance protein 4 (MCM4) belongs to the family of mini chromosome maintenance proteins (MCMs) that plays a crucial role in DNA replication and cell cycle regulation. Given that MCM4 has been reported to be aberrantly expressed in a variety of tumor tissues, and is strongly associated with poor patient prognosis, it has rarely been reported in uterine corpus endometrial carcinoma (UCEC). Methods: We explored the role of MCM4 in UCEC through multi-omics analysis, including gene expression levels, survival prognosis, the biological function of interacting proteins, immune infiltration, and diagnostic value. Finally, these results were confirmed by biological experiments. Results: MCM4 was highly expressed in various malignancies including UCEC compared to normal samples and was associated with poor prognosis in patients with UCEC [including OS (HR = 1.74, p = 0.009), PFI (HR = 1.73, p = 0.002), PFI (HR = 2.23, p = 0.003)]. In the Cox regression analysis, MCM4 was an independent prognostic biomarker. Further studies showed those interacting proteins of MCM4 were enriched in DNA repair and cell cycle. Moreover, high expression of MCM4 was accompanied by lower infiltration of immune cells such as Treg cells and B cells. The distribution of MCM4 expression in molecular and immune subtypes was significantly different (p < 0.05), with high expression in the copynumber high (CN_HIGH) molecular subtype and the IFN-gamma dominant (C2) immune subtype. RT-qPCR and immunohistochemistry results also showed that MCM4 expression was significantly upregulated in endometrial cancer tissues and negatively correlated with patient prognosis (p < 0.05). Subsequent biological experiments confirmed that MCM4 promoted cell growth and invasion and inhibited apoptosis in vitro. Conclusion: Therefore, MCM4 could be a new potential biomarker for UCEC.

MicroRNA miR-106a-5p targets forkhead box transcription factor FOXC1 to suppress the cell proliferation, migration, and invasion of ectopic endometrial stromal cells via the PI3K/Akt/mTOR signaling pathway.

Emerging evidence has exhibited an obvious decreased expression of miR-106a-5p in the ectopic endometrial tissue of endometriosis (EMS) patients. Thus far, the pathophysiological function of miR-106a-5p in EMS is unknown. A previous study showed an increased FOXC1 expression in the ectopic endometrial tissue of patients with EMS. Moreover, we found that there was a binding site of miR-106a-5p on the 3'UTR of FOXC1 through bioinformatics predictions. Hence, we speculated that miR-106a-5p might affect the development of EMS via targeting FOXC1. We first showed a decreased level of miR-106a-5p and an increased level of FOXC1 mRNA in ectopic endometrial tissues compared with normal tissues. Functionally, we transfected ectopic endometrial stromal cells (ESCs) with miR-106a-5p mimics or NC mimics and indicated an inhibitory role of miR-106a-5p on ESC proliferation, invasion, and migration. Mechanistically, FOXC1 was found to be a target gene of miR-106a-5p. To confirm whether miR-106a-5p exerted an inhibitory activity in ESCs via targeting FOXC1, miR-106a-5p mimic was co-transfected into ESCs with the FOXC1-plasmid or vector. We found that FOXC1 overexpression evidently reversed the results caused by a miR-106a-5p mimic in ESCs. Additionally, our results demonstrated that miR-106a-5p mimic inhibited the expression of p-Akt and p-PI3K. Collectively, these results revealed that miR-106a-5p inhibited the proliferative, migratory, and invasive ability of ESCs via directly binding to FOXC1, likely through the suppression of the PI3K and its downstream signaling pathway, which offered a potential and novel therapeutic strategy for EMS treatment.

Syringic acid regulates suppression of the STAT3/JNK/AKT pathway via inhibition of human ovarian teratoma cancer cell (PA-1) growth-in vitro study.

Among the various gynaecological cancers, ovarian cancer (OC) is the third most severe cancer worldwide affecting women. Syringic acid (SRA) exhibits several hypoglycaemia, antioxidant, and anti-inflammatory properties. The study aimed to examine the proapoptotic activities of SRA on OC in PA-1 cells. SRA has been shown to decrease cell viability, increase the rate of cell apoptosis, and cause mitochondrial membrane potential to dissipate and induce over-accumulation of intracellular reactive oxygen species in PA-1 cells after 24 h of exposure. We examined the anticancer efficacy of SRA with its responsible molecular mechanism in the PA-1 cell lines of human OC. In a dose-dependent manner, SRA substantially suppressed cell proliferation and migration. SRA exhibited significant downregulation of cyclins including CDK2, CDK4, and Cyclin D1 responsible for cell-cycle regulation. The apoptosis-mediated anticancer activity was mainly mediated through caspase-3, caspase-8, caspase-9 and Bax upregulation, and Bcl-2 downregulation. We report that SRA significantly inhibits the expression of signal transducer and activator of transcription 3 (STAT3), c-Jun N-terminal kinase (JNK), P65, and protein kinase B (AKT) pathways. These findings depict the effective inhibition of STAT3, p38, and AKT expression by SRA, making it a potential therapeutic candidate for human OC.

[Changes of maternal plasma and umbilical cord plasma inhibin and epidermal growth factor in patients with hypertensive disorder complicating pregnancy].

OBJECTIVE: To study the levels of inhibin (INH) and epidermal growth factor (EGF) in maternal plasma and umbilical cord plasma of patients with hypertensive disorder complicating pregnancy, and to explore their influence on the disease and fetal growth. METHODS: Enzyme linked immunosorbent assay (ELISA) was used to detect maternal and umbilical cord plasma INH and EGF levels in 65 patients with hypertensive disorder complicating pregnancy (test groups) and 21 normal pregnant women (control group). RESULTS: Plasma level of INH in test groups (499 +/- 52) ng/L was significantly higher than that (421 +/- 36) ng/L in control group (P < 0.01); however, the umbilical cord plasma level of INH had no significant difference (P > 0.05). Plasma level of EGF in test groups (408 +/- 60) ng/L was significantly lower than that (463 +/- 87) ng/L in control group (P < 0.05), also there was significant difference in umbilical cord plasma level of two groups (232 +/- 99) ng/L vs (380 +/- 97) ng/L (P < 0.01). The level of EGF in umbilical cord blood was positively correlated with newborn's body weight and placental weight. CONCLUSIONS: Plasma levels of INH and EGF in pregnancy women are related with hypertensive disorder complicating pregnancy. EGF level of umbilical cord blood affects the growth of fetus and placenta.