A model of tertiary lymphatic structure-related prognosis for penile squamous cell carcinoma.

BACKGROUND: We investigated the feasibility of the tertiary lymphoid structure (TLS) as a prognostic marker for penile squamous cell carcinoma(SCC). METHODS: We retrospectively collected data from 83 patients with penile squamous cell carcinoma. H&E-stained slides were reviewed for TLS density. In addition, clinical parameters were analyzed, the prognostic value of these parameters on overall survival (OS) was evaluated using ‒ Kaplan-Meier survival curves, and the prognostic value of influencing factors was evaluated using Cox multifactor design nomogram analysis. RESULT: BMI, T, N, and M are significant in the survival curve with or without tertiary lymphoid structure. BMI, T, N, M and TLS were used to construct a prognostic model for penile squamous cell carcinoma, and the prediction accuracy reached a consensus of 0.884(0.835-0.932), and the decision consensus reached 0.581(0.508-0.655). CONCLUSION: TLS may be a positive prognostic factor for penile squamous cell carcinoma, and the combination of BMI, T, N and M can better evaluate the prognosis of patients.

CT-Based Radiomics and Machine Learning for Differentiating Benign, Borderline, and Early-Stage Malignant Ovarian Tumors.

To explore the value of CT-based radiomics model in the differential diagnosis of benign ovarian tumors (BeOTs), borderline ovarian tumors (BOTs), and early malignant ovarian tumors (eMOTs). The retrospective research was conducted with pathologically confirmed 258 ovarian tumor patients from January 2014 to February 2021. The patients were randomly allocated to a training cohort (n = 198) and a test cohort (n = 60). By providing a three-dimensional (3D) characterization of the volume of interest (VOI) at the maximum level of images, 4238 radiomic features were extracted from the VOI per patient. The Wilcoxon-Mann-Whitney (WMW) test, least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM) were employed to select the radiomic features. Five machine learning (ML) algorithms were applied to construct three-class diagnostic models. Leave-one-out cross-validation (LOOCV) was implemented to evaluate the performance of the radiomics models. The test cohort was used to verify the generalization ability of the radiomics models. The receiver-operating characteristic (ROC) was used to evaluate diagnostic performance of radiomics model. Global and discrimination performance of five models was evaluated by average area under the ROC curve (AUC). The average ROC indicated that random forest (RF) diagnostic model in training cohort demonstrated the best diagnostic performance (micro/macro average AUC, 0.98/0.99), which was then confirmed with by LOOCV (micro/macro average AUC, 0.89/0.88) and external validation (test cohort) (micro/macro average AUC, 0.81/0.79). Our proposed CT-based radiomics diagnostic models may effectively assist in preoperatively differentiating BeOTs, BOTs, and eMOTs.

Diagnostic value of a CT-based radiomics nomogram for discrimination of benign and early stage malignant ovarian tumors.

BACKGROUND: This study aimed to identify the diagnostic value of models constructed using computed tomography-based radiomics features for discrimination of benign and early stage malignant ovarian tumors. METHODS: The imaging and clinicopathological data of 197 cases of benign and early stage malignant ovarian tumors (FIGO stage I/II), were retrospectively analyzed. The patients were randomly assigned into training data set and validation data set. Radiomics features were extracted from images of plain computed tomography scan and contrast-enhanced computed tomography scan, were then screened in the training data set, and a radiomics model was constructed. Multivariate logistic regression analysis was used to construct a radiomic nomogram, containing the traditional diagnostic model and the radiomics model. Moreover, the decision curve analysis was used to assess the clinical application value of the radiomics nomogram. RESULTS: Six textural features with the greatest diagnostic efficiency were finally screened. The value of the area under the receiver operating characteristic curve showed that the radiomics nomogram was superior to the traditional diagnostic model and the radiomics model (P < 0.05) in the training data set. In the validation data set, the radiomics nomogram was superior to the traditional diagnostic model (P < 0.05), but there was no statistically significant difference compared to the radiomics model (P > 0.05). The calibration curve and the Hosmer-Lemeshow test revealed that the three models all had a great degree of fit (All P > 0.05). The results of decision curve analysis indicated that utilization of the radiomics nomogram to distinguish benign and early stage malignant ovarian tumors had a greater clinical application value when the risk threshold was 0.4-1.0. CONCLUSIONS: The computed tomography-based radiomics nomogram could be a non-invasive and reliable imaging method to discriminate benign and early stage malignant ovarian tumors.

Computed tomography-based texture assessment for the differentiation of benign, borderline, and early-stage malignant ovarian neoplasms.

OBJECTIVE: This study was performed to examine the value of computed tomography-based texture assessment for characterizing different types of ovarian neoplasms. METHODS: This retrospective study involved 225 patients with histopathologically confirmed ovarian tumors after surgical resection. Two different data sets of thick (5-mm) slices (during regular and portal venous phases) were analyzed. Raw data analysis, principal component analysis, linear discriminant analysis, and nonlinear discriminant analysis were performed to classify ovarian tumors. The radiologist's misclassification rate was compared with the MaZda (texture analysis software) findings. The results were validated with the neural network classifier. Receiver operating characteristic curves were analyzed to determine the performances of different parameters. RESULTS: Nonlinear discriminant analysis had a lower misclassification rate than the other analyses. Thirty texture parameters significantly differed between the two groups. In the training set, WavEnLH_s-3 and WavEnHL_s-3 were the optimal texture features during the regular phase, while WavEnHH_s-4 and Kurtosis seemed to be the most discriminative features during the portal venous phase. In the validation test, benign versus malignant tumors and benign versus borderline lesions were well-distinguished. CONCLUSIONS: Computed tomography-based texture features provide a useful imaging signature that may assist in differentiating benign, borderline, and early-stage ovarian cancer.

Transcription factor c-Rel regulated by E5 affects the whole process after HPV16 infection through miR-133a-modulated feedback loop aim at mir-379-369 cluster.

BACKGROUND: During the development of cervical cancer, HPV infection causes a series of changes in transcription factors and microRNAs. But their relationships with pathogenic processes are not clear. METHODS: Base on previous study, to analyse the relationship among HPV16 infection and the related transcription factors, related miRNAs, so as to further understand the molecular mechanism of HPV16 infection to cervical cancer, around the HPV16 related miRNAs we have reported, the methods of bioinformatics prediction, histology, cell model in vitro and molecular interaction were used for prediction and validation respectively RESULTS: The results showed that NF-κB family members(c-Rel, p65 and p50) were identified as main HPV16rmiR-transcription factors. They have different expressive characteristics in cervical lesions and play tumorigenesis or progression roles in different periods of HPV16 infection. c-Rel, p65 and p50 act as mediators which link the HPV16 E5 and HPV16 related miRNAs. Among them, c-Rel affects the occurrence and progression of cervical cancer during whole HPV16 infection stage through miR133a-3p-modulated mir-379-369 cluster with a positive feedback way which targeted c-Rel itself and its positive regulator AKT3. CONCLUSION: So in the course of HPV16 infection, the E5, c-Rel, and miR-133a-3p form a positive feedback system which aim at mir-379-369 cluster for the whole process from HPV16 infection to cervical cancer.

Urine-based regenerative RNA biomarkers for urinary bladder wound healing.

Background: This study aimed to investigate the expression of regeneration-related genes in canine urine during bladder repair. Materials & methods: Canine urine samples were collected after partial cystectomy. Regenerative mRNA of hypoxia-inducible factor (HIF), vascular endothelial growth factor (VEGF), key stem cell transcription factors and cholinergic signals were detected. Results: HIF-1α, VEGF, CD44, IL-6 and prominin-1 expression in canine urine after partial cystectomy exhibited two similar peaks at ∼2 weeks. HIF-1α and VEGF expression were higher in the afternoon than the morning. The expression of key stem cell transcription factors and cholinergic signals also exhibited a rhythm along with bladder healing. Conclusions: The expression of HIF-1α, VEGF, key stem cell transcription factors and cholinergic signals exhibited a time curve distribution during canine bladder healing. The expression trend of some regenerative genes was similar during bladder healing, and a cooperative effect may exist.

α-Tomatine, a novel early-stage autophagy inhibitor, inhibits autophagy to enhance apoptosis via Beclin-1 in Skov3 cells.

Targeting the autophagy process is considered to be a promising new strategy for drug treatment of ovarian cancer. α-Tomatine, a steroidal alkaloid extracted, is mainly isolated from leaves, roots and immature green tomatoes. α-Tomatine has biological activities such as anticancer, antioxidative and anti-inflammatory. The study aimed to explore the effects of α-tomatine on proliferation, apoptosis and autophagy and the underlying mechanisms in ovarian cancer Skov3 cells. After treatment with different concentrations of α-tomatine (0, 0.75, 1 and 1.5 µM) in Skov3 cells for 24 h, proliferation was determined by the CCK-8 assay, and apoptosis was detected by flow cytometric analysis. Autophagy in cells was determined by the number of fluorescent spots using confocal fluorescence microscopy after mRFP-GFP-LC3 transfection. The relationship between autophagy and apoptosis was proved by Beclin-1 overexpression. The protein expression levels were tested by western blotting. The results demonstrated that α-tomatine effectively repressed proliferation, exerted a proapoptotic effect and inhibited early-stage autophagy in Skov3 cells in a dose- and time-dependent manner. Additionally, Beclin-1 overexpression significantly suppressed α-tomatine-treated apoptosis in Skov3 cells, indicating that α-tomatine inhibits autophagy to induce apoptosis. We also found α-tomatine inhibited the protein expression levels of PI3K/Akt/mTOR signaling pathway. However, the autophagy inhibition of α-tomatine could be reversed obviously by Beclin-1 overexpression. Taken together, α-tomatine inhibited autophagy through Beclin-1. Our study suggests that α-tomatine, as a novel early-stage autophagy inhibitor, might be a potential drug for further treatment of ovarian cancer by inhibiting proliferation and promoting apoptosis.

The Validity of Using Human Squamous Cell Carcinoma Associated Antigen and Cytokeratin 19 Fragment Antigen 21-1 to Predict Postoperative Adjuvant Radiotherapy for Nonbulky Early-Stage Squamous Cell Carcinoma of the Cervix.

OBJECTIVE: There are no generally accepted biomarkers for the optimal selection of radiotherapy-based or surgical-based treatment options for nonbulky early-stage squamous cell carcinoma of the cervix (IA1-IB1 and IIA1). The objective of this study was to assess the value of human squamous cell carcinoma-associated antigen (SCC-Ag) and cytokeratin 19 fragment antigen 21-1 (CYFRA21-1) in evaluation of patients with nonbulky early-stage squamous cell carcinoma of the cervix to determine if radiotherapy is warranted after radical surgery. METHODS: Patients with stage IA1-IB1 and IIA1 squamous cell carcinoma of the cervix who were treated at the Department of Gynecological Oncology, Affiliated Tumor Hospital of Guangxi Medical University, from March 2012 to August 2014 (n = 308) were treated with radical hysterectomy and pelvic lymphadenectomy. The levels of SCC-Ag and CYFRA21-1 were detected by enzyme-linked immunosorbent assay before surgery. The relationship between the concentrations of SCC-Ag and CYFRA21-1 and risk factors was estimated through logistic regression and analysis of variance t test. The cutoff values of these 2 markers to evaluate the need for postoperative radiotherapy were identified and validated by receiver operating characteristic curve and κ consistency test, respectively. RESULTS: Serum SCC-Ag and CYFRA21-1 levels are significantly increased in patients who require postoperative radiotherapy with a risk factor score of at least 2 (n = 162). Logistic regression analysis revealed that deep stromal invasion and lymph node metastasis are independent risk factors for serum SCC-Ag value, and deep stromal invasion is an independent risk factor for the serum CYFRA21-1 value. Receiver operating characteristic curve revealed that the best predictive cutoff points of SCC-Ag and CYFRA21-1 values were 1.425 and 3.210 ng/mL, respectively. These results were validated by the κ consistency test applied to a validation group of patients. The results suggest that most patients with SCC-Ag and CYFRA21-1 values of at least 1.425 and 3.210 ng/mL, respectively, require postoperative radiotherapy. CONCLUSIONS: Detection of the levels of SCC-Ag and CYFRA21-1 may help guide an individual primary treatment plan for patients with nonbulky early-stage squamous cell carcinoma of the cervix.

Prognostic value and characterization of the ovarian cancer-specific antigen CA166-9.

COC166-9 is an ovarian cancer-specific monoclonal antibody, and COC166-9-based immunotherapy has been shown to possess killing effects against ovarian cancer cells in vitro and in vivo. However the antigen recognized by COC166-9 (COC166-9-Ag, CA166-9) has not been identified and the clinical significance of CA166-9 expression remains unknown. We found that CA166-9 was positive in 53.1% of ovarian cancer tissues. Expression of CA166-9 was strongly correlated with the cancer recurrence (P<0.001). Patients with positive CA166-9 had substantially shorter overall survival (P=0.026) and disease-free survival (P=0.002). CA166-9 was also shown to be an independent predictive factor for overall survival (HR=2.454, P=0.016) and disease-free survival (HR=2.331, P=0.021). We identified CA166-9 as human immunoglobulin γ-1 heavy chain constant region (IGHG1). Purified IGHG1 promoted proliferation, migration, and invasion of CA166-9-negative ovarian cancer HOC1A cells, whereas it had minimal effects on the phenotypes of CA166-9-positive ovarian cancer CAOV-3 cells. In addition, overexpression of IGHG1 enhanced migration of ovarian cancer cells. On the contrary, COC166-9 inhibited proliferation, migration, and invasion of CAOV-3 cells, but had no effects on HOC1A cells. Therefore, IGHG1 similarly to CA166-9, could play an important role in ovarian cancer development and may serve as a potential prognostic marker and a therapeutical target for ovarian cancer.

HPV16 early gene E5 specifically reduces miRNA-196a in cervical cancer cells.

High-risk human papillomavirus (HPV) type 16, which is responsible for greater than 50% of cervical cancer cases, is the most prevalent and lethal HPV type. However, the molecular mechanisms of cervical carcinogenesis remain elusive, particularly the early steps of HPV infection that may transform normal cervical epithelium into a pre-neoplastic state. Here, we report that a group of microRNAs (microRNAs) were aberrantly decreased in HPV16-positive normal cervical tissues, and these groups of microRNAs are further reduced in cervical carcinoma. Among these miRNAs, miR196a expression is the most reduced in HPV16-infected tissues. Interestingly, miR196a expression is low in HPV16-positive cervical cancer cell lines but high in HPV16-negative cervical cancer cell lines. Furthermore, we found that only HPV16 early gene E5 specifically down-regulated miRNA196a in the cervical cancer cell lines. In addition, HoxB8, a known miR196a target gene, is up-regulated in the HPV16 cervical carcinoma cell line but not in HPV18 cervical cancer cell lines. Various doses of miR196a affected cervical cancer cell proliferation and apoptosis. Altogether, these results suggested that HPV16 E5 specifically down-regulates miR196a upon infection of the human cervix and initiates the transformation of normal cervix cells to cervical carcinoma.

[Research on medical data mining and its applications].

With the development of computer technology, medical data has developed from traditional paper pattern into electronic mode, which could effectively promote the medical development. This paper at first presents the status and characteristics of medical data mining. Then, it discusses the critical method of medical data mining in classification, clustering and prediction, respectively. The paper focuses on the application and assessment of five algorithms which are designed for medical data mining, including decision tree, cluster analysis, association rule, intelligent algorithm and the mix algorithm. Finally, this paper outlooks the data mining application in medical domain.

Overexpression and immunosuppressive functions of transforming growth factor 1, vascular endothelial growth factor and interleukin-10 in epithelial ovarian cancer.

OBJECTIVE: Transforming growth factor-1 (TGF-ß1), vascular endothelial growth factor (VEGF), and interleukin-10 (IL-10) may be critical cytokines in the microenvironment of a tumor, playing roles in immune suppression. This study was conducted to elucidate the roles and immunosuppressive functions of these cytokines in epithelial ovarian cancer (EOC). METHODS: The expression levels of TGF-ß1, VEGF and IL-10 in malignant tissue were evaluated by immune- histochemistry and compared with corresponding borderline, benign, and tumor-free tissues. Moreover, relationships among the levels of these cytokines and correlations between expression and the prognosis of EOC were analyzed by Pearson rank correlations and multi-factor Logistic regression. The roles of TGF-ß1, VEGF, and IL-10 in the immunosuppressive microenvironment of ovarian cancer were studied through dendritic cell (DC) maturation and CD4+CD25+FoxP3+ Treg generation in vitro experiments. RESULTS: TGF-ß1, VEGF, and IL-10 were expressed in 100%, 74.69%, and 54.96% of EOC patients, respectively. TGF-ß1 was an independent prognostic factor for EOC. IL-10 was significantly co-expressed with VEGF. In vitro, VEGF and TGF-ß1 strongly interfered with DC maturation and consequently led to immature DCs, which secreted high levels of IL-10 that accumulated around the tumor site. TGF-ß1 and IL-10 induced Treg generation without antigen presentation in DCs. CONCLUSIONS: TGF-ß1, VEGF and IL-10 play important roles in EOC and can lead to frequent immune evasion events.