RESUMEN
BACKGROUND: Human endogenous retrovirus (HERV)-K is a type of retrovirus that is present in the human genome, and its expression is usually silenced in healthy tissues. The precise mechanism by which HERV-K env influences cancer stemness is not fully understood, but it has been suggested that HERV-K env may activate various signaling pathways that promote stemness traits in cancer cells. OBJECTIVE: To establish the connection between HERV-K env expression and cancer stemness in ovarian cancer cells, we carried out correlation analyses between HERV-K env and the cancer stem cell (CSC) marker known as the cluster of differentiation 133 (CD133) gene in SKOV3 ovarian cancer cells. METHOD: To perform correlation analysis between HERV-K env and CSCs, ovarian cancer cells were cultured in a medium designed for cancer stem cell induction. The expression of HERV-K env and CD133 genes was verified using quantitative real-time polymerase chain reaction (RT-qPCR) and Western blot analyses. Additionally, the expression of stemness-related markers, such as OCT-4 and Nanog, was also confirmed using RT-qPCR. RESULTS: In the stem cell induction medium, the number of tumorsphere-type SKOV3 cells increased, and the expression of CD133 and HERV-K env genes was up-regulated. Additionally, other stemness-related markers like OCT-4 and Nanog also exhibited increased expression when cultured in the cancer stem cell induction medium. However, when HERV-K env knockout (KO) SKOV3 cells were cultured in the same cancer stem cell induction medium, there was a significant decrease in the number of tumorsphere-type cells compared to mock SKOV3 cells subjected to the same conditions. Furthermore, the expression of CD133, Nanog, and OCT-4 did not show a significant increase in HERV-K env KO SKOV3 cells compared to mock SKOV3 cells cultured in the same cancer stem cell induction medium. CONCLUSION: These findings indicate that the expression of HERV-K env increased in SKOV3 cells when cultured in cancer stem cell induction media, and cancer stem cell induction was inhibited by KO of HERV-K env in SKOV3 cells. These results suggest a strong association between HERV-K env and stemness in SKOV3 ovarian cancer cells.
Asunto(s)
Retrovirus Endógenos , Neoplasias Ováricas , Femenino , Humanos , Retrovirus Endógenos/genética , Retrovirus Endógenos/metabolismo , Células Madre Neoplásicas/metabolismo , Neoplasias Ováricas/metabolismo , Proteínas del Envoltorio Viral/genética , Proteínas del Envoltorio Viral/metabolismo , Antígeno AC133/inmunología , Antígeno AC133/metabolismoRESUMEN
Background: This study aimed to determine the optimal combination of biomarkers that can predict epithelial ovarian cancer (EOC) and compare the combination with the risk of ovarian malignancy algorithm (ROMA) or Copenhagen index (CPH-I). Methods: Data from 66 patients with EOC and 599 patients with benign ovarian masses who underwent definitive tissue diagnosis of adnexal masses between January 2017 and March 2021 were analyzed. The Mann-Whitney U test or Kruskal-Wallis test was used for between-group comparisons of medians. Logistic regression was used to establish an EOC predictor model. Area under the curve (AUC) comparisons between models were performed using the Delong nonparametric approach. Results: The median age of the patients was 43 years. Twenty-nine (43.9%) patients had early-stage disease (stages I-II) and 37 (56.1%) patients had advanced-stage disease (stages III-IV). The median age, body mass index, white blood cell count, hemoglobin-to-red cell distribution width ratio (HRR), platelet count, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, serum albumin level, cancer antigen 125, human epididymal secretory protein 4 (HE4), ROMA, and CPH-I were significantly different between the stage I-IV EOC and benign ovarian mass groups. Multivariate logistic regression analysis revealed that HE4, HRR, and computed tomography (CT) imaging were significant predictors of both stages I-IV and I-II EOC. Using these covariates, an interim model (IM) (consisting of HE4 and HRR) and a full model (FM) (consisting of HE4, HRR, and CT imaging) were constructed. When predicting stage I-IV EOC, the AUC of IM was comparable to that of ROMA or CPH-I, whereas the AUC of FM outperformed ROMA or CPH-I. In predicting stage I-II EOC, the AUC of IM was comparable to that of CPH-I but higher than that of ROMA, and the AUC of FM outperformed ROMA or CPH-I. Conclusion: FM outperformed ROMA or CPH-I in predicting stage I-IV EOC and stage I-II EOC. Therefore, FM could be a promising model for improving preoperative prediction of EOC at an early stage. However, further prospective studies are required to validate these results.
RESUMEN
BACKGROUND: Among various human endogenous retroviruses (HERVs), the HERV-K (HML-2) group has been reported to be highly related to cancer. In pancreatic cancer cells, shRNA-mediated downregulation of HERV-K env RNA decreases cell proliferation and tumor growth through the RAS-ERK-RSK pathway; in colorectal cancer, CRISPR-Cas9 knockout (KO) of the HERV-K env gene affects tumorigenic characteristics through the nupr-1 gene. OBJECTIVE: The effect of HERV-K env KO has not been studied in ovarian cancer cell lines. In this study, we analyzed the tumorigenic characteristics of ovarian cancer cell lines, including cell proliferation, migration, and invasion, and the expression patterns of related proteins after CRISPR-Cas9 KO of the HERV-K env gene. METHODS: The HERV-K env gene KO was achieved using the CRISPR-Cas9 system in ovarian cancer cell lines SKOV3 and OVCAR3. Tumorigenic characteristics including cell proliferation, migration, and invasion were analyzed, and related protein expression was investigated by western blot analysis. RESULTS: The expression of the HERV-K env gene in KO cells was significantly reduced at RNA and protein levels, and tumorigenic characteristics including cell proliferation, migration, and invasion were significantly reduced. In HERV-K env KO SKOV3 cells, the expression of the RB protein was significantly up-regulated and the cyclin B1 protein level was significantly reduced. In contrast, in HERV-K env KO OVCAR3 cells, the level of phospho-RB protein was significantly reduced, but other protein levels were not changed. CONCLUSION: The results of this study showed that HERV-K env gene KO affects cell proliferation, invasion, and migration of ovarian cells through RB and Cyclin B1 proteins, but the specific regulation pattern can differ by cell line.
Asunto(s)
Retrovirus Endógenos , Neoplasias Ováricas , Apoptosis , Carcinogénesis/genética , Línea Celular Tumoral , Proliferación Celular/genética , Ciclina B1/genética , Ciclina B1/metabolismo , Retrovirus Endógenos/genética , Femenino , Técnicas de Inactivación de Genes , Genes env , Humanos , Neoplasias Ováricas/genética , ARN Interferente Pequeño , Proteína de Retinoblastoma/genética , Proteína de Retinoblastoma/metabolismoRESUMEN
OBJECTIVE: To determine whether the preoperative lymphocyte-monocyte ratio (LMR) is a predictor of suboptimal cytoreduction in advanced-stage epithelial ovarian cancer (EOC). METHODS: Preoperative clinico-pathologic and hematologic parameters were reviewed in a total of 154 patients with EOC submitted to primary cytoreductive surgery. Patients were categorized into two different groups according to the results of cytoreductive surgery: optimal and suboptimal cytoreduction. Continuous variables were categorized into two groups using the best cutoff points selected on the receiver operating characteristic (ROC) curve for suboptimal cytoreduction. RESULTS: Based on data collected from the 154 patients, 133 (86.4%) and 21 (13.6%) patients presented with stage III and IV disease, respectively. One hundred seventeen (76.0%) patients had serous adenocarcinoma, and 92 (59.7%) had histologic tumor grade 3. The optimal and suboptimal cytoreduction groups included 96 (62.3%) and 58 patients (37.7%), respectively. The best LMR cutoff point for suboptimal cytoreduction was 3.75. On multivariate logistic regression analysis, age, cancer antigen 125, white blood cell count, and LMR were found to be the strongest predictors for suboptimal cytoreduction (P=0.0037, 0.0249, 0.0062, and 0.0015, respectively). Conclusion: Preoperative LMR is an independent predictor of suboptimal cytoreduction. It provides additional prognostic information beyond the biological parameters of the tumor.