Qi Zhou

Fang C, et al. J Gynecol Oncol. 2024 Mar;35:e77. https://doi.org/10.3802/jgo.2024.35.e77

Cancer stem cells (CSCs) play a central role in tumor formation, invasion, metastasis, chemoresistance and relapse of ovarian cancer (OC). Here we report myo-inositol biosynthesis rate-limiting enzyme (ISYNA1), as a suppressor of OC and regulate cancer stem-like properties of ovarian cancer cells. The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database results showed that lower ISYNA1 level was correlated with shorter overall survival (OS) in TCGA and GEO database. In GEO database, cancer tissues expressed lower level of ISYNA1 compared to normal tissues, and negative associated with the stemness markers. ISYNA1 deficiency promoting the growth, migration, invasion, and self-renewal capability of ovarian cancer cells. We also found that silencing ISYNA1 in ovarian cancer cells enhance CSC properties including sphere formation, the expression level of stem cell factors such as SOX2, NANOG and OCT4, as well as the expression of CSC markers CD44 and CD133, besides, the aldehyde dehydrogenase (ALDH) activity, CD44⁺/CD117⁺expression also be analyzed. In contrast, ectopic overexpression of ISYNA1 suppress cell proliferation, migration, and invasion, decrease the stemness of ovarian cancer cells. In xenograft models, ISYNA1 deficiency significantly increases the tumorgenicity and CSC frequency. In addition, we identified P53 could regulate the expression of ISYNA1, and the myo-inositol addition rescue the stemness increased by ISYNA1 knockdown. In conclusion, these data establish the evidence of ISYNA1 as a suppressor of OC and a regulator of OCSCs, providing insight into potentially targetable pathways for ovarian cancer therapy.

Background: Accurately forecasting the prognosis could improve cervical cancer management, however, the currently used clinical features are difficult to provide enough information. The aim of this study is to improve forecasting capability by developing a miRNAs-based machine learning survival prediction model. Results: The expression characteristics of miRNAs were chosen as features for model development. The cervical cancer miRNA expression data was obtained from The Cancer Genome Atlas database. Preprocessing, including unquantified data removal, missing value imputation, samples normalization, log transformation, and feature scaling, was performed. In total, 42 survival-related miRNAs were identified by Cox Proportional-Hazards analysis. The patients were optimally clustered into four groups with three different 5-years survival outcome (≥ 90%, ≈ 65%, ≤ 40%) by K-means clustering algorithm base on top 10 survival-related miRNAs. According to the K-means clustering result, a prediction model with high performance was established. The pathways analysis indicated that the miRNAs used play roles involved in the regulation of cancer stem cells. Conclusion: A miRNAs-based machine learning cervical cancer survival prediction model was developed that robustly stratifies cervical cancer patients into high survival rate (5-years survival rate ≥ 90%), moderate survival rate (5-years survival rate ≈ 65%), and low survival rate (5-years survival rate ≤ 40%).

Purpose: To evaluate the effectiveness and safety of pegylated recombinant human granulocyte colony stimulating factor (PEG-rhG-CSF) in preventing neutropenia during chemoradiotherapy in patients with cervical cancer. Methods: From August 2018 to April 2020, 60 patients who were pathologically confirmed as cervical cancer were randomly divided into two groups at a ratio of 2:1: PEG-modified-rhG-CSF experimental group and control group. The primary endpoints were the incidence of grade 3–4 neutropenia. Secondary endpoints included the duration of grade 3–4 neutropenia, the incidence of grade 4 neutropenia, the incidence of febrile neutropenia (FN), delay rate of chemotherapy, prolonged time of chemotherapy, time to complete radiotherapy and safety. Results: The incidence of grade 3–4 neutropenia in the experimental group was significantly lower than the control group (10% vs. 77.78%, P < 0.001). However, there was no statistical significance between the two groups in the duration of grade 3–4 neutropenia (3.75 days vs. 5.07 days, P = 0.871). The experimental group was better than the control group in the incidence of grade 4 neutropenia, the incidence of FN and delay rate of chemotherapy, and the difference was statistically significant (P < 0.05). Besides, the prolonged time of chemotherapy and the time to complete radiotherapy in the experimental group were less than those in the control group, but the difference was not statistically significant (P > 0.05). The incidence of adverse events in the experimental group and control group were 55.00 and 94.44%, respectively, and the difference was statistically significant (P = 0.003). Conclusion: PEG-rhG-CSF preventive treatment used in the course of chemoradiotherapy for patients with cervical cancer can reduce the incidence of neutropenia and improve the incidence of delayed chemotherapy cycles. Trial registration: ClinicalTrials.gov, NCT04542356. Registered 9 September 2020 - Retrospectively registered.

Background: Cancer stem cells (CSCs) are the root of human cancer development and the major cause of treatment failure. Aberrant elevation of SOX4, a member of SOX (SRY-related HMG-box) family transcription factors, has been identified in many types of human cancer and promotes cancer development. However, the role of SOX4 in CSCs, especially at a proteome-wide level, has remained elusive. The aim of this study is to investigate the effect of SOX4 on the stemness of CSCs and reveal the underlying mechanisms by identification of SOX4-induced proteome changes through proteomics study. Results: Overexpression of SOX4 promotes sphere formation and self-renewal of colorectal cancer cells in vitro and in vivo and elevates the expression levels of CSCs markers. Through iTRAQ-based quantitative proteomics analysis, 215 differentially expressed proteins (128 upregulated, 87 downregulated) in SOX4-overexpressing HCT-116 spheres were identified. The bioinformatic analysis highlighted the importance of HDAC1 as the fundamental roles of its impacted pathways in stem cell maintenance, including Wnt, Notch, cell cycle, and transcriptional misregulation in cancer. The mechanistic study showed that SOX4 directly binds to the promoter of HDAC1, promotes HDAC1 transcription, thereby supporting the stemness of colorectal cancer cells. HDAC1 hallmarks colorectal cancer stem cells and depletion of HDAC1 abolished the stimulatory effect of SOX4. Furthermore, SOX4-HDAC1 axis is conserved in multiple types of cancer. Conclusions: The results of this study reveal SOX4-induced proteome changes in HCT-116 spheres and demonstrates that transcriptional activation of HDAC1 is the primary mechanism underlying SOX4 maintaining CSCs. This finding suggests that HDAC1 is a potential drug target for eradicating SOX4-driven human CSCs.

Backgroud: Accurately forecasting the prognosis could improve therapeutic management of cancer patients, however, the currently used clinical features are difficult to provide enought information. The purpose of this study is to develop a survival prediction model for cervical cancer patients with big data and machine learning algorithms. Results: The cancer genome atlas cervical cancer data, including the expression of 1046 microRNAs and the clinical information of 309 cervical and endocervical cancer and 3 control samples, were downloaded. Missing values and outliers imputation, samples normalization, log transformation and features scaling were performed for preprocessing and 3 control, 2 metastatic samples and 707 microRNAs with missing values ≥ 20% were excluded. By Cox Proportional-Hazards analysis, 55 prognosis-related microRNAs (20 positively and 35 negatively correlated with survival) were identified. K-means clustering analysis showed that the cervical cancer samples can be separated into two and three subgroups with top 20 identified survival-related microRNAs for best stratification. By Support Vector Machine algorithm, two prediction models were developed which can segment the patients into two and three groups with different survival rate, respectively. The models exhibite high performance : for two classes, Area under the curve = 0.976 (training set), 0.972 (test set), 0.974 (whole data set); for three classes, AUC = 0.983, 0.996 and 0.991 (group1, 2 and 3 in training set), 0.955, 0.989 and 0.991 (group 1, 2 and 3 in test set), 0.974, 0.993 and 0.991 (group 1, 2 and 3 in whole data set) .Conclusion: The survival prediction models for cervical cancer were developed. The patients with very low survival rate (≤ 40%) can be separated by the three classes prediction model first. The rest patients can be identified by the two classes prediction model as high survival rate (≈ 75%) and low survival rate (≈ 50%).

Epigenetic inactivation of GADD45A is a common occurrence in different types of cancer. However, little is known regarding its association with radiosensitivity in cervical cancer (CC). Thus, the present study aimed to investigate the association between aberrant GADD45A methylation and radiosensitivity in CC. SiHa, HeLa and CaSki CC cells were treated with 5‑azacytidine (5‑azaC), with or without irradiation. The expression levels of GADD45A and AKT related molecules were detected via reverse transcription‑quantitative PCR and western blot analyses. The methylation status of GADD45A was assessed via methylation‑specific PCR and cell proliferation assays, while clonogenic assays and flow cytometric analysis were performed to assess the function of the genes (GADD45A and AKT) in the CC cell lines. The results demonstrated that methylation of GADD45A was significantly higher in the radioresistant tissues (63.16%) compared with the radiosensitive samples (33.33%). In addition, the surviving fraction of SiHa cells following irradiation with 2 Gy was demonstrated to be highest amongst the three CC cells (CaSki, 57±9.5%; HeLa, 70±4% and SiHa, 75±10%). The survival rate of SiHa cells following treatment with 5‑azaC and ionizing radiation (IR) significantly decreased as the radiation dose increased, compared with treatment with IR alone. Following overexpression of GADD45A or treatment with 5‑azaC, the radiosensitivity of SiHa cells significantly increased compared with both the control vector and PBS treated groups. In addition, the AKT inhibitor, MK‑2206, increased the radiosensitivity of SiHa cells. Notably, aberrant methylation of GADD45A was associated with decreased radiosensitivity in CC, and the PI3K/AKT signaling pathway was essential for radioresistance, which was mediated through downregulation of GADD45A.