Comprehensive analysis of the interaction of antigen presentation during anti-tumour immunity and establishment of AIDPS systems in ovarian cancer.

There are hundreds of prognostic models for ovarian cancer. These genes are based on different gene classes, and there are many ways to construct the models. Therefore, this paper aims to build the most stable prognostic evaluation system known to date through 101 machine learning strategies. We combined 101 algorithm combinations with 10 machine learning algorithms to create antigen presentation-associated genetic markers (AIDPS) with outstanding precision and steady performance. The inclusive set of algorithms comprises the elastic network (Enet), Ridge, stepwise Cox, Lasso, generalized enhanced regression model (GBM), random survival forest (RSF), supervised principal component (SuperPC), Cox partial least squares regression (plsRcox), survival support vector machine (Survival-SVM). Then, in the train cohort, the prediction model was fitted using a leave-one cross-validation (LOOCV) technique, which involved 101 different possible combinations of prognostic genes. Seven validation data sets (GSE26193, GSE26712, GSE30161, GSE63885, GSE9891, GSE140082 and ICGC_OV_AU) were compared and analysed, and the C-index was calculated. Finally, we collected 32 published ovarian cancer prognostic models (including mRNA and lncRNA). All data sets and prognostic models were subjected to a univariate Cox regression analysis, and the C-index was calculated to demonstrate that the antigen presentation process should be the core criterion for evaluating ovarian cancer prognosis. In a univariate Cox regression analysis, 22 prognostic genes were identified based on the expression profiles of 283 genes involved in antigen presentation and the intersection of genes (p < 0.05). AIDPS were developed by our machine learning-based integration method, which was applied to these 22 genes. One hundred and one prediction models are fitted using the LOOCV framework, and the C-index is calculated for each model across all validation sets. Interestingly, RSF + Lasso was the best model overall since it had the greatest average C-index and the highest C-index of any combination of models tested on the validated data sets. In comparing external cohorts, we found that the C-index correlated AIDPS method using the RSF + Lasso method in 101 prediction models was in contrast to other features. Notably, AIDPS outperformed the vast majority of models across all data sets. Antigen-presenting anti-tumour immune pathways can be used as a representative gene set of ovarian cancer to track the prognosis of patients with cancer. The antigen-presenting model obtained by the RSF + Lasso method has the best C-INDEX, which plays a key role in developing antigen-presenting targeted drugs in ovarian cancer and improving the treatment outcome of patients.

Histone modification-linked prognostic model for ovarian cancer reveals LBX2 as a novel growth promoter.

Ovarian cancer (OC) is a deadly disease with limited treatment options and poor overall survival rates. This study aimed to investigate the role of histone modification-related genes in predicting the prognosis of OC patients. Transcriptome data from multiple cohorts, including bulk RNA-Seq data and single-cell scRNA-Seq data, were collected. Gene set enrichment analysis was used to identify enriched gene sets in the histone modification pathway. Differentially expressed genes (DEGs) between histone modification-high and histone modification-low groups were identified using Lasso regression. A prognostic model was constructed using five selected prognostic genes from the DEGs in the TCGA-OV cohort. The study found enrichment of gene sets in the histone modification pathway and identified five prognostic genes associated with OC prognosis. The constructed risk score model based on histone modification-related genes was correlated with immune infiltration of T cells and M1 macrophages. Mutations are more prevalent in the high-risk group compared to the low-risk group. Several drugs were screened against the model genes. Through in vitro experiments, we confirmed the expression patterns of the model genes. LBX2 facilitates the proliferation of OC. Histone modification-related genes have the potential to serve as biomarkers for predicting OC prognosis. Targeting these genes may lead to the development of more effective therapies for OC. Additionally, LBX2 represents a novel cell proliferation promoter in OC carcinogenesis.

METTL3/MALAT1/ELAVL1 Axis Promotes Tumor Growth in Ovarian Cancer.

Background: Studies increasingly recognize the role of N6-methyladenosine (m6A) modification in cancer occurrence and development. METTL3 is a core catalytic subunit of m6A-modified methyltransferases complex, but its regulatory mechanism in ovarian cancer (OC) is not clear. Methods: In this study, GEPIA 2.0 database was applied for expression analysis, survival analysis and correlation analysis for OC. Additionally, in vitro and in vivo assays were conducted to explore regulatory mechanisms of METTL3 in OC. Results: We found that METTL3 and MALAT1 were significantly overexpressed in OC tissues and cells compared to normal ovarian tissues and cells. The proliferation rate of OC cells was reduced significantly after knocking down the expression of METTL3 or MALAT1. Subsequently, MALAT1 as oncogene was found to interact with METTL3 and was upregulated in OC tissues and cells. Silencing MALAT1 inhibited OC cell proliferation. Further studies indicated that METTL3 enhanced the stability of MALAT1 by promoting the m6A modification of MALAT1 and that ELAVL1 as a downstream binding protein significantly up-regulated MALAT1 expression. Conclusion: In conclusion, METTL3 was a carcinogenic molecule that promoted the occurrence of OC. The potential mechanism of the carcinogenic effect of METTL3 was realized by enhancing the m6A modification of MALAT1 mRNA through RNA binding protein ELAVL1.

Ovarian carcinoma immune-related microRNA affects the heterogeneity of the endocrine microenvironment and anti-tumor immune pattern.

BACKGROUND: The eighth-leading cause of cancer-related mortality and the seventh-most prevalent malignancy in women globally is ovarian cancer (OV). However, 5-year survival expectancy after conventional treatment is not good. Therefore, there is an urgent need for novel signatures to guide the designation of therapeutic schemes for OV patients. METHODS: We used univariate Cox analysis to screen hormone secretion regulation axis-related microRNAs (miRNAs), least absolute shrinkage and selection operator analysis to select candidate miRNAs and multivariate Cox analysis to build the risk model. To evaluate possible route and functional differences, enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on the differentially expressed genes (DEGs) across various risk groups. We compared Tumor Immune Dysfunction and Exclusion (TIDE) scores across risk categories by analyzing immune cell infiltration, immune checkpoint gene expression, immunological function and TIDE scores. In the end, we determined the half maximal inhibitory concentration (IC50 ) of chemotherapy and targeted medicines for individual patients. Cell assays were determined to test the migration of the miRNA-target genes and western blotting was used to test the correlation of the miRNA-target genes and the pathways. RESULTS: We finally identified hormone secretion regulation axis-related 13 microRNAs to build a risk model. The validation of observed and anticipated values revealed a fair level of agreement. To evaluate the molecular pathways between various groups in accordance with the GO and KEGG analyses, we then discovered 173 DEGs between distinct risk groups. The risk score was shown to be inversely related to the number of immune cells, including myeloid dendritic, granulocytes, M1 and M2 macrophages, B cells, t-lymphocytes, and CD4+ and CD8+ cells, suggesting that immune cells are more frequent in the low-risk group. Immune cell infiltration investigation yielded these results. Finally, we recognized 11 chemotherapeutic drugs and 30 novels targeted drugs on the basis of IC50 between the different risk groups. GJB5 was determined to be the mir-219 target gene and was identified as promoting the cell cycle process. In addition, hormone secretion regulation axis related miRNAs were reported to affects the heterogeneity of endocrine microenvironment and anti-tumor immune pattern. CONCLUSIONS: In conclusion, a 13-miRNA prognostic model was constructed to know the immune status, prognosis, immunotherapeutic response and anti-tumor drug sensitivity for OV, which provides theoretical guidance for the effective and individualized treatment of OV patients.

The inflammatory response-related robust machine learning signature in endometrial cancer: Based on multi-cohort studies.

Uterine corpus endometrial carcinoma (UCEC) is a prevalent form of cancer in women, affecting the inner lining of the uterus. Inflammation plays a crucial role in the progression and prognosis of cancer, making it important to identify inflammatory response-related subtypes in UCEC for targeted therapy and personalized medicine. This study discovered significant variation in immune response within UCEC tumors based on molecular subtypes of inflammatory response-related genes. Subtype A showed a more favorable prognosis and better response to immunotherapies like anti-CTLA4 and anti-PDCD1 therapy. Functional analysis revealed subtype-specific differences in immune response, with subtype A exhibiting higher expression of genes related to cytokine signaling pathways, NK cell-mediated cytotoxicity pathways and inflammatory processes. Subtype A also showed increased sensitivity to three chemotherapeutic agents. A 12-gene inflammatory response-related signature was found to have prognostic value for 1, 2 and 3 year survival in UCEC patients. Additionally, a validated machine learning-based signature demonstrated significant differences in clinical traits between low-risk and high-risk cohorts. Elevated risk scores were associated with higher pathological grading, older age, advanced stage and immune subtype C2. Low-risk groups had higher infiltration of immune cell types such as CD8 + T cells and activated CD4 + cells. However, the abundance of cytotoxic immune cells decreased with increasing risk scores. Finally, PCR was applied to test the different expression in P2PX4. P2RX4 knockdown inhibited the proliferation and proliferation of the endometrial carcinoma Ishikawa cell line. In conclusion, this developed signature can serve as a clinical prediction index and reveal distinct immune expression patterns. Ultimately, this study has the potential to enhance targeted therapy and personalized medicine for UCEC patients.

Cuproptosis-related lncRNAs ovarian cancer: Multi-omics analysis of molecular mechanisms and potential therapeutic targets.

Ovarian cancer (OV) is an aggressive malignancy that poses a significant threat to the health and lives of women. Cuproptosis is a newly discovered form of programmed cell death that offers a promising therapeutic target, although its significance in cancer progression remains uncertain. In this study, we established a prognostic model of OV with six cuproptosis-related long non-coding RNAs (lncRNAs), including CTC.246B18.8, LINC00337, RP11.568N6.1, RP11.158I9.8, RP11.678G14.3 and CYP4F26P, based on the data of The Cancer Genome Atlas (TCGA). Lower risk scores were associated with favorable prognosis. In addition, a negative outcome was associated with high expression of CTC.246B18.8. According to the ESTIMATE algorithm, CTC.246B18.8 was negatively correlated with the ImmuneScore, and positively with immune checkpoints, immune cell infiltration, and tumor mutation burden (TMB). Moreover, gene set enrichment analysis (GSEA) revealed that pathways related to immunosuppression are likely activated in response to CTC-246B18.8 overexpression. Furthermore, CTC-246B18.8 expression was also associated with the sensitivity to various chemotherapy drugs. The expression patterns of the above lncRNAs were verified in ovarian tumor cell lines (SK-OV-3, COC1, and A2780) and normal ovarian epithelial cells (IOSE - 80). Six cuproptosis-related genes (CRGs), including ATP7B, MTF1, SLC31A1, DLD, ATP7A and DLAT, were differentially expressed between CTC-246B18.8high and CTC-246B18.8low patient groups, and exhibited organ-specific expression patterns pan-cancer. Small molecule drugs that target these CRGs were predicted, and potential candidates included DIAMIDE, bathocuproine disulfonate, D-penicillamine, etc. To summarize, our findings provide molecular insights into the role of cuproptosis in OV, and the signature lncRNAs and CRGs should be investigated further as immunotherapy biomarkers of OV.

Prognostic role of long non-coding RNA USP30-AS1 in ovarian cancer: insights into immune cell infiltration in the tumor microenvironment.

Ovarian cancer represents a formidable gynecologic malignancy bearing a dismal prognosis owing to the dearth of reliable early detection approaches and a high recurrence rate. Long non-coding RNAs (lncRNAs) have garnered immense attention as key orchestrators involved in diverse biological processes and take part in cancer initiation and progression. The present study investigated the potential significance of lncRNA USP30-AS1 in ovarian cancer prognosis, as well as its putative association with immune cell infiltration in tumor immune microenvironment (TIME). By analyzing publicly available datasets, we identified six lncRNAs with prognostic prediction ability, including USP30-AS1. The results revealed a significant positive correlation of USP30-AS1 expression with the infiltration of immune cells such as Th1 cells, TFH, CD8 T cells, B cells, antigen-presenting dendritic cells (aDC), and plasmacytoid dendritic cells (pDC) in ovarian cancer specimens. These findings provide compelling evidence of the potential involvement of lncRNA in the regulation of the TME in ovarian carcinoma. The outcomes from this study underscore the potential of USP30-AS1 as a promising prognostic biomarker for ovarian cancer. Additionally, the findings offer significant insights into the plausible role of lncRNAs in modulating immune activities, thus adding to our understanding of the disease biology. Additional investigations are necessary to unravel the molecular mechanisms underpinning these connections and validate the results seen in independent cohorts and experimental models.

The roles of FXYD family members in ovarian cancer: an integrated analysis by mining TCGA and GEO databases and functional validations.

BACKGROUND: The FXYD family of ion transport regulators have emerged as important modulators of cancer progression and metastasis. However, their expression and roles in ovarian cancer (OCa) have not been systematically investigated. METHODS: The expression of FXYD genes in OCa was analyzed using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), as well as independent clinical samples. The prognostic values of FXYD genes were evaluated by Kaplan-Meier and Cox regression analysis. To explore potential mechanisms, bioinformatics approaches including Gene Ontology, KEGG pathway analysis, GSEA and drug sensitivity correlation analysis were performed. OCa cell lines overexpressing FXYD1, FXYD5 or FXYD7 were also generated and their impacts on proliferation, migration and invasion were assessed. RESULTS: FXYD1 and FXYD6 were significantly downregulated while FXYD3, FXYD4 and FXYD5 were upregulated in OCa tissues compared to normal tissues. FXYD1, FXYD5 and FXYD7 were independent adverse prognostic factors for OCa patients. Pathway and drug correlation analysis revealed that FXYD1, FXYD5 and FXYD7 genes regulated diverse oncogenic signaling cascades and modulated the response to various chemotherapeutic agents. Overexpression of FXYD1, FXYD5 or FXYD7 enhanced OCa cell motility and invasiveness in vitro. CONCLUSION: Our results demonstrate aberrant expression patterns, prognostic values, and oncogenic activities of FXYD genes in OCa. FXYD1, FXYD5 and FXYD7 may serve as biomarkers and therapeutic targets for this disease. Targeting FXYD-mediated signaling represents a promising therapeutic strategy against OCa.

A novel machine learning-based programmed cell death-related clinical diagnostic and prognostic model associated with immune infiltration in endometrial cancer.

Background: To explore the underlying mechanism of programmed cell death (PCD)-related genes in patients with endometrial cancer (EC) and establish a prognostic model. Methods: The RNA sequencing data (RNAseq), single nucleotide variation (SNV) data, and corresponding clinical data were downloaded from TCGA. The prognostic PCD-related genes were screened and subjected to consensus clustering analysis. The two clusters were compared by weighted correlation network analysis (WGCNA), immune infiltration analysis, and other analyses. The least absolute shrinkage and selection operator (LASSO) algorithm was used to construct the PCD-related prognostic model. The biological significance of the PCD-related gene signature was evaluated through various bioinformatics methods. Results: We identified 43 PCD-related genes that were significantly related to prognoses of EC patients, and classified them into two clusters via consistent clustering analysis. Patients in cluster B had higher tumor purity, higher T stage, and worse prognoses compared to those in cluster A. The latter generally showed higher immune infiltration. A prognostic model was constructed using 11 genes (GZMA, ASNS, GLS, PRKAA2, VLDLR, PRDX6, PSAT1, CDKN2A, SIRT3, TNFRSF1A, LRPPRC), and exhibited good diagnostic performance. Patients with high-risk scores were older, and had higher stage and grade tumors, along with worse prognoses. The frequency of mutations in PCD-related genes was correlated with the risk score. LRPPRC, an adverse prognostic gene in EC, was strongly correlated with proliferation-related genes and multiple PCD-related genes. LRPPRC expression was higher in patients with higher clinical staging and in the deceased patients. In addition, a positive correlation was observed between LRPPRC and infiltration of multiple immune cell types. Conclusion: We identified a PCD-related gene signature that can predict the prognosis of EC patients and offer potential targets for therapeutic interventions.

Characteristics of patients with stage III and IV ovarian endometriomas and trends in postoperative anti-Mullerian hormone changes.

Introduction: This study aimed to investigate the manifestations of postoperative Anti-Mullerian hormone (AMH) changes in patients with stage III and IV ovarian endometriomas. Methods: Trends in postoperative AMH were categorized and described, and the risk factors for postoperative AMH decline were screened using dichotomous logistic regression. Results: The overall trend of postoperative AMH decreased, with a more significant decrease in stage IV than stage III cases. Elevated preoperative CA-125 levels, a history of caesarean section, and abortion were independent risk factors for postoperative AMH decline. Conclusions: There is a general trend toward decreasing AMH levels after surgery, but each case may also show a different elevation.

The joint role of methylation and immune-related lncRNAs in ovarian cancer: Defining molecular subtypes and developing prognostic signature.

INTRODUCTION: Complex outcome of ovarian cancer (OC) stems from the tumor immune microenvironment (TIME) influenced by genetic and epigenetic factors. This study aimed to comprehensively explored the subclasses of OC through lncRNAs related to both N6-methyladenosine (m6A)/N1-methyladenosine (m1A)/N7-methylguanosine (m7G)/5-methylcytosine (m5C) in terms of epigenetic variability and immune molecules and develop a new set of risk predictive systems. MATERIAL AND METHODS: The lncRNA data of OC were collected from TCGA. Spearman correlation analysis on lncRNA data of OC with immune-related gene expression and with m6A/m5C/m1A/m7G were respectively conducted. The m6A/m5C/m1A/m7G-related m6A/m5C/m1A/m7G related immune lncRNA subtypes were identified on the basis of the prognostic lncRNAs. Heterogeneity among subtypes was evaluated by tumor mutation analysis, tumor microenvironment (TME) component analysis, response to immune checkpoint blocked (ICB) and chemotherapeutic drugs. A risk predictive system was developed based on the results of Cox regression analysis and random survival forest analysis of the differences between each specific cluster and other clusters. RESULTS: Three m6A/m5C/m1A/m7G-related immune lncRNA subtypes of OC showing distinct differences in prognosis, mutation pattern, TIME components, immunotherapy and chemotherapy response were identified. A set of risk predictive system consisting of 10 lncRNA for OC was developed, according to which the risk score of samples in each OC dataset was calculated and risk type was defined. CONCLUSIONS: This study classified three m6A/m5C/m1A/m7G-related immune lncRNA subtypes with distinct heterogeneous mutation patterns, TME components, ICB therapy and immune response, and provided a set of risk predictive system consisted of 10 lncRNA for OC.

Human Hematopoietic Stem Cell Engrafted IL-15 Transgenic NSG Mice Support Robust NK Cell Responses and Sustained HIV-1 Infection.

Mice reconstituted with human immune systems are instrumental in the investigation of HIV-1 pathogenesis and therapeutics. Natural killer (NK) cells have long been recognized as a key mediator of innate anti-HIV responses. However, established humanized mouse models do not support robust human NK cell development from engrafted human hematopoietic stem cells (HSCs). A major obstacle to human NK cell reconstitution is the lack of human interleukin-15 (IL-15) signaling, as murine IL-15 is a poor stimulator of the human IL-15 receptor. Here, we demonstrate that immunodeficient NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice expressing a transgene encoding human IL-15 (NSG-Tg(IL-15)) have physiological levels of human IL-15 and support long-term engraftment of human NK cells when transplanted with human umbilical-cord-blood-derived HSCs. These Hu-NSG-Tg(IL-15) mice demonstrate robust and long-term reconstitution with human immune cells, but do not develop graft-versus-host disease (GVHD), allowing for long-term studies of human NK cells. Finally, we show that these HSC engrafted mice can sustain HIV-1 infection, resulting in human NK cell responses in HIV-infected mice. We conclude that Hu-NSG-Tg(IL-15) mice are a robust novel model to study NK cell responses to HIV-1.

Tetramethylpyrazine ameliorates acute lung injury by regulating the Rac1/LIMK1 signaling pathway.

Acute lung injury (ALI) is a respiratory disorder characterized by severe inflammation of the alveoli and lung parenchyma. Tetramethylpyrazine (TMP), the main active compound in Ligusticum chuanxiong Hort (LC), can protect against lipopolysaccharide (LPS)-induced ALI. Our study aimed to investigate how TMP protects the endothelial cell barrier in pulmonary capillaries. We administered TMP intraperitoneally at different doses and found that acute lung injury in mice was improved, but not in a dose-dependent manner. TMP toxicity was tested in vitro. We observed that LPS-induced cytoskeletal remodeling was inhibited by TMP. Murine ALI was induced as follows: For the 1st hit, LPS (2 mg/kg) was injected intraperitoneally; after 16 h, for the 2nd hit, LPS (4 mg/kg) was instilled intratracheally. The mice in treatment groups had TMP or dexamethasone administered intraperitoneally 30 min prior to the 1st hit and 30 min past the 2nd hit. Mice were euthanized 24 h after the last injecting. We measured protein and mRNA levels using enzyme-linked immunosorbent assay (ELISA) and reverse transcriptase real-time PCR (RT-qPCR), respectively. The ultrastructural analysis was performed with transmission electron microscopy (TEM) and the cytoskeleton was observed by immunofluorescence. Immunohistochemistry and Western blotting were used to detect protein expression in the Rac1/LIMK1/ZO-1/occludin signal pathway. The results showed that TMP treatment decreased inflammatory cell infiltration and alleviated LPS-induced damage in lung tissue. Also, TMP significantly inhibited the Rac1/LIMK1/ZO-1/occludin signaling pathway. Our findings show that using TMP during sepsis can protect the pulmonary microvascular endothelial cell barrier and suppress inflammation. Therefore, TMP may have a promising therapeutic role in preventing acute lung injury from sepsis.

Differentiation of primordial germ cells from premature ovarian insufficiency-derived induced pluripotent stem cells.

BACKGROUND: Premature ovarian insufficiency (POI) is a common disease in reproductive women. The pathogenesis of POI is not clear, although it is known that it involves the disorder of oocyte differentiation and development. The introduction of reprogramming human somatic cells into induced pluripotent stem cells (iPSCs) offers a unique opportunity to study many aspects of POI from cell differentiation in vitro that could ultimately lead to novel drug development and testing to help treat the disorder. METHODS: The fibroblasts from POI patients, including fragile X syndrome, abnormal karyotype (45, X; 45, X/46, XX; 45, XO and 47, XXX), and the gene mutation (FIGLA and GDF9) were reprogrammed to pluripotency status by retroviral transduction using defined factors. The morphology, growth characteristics, gene expression profiles, epigenetic status, and in vitro and in vivo differentiation potential of the POI-1-iPSCs (from fragile X syndrome) were analyzed. Then, POI-1-iPSCs were induced to differentiation into primordial germ cells (PGCs) with DNA methyltransferase inhibitors. RESULTS: The iPSCs were successfully generated from POI patients' fibroblasts. The formed iPS clones have the same characteristics of human ESCs. POI-1-iPSCs were successfully generated with germline competence. The POI-1-iPSCs, with genotypes of fragile X syndrome, can be induced to differentiation into PGCs with high efficiency under our culture system by DNA demethylation. This study proved that disease-specific iPSC lines derived from POI patients could be generated and successfully differentiated into PGCs. CONCLUSIONS: We established some novel, systemic cell models for the studying of the pathogenesis of POI patients. Second, DNA demethylation may accelerate the induction of human PGCs from iPSCs in vitro and the conclusion needs further exploration. This represents an important step in the novel approach for the study of the pathophysiology and potential egg resource for POI patients.

[Comparison of therapeutic efficacy between TP regimen and CBP regimen on epithelial ovarian cancer after optimal cytoreductive operation].

BACKGROUND & OBJECTIVE: The most effective treatment for epithelial ovarian cancer is the combination of surgical operation and chemotherapy. Complete removal of the tumor is the key of surgical treatment; TP regimen (paclitaxel plus carboplatin) is the preference for postoperative chemotherapy, but its superiority is controversial. This study was to compare the efficacy of TP regimen and CBP regimen (cyclophosphamide, bleomycin plus carboplatin/cisplatin) on epithelial ovarian cancer. METHODS: Clinical data of 125 patients with stage IIb-IV epithelial ovarian cancer, underwent optimal cytoreductive operation and received regular postoperative chemotherapy in Cancer Center of Sun Yat-sen University, were analyzed. Of the 125 patients, 65 were treated with CBP regimen, 60 were treated with TP regimen. The 3-year survival statuses and main adverse events were compared between the 2 groups. RESULTS: The 3-year survival rates were 69.2% in CBP group and 75.3% in TP group (P=0.473); the 3-year tumor-free survival rates were 38.5% and 43.3%, respectively (P=0.580); the medians of progression-free survival time of the patients with recurrent disease were 12 months and 13 months, respectively (P=0.672). The comparisons of overall survival curves and tumor-free survival curves between the 2 groups showed no significant differences, too (P=0.285 and P=0.517). The comparisons of adverse effects between the 2 groups showed no significant differences except for neurologic toxicity. CONCLUSION: TP regimen and CBP regimen have identical therapeutic effects when used as first-line chemotherapy regimen for epithelial ovarian cancer after optimal cytoreductive operation.