Ferroptosis-Related Gene Signature Promotes Ovarian Cancer by Influencing Immune Infiltration and Invasion

Ovarian cancer is a kind of gynecological malignancy with high mortality. Ferroptosis is a new type of iron-dependent cell death characterized by the formation of lipid peroxides and excessive accumulation of reactive oxygen species. Studies have shown that ferroptosis modulates tumor genesis, progression, and invasion, including ovarian cancer. Based on the mRNA expression data from TCGA, we construct a scoring system using consensus clustering analysis, univariate Cox regression analysis, and least absolute selection operator. Then, we systematically evaluate the relationship between score and clinical characteristics of ovarian cancer. The result from the prediction of biofunction pathways shows that score serves as an independent prognostic marker for ovarian cancer and affects tumor progression by modulating tumor metastasis. Moreover, immunocytes such as activated CD4 T cell, activated CD8 T cell, regulatory T cells, macrophage, and stromal cells, including adipocytes, epithelial cells, and fibroblast infiltrate more in the tumor microenvironment in a high-score group, indicating ferroptosis can also affect tumor immune landscape. Critically, four potentially sensitive drugs, including staurosporine, epothilone B, DMOG, and HG6-64-1 based on the scores, are predicted, and DMOG is recognized as a novel targeted drug for ovarian cancer. In general, we construct the scoring system based on ferroptosis-related genes that can predict the prognosis of ovarian cancer patients and propose that ferroptosis may affect ovarian cancer progression by mediating tumor metastasis and immune landscape. Novel drugs to target ovarian cancer are also predicted.

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CAMK2N1/RUNX3 methylation is an independent prognostic biomarker for progression-free and overall survival of platinum-sensitive epithelial ovarian cancer patients

Clinical Epigenetics ◽

10.1186/s13148-021-01006-8 ◽

2021 ◽

Vol 13 (1) ◽

Cited By ~ 1

Author(s):

Karolin Heinze ◽

Matthias Rengsberger ◽

Mieczyslaw Gajda ◽

Lars Jansen ◽

Linea Osmers ◽

...

Keyword(s):

Ovarian Cancer ◽

Overall Survival ◽

Epithelial Ovarian Cancer ◽

Prognostic Value ◽

Cox Regression ◽

Univariate Analysis ◽

Cox Regression Analysis ◽

Gynecological Malignancy ◽

Platinum Sensitive ◽

Marker Combination

Abstract Background To date, no predictive or prognostic molecular biomarkers except BRCA mutations are clinically established for epithelial ovarian cancer (EOC) despite being the deadliest gynecological malignancy. Aim of this biomarker study was the analysis of DNA methylation biomarkers for their prognostic value independent from clinical variables in a heterogeneous cohort of 203 EOC patients from two university medical centers. Results The marker combination CAMK2N1/RUNX3 exhibited a significant prognostic value for progression-free (PFS) and overall survival (OS) of sporadic platinum-sensitive EOC (n = 188) both in univariate Kaplan–Meier (LogRank p < 0.05) and multivariate Cox regression analysis (p < 0.05; hazard ratio HR = 1.587). KRT86 methylation showed a prognostic value only in univariate analysis because of an association with FIGO staging (Fisher’s exact test p < 0.01). Thus, it may represent a marker for EOC staging. Dichotomous prognostic values were observed for KATNAL2 methylation depending on BRCA aberrations. KATNAL2 methylation exhibited a negative prognostic value for PFS in sporadic EOC patients without BRCA1 methylation (HR 1.591, p = 0.012) but positive prognostic value in sporadic EOC with BRCA1 methylation (HR 0.332, p = 0.04) or BRCA-mutated EOC (HR 0.620, n.s.). Conclusion The retrospective analysis of 188 sporadic platinum-sensitive EOC proved an independent prognostic value of the methylation marker combination CAMK2N1/RUNX3 for PFS and OS. If validated prospectively this combination may identify EOC patients with worse prognosis after standard therapy potentially benefiting from intensive follow-up, maintenance therapies or inclusion in therapeutic studies. The dichotomous prognostic value of KATNAL2 should be validated in larger sample sets of EOC.

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A Robust Gene Expression Prognostic Signature for Overall Survival in High-Grade Serous Ovarian Cancer

Journal of Oncology ◽

10.1155/2019/3614207 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Yue Zhao ◽

Shao-Min Yang ◽

Yu-Lan Jin ◽

Guang-Wu Xiong ◽

Pin Wang ◽

...

Keyword(s):

Gene Expression ◽

Ovarian Cancer ◽

Overall Survival ◽

Scoring System ◽

Cox Regression ◽

High Grade ◽

Serous Ovarian Cancer ◽

Prognostic Signature ◽

Clinical Value ◽

Cox Regression Analysis

The objective of this research was to develop a robust gene expression-based prognostic signature and scoring system for predicting overall survival (OS) of patients with high-grade serous ovarian cancer (HGSOC). Transcriptomic data of HGSOC patients were obtained from six independent studies in the NCBI GEO database. Genes significantly deregulated and associated with OS in HGSOCs were selected using GEO2R and Kaplan–Meier analysis with log-rank testing, respectively. Enrichment analysis for biological processes and pathways was performed using Gene Ontology analysis. A resampling/cross-validation method with Cox regression analysis was used to identify a novel gene expression-based signature associated with OS, and a prognostic scoring system was developed and further validated in nine independent HGSOC datasets. We first identified 488 significantly deregulated genes in HGSOC patients, of which 232 were found to be significantly associated with their OS. These genes were significantly enriched for cell cycle division, epithelial cell differentiation, p53 signaling pathway, vasculature development, and other processes. A novel 11-gene prognostic signature was identified and a prognostic scoring system was developed, which robustly predicted OS in HGSOC patients in 100 sampling test sets. The scoring system was further validated successfully in nine additional HGSOC public datasets. In conclusion, our integrative bioinformatics study combining transcriptomic and clinical data established an 11-gene prognostic signature for robust and reproducible prediction of OS in HGSOC patients. This signature could be of clinical value for guiding therapeutic selection and individualized treatment.

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Integrin α2β1 Represents a Prognostic and Predictive Biomarker in Primary Ovarian Cancer

Biomedicines ◽

10.3390/biomedicines9030289 ◽

2021 ◽

Vol 9 (3) ◽

pp. 289

Author(s):

Katharina Dötzer ◽

Friederike Schlüter ◽

Franz Edler von Koch ◽

Christine E. Brambs ◽

Sabine Anthuber ◽

...

Keyword(s):

Ovarian Cancer ◽

Growth Factor ◽

Cancer Progression ◽

Survival Data ◽

Cox Regression ◽

Treatment Strategies ◽

Growth Factor Receptor ◽

High Recurrence Rate ◽

Cox Regression Analysis ◽

Primary Ovarian Cancer

Currently, the same first-line chemotherapy is administered to almost all patients suffering from primary ovarian cancer. The high recurrence rate emphasizes the need for precise drug treatment in primary ovarian cancer. Being crucial in ovarian cancer progression and chemotherapeutic resistance, integrins became promising therapeutic targets. To evaluate its prognostic and predictive value, in the present study, the expression of integrin α2β1 was analyzed immunohistochemically and correlated with the survival data and other therapy-relevant biomarkers. The significant correlation of a high α2β1-expression with the estrogen receptor alpha (ERα; p = 0.035) and epithelial growth factor receptor (EGFR; p = 0.027) was observed. In addition, high α2β1-expression was significantly associated with a low number of tumor-infiltrating immune cells (CD3 intratumoral, p = 0.017; CD3 stromal, p = 0.035; PD-1 intratumoral, p = 0.002; PD-1 stromal, p = 0.049) and the lack of PD-L1 expression (p = 0.005). In Kaplan–Meier survival analysis, patients with a high expression of integrin α2β1 revealed a significant shorter progression-free survival (PFS, p = 0.035) and platinum-free interval (PFI, p = 0.034). In the multivariate Cox regression analysis, integrin α2β1 was confirmed as an independent prognostic factor for both PFS (p = 0.021) and PFI (p = 0.020). Dual expression of integrin α2β1 and the hepatocyte growth factor receptor (HGFR; PFS/PFI, p = 0.004) and CD44v6 (PFS, p = 0.000; PFI, p = 0.001; overall survival [OS], p = 0.025) impaired survival. Integrin α2β1 was established as a prognostic and predictive marker in primary ovarian cancer with the potential to stratify patients for chemotherapy and immunotherapy, and to design new targeted treatment strategies.

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The Detection of Stem-Like Circulating Tumor Cells Could Increase the Clinical Applicability of Liquid Biopsy in Ovarian Cancer

Life ◽

10.3390/life11080815 ◽

2021 ◽

Vol 11 (8) ◽

pp. 815

Author(s):

Snezhanna O. Gening ◽

Tatyana V. Abakumova ◽

Dina U. Gafurbaeva ◽

Albert A. Rizvanov ◽

Inna I. Antoneeva ◽

...

Keyword(s):

Ovarian Cancer ◽

Tumor Cells ◽

Circulating Tumor Cells ◽

Cancer Progression ◽

Cox Regression ◽

Progression Free Survival ◽

First Line ◽

Free Survival ◽

Cox Regression Analysis ◽

Paired Samples

Stem properties allow circulating tumor cells (CTCs) to survive in the bloodstream and initiate cancer progression. We aimed to assess the numbers of stem-like CTCs in patients with ovarian cancer (OC) before treatment and during first-line chemotherapy (CT). Flow cytometry was performed (Cytoflex S (Beckman Coulter, CA, USA)) using antibodies against CD45; epithelial markers EpCAM and cytokeratin (CK) 8,18; mesenchymal vimentin (vim); and stem-like CD44, CD133 and ALDH. This study included 38 stage I–IV OC patients (median age 66 (Q1–Q3 53–70)). The CK+vim- counts were higher (p = 0.012) and the CD133+ALDHhigh counts were lower (p = 0.010) before treatment in the neoadjuvant CT group than in the adjuvant group. The patients with ascites had more CK+vim- cells before treatment (p = 0.009) and less EpCAM-vim+ cells during treatment (p = 0.018) than the patients without ascites. All the CTC counts did not differ significantly in paired samples. Correlations were found between the CK-vim+ and CD133+ALDHhigh (r = 0.505, p = 0.027) and EpCAM-vim+ and ALDHhigh (r = 0.597, p = 0.004) cells before but not during treatment. Multivariate Cox regression analysis showed that progression-free survival was longer with the presence of surgical treatment (HR 0.06 95% CI 0.01–0.48, p = 0.009) and fewer CD133+ALDHveryhigh cells (HR 1.06 95% CI 1.02–1.12, p = 0.010). Thus, CD133+ALDH+ CTCs have the greatest prognostic potential in OC among the phenotypes studied.

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Alternative splicing acts as an independent prognosticator in ovarian carcinoma

Scientific Reports ◽

10.1038/s41598-021-89778-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yan Ouyang ◽

Kaide Xia ◽

Xue Yang ◽

Shichao Zhang ◽

Li Wang ◽

...

Keyword(s):

Ovarian Cancer ◽

Regression Analysis ◽

Alternative Splicing ◽

Ovarian Carcinoma ◽

Cancer Patients ◽

Cox Regression ◽

Excision Repair ◽

Splicing Factors ◽

Prognostic Signature ◽

Cox Regression Analysis

AbstractAlternative splicing (AS) events associated with oncogenic processes present anomalous perturbations in many cancers, including ovarian carcinoma. There are no reliable features to predict survival outcomes for ovarian cancer patients. In this study, comprehensive profiling of AS events was conducted by integrating AS data and clinical information of ovarian serous cystadenocarcinoma (OV). Survival-related AS events were identified by Univariate Cox regression analysis. Then, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to construct the prognostic signatures within each AS type. Furthermore, we established a splicing-related network to reveal the potential regulatory mechanisms between splicing factors and candidate AS events. A total of 730 AS events were identified as survival-associated splicing events, and the final prognostic signature based on all seven types of AS events could serve as an independent prognostic indicator and had powerful efficiency in distinguishing patient outcomes. In addition, survival-related AS events might be involved in tumor-related pathways including base excision repair and pyrimidine metabolism pathways, and some splicing factors might be correlated with prognosis-related AS events, including SPEN, SF3B5, RNPC3, LUC7L3, SRSF11 and PRPF38B. Our study constructs an independent prognostic signature for predicting ovarian cancer patients’ survival outcome and contributes to elucidating the underlying mechanism of AS in tumor development.

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Derivation and validation of a lipid-covered prognostic model for mature T-cell lymphomas

Cancer Cell International ◽

10.1186/s12935-021-02042-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Tiange Lu ◽

Lei Shi ◽

Guanggang Shi ◽

Yiqing Cai ◽

Shunfeng Hu ◽

...

Keyword(s):

Lipid Metabolism ◽

T Cell ◽

Scoring System ◽

Serum Lipid ◽

Prognostic Model ◽

Validation Cohort ◽

Univariate Analysis ◽

Prognostic Significance ◽

Cox Regression Analysis ◽

T Cell Lymphomas

Abstract Background Mature T-cell lymphomas (MTCLs), a group of diseases with high aggressiveness and vulnerable prognosis, lack for the accurate prognostic stratification systems at present. Novel prognostic markers and models are urgently demanded. Aberrant lipid metabolism is closely related to the tumor progression but its prognostic significance in MTCLs remains unexplored. This study aims to investigate the relationship between dysregulated lipid metabolism and survival prognosis of MTCLs and establish a novel and well-performed prognostic scoring system for MTCL patients. Methods A total of 173 treatment-naive patients were enrolled in this study. Univariate and multivariate Cox regression analysis were performed to assess the prognostic significance of serum lipid profiles and screen out independent prognostic factors, which constituted a novel prognostic model for MTCLs. The performance of the novel model was assessed in the training and validation cohort, respectively, by examining its calibration, discrimination and clinical utility. Results Among the 173 included patients, 115 patients (01/2006–12/2016) constituted the training cohort and 58 patients (01/2017–06/2020) formed the validation cohort. Univariate analysis revealed declined total cholesterol (TC, P = 0.000), high-density lipoprotein cholesterol (HDL-C, P = 0.000) and increased triglycerides (TG, P = 0.000) correlated to inferior survival outcomes. Multivariate analysis revealed extranodal involved sites ≥ 2 (hazard ratio [HR]: 2.439; P = 0.036), β2-MG ≥ 3 mg/L (HR: 4.165; P = 0.003) and TC < 3.58 mmol/L (HR: 3.338; P = 0.000) were independent predictors. Subsequently, a novel prognostic model, EnBC score, was constructed with these three factors. Harrell’s C-index of the model in the training and validation cohort was 0.840 (95% CI 0.810–0.870) and 0.882 (95% CI 0.822–0.942), respectively, with well-fitted calibration curves. The model divided patients into four risk groups with distinct OS [median OS: not available (NA) vs. NA vs. 14.0 vs. 4.0 months, P < 0.0001] and PFS (median PFS: 84.0 vs. 19.0 vs. 8.0 vs. 1.5 months, P < 0.0001). Time-dependent receiver operating characteristic curve and decision curve analysis further revealed that EnBC score provided higher diagnostic capacity and clinical benefit, compared with International Prognostic Index (IPI). Conclusion Firstly, abnormal serum lipid metabolism was demonstrated significantly related to the survival of MTCL patients. Furthermore, a lipid-covered prognostic scoring system was established and performed well in stratifying patients with MTCLs.

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Clinical relevance of kallikrein-related peptidase 6 (KLK6) and 8 (KLK8) mRNA expression in advanced serous ovarian cancer

Biological Chemistry ◽

10.1515/hsz-2016-0177 ◽

2016 ◽

Vol 397 (12) ◽

pp. 1265-1276 ◽

Cited By ~ 14

Author(s):

Nancy Ahmed ◽

Julia Dorn ◽

Rudolf Napieralski ◽

Enken Drecoll ◽

Matthias Kotzsch ◽

...

Keyword(s):

Ovarian Cancer ◽

Mrna Expression ◽

Cox Regression ◽

Multivariable Analysis ◽

Progression Free Survival ◽

Predictive Marker ◽

Residual Tumor ◽

Mrna Levels ◽

Serous Ovarian Cancer ◽

Cox Regression Analysis

Abstract Most members of the kallikrein-related peptidase family have been demonstrated to be dysregulated in ovarian cancer and modulate tumor growth, migration, invasion, and resistance to chemotherapy. In the present study, we assessed the mRNA expression levels of KLK6 and KLK8 by quantitative PCR in 100 patients with advanced serous ovarian cancer FIGO stage III/IV. A pronounced correlation between KLK6 and KLK8 mRNA expression (rs = 0.636, p < 0.001) was observed, indicating coordinate expression of both peptidases. No significant associations of clinical parameters with KLK6, KLK8, and a combined score KLK6+KLK8 were found. In univariate Cox regression analysis, elevated mRNA levels of KLK6 were significantly linked with shortened overall survival (OS) (hazard ratio [HR] = 2.07, p = 0.007). While KLK8 values were not associated with patients’ outcome, high KLK6+KLK8 values were significantly associated with shorter progression-free survival (HR = 1.82, p = 0.047) and showed a trend towards significance in the case of OS (HR = 1.82, p = 0.053). Strikingly, in multivariable analysis, elevated KLK6 mRNA values, apart from residual tumor mass, remained an independent predictive marker for poor OS (HR = 2.33, p = 0.005). As KLK6 mRNA and protein levels correlate, KLK6 may represent an attractive therapeutic target for potent and specific inhibitors of its enzymatic activity.

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High expression of fibroblast activation protein (FAP) predicts poor outcome in high-grade serous ovarian cancer

BMC Cancer ◽

10.1186/s12885-020-07541-6 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Min Li ◽

Xue Cheng ◽

Rong Rong ◽

Yan Gao ◽

Xiuwu Tang ◽

...

Keyword(s):

Ovarian Cancer ◽

Cox Regression ◽

Paraffin Section ◽

Progression Free Survival ◽

High Grade ◽

Serous Ovarian Cancer ◽

Systematic Analysis ◽

Cox Regression Analysis ◽

Genes Expression ◽

High Level

Abstract Background High-grade serous ovarian cancer (HGSOC) is a fatal form of ovarian cancer. Previous studies indicated some potential biomarkers for clinical evaluation of HGSOC prognosis. However, there is a lack of systematic analysis of different expression genes (DEGs) to screen and detect significant biomarkers of HGSOC. Methods TCGA database was conducted to analyze relevant genes expression in HGSOC. Outcomes of candidate genes expression, including overall survival (OS) and progression-free survival (PFS), were calculated by Cox regression analysis for hazard rates (HR). Histopathological investigation of the identified genes was carried out in 151 Chinese HGSOC patients to validate gene expression in different stages of HGSOC. Results Of all 57,331 genes that were analyzed, FAP was identified as the only novel gene that significantly contributed to both OS and PFS of HGSOC. In addition, FAP had a consistent expression profile between carcinoma-paracarcinoma and early-advanced stages of HGSOC. Immunological tests in paraffin section also confirmed that up-regulation of FAP was present in advanced stage HGSOC patients. Prediction of FAP network association suggested that FN1 could be a potential downstream gene which further influenced HGSOC survival. Conclusions High-level expression of FAP was associated with poor prognosis of HGSOC via FN1 pathway.

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Identification and Validation of a Seven m6A-related lncRNAs Signature Predicting Prognosis of Ovarian Cancer

10.21203/rs.3.rs-915700/v1 ◽

2021 ◽

Author(s):

Yan Li ◽

Xiaoying Wang ◽

Yue Han ◽

Xun Li

Keyword(s):

Ovarian Cancer ◽

Regression Analysis ◽

Correlation Analysis ◽

Prognostic Value ◽

Cox Regression ◽

Risk Group ◽

Pearson Correlation ◽

Regression Analyses ◽

Cox Regression Analysis ◽

Pearson Correlation Analysis

Abstract Background: Long non-coding RNAs (lncRNAs) play an important role in angiogenesis, immune response, inflammatory response and tumor development and metastasis. m6 A (N6 - methyladenosine) is one of the most common RNA modifications in eukaryotes. The aim of our research was to investigate the potential prognostic value of m6A-related lncRNAs in ovarian cancer (OC).Methods: The data we need for our research was downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Pearson correlation analysis between 21 m6A regulators and lncRNAs was performed to identify m6A-related lncRNAs. Univariate Cox regression analysis was implemented to screen for lncRNAs with prognostic value. A least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression analyses was used to further reduct the lncRNAs with prognostic value and construct a m6A-related lncRNAs signature for predicting the prognosis of OC patients. Results: 275 m6A-related lncRNAs were obtained using pearson correlation analysis. 29 m6A-related lncRNAs with prognostic value was selected through univariate Cox regression analysis. Then, a seven m6A-related lncRNAs signature was identified by LASSO Cox regression. Each patient obtained a riskscore through multivariate Cox regression analyses and the patients were classified into high-and low-risk group using the median riskscore as a cutoff. Kaplan-Meier curve revealed that the patients in high-risk group have poor outcome. The receiver operating characteristic curve revealed that the predictive potential of the m6A-related lncRNAs signature for OC was powerful. The predictive potential of the m6A-related lncRNAs signature was successfully validated in the GSE9891, GSE26193 datasets and our clinical specimens. Multivariate analyses suggested that the m6A-related lncRNAs signature was an independent prognostic factor for OC patients. Moreover, a nomogram based on the expression level of the seven m6A-related lncRNAs was established to predict survival rate of patients with OC. Finally, a competing endogenous RNA (ceRNA) network associated with the seven m6A-related lncRNAs was constructed to understand the possible mechanisms of the m6A-related lncRNAs involed in the progression of OC.Conclusions: In conclusion, our research revealed that the m6A-related lncRNAs may affect the prognosis of OC patients and identified a seven m6A-related lncRNAs signature to predict the prognosis of OC patients.

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Development and Validation of a Novel M6A-related LncRNA Prognostic Signature Associated with Immune Microenvironment for Ovarian Serous Cystadenocarcinoma

10.21203/rs.3.rs-1120501/v1 ◽

2021 ◽

Author(s):

Rui Geng ◽

Tian Chen ◽

Zihang Zhong ◽

Senmiao Ni ◽

Jianling Bai ◽

...

Keyword(s):

Immune Modulation ◽

Cox Regression ◽

Great Influence ◽

Clinical Samples ◽

Consensus Clustering ◽

Prognostic Signature ◽

Cancer Stemness ◽

Gynecological Malignancy ◽

Pan Cancer ◽

Geo Database

Abstract Background: OV is the most lethal gynecological malignancy. M6A and lncRNAs have great influence on OV development and patients' immunotherapy response. Here, we decided to establish a reliable signature in the light of mRLs. Method: The lncRNAs associated with m6A in OV were analyzed and obtained by co-expression analysis in the light of TCGA-OV database. Univariate, LASSO and multivariate Cox regression analyses were employed to establish the model in the light of the mRLs. K-M analysis, PCA, GSEA, and nomogram based on the TCGA-OV and GEO database were conducted to prove the predictive value and independence of the model. The underlying relationship between the model and TME and cancer stemness properties were further investigated through immune features comparison, consensus clustering analysis, and Pan-cancer analysis.Results: A prognostic signature comprising four mRLs: WAC-AS1, LINC00997, DNM3OS, and FOXN3-AS1, was constructed and verified for OV according to TCGA and GEO database. The expressions of the four mRLs were confirmed by qRT-PCR in clinical samples. Applying this signature, people can identify patients more effectively. All the sample were assigned into two clusters, and the clusters had different overall survival, clinical features, and tumor microenvironment. Finally, Pan-cancer analysis further demonstrated the four mRLs significantly related to immune infiltration, TME and cancer stemness properties in various cancer types. Conclusion: This study provided an accurate prognostic signature for patients with OV and elucidated the potential mechanism of the mRLs in immune modulation and treatment response, giving new insights into identifying new therapeutic targets.

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