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

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

10.21203/rs.3.rs-28242/v1 ◽

2020 ◽

Author(s):

Min Li ◽

Xue Cheng ◽

Rong Rong ◽

Xiuwu Tang ◽

Youguo Chen

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 (HSOC) is a fatal form of ovarian cancer. Previous studies indicated some potential biomarkers for clinical evaluation of HSOC prognosis. However, there is a lack of systematic analysis of different expression genes (DEGs) to screen and detect significant biomarkers of HSOC. Method and materials: TCGA database was conducted to analyze relevant genes expression in HSOC. 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 32 Chinese HSOC patients to validate gene expression in different stages of HSOC. 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 HSOC. In addition, FAP had a consistent expression profile between carcinoma-paracarcinoma and early-advanced stages of HSOC. Immunological tests in paraffin section also confirmed that up-regulation of FAP was present in advanced stage HSOC patients. Prediction of FAP network association suggested that FN1 could be a potential downstream gene which further influenced HSOC survival. Conclusions High-level expression of FAP was associated with poor prognosis of HSOC via FN1 pathway.

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

10.21203/rs.3.rs-28242/v2 ◽

2020 ◽

Author(s):

Min Li ◽

Xue Cheng ◽

Rong Rong ◽

Xiuwu Tang ◽

Youguo Chen

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 (HSOC) is a fatal form of ovarian cancer. Previous studies indicated some potential biomarkers for clinical evaluation of HSOC prognosis. However, there is a lack of systematic analysis of different expression genes (DEGs) to screen and detect significant biomarkers of HSOC. Method and materials: TCGA database was conducted to analyze relevant genes expression in HSOC. 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 HSOC patients to validate gene expression in different stages of HSOC. 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 HSOC. In addition, FAP had a consistent expression profile between carcinoma-paracarcinoma and early-advanced stages of HSOC. Immunological tests in paraffin section also confirmed that up-regulation of FAP was present in advanced stage HSOC patients. Prediction of FAP network association suggested that FN1 could be a potential downstream gene which further influenced HSOC survival. Conclusions: High-level expression of FAP was associated with poor prognosis of HSOC via FN1 pathway.

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

10.21203/rs.3.rs-28242/v3 ◽

2020 ◽

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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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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Plasmin(ogen) serves as a favorable biomarker for prediction of survival in advanced high-grade serous ovarian cancer

Biological Chemistry ◽

10.1515/hsz-2016-0282 ◽

2017 ◽

Vol 398 (7) ◽

pp. 765-773 ◽

Cited By ~ 6

Author(s):

Shuo Zhao ◽

Julia Dorn ◽

Rudolf Napieralski ◽

Axel Walch ◽

Sandra Diersch ◽

...

Keyword(s):

Ovarian Cancer ◽

Cox Regression ◽

Multivariable Analysis ◽

Positive Staining ◽

Mrna Levels ◽

High Grade ◽

Serous Ovarian Cancer ◽

Data Set ◽

Cox Regression Analysis ◽

Kaplan Meier

Abstract In serous ovarian cancer, the clinical relevance of tumor cell-expressed plasmin(ogen) (PLG) has not yet been evaluated. Due to its proteolytic activity, plasmin supports tumorigenesis, however, angiostatin(-like) fragments, derived from PLG, can also function as potent anti-tumorigenic factors. In the present study, we assessed PLG protein expression in 103 cases of advanced high-grade serous ovarian cancer (FIGO III/IV) by immunohistochemistry (IHC). In 70/103 cases, positive staining of tumor cells was observed. In univariate Cox regression analysis, PLG staining was positively associated with prolonged overall survival (OS) [hazard ratio (HR)=0.59, p=0.026] of the patients. In multivariable analysis, PLG, together with residual tumor mass, remained a statistically significant independent prognostic marker (HR=0.49, p=0.009). In another small patient cohort (n=29), we assessed mRNA expression levels of PLG by quantitative PCR. Here, elevated PLG mRNA levels were also significantly associated with prolonged OS of patients (Kaplan-Meier analysis; p=0.001). This finding was validated by in silico analysis of a microarray data set (n=398) from The Cancer Genome Atlas (Kaplan-Meier analysis; p=0.031). In summary, these data indicate that elevated PLG expression represents a favorable prognostic biomarker in advanced (FIGO III/IV) high-grade serous ovarian cancer.

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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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