Dataset Information

Ovarian cancer risk score predicts chemo-response and outcome in epithelial ovarian carcinoma patients.

ABSTRACT:

Objective

Cytoreductive surgery followed by adjuvant chemotherapy is a standard frontline treatment for epithelial ovarian cancer (EOC). We aimed to develop an ovarian cancer risk score (OVRS) based on the expression of 10 ovarian-cancer-related genes to predict the chemoresistance, and outcomes of EOC patients.

Methods

We designed a case-control study with total 149 EOC women including 75 chemosensitives and 74 chemoresistants. Gene expression was measured using the quantitative real-time polymerase chain reaction. We tested for correlation between the OVRS and chemosensitivity or chemoresistance, disease-free survival (DFS), and overall survival (OS), and validated the OVRS by analyzing patients from the TCGA database.

Results

The chemosensitive group had lower OVRS than the chemoresistant group (5 vs. 15, p?0.001, Mann-Whitney U test). Patients with disease relapse (13 vs. 5, p<0.001, Mann-Whitney U test) or disease-related death (13.5 vs. 6, p<0.001) had higher OVRS than those without. OVRS ?10 (hazard ratio=3.29; 95% confidence interval=1.94-5.58; p<0.001) was the only predictor for chemoresistance in multivariate analysis. The median DFS (5 months vs. 24 months) and OS (39 months vs. >60 months) of patients with OVRS ?10 were significantly shorter than those of patients with OVRS <10). The high OVRS group also had significantly shorter median OS than the low OVRS group in 255 patients in the TCGA database (39 vs. 49 months, p=0.046).

Conclusions

Specific genes panel can be clinically applied in predicting the chemoresistance and outcome, and decision-making of epithelial ovarian cancer.

SUBMITTER: Lu HY

PROVIDER: S-EPMC7930441 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

Ovarian cancer risk score predicts chemo-response and outcome in epithelial ovarian carcinoma patients.

Lu Hsiao Yun HY Tai Yi Jou YJ Chen Yu Li YL Chiang Ying Cheng YC Hsu Heng Cheng HC Cheng Wen Fang WF

Journal of gynecologic oncology 20201203 2

<h4>Objective</h4>Cytoreductive surgery followed by adjuvant chemotherapy is a standard frontline treatment for epithelial ovarian cancer (EOC). We aimed to develop an ovarian cancer risk score (OVRS) based on the expression of 10 ovarian-cancer-related genes to predict the chemoresistance, and outcomes of EOC patients.<h4>Methods</h4>We designed a case-control study with total 149 EOC women including 75 chemosensitives and 74 chemoresistants. Gene expression was measured using the quantitative ...[more]

PMID: 33327048

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Project description:BackgroundEpithelial ovarian cancer (EOC) is an aggressive disease with poor prognosis. The expression of cytokine-induced apoptosis inhibitor 1 (CIAPIN1) correlates with the malignant progression of several cancers. However, the relationship between the subcellular localization of CIAPIN1 and clinical characteristics in EOC remains unclear.MethodsImmunohistochemistry was performed to detect CIAPIN1 expression in 108 EOC tissues. CIAPIN1 expressions in eight fresh EOC tissues were detected by Western blotting. The relationship between CIAPIN1 subcellular expression and patients' clinicopathological features, including prognosis, was evaluated. Immunohistochemistry and immunofluorescence were employed to assess the CIAPIN1 subcellular localization in the EOC cell lines A2780 and HO8910. In addition, all patients were followed up to assess the prognostic value of CIAPIN1 in patients with EOC.ResultsCIAPIN1 is highly expressed in EOC, but is present at low levels in paired non-cancerous ovarian epithelial tissues. The results of Western blotting were in accordance with the immunohistochemical results. Poor differentiation of the tumors and EOC cell lines correlated with higher levels of CIAPIN1 nuclear expression. CIAPIN1 nuclear expression significantly correlated with the Federation International of Gynecology and Obstetrics (FIGO) stage and histological differentiation (P?=?0.034 and P?<?0.0001, respectively). Moreover, nuclear localization of CIAPIN1 was selected as an unfavorable prognostic factor by both univariate and multivariate analyses ( P?<?0.001). However, no significant correlations were observed between cytoplasmic localization of CIAPIN1 and clinicopathological parameters.ConclusionsCIAPIN1 might play a crucial role in the differentiation of EOC cells. Elevated expression of nuclear CIAPIN1 negatively correlated with the survival of EOC patients, suggesting that nuclear CIAPIN1 might serve as a prognostic biomarker for EOC patients.

Project description:BACKGROUND:Currently, the measurement of immune cells in previous studies is usually subjective, and no immune-based prognostic model has been established for chordoma. In this study, we sought to simultaneously measure tumor-infiltrating lymphocyte (TIL) subtypes in chordoma samples using an objective method and develop an immune risk score (IRS) model for survival prediction. METHODS:Multiplexed quantitative immunofluorescence staining was used to determine the TIL levels in the tumoral and stromal subareas of 114 spinal chordoma specimens (54 in the training and 60 in the validation cohort) for programmed death-1 (PD-1), CD3, CD8, CD20 (where CD is cluster of differentiation), and FOXP3. Flow cytometry was performed to validate the immunofluorescence assay for lymphocyte measurement on an additional five fresh chordoma specimens. Subsequently, the IRS model was built using the least absolute shrinkage and selection operator (LASSO) Cox regression method. RESULTS:Flow cytometry and quantitative immunofluorescence showed similar lymphocytic percentages and TIL subpopulation proportions in the fresh tumor specimens. With the training data, the LASSO model identified four immune features for IRS construction: tumoral FOXP3, tumoral PD-1, stromal FOXP3, and stromal CD8. In both cohorts, a high IRS was significantly associated with tumoral programmed cell death-1 ligand 1 expression, Enneking inappropriate tumor resection, and surrounding muscle invasion by tumor. Multivariate Cox regression and stratified analysis in the two cohorts revealed that the IRS was an independent predictor and could effectively separate patients with similar Enneking staging into different risk subgroups, with significantly different survival rates. Further receiver operating characteristic analysis found that the IRS classifier had a better prognostic value than the traditional clinicopathological factors and compensated for the deficiency of Enneking staging for outcome prediction. More importantly, a nomogram based on the IRS and clinical predictors showed adequate performance in estimating disease recurrence and survival of patients. CONCLUSIONS:These data support the use of the IRS signature as a reliable prognostic tool in spinal chordoma and may facilitate individualized therapy decision making for patients.

Project description:Background As we all know, patients with epithelial ovarian carcinoma have poor prognosis and high recurrence rate. It is critical and challenging to screen out the patients with high risk of recurrence. At present, there are some models predicting the overall survival of epithelial ovarian carcinoma, however, there is no widely accepted tool or applicable model predicting the recurrence risk of epithelial ovarian carcinoma patients. The objective of this study was to establish and verify a nomogram to predict the recurrence risk of EOC. Methods We reviewed the clinicopathological and prognostic data of 193 patients with EOC who achieved clinical complete remission after cytoreductive surgery and chemotherapy between January 2003 and December 2013 in Peking University First Hospital. The nomogram was established with the risk factors selected by LASSO regression. The medical data of 187 EOC patients with 5-year standard follow-up in Peking University Third Hospital and Beijing Obstetrics and Gynecology Hospital were used for external validation of the nomogram. AUC curve and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration. Results The nomogram for 3-year recurrence risk was established with FIGO stage, histological grade, histological type, lymph node metastasis status and serum CA125 level at diagnosis. The total score can be obtained by adding the grading values of these factors together. The C statistics was 0.828 [95% CI, 0.764–0.884] and the Chi-square value is 3.6 (P?=?0.731?>?0.05) with the training group. When the threshold value was set at 198, the sensitivity, specificity, positive predictive value, negative predictive value and concordance index were 88.8, 67.0, 71.8, 86.3% and 0.558 respectively. In the external validation, the C statistics was 0.803 [95%CI, 0.738–0.867] and the Chi-square value is 11.04 (P?=?0.135?>?0.05). With the threshold value of 198, the sensitivity, specificity, positive predictive value, negative predictive value and concordance index of the nomogram were 75.7, 77.0, 83.2, 67.9%, and 0.52 respectively. Conclusions We established and validated a nomogram to predict 3-year recurrence risk of patients with EOC who achieved clinical complete remission after cytoreductive surgery and chemotherapy. This nomogram with good discrimination and calibration might be useful for screening out the patients with high risk of recurrence.

Dataset Information

Ovarian cancer risk score predicts chemo-response and outcome in epithelial ovarian carcinoma patients.

Objective

Methods

Results

Conclusions

Publications

Ovarian cancer risk score predicts chemo-response and outcome in epithelial ovarian carcinoma patients.

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