Antibody Immunity to the p53 Oncogenic Protein Is a Prognostic Indicator in Ovarian Cancer

2006 ◽  
Vol 24 (5) ◽  
pp. 762-768 ◽  
Author(s):  
Vivian Goodell ◽  
Lupe G. Salazar ◽  
Nicole Urban ◽  
Charles W. Drescher ◽  
Heidi Gray ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Tumor Antigens ◽  
Enzyme Linked Immunosorbent Assay ◽  
Advanced Stage ◽  
Topoisomerase Iiα ◽  
P53 Antibodies ◽  
Stage Disease ◽  
Her 2

Purpose Presence of intratumoral T-cell infiltration has been linked to improved survival in ovarian cancer patients. We questioned whether antibody immunity specific for ovarian cancer tumor antigens would predict disease outcome. We evaluated humoral immune responses against ovarian cancer antigens p53, HER-2/neu, and topoisomerase IIα. Patients and Methods Serum was collected from 104 women (median age, 59 years; range, 34 to 89 years) at the time of their initial definitive surgery for ovarian cancer. Serum was analyzed by enzyme-linked immunosorbent assay for antibodies to p53, HER-2/neu, and topoisomerase IIα proteins. Antibody immunity to tetanus toxoid was assessed as a control. The incidence of humoral immunity at the time of diagnosis to any of these three antigens was tabulated. For patients with advanced-stage disease (III/IV), correlation was made between the presence of tumor-specific immunity at the time of diagnosis and overall survival. Patients were followed for a median of 1.8 years. Results Multivariate analysis showed the presence of p53 antibodies to be an independent variable for prediction of overall survival in advanced-stage patients. Overall survival was significantly higher for patients with antibodies to p53 when compared with patients without p53 antibodies (P = .01). The median survival for p53 antibody-positive patients was 51 months (95% CI, 23.5 to 60.5 months) compared with 24 months (95% CI, 19.4 to 28.6 months) for patients without antibodies to p53. Conclusion Data presented here demonstrate that advanced stage ovarian cancer patients can have detectable tumor-specific antibody immunity and that immunity to p53 may predict improved overall survival in patients with advanced-stage disease.

Survival in advanced-stage ovarian cancer patients with non-Ashkenazi Jewish BRCA mutations

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 5514-5514
Author(s):  
R. A. Lacour ◽  
S. N. Westin ◽  
M. S. Daniels ◽  
M. R. Milam ◽  
C. C. Sun ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Initial Treatment ◽  
Brca Mutation ◽  
Complete Response ◽  
Advanced Stage ◽  
Ashkenazi Jewish ◽  
Brca Mutations ◽  
Brca Mutation Carriers

5514 Background: Previous studies have shown a survival advantage in ovarian cancer patients with Ashkenazi-Jewish BRCA founder mutations compared to sporadic ovarian cancer patients. The purpose of this study is to determine if this association exists in ovarian cancer patients with non- Ashkenazi Jewish (non-AJ) BRCA1 or BRCA2 mutations. Methods: Patients with stage III or IV ovarian, fallopian tube, or primary peritoneal cancer and a BRCA1 or BRCA2 mutation, seen for genetic testing between January 1996 and October 2006, were identified from the institutional and genetics databases. Medical records were reviewed for clinical factors including response to initial chemotherapy. Response is defined as no clinical evidence of disease with normalization of serum CA-125 and no radiographic evidence of disease or a negative second-look surgery. Patients with sporadic ovarian cancer, without a family history of breast or ovarian cancer, were compared to similar cases, matched by age, stage, and year of diagnosis. Progression-free and overall survival were calculated by the method of Kaplan-Meier. Chi-square tests and univariate logistic regression were also used in the data analysis. Results: Thirty-nine advanced-stage ovarian cancer patients with non-AJ BRCA mutations and 47 matched, advanced-stage sporadic ovarian cancer patients have been analyzed. Compared to patients with sporadic ovarian cancer, non-AJ BRCA mutation carriers had a longer progression-free survival (PFS, 32.4 mos. vs. 22.1 mos., p = 0.0303) and overall survival (OS, 101.4 mos. vs. 51.3 mos., p < 0.001). Similarly, 72% of the non-AJ BRCA mutation carriers had a complete response to initial treatment, compared to 45% of the sporadic ovarian cancer patients (p = 0.01). The odds of complete response to initial treatment were 3.2 times greater in the non-AJ BRCA group than in the sporadic group (OR 3.2; 95% CI 1.27 - 8.15). Conclusions: This study demonstrates a significant survival advantage in advanced-stage ovarian cancer patients with non-AJ BRCA mutations when compared to similar patients with sporadic ovarian cancer. Response to initial treatment appears to impact this improved survival. No significant financial relationships to disclose.

Consolidation hyperthermic intraperitoneal chemotherapy for the treatment of advanced stage ovarian carcinoma: A 3-year experience.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e17094-e17094
Author(s):  
Alberto Mendivil ◽  
Lisa Nicole Abaid ◽  
John V. Brown ◽  
Kristina Mori ◽  
Katrina Lopez ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Disease Progression ◽  
Cancer Patients ◽  
Intraperitoneal Chemotherapy ◽  
Hyperthermic Intraperitoneal Chemotherapy ◽  
Progression Free Survival ◽  
Advanced Stage ◽  
Free Survival ◽  
Primary Induction

e17094 Background: Hyperthermic intraperitoneal chemotherapy (HIPEC) potentially confers significant survival benefits in the management of ovarian cancer although the long-term data remain scant. We sought to compare the survival rates of advanced stage ovarian cancer patients who were treated with primary induction therapy alone or in conjunction with consolidation HIPEC. Methods: Sixty-nine ovarian cancer patients who underwent surgery and completed their primary induction chemotherapy were treated with consolidation carboplatin (AUC 10) based HIPEC and compared to a historical cohort that received surgery and primary chemotherapy alone (n=69). The demographic and clinical characteristics in which we were primarily interested included: patient age, body mass index, surgery and pathology data, chemotherapy regimen, toxicity, and progression free/overall survival. Results: The two patient groups were similar in terms of tumor characteristics, cyto-reductive status, distribution of neoadjuvant chemotherapy and number of maintenance chemotherapy cycles administered (P> 0.05). Progression free survival was significantly more pronounced in the HIPEC (25.1 months) patients compared to the control group (20 months) (P=0.024) and there was a decreased risk of disease progression accorded to the patients treated with HIPEC (HR, 2.1028; 95% CI: 1.2941 to 3.4167; P=0.0027). However, we did not discern any HIPEC related overall survival advantages (P=0.29). Conclusions: The results from our ovarian cancer study suggest that adjunctive HIPEC proffers a significant progression free survival advantage and a decreased risk for disease progression. There was, however, no overall survival advantage discerned in the HIPEC group. We also recognize that HIPEC remains controversial and thus, randomized studies evaluating HIPEC compared to standard chemotherapy in the management of ovarian cancer are warranted.

scholarly journals Interleukin-6, Cortisol, and Depressive Symptoms in Ovarian Cancer Patients

2008 ◽  
Vol 26 (29) ◽  
pp. 4820-4827 ◽  
Author(s):  
Susan K. Lutgendorf ◽  
Aliza Z. Weinrib ◽  
Frank Penedo ◽  
Daniel Russell ◽  
Koen DeGeest ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Depressive Symptoms ◽  
Cancer Patients ◽  
Interleukin 6 ◽  
Early Stage ◽  
Area Under The Curve ◽  
Pelvic Mass ◽  
Enzyme Linked Immunosorbent Assay ◽  
Advanced Stage ◽  
Affective Components

Purpose Inflammatory processes have been implicated in the pathogenesis of both depression and cancer. Links between depressive symptoms, interleukin-6 (IL-6), and cortisol dysregulation have been demonstrated in cancer patients, but vegetative versus affective components of depression have been minimally examined. The objective of the current study was to examine associations between IL-6, diurnal cortisol rhythms, and facets of depression in epithelial ovarian cancer patients. Patients and Methods Patients awaiting surgery for a pelvic mass suspected for ovarian cancer completed questionnaires, collected salivary samples for 3 days presurgery, and gave a presurgical blood sample. Ascites was obtained during surgery. IL-6 was measured by enzyme-linked immunosorbent assay and cortisol by a chemiluminescence immunoassay. The final sample included 112 invasive ovarian cancer patients (86 advanced stage, 26 early stage) and 25 patients with tumors of low malignant potential (LMP). Results Advanced-stage ovarian cancer patients demonstrated elevations in vegetative and affective depressive symptoms, plasma IL-6, and the cortisol area under the curve (AUC) compared with patients with LMP tumors (all P < .05). Among invasive ovarian cancer patients, greater vegetative depression was related to elevated IL-6 in plasma (P = .008) and ascites (P = .024), but affective depression was unrelated to IL-6. Elevations in total depression (P = .026) and vegetative depression (P = .005) were also related to higher evening cortisol levels. Plasma IL-6 was related to greater afternoon and evening cortisol and cortisol AUC (all P values < .005). Conclusion These results demonstrate significant relationships between IL-6, cortisol, and vegetative depression, and may have implications for treatment of depression in ovarian cancer patients.

scholarly journals Factors predict postoperative morbidity in advanced stage ovarian cancer patients who underwent cytoreductive surgery: a systematic review and meta-analysis

2021 ◽  
Author(s):  
Malika Kengsakul ◽  
Gatske M. Nieuwenhuyzen-de Boer ◽  
Suwasin Udomkarnjananun ◽  
Stephen J. Kerr ◽  
Christa D. Niehot ◽  
...  
Keyword(s):  
Systematic Review ◽  
Ovarian Cancer ◽  
Cancer Patients ◽  
Cytoreductive Surgery ◽  
Postoperative Morbidity ◽  
Meta Analysis ◽  
Advanced Stage

scholarly journals Novel Indications of Epigenetic Therapy in Ovarian Cancer

2021 ◽  
Author(s):  
Courtney Griffiths ◽  
Michelle Bilbao ◽  
Lauren Krill ◽  
Olga Ostrovsky
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Early Diagnosis ◽  
Gynecologic Cancer ◽  
Epigenetic Modifications ◽  
Epigenetic Therapy ◽  
Intratumor Heterogeneity ◽  
Survival Outcomes ◽  
Advanced Stage ◽  
Stage Disease

Early diagnosis and intervention are some of the longstanding challenges associated with ovarian cancer, which is the leading cause of gynecologic cancer mortality. While the majority of patients who present with advanced stage disease at time of diagnosis will initially respond to traditional combination platinum and taxane-based chemotherapy in conjunction with cytoreductive surgery, approximately 70% will ultimately recur due to chemoresistance within the first two years. Intratumor heterogeneity is proposed to be a leading factor in the development of chemoresistance and resultant poorer outcomes for those with recurrent or advanced stage disease. Both inherent and acquired mechanisms of chemoresistance are postulated to be a result of alterations in gene expression, also known as epigenetic modifications. Therefore, epigenetic therapy is a pivotal avenue which allows for reversal of chemoresistance in cancer through the targeting of aberrant mutations. In this chapter, we discuss how these epigenetic modifications prove to be promising targets in cancer therapy leading to heightened drug sensitivity and improved patient survival outcomes.

scholarly journals Potential Prognostic Immune Biomarkers of Overall Survival in Ovarian Cancer Through Comprehensive Bioinformatics Analysis: A Novel Artificial Intelligence Survival Prediction System

2021 ◽  
Vol 8 ◽  
Author(s):  
Tingshan He ◽  
Liwen Huang ◽  
Jing Li ◽  
Peng Wang ◽  
Zhiqiao Zhang
Keyword(s):  
Artificial Intelligence ◽  
Ovarian Cancer ◽  
Overall Survival ◽  
Transcription Factors ◽  
Cancer Patients ◽  
Prognostic Model ◽  
Cox Regression ◽  
Differentially Expressed ◽  
Immune Genes ◽  
Immune Biomarkers

Background: The tumour immune microenvironment plays an important role in the biological mechanisms of tumorigenesis and progression. Artificial intelligence medicine studies based on big data and advanced algorithms are helpful for improving the accuracy of prediction models of tumour prognosis. The current research aims to explore potential prognostic immune biomarkers and develop a predictive model for the overall survival of ovarian cancer (OC) based on artificial intelligence algorithms.Methods: Differential expression analyses were performed between normal tissues and tumour tissues. Potential prognostic biomarkers were identified using univariate Cox regression. An immune regulatory network was constructed of prognostic immune genes and their highly related transcription factors. Multivariate Cox regression was used to identify potential independent prognostic immune factors and develop a prognostic model for ovarian cancer patients. Three artificial intelligence algorithms, random survival forest, multitask logistic regression, and Cox survival regression, were used to develop a novel artificial intelligence survival prediction system.Results: The current study identified 1,307 differentially expressed genes and 337 differentially expressed immune genes between tumour samples and normal samples. Further univariate Cox regression identified 84 prognostic immune gene biomarkers for ovarian cancer patients in the model dataset (GSE32062 dataset and GSE53963 dataset). An immune regulatory network was constructed involving 63 immune genes and 5 transcription factors. Fourteen immune genes (PSMB9, FOXJ1, IFT57, MAL, ANXA4, CTSH, SCRN1, MIF, LTBR, CTSD, KIFAP3, PSMB8, HSPA5, and LTN1) were recognised as independent risk factors by multivariate Cox analyses. Kaplan-Meier survival curves showed that these 14 prognostic immune genes were closely related to the prognosis of ovarian cancer patients. A prognostic nomogram was developed by using these 14 prognostic immune genes. The concordance indexes were 0.760, 0.733, and 0.765 for 1-, 3-, and 5-year overall survival, respectively. This prognostic model could differentiate high-risk patients with poor overall survival from low-risk patients. According to three artificial intelligence algorithms, the current study developed an artificial intelligence survival predictive system that could provide three individual mortality risk curves for ovarian cancer.Conclusion: In conclusion, the current study identified 1,307 differentially expressed genes and 337 differentially expressed immune genes in ovarian cancer patients. Multivariate Cox analyses identified fourteen prognostic immune biomarkers for ovarian cancer. The current study constructed an immune regulatory network involving 63 immune genes and 5 transcription factors, revealing potential regulatory associations among immune genes and transcription factors. The current study developed a prognostic model to predict the prognosis of ovarian cancer patients. The current study further developed two artificial intelligence predictive tools for ovarian cancer, which are available at https://zhangzhiqiao8.shinyapps.io/Smart_Cancer_Survival_Predictive_System_17_OC_F1001/ and https://zhangzhiqiao8.shinyapps.io/Gene_Survival_Subgroup_Analysis_17_OC_F1001/. An artificial intelligence survival predictive system could help improve individualised treatment decision-making.

Determination of Both TP53 Mutation Status and the Amount of p53 Protein Has Limited Diagnostic Importance for Patients with Ovarian Cancer

2022 ◽  
Vol 29 ◽  
Author(s):  
Sebastian M. Klein ◽  
Maria Bozko ◽  
Astrid Toennießen ◽  
Nisar P. Malek ◽  
Przemyslaw Bozko
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Tp53 Mutation ◽  
P53 Protein ◽  
Mutation Status ◽  
Tumor Tissues ◽  
Tp53 Status ◽  
Diagnostic Importance

Background: Ovarian cancer is one of the most aggressive types of gynecologic cancers. Many patients have a relapse within two years after diagnosis and subsequent therapy. Among different genetic changes generally believed to be important for the development of cancer, TP53 is the most common mutation in the case of ovarian tumors. Objective: Our work aims to compare the outcomes of different comparisons based on the overall survival of ovarian cancer patients, determination of TP53 status, and amount of p53 protein in tumor tissues. Methods: We analyzed and compared a collective of 436 ovarian patient’s data. Extracted data include TP53 mutation status, p53 protein level, and information on the overall survival. Values for p53 protein level in dependence of TP53 mutation status were compared using the Independent-Samples t-Test. Survival analyses were displayed by Kaplan-Meier plots, using the log-rank test to check for statistical significance. Results: We have not found any statistically significant correlations between determination of TP53 status, amount of p53 protein in tumor tissues, and overall survival of ovarian cancer patients. Conclusion: In ovarian tumors both determination of TP53 status as well as p53 protein amount has only limited diagnostic importance.

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