Online biomarker validation of survival-associated biomarkers in breast and ovarian cancer using microarray data of 3,862 patients.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 10571-10571
Author(s):  
Balazs Gyorffy ◽  
Andras Lanczky ◽  
Zoltan Szallasi
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Cancer Patients ◽  
Microarray Data ◽  
Cancer Prognosis ◽  
Analysis Tool ◽  
Breast And Ovarian Cancer ◽  
Kaplan Meier ◽  
Biomarker Validation ◽  
Prognostic Power

10571 Background: The pre-clinical validation of prognostic gene candidates in large independent patient cohorts is a pre-requisite for the development of robust biomarkers. Today, curated microarray cohorts combined with appropriate clinical data offer a cost effective tool to prescreen potential new biomarkers. In present study we expanded our online Kaplan-Meier plotter tool to assess the effect of genes on ovarian cancer prognosis. Methods: Gene expression data and survival information of breast and ovarian cancer patients were downloaded from GEO and TCGA. To analyze the prognostic value of the selected gene in the various cohorts the patients are divided into two groups according to the quantile expression of the gene. Filtering is implemented for stage, grade, and histology subtypes. Follow-up threshold is implemented to exclude long-term effects. A Kaplan-Meier survival plot is generated and significance is computed in the R statistical environment using Bioconductor packages. The combination of several probe sets can be employed to assess the mean of their expression as a multigene predictor of survival. Results: All together 1,390 ovarian cancer patients and 2,472 breast cancer patients were entered into the database. These groups can be compared using relapse free survival (n=2,324 in breast cancer and 1,090 in ovarian cancer) or overall survival (n=464 and n=1,287). We used this integrative data analysis tool to validate the prognostic power of 37 ovarian cancer associated biomarkers identified in the literature. Of these, CA125 (p=3.7e-5, HR=1.4), CDKN1B (p=5.4e-5, HR=1.4), KLK6 (p=0.002, HR=0.79), IFNG (p=0.004, HR=0.81), P16 (p=0.02, HR=0.66) and BIRC5 (p=0.00017, HR=0.75) were associated with survival. Conclusions: We set up a global online biomarker validation platform to mine all available microarray data to assess the prognostic power of 22,277 genes in 2,472 breast and 1,390 ovarian cancer patients. Registration-free online access at: http://www.kmplot.com/.

scholarly journals Implementing an online tool for genome-wide validation of survival-associated biomarkers in ovarian-cancer using microarray data from 1287 patients

2012 ◽  
Vol 19 (2) ◽  
pp. 197-208 ◽  
Author(s):  
Balázs Győrffy ◽  
András Lánczky ◽  
Zoltán Szállási
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Cancer Patients ◽  
Microarray Data ◽  
Prognostic Value ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Analysis Tool ◽  
Online Tool ◽  
Prognostic Power

The validation of prognostic biomarkers in large independent patient cohorts is a major bottleneck in ovarian cancer research. We implemented an online tool to assess the prognostic value of the expression levels of all microarray-quantified genes in ovarian cancer patients. First, a database was set up using gene expression data and survival information of 1287 ovarian cancer patients downloaded from Gene Expression Omnibus and The Cancer Genome Atlas (Affymetrix HG-U133A, HG-U133A 2.0, and HG-U133 Plus 2.0 microarrays). After quality control and normalization, only probes present on all three Affymetrix platforms were retained (n=22 277). To analyze the prognostic value of the selected gene, we divided the patients into two groups according to various quantile expressions of the gene. These groups were then compared using progression-free survival (n=1090) or overall survival (n=1287). A Kaplan–Meier survival plot was generated and significance was computed. The tool can be accessed online at www.kmplot.com/ovar. We used this integrative data analysis tool to validate the prognostic power of 37 biomarkers identified in the literature. Of these, CA125 (MUC16; P=3.7×10−5, hazard ratio (HR)=1.4), CDKN1B (P=5.4×10−5, HR=1.4), KLK6 (P=0.002, HR=0.79), IFNG (P=0.004, HR=0.81), P16 (P=0.02, HR=0.66), and BIRC5 (P=0.00017, HR=0.75) were associated with survival. The combination of several probe sets can further increase prediction efficiency. In summary, we developed a global online biomarker validation platform that mines all available microarray data to assess the prognostic power of 22 277 genes in 1287 ovarian cancer patients. We specifically used this tool to evaluate the effect of 37 previously published biomarkers on ovarian cancer prognosis.

scholarly journals An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients

2009 ◽  
Vol 123 (3) ◽  
pp. 725-731 ◽  
Author(s):  
Balazs Györffy ◽  
Andras Lanczky ◽  
Aron C. Eklund ◽  
Carsten Denkert ◽  
Jan Budczies ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Survival Analysis ◽  
Microarray Data ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Analysis Tool

scholarly journals Analysis of clinical characteristics in breast cancer patients with the Japanese founder mutation of BRCA1 L63X.

2015 ◽  
Vol 33 (28_suppl) ◽  
pp. 22-22
Author(s):  
Reiko Yoshida ◽  
Mayuko Inuzuka ◽  
Tomoko Watanabe ◽  
Junko Yotsumoto ◽  
Takashi Kuwayama ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Cancer Patients ◽  
Clinical Characteristics ◽  
Founder Mutation ◽  
Breast Cancers ◽  
Pathological Features ◽  
Breast Cancer Patients ◽  
Breast And Ovarian Cancer ◽  
Brca1 Mutations

22 Background: Hereditary breast and ovarian cancer (HBOC) is a high-penetrance inherited disease, and founder mutation has been reported in the West. However, there are yet no reports of founder mutation of HBOC on breast cancer in the Japanese population. In this study, we report the breast cancer clinical characteristics of L63X, which is one of the founder mutations in BRCA1 in the Japanese population. Methods: Data on 223 affected breast cancer patients (28 BRCA1 carriers, 19 BRCA2 carriers, and 176 non-carriers) were collected at Showa University in Tokyo from September 2010 to June 2015. In 22 independent mutations of BRCA1, the L63X mutation was detected in 9 patients. Data regarding the age of breast cancer onset, pathological features, clinical features, and family history were collected. Results: The age of onset was no significant differences between the L63X mutation and other BRCA1 mutations (39.7 vs. 38.5years). The proportion of triple negative breast cancer patients was 87.5% in the L63X mutation carriers and 89.5% in other BRCA1 mutation carriers. No patients of the L63X affected bilateral breast cancers. On the other hand, 36.7% of other BRCA1mutations affected bilateral breast cancers. There was no significant difference in pathological features (intrinsic subtype, nuclear grade and ki-67 index). The L63X carriers tended to have a family history of breast cancers. All L63X mutations were detected in the Eastern part of Japan. Conclusions: The breast cancer clinical characteristics of L63X might be considered no different from other types of BRCA1 mutations. Recently, it has been reported that breast and ovarian cancer risks varied according to the type and location of BRCA1/2 mutations. L63X mutation is located in the breast cancer cluster region in BRCA1. Further investigation is necessary for appropriate validation and accumulation of data.

scholarly journals Pedigree and BRCA gene analysis in breast cancer patients to identify hereditary breast and ovarian cancer syndrome to prevent morbidity and mortality of disease in Indian population

Tumor Biology ◽  
2017 ◽  
Vol 39 (2) ◽  
pp. 101042831769430 ◽  
Author(s):  
Mina Darooei ◽  
Subhadra Poornima ◽  
Bibi Umae Salma ◽  
Gayatri R Iyer ◽  
Akhilesh N Pujar ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Genetic Counseling ◽  
Cancer Patients ◽  
Pedigree Analysis ◽  
Care Hospital ◽  
Breast Cancer Patients ◽  
Cancer Syndrome ◽  
Breast And Ovarian Cancer ◽  
Targeted Mutation

Global burden of breast cancer is expected to increase to >2 million new cases every year by 2030 and 10% of these are likely to have hereditary breast and ovarian cancer syndrome. Identifying these individuals by pedigree and BRCA1/2 mutation analyses will enable us to offer targeted mutation testing and appropriate counseling. This study from a tertiary care hospital showed that of the 127 breast cancer patients on treatment during 2014–2015, 24 of them fulfilled the criteria of hereditary breast and ovarian cancer syndrome after detailed verbal autopsy and pedigree analysis, and BRCA1 and 2 next-generation sequencing done after pre-test counseling revealed mutations in 13 cases (54%), these included 9 BRCA1 mutations (69%) and 4 BRCA2 mutation (31%). Subsequent post-test counseling recommended targeted mutation analysis for 64 high-risk members in these 13 families with pathogenic mutations, which will help in surveillance for early detection, appropriate management, and prevention of the disease by decreasing the burden to both family and nation. Results from this preliminary study highlight the importance of genetic counseling, pedigree analysis, and genetic testing. It can be recommended that all oncology units should have a genetic counseling service for providing appropriate support to oncologists, patients, and families to prevent unnecessary testing; however, breast cancer screening program is incomplete without evaluating for hereditary breast and ovarian cancer syndrome.

scholarly journals Breast cancer prognosis in relation to family history of breast and ovarian cancer

2004 ◽  
Vol 90 (7) ◽  
pp. 1378-1381 ◽  
Author(s):  
L Thalib ◽  
S Wedrén ◽  
F Granath ◽  
H-O Adami ◽  
B Rydh ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Family History ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Breast And Ovarian Cancer ◽  
History Of

Exploratory Data Analysis on Breast Cancer Prognosis

2018 ◽  
pp. 1794-1805
Author(s):  
Mohammad Mehdi Owrang O. ◽  
Yasmine M. Kanaan ◽  
Robert L. Copeland Jr. ◽  
Melvin Gaskins ◽  
Robert L. DeWitty Jr.
Keyword(s):  
Breast Cancer ◽  
Marital Status ◽  
Cancer Patients ◽  
Proportional Hazards ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Breast Cancer Patients ◽  
Howard University ◽  
Kaplan Meier ◽  
Seer Data

Breast cancer prognosis is a vital element of providing effective treatment for breast cancer patients. Breast cancer prediction survivability has mainly been studied based on pathological factors such as tumor size, tumor grade, number of positive lymph nodes, and hormone receptors among others. This chapter looks at the significance of the non-clinical prognostic factors of age, ethnicity, and marital status in finding the prognosis for breast cancer patients. The National Cancer Institute's SEER data and the Howard University Cancer Center Tumor Registry data are analyzed. Prognostic tool NPI (Nottingham Prognostic Index) and survival analysis tools of Cox proportional hazards and Kaplan-Meier survival curve are used in analyzing the experiments. The results suggest that age, ethnicity, and marital status have some influence on the survivability rate of breast cancer patients.

BRCA1/2 mutation prevalence in triple-negative breast cancer patients without family history of breast and ovarian cancer.

2016 ◽  
Vol 34 (15_suppl) ◽  
pp. 1090-1090 ◽  
Author(s):  
Kerstin Rhiem ◽  
Christoph Engel ◽  
Jutta Engel ◽  
Dieter Niederacher ◽  
Christian Sutter ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Family History ◽  
Cancer Patients ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Breast Cancer Patients ◽  
Breast And Ovarian Cancer ◽  
History Of

scholarly journals Genetic Testing and Results in a Population-Based Cohort of Breast Cancer Patients and Ovarian Cancer Patients

2019 ◽  
Vol 37 (15) ◽  
pp. 1305-1315 ◽  
Author(s):  
Allison W. Kurian ◽  
Kevin C. Ward ◽  
Nadia Howlader ◽  
Dennis Deapen ◽  
Ann S. Hamilton ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Genetic Testing ◽  
Cancer Patients ◽  
Population Based ◽  
Cancer Type ◽  
Breast Cancer Patients ◽  
Breast And Ovarian Cancer ◽  
Pathogenic Variants ◽  
Genetic Test Results

PURPOSE Genetic testing for cancer risk has expanded rapidly. We examined clinical genetic testing and results among population-based patients with breast and ovarian cancer. METHODS The study included all women 20 years of age or older diagnosed with breast or ovarian cancer in California and Georgia between 2013 and 2014 and reported to the SEER registries covering the entire state populations. SEER data were linked to results from four laboratories that performed nearly all germline cancer genetic testing. Testing use and results were analyzed at the gene level. RESULTS There were 77,085 patients with breast cancer and 6,001 with ovarian cancer. Nearly one quarter of those with breast cancer (24.1%) and one third of those with ovarian cancer (30.9%) had genetic test results. Among patients with ovarian cancer, testing was lower in blacks (21.6%; 95% CI, 18.1% to 25.4%; v whites, 33.8%; 95% CI, 32.3% to 35.3%) and uninsured patients (20.8%; 95% CI, 15.5% to 26.9%; v insured patients, 35.3%; 95% CI, 33.8% to 36.9%). Prevalent pathogenic variants in patients with breast cancer were BRCA1 (3.2%), BRCA2 (3.1%), CHEK 2 (1.6%), PALB2 (1.0%), ATM (0.7%), and NBN (0.4%); in patients with ovarian cancer, prevalent pathogenic variants were BRCA1 (8.7%), BRCA2 (5.8%), CHEK2 (1.4%), BRIP1 (0.9%), MSH2 (0.8%), and ATM (0.6%). Racial/ethnic differences in pathogenic variants included BRCA1 (ovarian cancer: whites, 7.2%; 95% CI, 5.9% to 8.8%; v Hispanics, 16.1%; 95% CI, 11.8% to 21.2%) and CHEK2 (breast cancer: whites, 2.3%; 95% CI, 1.8% to 2.8%; v blacks, 0.1%; 95% CI, 0% to 0.8%). When tested for all genes that current guidelines designate as associated with their cancer type, 7.8% of patients with breast cancer and 14.5% of patients with ovarian cancer had pathogenic variants. CONCLUSION Clinically-tested patients with breast and ovarian cancer in two large, diverse states had 8% to 15% prevalence of actionable pathogenic variants. Substantial testing gaps and disparities among patients with ovarian cancer are targets for improvement.

scholarly journals BRCA Genetic Test and Risk-Reducing Salpingo-Oophorectomy for Hereditary Breast and Ovarian Cancer: State-of-the-Art

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2562
Author(s):  
Masayuki Sekine ◽  
Koji Nishino ◽  
Takayuki Enomoto
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Cancer Patients ◽  
Genetic Test ◽  
State Of The Art ◽  
Parp Inhibitors ◽  
Pathogenic Variant ◽  
Breast And Ovarian Cancer ◽  
All Cause Mortality ◽  
Risk Reducing

In the field of gynecology, the approval of the PARP inhibitors (PARPi) has been changing the treatment of ovarian cancer patients. The BRCA genetic test and the HRD test are being used as a companion diagnosis before starting PARPi treatment. BRACAnalysis CDx® and Myriad myChoice® HRD test are widely used as a BRCA genetic test and HRD test, respectively. In addition, FoundationOne®CDx is sometimes used as a tumor BRCA test and HRD test. In clinical practice, gynecologists treating ovarian cancer are faced with making decisions such as whether to recommend the gBRCA test to all ovarian cancer patients, whether to perform the gBRCA test first or HRD test first, and so on. Regarding the judgment result of the HRD test, the cutoff value differs depending on the clinical trial, and the prevalence of gBRCA pathogenic variant rate is different in each histological type and country. A prospective cohort study showed that RRSO reduced all-cause mortality in both pre- and postmenopausal women; however, RRSO significantly reduced the risk of breast cancer for BRCA2 pathogenic variant carriers, but not for BRCA1 pathogenic variant carriers. Moreover, salpingectomy alone is said to not decrease the risk of developing ovarian or breast cancer, so further discussion is evidently required. We discuss the current situation and problems in doing BRCA genetic test and RRSO in this review article.

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