scholarly journals Characterization of Potential Driver Genes Involved in Human Breast Cancer in Maysan Province, Iraq

2021 ◽  
Author(s):  
Zainab Zamil gataa Allami ◽  
Maytham A Dragh
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Breast Cancer Incidence ◽  
Brca1 Gene ◽  
Receptor Expression ◽  
Breast Cancers ◽  
Driver Genes ◽  
Healthy Control ◽  
Hormone Receptor Expression ◽  
The Relationship

Abstract Background: Breast cancer is a heterogeneous disease regarding its morphology, invasive behaviour, metastatic capacity, hormone receptor expression and clinical outcome. There are many risk factors for breast cancer, including genetic factors that account for 25-30% of the incidence; from this percentage, only 15-30% of the heritable component of breast cancer is due to known familiar highly penetrating genes, and the others are sporadic.Methods: This study was the first to include amplified genes as PCR templates to determine the relationship between their polymorphism and breast cancer incidence using RAPD of amplified genes. The study was designed first to evaluate the association of ABCG2, ABCB1 and BRCA1 gene polymorphisms in addition to miRNA-152 and ER-a using the RAPD technique with breast cancer incidence in Maysan Province women and second to use those genes as indicators for breast cancer prediction and diagnosis. The study included 100 patients with breast cancer and 30 healthy control women, and then all samples were amplified by conventional PCR with specific F and R primers for ABCG2, ABCB1, BRCA1, ER-α, and miRNA-152 genes. Then, the best PCR product (20) was chosen as the template for the RAPD technique.Results: The results revealed that all RAPD primers showed polymorphisms with higher values and more specific bands in patient samples. Our study proved the relationship between genetic polymorphisms of breast cancer-related genes and a higher incidence of cancer.Conclusion: The current study recommends employing these results for the future prediction and diagnosis of breast cancers.

scholarly journals Diabetes, Metformin, and Breast Cancer in Postmenopausal Women

2012 ◽  
Vol 30 (23) ◽  
pp. 2844-2852 ◽  
Author(s):  
Rowan T. Chlebowski ◽  
Anne McTiernan ◽  
Jean Wactawski-Wende ◽  
JoAnn E. Manson ◽  
Aaron K. Aragaki ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Postmenopausal Women ◽  
Cancer Incidence ◽  
Proportional Hazards ◽  
Breast Cancer Incidence ◽  
Cox Proportional Hazards ◽  
Diabetes Incidence ◽  
Breast Cancers ◽  
Cancer Risk Factors ◽  
Cancer Management

Purpose Emerging evidence suggests that metformin may reduce breast cancer incidence, but reports are mixed and few provide information on tumor characteristics. Therefore, we assessed associations among diabetes, metformin use, and breast cancer in postmenopausal women participating in Women's Health Initiative clinical trials. Patients and Methods In all, 68,019 postmenopausal women, including 3,401 with diabetes at study entry, were observed over a mean of 11.8 years with 3,273 invasive breast cancers diagnosed. Diabetes incidence status was collected throughout follow-up, with medication information collected at baseline and years 1, 3, 6, and 9. Breast cancers were confirmed by review of central medical records and pathology reports. Cox proportional hazards regression, adjusted for breast cancer risk factors, compared breast cancer incidence in women with diabetes who were metformin users or nonusers with breast cancer incidence in women without diabetes. Results Compared with that in women without diabetes, breast cancer incidence in women with diabetes differed by diabetes medication type (P = .04). Women with diabetes receiving medications other than metformin had a slightly higher incidence of breast cancer (hazard ratio [HR], 1.16; 95% CI, 0.93 to 1.45), and women with diabetes who were given metformin had lower breast cancer incidence (HR, 0.75; 95% CI, 0.57 to 0.99). The association was observed for cancers positive for both estrogen receptor and progesterone receptor and those that were negative for human epidermal growth factor receptor 2. Conclusion Metformin use in postmenopausal women with diabetes was associated with lower incidence of invasive breast cancer. These results can inform future studies evaluating metformin use in breast cancer management and prevention.

Qualitative age interactions (or effect modification) suggest divergent pathways for early-onset and late-onset breast cancers

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 21036-21036 ◽  
Author(s):  
W. F. Anderson ◽  
L. A. Brinton ◽  
B. Chen ◽  
S. S. Devesa
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Early Onset ◽  
Late Onset ◽  
Breast Cancer Incidence ◽  
Temporal Trends ◽  
Effect Modification ◽  
Low Grade ◽  
High Grade ◽  
Breast Cancers

21036 Background: Notwithstanding some recent declines, breast cancer incidence rates have risen for decades, though not equally for all age groups. We used the National Cancer Institute's SEER program to further explore the effect of aging upon breast cancer incidence. Materials and Methods: The SEER program collected data on n=494,543 in-situ + invasive female breast cancer cases, newly diagnosed during 1974–2003. Temporal trends by race, stage, and grade were stratified by age at diagnosis in decades: 20–29 to 80+ years. Results: We observed age interactions over time. For example, as the specification of grade improved from 1974–2003, temporal trends for high and low grade tumors varied with age. Among women ages <40 years, high grade lesions were more common than low grade tumors for all time periods. Among women ages 40+ years, high grade lesions were more common during the early years, and then rates crossed, after which low-grade tumors were more common than high grade lesions. Conclusion: Age at diagnosis was both a quantitative (non- crossover) and qualitative (crossover) effect modifier. The crossing of rates from high to low grade tumors among women ages 40+ years in the 1980s is consistent with more aggressive breast cancer screening, with mammography preferentially detecting low grade tumors among women targeted for screening, i.e., ages 40–80 years. Though once thought to be rare or artifactual, qualitative interactions or effect modification suggest etiologic heterogeneity in an otherwise homogeneous disease process. Indeed, if true, qualitative age interactions imply divergent pathways for early-onset and late-onset breast cancers. No significant financial relationships to disclose.

Influence of the dramatic fall of hormone replacement therapy (HRT) prescription on postmenopausal breast cancer incidence: The Austrian data

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 1529-1529
Author(s):  
G. Pfeiler ◽  
C. Glatz ◽  
R. Königsberg ◽  
C. Vutuc ◽  
E. Kubista ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Postmenopausal Women ◽  
Cancer Incidence ◽  
Hormone Receptor ◽  
Breast Cancer Incidence ◽  
Postmenopausal Breast Cancer ◽  
Receptor Expression ◽  
Incidence Data ◽  
Cancer Incidence Data ◽  
Dramatic Fall

1529 Background: The Women's Health Initiative trial showed a significant increase in breast cancer risk among women using HRT. This publication led to a dramatic fall in HRT prescription worldwide. Several studies argued that the ensuing decline in breast cancer incidence among postmenopausal women was due to the reduced HRT prescriptions. We have investigated whether the strong decline in HRT prescription in Austrian women from 2002 onward was associated with a decrease in postmenopausal breast cancer incidence in Austria. Methods: Breast cancer incidence data were obtained from the National Austrian Cancer Registry. HRT prescription data were calculated using Pharmaceutical Benefits Scheme data. Hormone receptor expression data were taken from the pathology report of all patients with breast cancer, who were operated on at the Division of Special Gynecology, as well as the Department of Surgery, Medical University of Vienna (MUW), from 1998 to 2000, and 2005 to 2007, respectively. Chi-Square test was used to identify significant differences. Results: HRT prescription slightly increased from 1998 to 2000, but dramatically decreased by 70% after 2003, reaching a significantly lower level. When comparing breast cancer incidence data from 1999 and 2004, a nonsignificant trend toward a decreased incidence in 50- to 54-year-old women could be observed. Comparing predicted breast cancer incidence for 2004 with the actual incidence for 2004 in this group, a significant decrease could be demonstrated. Ten percent to 12% of all new breast cancers in Austria are treated at the MUW every year. Regarding histopathologic breast cancer parameters of patients treated at the MUW from 1998 to 2000 and 2005 to 2007, respectively, a nonsignificant decline of hormone receptor positive tumors in 50- to 54-year-old patients with breast cancer could be observed. Conclusions: The decline of HRT use in Austria is associated with a reduction in breast cancer incidence in postmenopausal women. Our data underline the association between HRT and breast cancer. No significant financial relationships to disclose.

scholarly journals Effect of Changing Breast Cancer Incidence Rates on the Calibration of the Gail Model

2010 ◽  
Vol 28 (14) ◽  
pp. 2411-2417 ◽  
Author(s):  
Sara J. Schonfeld ◽  
David Pee ◽  
Robert T. Greenlee ◽  
Patricia Hartge ◽  
James V. Lacey ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Invasive Breast Cancer ◽  
Clinical Decision Making ◽  
Prediction Models ◽  
Breast Cancer Incidence ◽  
Incidence Rates ◽  
Breast Cancers ◽  
Gail Model ◽  
Cancer Incidence Rates

Purpose The Gail model combines relative risks (RRs) for five breast cancer risk factors with age-specific breast cancer incidence rates and competing mortality rates from the Surveillance, Epidemiology, and End Results (SEER) program from 1983 to 1987 to predict risk of invasive breast cancer over a given time period. Motivated by changes in breast cancer incidence during the 1990s, we evaluated the model's calibration in two recent cohorts. Methods We included white, postmenopausal women from the National Institutes of Health (NIH) –AARP Diet and Health Study (NIH-AARP, 1995 to 2003), and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO, 1993 to 2006). Calibration was assessed by comparing the number of breast cancers expected from the Gail model with that observed. We then evaluated calibration by using an updated model that combined Gail model RRs with 1995 to 2003 SEER invasive breast cancer incidence rates. Results Overall, the Gail model significantly underpredicted the number of invasive breast cancers in NIH-AARP, with an expected-to-observed ratio of 0.87 (95% CI, 0.85 to 0.89), and in PLCO, with an expected-to-observed ratio of 0.86 (95% CI, 0.82 to 0.90). The updated model was well-calibrated overall, with an expected-to-observed ratio of 1.03 (95% CI, 1.00 to 1.05) in NIH-AARP and an expected-to-observed ratio of 1.01 (95% CI: 0.97 to 1.06) in PLCO. Of women age 50 to 55 years at baseline, 13% to 14% had a projected Gail model 5-year risk lower than the recommended threshold of 1.66% for use of tamoxifen or raloxifene but ≥ 1.66% when using the updated model. The Gail model was well calibrated in PLCO when the prediction period was restricted to 2003 to 2006. Conclusion This study highlights that model calibration is important to ensure the usefulness of risk prediction models for clinical decision making.

scholarly journals Breast Cancer beyond the Age of Mutation

Gerontology ◽  
2015 ◽  
Vol 62 (4) ◽  
pp. 434-442 ◽  
Author(s):  
Mark A. LaBarge ◽  
E. Lorena Mora-Blanco ◽  
Susan Samson ◽  
Masaru Miyano
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Breast Tissue ◽  
Breast Cancer Incidence ◽  
Epigenetic Changes ◽  
Breast Cancers ◽  
Age Related ◽  
Age Dependent ◽  
Tissue Changes ◽  
Cellular Phenotypes

Age is the greatest risk factor for breast cancer, but the reasons underlying this association are unclear. While there is undeniably a genetic component to all cancers, the accumulation of mutations with age is insufficient to explain the age-dependent increase in breast cancer incidence. In this viewpoint, we propose a multilevel framework to better understand the respective roles played by somatic mutation, microenvironment, and epigenetics making women more susceptible to breast cancer with age. The process of aging is associated with gradual breast tissue changes that not only corrupt the tumor-suppressive activity of normal tissue but also impose age-specific epigenetic changes that alter gene expression, thus reinforcing cellular phenotypes that are associated with a continuum of age-related tissue microenvironments. The evidence discussed here suggests that while the riddle of whether epigenetics drives microenvironmental changes, or whether changes in the microenvironment alter heritable cellular memory has not been solved, a path has been cleared enabling functional analysis leading to the prediction of key nodes in the network that link the microenvironment with the epigenome. The hypothesis that the accumulation of somatic mutations with age drives the age-related increase in breast cancer incidence, if correct, has a somewhat nihilistic conclusion, namely that cancers will be impossible to avoid. Alternatively, if microenvironment-driven epigenetic changes are the key to explaining susceptibility to age-related breast cancers, then there is hope that primary prevention is possible because epigenomes are relatively malleable.

scholarly journals DNA methylation profiling identifies two distinct subgroups in breast cancers with low hormone receptor expression, mainly associated with HER2 amplification status

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Philipp Jurmeister ◽  
Karsten Weber ◽  
Sonia Villegas ◽  
Thomas Karn ◽  
Michael Untch ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Hormone Receptor ◽  
Receptor Expression ◽  
Proliferation Index ◽  
Breast Cancers ◽  
Hormone Receptor Positive ◽  
Dna Methylation Profiling ◽  
Hormone Receptor Expression ◽  
Methylation Profiling

Abstract Background Current clinical guidelines suggest that breast cancers with low hormone receptor expression (LowHR) in 1–10% of tumor cells should be regarded as hormone receptor positive. However, clinical data show that these patients have worse outcome compared to patients with hormone receptor expression above 10%. We performed DNA methylation profiling on 23 LowHR breast cancer specimens, including 13 samples with HER2 amplification and compared our results with a reference breast cancer cohort from The Cancer Genome Atlas to clarify the status for this infrequent but important patient subgroup. Results In unsupervised clustering and dimensionality reduction, breast cancers with low hormone receptor expression that lacked HER2 amplification usually clustered with triple negative breast cancer (TNBC) reference samples (8/10; “LowHR TNBC-like”). In contrast, most specimens with low hormone receptor expression and HER2 amplification grouped with hormone receptor positive cancers (11/13; “LowHR HRpos-like”). We observed highly similar DNA methylation patterns of LowHR TNBC-like samples and true TNBCs. Furthermore, the Ki67 proliferation index of LowHR TNBC-like samples and clinical outcome parameters were more similar to TNBCs and differed from LowHR HRpos-like cases. Conclusions We here demonstrate that LowHR breast cancer comprises two epigenetically distinct groups. Our data strongly suggest that LowHR TNBC-like samples are molecularly, histologically and clinically closely related to TNBC, while LowHR HRpos-like specimens are closely related to hormone receptor positive tumors.

scholarly journals Evaluating the Prognostic Performance of a Polygenic Risk Score for Breast Cancer Risk Stratification

2020 ◽  
Author(s):  
Maria Olsen ◽  
Krista Fischer ◽  
Patrick M. Bossuyt ◽  
Els Goetghebeur
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Cox Regression ◽  
Breast Cancer Incidence ◽  
Independent Study ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Breast Cancers ◽  
Polygenic Risk ◽  
Prognostic Performance

Abstract Background: Polygenic risk scores (PRS) could potentially improve breast cancer screening recommendations. We analyzed how well a recently developed prevalence-based breast cancer PRS (Läll et al., 2009) performs in expressing women’s future risk of incident breast cancer. Objectives: To evaluate the prognostic performance of models using PRS and age as predictors, vs age alone, for breast cancer incidence in women from the Estonian biobank (EstBB) cohort. Methods: We analyzed data on 30,312 women from the EstBB cohort. They entered the cohort between 2002 and 2011, were between 20-89 years, without history of breast cancer, and with full 5-year follow-up by 2015. We examined PRS and other potential risk factors as possible predictors in Cox regression models for breast cancer incidence. With 10-fold cross validation we estimated 3- and 5-year breast cancer incidence from age alone and PRS plus age, fitting models on 90% of the data. Calibration, discrimination, and reclassification then expressed prognostic performance on the left-out folds. Results: A total of 101 (3.33‰) and 185 (6.1‰) incident breast cancers were observed within 3 and 5 years, respectively. For women in the current Estonian screening age (50-62 years), the ratio of observed vs PRS-age modelled 3-year incidence was 0.86 for women in the 75-85% PRS-group, 1.34 for the 85-95% PRS-group, and 1.41 for the top 5% PRS-group. For 5-year incidence, this was respectively 0.94, 1.15, and 1.08. Yet, the number of breast cancer events were relatively low in each PRS-subgroup. The model’s AUC was 0.720 (95% CI: 0.675-0.765) for 3-year and 0.704 (95% CI: 0.670-0.737) for 5-year, respectively, just 0.022 and 0.023 higher than for the model with age alone. Using a 1% risk prediction threshold, the 3-year NRI for the PRS-age model was 0.09 and 0.05 for 5 years.Conclusion: The model including PRS had modest incremental performance. This suggests that the potential benefit of adding PRS to age for guiding screening likely affects a relatively small proportion of women. A larger, independent study is needed to assess whether and how the PRS can meaningfully contribute to developing more efficient screening strategies.

scholarly journals Protein Intake by Source and Breast Cancer Incidence and Mortality: The Women’s Health Initiative

2020 ◽  
Vol 4 (6) ◽  
Author(s):  
Kathy Pan ◽  
Joseph C Larson ◽  
Ross L Prentice ◽  
Joanne E Mortimer ◽  
Marian L Neuhouser ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Incidence ◽  
Total Protein ◽  
Protein Intake ◽  
Vegetable Protein ◽  
Breast Cancer Incidence ◽  
Animal Protein ◽  
Breast Cancers ◽  
Risk Of Death ◽  
Total Protein Intake

Abstract Background Prior studies of dietary protein intake and breast cancer have been mixed and were limited by dietary self-report measurement error. Methods Biomarker-calibrated total protein intake and estimated vegetable protein and animal protein intake were determined from baseline food frequency questionnaires in 100 024 Women’s Health Initiative participants. Associations between total, animal, and vegetable protein intake and breast cancer incidence, deaths from breast cancer, and deaths after breast cancer were estimated using Cox proportional hazards regression. Breast cancers were verified by medical record review and survival outcomes enhanced by National Death Index queries. All statistical tests were 2-sided. Results After 14 years of follow-up, there were 6340 incident breast cancers, 764 deaths from breast cancer, and 2059 deaths after breast cancer. In multivariable analyses, higher calibrated total protein intake was not associated with breast cancer incidence or deaths from or after breast cancer. Vegetable protein intake was associated with statistically significantly lower breast cancer incidence (hazard ratio [HR] = 0.98, 95% confidence interval [CI] = 0.96 to 0.99, Ptrend = .006) and statistically significantly lower risk of death after breast cancer (HR = 0.93, 95% CI = 0.91 to 0.97, Ptrend &lt; .001) but not with deaths from breast cancer. In contrast, higher animal protein intake was associated with statistically significantly higher breast cancer incidence (HR = 1.03, 95% CI = 1.01 to 1.06, Ptrend = .02) but not with deaths from or after breast cancer. Conclusions Calibrated total protein intake was not associated with breast cancer incidence or mortality. Higher vegetable protein intake was associated with lower breast cancer incidence and lower risk of death after breast cancer. Higher animal protein intake was associated with higher breast cancer incidence.

Estrogen plus progestin (E+P) and breast cancer incidence and mortality.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 1501-1501
Author(s):  
Rowan T. Chlebowski ◽  
Garnet L Anderson ◽  
Lewis H Kuller ◽  
Aaron K Aragaki ◽  
JoAnn E Manson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Trial ◽  
Cancer Incidence ◽  
Cancer Mortality ◽  
Breast Cancer Mortality ◽  
Breast Cancer Incidence ◽  
Cancer Prognosis ◽  
Breast Cancers ◽  
Incidence And Mortality ◽  
Mortality Table

1501 Background: In the WHI clinical trial, E+P increased both breast cancer incidence and breast cancer mortality (JAMA 2010;304:1684). In contrast, breast cancers associated with E+P use in most observational studies have a more favorable prognosis. To address differences, a cohort of WHI Observational Study participants with characteristics similar to the WHI clinical trial was identified to examine E+P association with invasive breast cancer incidence and outcome. Methods: 41,449 postmenopausal women with no prior hysterectomy and mammogram negative for breast cancer < 2 years before who either were not hormone users (25,328) or were using E+P (16,121) were identified. Breast cancers were verified by centralized medical record review. Adjusted Cox proportional hazard regression was used to calculate hazard ratios (HRs) with 95% confidence intervals (CI). Additional analyses adjusted for breast cancer screening, censoring participants for incidence analyses who had a > 2 year interval without a mammogram. Results: After a mean (SD) follow-up 11.3 (3.1) years, 2,236 breast cancers were diagnosed. Breast cancer incidence was higher in E+P users (0.60% vs 0.42%, annualized rate, respectively: HR 1.55, 95% CI 1.41-1.70, P<0.001). Screening adjusted analyses had stronger breast cancer association (0.63% vs 0.39%, HR 1.72, 95% CI 1.54-1.93; P<0.001). Survival following breast cancer, measured from diagnosis date, was similar in E+P users and non-users (HR 0.95, 95% CI 0.74-1.23). Breast cancer mortality, analyzed from cohort entry date, are shown in the table. Conclusions: E+P use is associated with increased breast cancer incidence. As breast cancer prognosis following diagnosis on E+P is similar to that of nonusers, the higher incidence with E+P leads to increased breast cancer mortality. [Table: see text]

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