Dataset Information

Imaging Biomarkers as Predictors for Breast Cancer Death.

ABSTRACT:

Background

To differentiate the risk of breast cancer death in a longitudinal cohort using imaging biomarkers of tumor extent and biology, specifically, the mammographic appearance, basal phenotype, histologic tumor distribution, and conventional tumor attributes.

Methods

Using a prospective cohort study design, 498 invasive breast cancer patients diagnosed between 1996 and 1998 were used as the test cohort to assess the independent effects of the imaging biomarkers and other predictors on the risk of breast cancer death. External validation was performed with a cohort of 848 patients diagnosed between 2006 and 2010.

Results

Mammographic tumor appearance was an independent predictor of risk of breast cancer death (P=0.0003) when conventional tumor attributes and treatment modalities were controlled. The casting type calcifications and architectural distortion were associated with 3.13-fold and 3.19-fold risks of breast cancer death, respectively. The basal phenotype independently conferred a 2.68-fold risk compared with nonbasal phenotype. The observed deaths did not differ significantly from expected deaths in the validation cohort. The application of imaging biomarkers together with other predictors classified twelve categories of risk for breast cancer death.

Conclusion

Combining imaging biomarkers such as the mammographic appearance of the tumor with the histopathologic distribution and basal phenotype, accurately predicted long-term risk of breast cancer death. The information may be relevant for determining the need for molecular testing, planning treatment, and determining the most appropriate clinical surveillance schedule for breast cancer patients.

SUBMITTER: Wu WY

PROVIDER: S-EPMC6481030 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Imaging Biomarkers as Predictors for Breast Cancer Death.

Wu Wendy Yi-Ying WY Tabar Laszlo L Tot Tibor T Fann Ching-Yuan CY Yen Amy Ming-Fang AM Chen Sam Li-Sheng SL Chiu Sherry Yueh-Hsia SY Ku May Mei-Sheng MM Hsu Chen-Yang CY Beckmann Kerri R KR Smith Robert A RA Duffy Stephen W SW Chen Hsiu-Hsi HH

Journal of oncology 20190410

<h4>Background</h4>To differentiate the risk of breast cancer death in a longitudinal cohort using imaging biomarkers of tumor extent and biology, specifically, the mammographic appearance, basal phenotype, histologic tumor distribution, and conventional tumor attributes.<h4>Methods</h4>Using a prospective cohort study design, 498 invasive breast cancer patients diagnosed between 1996 and 1998 were used as the test cohort to assess the independent effects of the imaging biomarkers and other pred ...[more]

PMID: 31093281

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Project description:Objective To identify factors predicting early death in women with breast cancer. Design Cohort study. Setting 29 trusts across seven cancer networks in the North Thames area. Participants 15?037 women with primary breast cancer diagnosed between January 1996 and December 2005. Methods Logistic regression analyses to determine predictors of early death and factors associated with lack of surgical treatment. Main exposures Age at diagnosis, mode of presentation, ethnicity, disease severity, comorbidities, treatment and period of diagnosis in relation to the Cancer Plan (the NHS's strategy in 2000 for investment in and reform of cancer services). Main outcome measures Death from any cause within 1 year of diagnosis, and receipt of surgical treatment. Results By 31 December 2006, 4765 women had died, 980 in the year after diagnosis. Older age and disease severity independently predicted early death. Women over 80 were more likely to die early than women under 50 (OR 8.05, 95% CI 5.96 to 10.88). Presence of distant metastases on diagnosis increased the odds of early death more than eightfold (OR 8.41, 95% CI 6.49 to 10.89). Two or more recorded comorbidities were associated with a nearly fourfold increase. There was a significant decrease in odds associated with surgery (OR 0.29, 95% CI 0.24 to 0.35). Independently of disease severity and comorbidities, women over 70 were less likely than those under 50 to be treated surgically and this was even more pronounced in those aged over 80 (OR 0.09, 95% CI 0.07 to 0.10). Other factors independently associated with a reduced likelihood of surgery included a non-screening presentation, non-white ethnicity and additional comorbidities. Conclusions These findings may partially explain the survival discrepancies between the UK and other European countries in female patients with breast cancer. The study identifies a group of women with a particularly poor prognosis for whom interventions aiming at early detection may be targeted.

Project description:Background: Numerous studies have focused on the PI3K/AKT/mTOR pathway in estrogen receptor positive (ER) breast cancer (BC), as a linear signal transduction pathway and reported its association with worse clinical outcomes. To gain better insight into the relative contribution of each of the signalling pathways which lie downstream to PI3K (namely AKT and mTOR) to BC outcomes, we have developed a novel in silico approach which assessed the activation of each of these signalling pathways separately. Methods: By analysing gene expression and matched proteomic data in ER-positive patients from the TCGA repository, we developed gene signatures that reflect the level of expression of phosphorylated-Serine473-AKT (pAKT) and phosphorylated-Serine2448-mTOR (p-mTOR) separately, capturing their corresponding level of pathway activation. Using pooled analysis of gene-expression data from over 7,000 patients with ER-positive early BC, we then investigated the association between pathway activation and outcomes. Results: Our analysis revealed that the pAKT pathway activation (as measured by the developed signature) was associated with luminal A BC while the p-mTOR pathway activation was more associated with luminal B BC (Kruskal-Wallis test p<10-10). pAKT pathway activation was significantly associated with better outcomes (multivariable HR, 0.79; 95% CI, 0.74 to 0.85; p=2.5x10-10) whereas p-mTOR pathway activation showed worse outcomes (multivariable HR, 1.1; 95% CI, 1.1 to 1.2; p=9.9x10-4). Similar associations between activation and outcomes were obtained when the analysis was performed in patients who were treated with hormonal therapy. Additionally, pAKT pathway activation predicted better outcomes irrespective of the BC molecular subtypes (luminal A multivariable HR, 0.85; 95% CI, 0.75 to 0.96; p=0.01; luminal B HR, 0.91; 95% CI, 0.83 to 0.99; p=0.033). pAKT pathway activation was associated with PIK3CA mutations (p=0.0001) while p-mTOR pathway activation was associated with p53 mutations (p=0.04). Finally, we show that pAKT pathway activation was associated with less response to Everolimus. Conclusions: Our data show that pAKT and p-mTOR pathway activation have differing impact on prognosis and suggest that they are not linearly connected in luminal breast cancers. These findings add to our understanding of signalling through the PI3K pathway and could have important implications for the treatment of luminal BC.

Dataset Information

Imaging Biomarkers as Predictors for Breast Cancer Death.

Background

Methods

Results

Conclusion

Publications

Imaging Biomarkers as Predictors for Breast Cancer Death.

Similar Datasets

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