Intratumor heterogeneity of the estrogen receptor and the long-term risk of fatal Breast cancer

Background: Breast cancer patients with estrogen receptor (ER)–positive disease have a continuous long-term risk for fatal Breast cancer, but the biological factors influencing this risk are unknown. We aimed to determine whether high intratumor heterogeneity of ER predicts an increased long-term risk (25 years) of fatal Breast cancer. Methods: The STO-3 trial enrolled 1780 postmenopausal lymph node–negative Breast cancer patients randomly assigned to receive adjuvant tamoxifen vs not. The fraction of cancer cells for each ER intensity level was scored by Breast cancer pathologists, and intratumor heterogeneity of ER was calculated using Rao’s quadratic entropy and categorized into high and low heterogeneity using a predefined cutoff at the second tertile (67%). Long-term Breast cancer-specific survival analyses by in-tra-tumor heterogeneity of ER were performed using Kaplan-Meier and multivariable Cox proportional hazard modeling adjusting for patient and tumor characteristics. Results: A statistically significant difference in long-term survival by high vs low intratumor heterogeneity of ER was seen for all ER-positive patients (P < .001) and for patients with luminal A subtype tumors (P ¼ .01). In multivariable analyses, patients with high intratumor heterogeneity of ER had a twofold increased long-term risk as compared with patients with low intratumor heterogeneity (ER-positive: hazard ratio [HR] ¼ 1.98, 95% confidence interval [CI] ¼ 1.31 to 3.00; luminal A subtype tumors: HR ¼ 2.43, 95% CI ¼ 1.18 to 4.99). Conclusions: Patients with high intratumor heterogeneity of ER had an increased long-term risk of fatal Breast cancer. Interestingly, a similar long-term risk increase was seen in patients with luminal A subtype tumors. Our findings suggest that intratumor heterogeneity of ER is an independent long-term prognosticator with potential to change clinical management, especially for patients with luminal A tumors

Evaluation of ultra-deep targeted sequencing for personalized breast cancer care

Introduction: The increasing number of targeted therapies, together with a deeper understanding of cancer genetics and drug response, have prompted major healthcare centers to implement personalized treatment approaches relying on high-throughput tumor DNA sequencing. However, the optimal way to implement this transformative methodology is not yet clear. Current assays may miss important clinical information such as the mutation allelic fraction, the presence of sub-clones or chromosomal rearrangements, or the distinction between inherited variants and somatic mutations. Here, we present the evaluation of ultra-deep targeted sequencing (UDT-Seq) to generate and interpret the molecular profile of 38 breast cancer patients from two academic medical centers.Methods: We sequenced 47 genes in matched germline and tumor DNA samples from 38 breast cancer patients. The selected genes, or the pathways they belong to, can be targeted by drugs or are important in familial cancer risk or drug metabolism.Results: Relying on the added value of sequencing matched tumor and germline DNA and using a dedicated analysis, UDT-Seq has a high sensitivity to identify mutations in tumors with low malignant cell content. Applying UDT-Seq to matched tumor and germline specimens from the 38 patients resulted in a proposal for at least one targeted therapy for 22 patients, the identification of tumor sub-clones in 3 patients, the suggestion of potential adverse drug effects in 3 patients and a recommendation for genetic counseling for 2 patients.Conclusion: Overall our study highlights the additional benefits of a sequencing strategy, which includes germline DNA and is optimized for heterogeneous tumor tissues. © 2013 Harismendy et al.; licensee BioMed Central Ltd