Ongoing controversy over the optimal approach to breast cancer screening has led to discordant professional society recommendations, particularly in women age 40 to 49 years. One potential solution ...is risk-based screening, where decisions around the starting age, stopping age, frequency, and modality of screening are based on individual risk to maximize the early detection of aggressive cancers and minimize the harms of screening through optimal resource utilization. We present a novel approach to risk-based screening that integrates clinical risk factors, breast density, a polygenic risk score representing the cumulative effects of genetic variants, and sequencing for moderate- and high-penetrance germline mutations. We demonstrate how thresholds of absolute risk estimates generated by our prediction tools can be used to stratify women into different screening strategies (biennial mammography, annual mammography, annual mammography with adjunctive magnetic resonance imaging, defer screening at this time) while informing the starting age of screening for women age 40 to 49 years. Our risk thresholds and corresponding screening strategies are based on current evidence but need to be tested in clinical trials. The Women Informed to Screen Depending On Measures of risk (WISDOM) Study, a pragmatic, preference-tolerant randomized controlled trial of annual vs personalized screening, will study our proposed approach. WISDOM will evaluate the efficacy, safety, and acceptability of risk-based screening beginning in the fall of 2016. The adaptive design of this trial allows continued refinement of our risk thresholds as the trial progresses, and we discuss areas where we anticipate emerging evidence will impact our approach.
Breast cancer metastasis: markers and models van't Veer, Laura J; Weigelt, Britta; Peterse, Johannes L
Nature reviews. Cancer,
200508, 2005-Aug, 2005-08-01, 20050801, Volume:
5, Issue:
8
Journal Article
Peer reviewed
Breast cancer starts as a local disease, but it can metastasize to the lymph nodes and distant organs. At primary diagnosis, prognostic markers are used to assess whether the transition to systemic ...disease is likely to have occurred. The prevailing model of metastasis reflects this view--it suggests that metastatic capacity is a late, acquired event in tumorigenesis. Others have proposed the idea that breast cancer is intrinsically a systemic disease. New molecular technologies, such as DNA microarrays, support the idea that metastatic capacity might be an inherent feature of breast tumours. These data have important implications for prognosis prediction and our understanding of metastasis.
It is well understood that antigen-presenting cells (APCs) within tumors typically do not maintain cytotoxic T cell (CTL) function, despite engaging them. Across multiple mouse tumor models and human ...tumor biopsies, we have delineated the intratumoral dendritic cell (DC) populations as distinct from macrophage populations. Within these, CD103+ DCs are extremely sparse and yet remarkably capable CTL stimulators. These are uniquely dependent on IRF8, Zbtb46, and Batf3 transcription factors and are generated by GM-CSF and FLT3L cytokines. Regressing tumors have higher proportions of these cells, T-cell-dependent immune clearance relies on them, and abundance of their transcripts in human tumors correlates with clinical outcome. This cell type presents opportunities for prognostic and therapeutic approaches across multiple cancer types.
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•Mouse and human tumors contain rare DCs that are stimulatory for T cells•Stimulatory DCs are programmed through unique cytokines and transcription factors•CD103+ DCs are sparse proximal to tumor margins but plentiful in distal regions•Tumoral DCs are necessary for T-cell-mediated tumor rejection and predict survival
Broz et al. identify a rare intratumoral CD103+ dendritic cell population (DC2) that is potent in stimulating cytotoxic T cells and show that high DC2 transcriptional signature in human tumors correlates with good patient survival across many cancer types.
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.
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 intra-tumor heterogeneity of ER were performed using Kaplan-Meier and multivariable Cox proportional hazard modeling adjusting for patient and tumor characteristics.
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 = .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 = 1.98, 95% confidence interval CI = 1.31 to 3.00; luminal A subtype tumors: HR = 2.43, 95% CI = 1.18 to 4.99).
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.
Multigene assays have been developed and validated to determine the prognosis of breast cancer. In this study, we assessed the additional predictive value of the 70-gene MammaPrint signature for ...chemotherapy (CT) benefit in addition to endocrine therapy (ET) from pooled study series. For 541 patients who received either ET (n = 315) or ET + CT (n = 226), breast cancer-specific survival (BCSS) and distant disease-free survival (DDFS) at 5 years were assessed separately for the 70-gene high and low risk groups. The 70-gene signature classified 252 patients (47%) as low risk and 289 (53%) as high risk. Within the 70-gene low risk group, BCSS was 97% for the ET group and 99% for the ET + CT group at 5 years with a non-significant univariate hazard ratio (HR) of 0.58 (95% CI 0.07-4.98; P = 0.62). In the 70-gene high risk group, BCSS was 81% (ET group) and 94% (ET + CT group) at 5 years with a significant HR of 0.21 (95% CI 0.07-0.59; P < 0.01). DDFS was 93% (ET) versus 99% (ET + CT), respectively, in the 70-gene low risk group, HR 0.26 (95% CI 0.03-2.02; P = 0.20). In the high risk group DDFS was 76 versus 88%, HR of 0.35 (95% CI 0.17-0.71; P < 0.01). Results were similar in multivariate analysis, showing significant survival benefit by adding CT in the 70-gene high risk group. A significant and clinically meaningful benefit was observed by adding chemotherapy to endocrine treatment in 70-gene high risk patients. This benefit was not significant in low risk patients, who were at such low risk for recurrence and cancer-related death, that adding CT does not appear to be clinically meaningful.
Purpose
The Breast Cancer Surveillance Consortium (BCSC) model is a widely used risk model that predicts 5- and 10-year risk of developing invasive breast cancer for healthy women aged 35–74 years. ...Women with high BCSC risk may also be at elevated risk to develop interval cancers, which present symptomatically in the year following a normal screening mammogram. We examined the association between high BCSC risk (defined as the top 2.5% by age) and breast cancers presenting as interval cancers.
Methods
We conducted a case-case analysis among women with breast cancer in which we compared the mode of detection and tumor characteristics of patients in the top 2.5% BCSC risk by age with age-matched (1:2) patients in the lower 97.5% risk. We constructed logistic regression models to estimate the odds ratio (OR) of presenting with interval cancers, and poor prognosis tumor features, between women from the top 2.5% and bottom 97.5% of BCSC risk.
Results
Our analysis included 113 breast cancer patients in the top 2.5% of risk for their age and 226 breast cancer patients in the lower 97.5% of risk. High-risk patients were more likely to have presented with an interval cancer within one year of a normal screening, OR 6.62 (95% CI 3.28–13.4,
p
< 0.001). These interval cancers were also more likely to be larger, node positive, and higher stage than the screen-detected cancers.
Conclusion
Breast cancer patients in the top 2.5% of BCSC risk for their age were more likely to present with interval cancers. The BCSC model could be used to identify healthy women who may benefit from intensified screening.
First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data ...types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets.
We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples.
These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.
Background
Symptom burden and reduced quality of life (QOL) are considerable hurdles in oncology. The authors used the Patient‐Reported Outcomes Measurement Information System (PROMIS), which ...assesses physical and psychosocial health, to establish a mean symptom burden, examine potential drivers, and characterize severe symptom burden in breast cancer patient subgroups with the goal of characterizing stage IV patient QOL and triaging patients to individualized supportive care services.
Methods
New patients at the University of California San Francisco Breast Care Center received questionnaires with 8 PROMIS domains: depression, anxiety, fatigue, sleep‐related impairment, sleep disturbance, cognitive function, cognitive abilities, and physical function. PROMIS values were scored with the HealthMeasures service and were compared by age, cancer stage, and educational status.
Results
Stage IV patients with breast cancer (n = 169) reported higher depression and fatigue and worse cognitive function, cognitive abilities, and physical function than patients with stage 0 to III disease (n = 2577). As age increased, cognitive function impairment, depression, anxiety, and sleep‐related symptoms decreased. More educated patients showed better physical function and less severe sleep disturbance and fatigue. Across all subgroups, patients with high anxiety had the greatest probability of worse symptom burden and function in other domains.
CONCLUSIONS
This study provides an additional set of PROMIS population estimates across breast cancer demographic groups. The analysis of a large stage IV population reinforces that metastatic patients have impaired QOL across multiple domains. Because anxiety emerged as a potential driver of impaired QOL in other domains, earlier interventions to reduce anxiety could improve QOL overall. These analyses will help to determine appropriate thresholds of intervention.
Lay Summary
Patients receiving treatment for breast cancer can experience decreased quality of life.
This study characterized differences in self‐reported quality of life among patients of different ages, with different stages of cancer, and with different educational backgrounds. This study also examined the effect of decreased quality of life in one area (eg, anxiety) on another area (eg, difficulty in sleeping).
Patients who were younger, had not attended college or technical school, or had stage IV cancer tended to have worse quality of life. Patients who had high levels of anxiety also tended to have high levels of impairment in other areas.
This analysis of the association between clinical factors and Patient‐Reported Outcomes Measurement Information System (PROMIS) scores shows that higher stage, younger age, and lower education are associated with worse quality of life in most domains. Across all subgroups, patients with high anxiety have the greatest probability of having worse symptom burden and function in the other quality‐of‐life domains.
Formalin Fixed Paraffin Embedded (FFPE) samples represent a valuable resource for cancer research. However, the discovery and development of new cancer biomarkers often requires fresh frozen (FF) ...samples. Recently, the Whole Genome (WG) DASL (cDNA-mediated Annealing, Selection, extension and Ligation) assay was specifically developed to profile FFPE tissue. However, a thorough comparison of data generated from FFPE RNA and Fresh Frozen (FF) RNA using this platform is lacking. To this end we profiled, in duplicate, 20 FFPE tissues and 20 matched FF tissues and evaluated the concordance of the DASL results from FFPE and matched FF material.
We show that after proper normalization, all FFPE and FF pairs exhibit a high level of similarity (Pearson correlation >0.7), significantly larger than the similarity between non-paired samples. Interestingly, the probes showing the highest correlation had a higher percentage G/C content and were enriched for cell cycle genes. Predictions of gene expression signatures developed on frozen material (Intrinsic subtype, Genomic Grade Index, 70 gene signature) showed a high level of concordance between FFPE and FF matched pairs. Interestingly, predictions based on a 60 gene DASL list (best match with the 70 gene signature) showed very high concordance with the MammaPrint® results.
We demonstrate that data generated from FFPE material with the DASL assay, if properly processed, are comparable to data extracted from the FF counterpart. Specifically, gene expression profiles for a known set of prognostic genes for a specific disease are highly comparable between two conditions. This opens up the possibility of using both FFPE and FF material in gene expressions analyses, leading to a vast increase in the potential resources available for cancer research.
The 70-gene signature (MammaPrint™) is a prognostic tool used to guide adjuvant treatment decisions. The aim of this study was to assess its value to predict chemosensitivity in the neoadjuvant ...setting. We obtained the 70-gene profile of stage II-III patients prior to neoadjuvant chemotherapy and classified the prognosis-signatures. Pathological complete remission (pCR) was used to measure chemosensitivity. Among 167 patients, 144 (86%) were having a poor and 23 (14%) a good prognosis-signature. None of the good prognosis-signature patients achieved a pCR (0/23), whereas 29/144 patients (20%) in the poor prognosis-signature group did (P = 0.015). All triple-negative tumors (n = 38) had a poor prognosis-signature. Within the non triple-negative subgroup, the response of the primary tumor remained associated with the classification of the prognosis-signature (P = 0.023). A pCR is unlikely to be achieved in tumors that have a good prognosis-signature. Tumors with a poor prognosis-signature are more sensitive to chemotherapy.
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