Patient preferences regarding incidental genomic findings discovered during tumor profiling.

BACKGROUND: During the process of tumor profiling, there is the potential to detect germline variants. To the authors' knowledge, there currently is no accepted standard of care for how to deal with these incidental findings. The goal of the current study was to assess disclosure preferences among patients with cancer regarding incidental genomic variants that may be discovered during tumor profiling. METHODS: A 45-item questionnaire was administered to 413 patients in ambulatory oncology clinics. The survey captured demographic and disease variables and personal and family history, and presented case scenarios for different types of incidental germline variants that could theoretically be detected during genomic analysis of a patient's tumor. RESULTS: The possibility of discovering non-cancer-related, germline variants did not deter patients from tumor profiling: 77% wanted to be informed concerning variants that could increase their risk of a serious but preventable illness, 56% wanted to know about variants that cause a serious but unpreventable illness, and 49% wanted to know about variants of uncertain significance. The majority of patients (75%) indicated they would share hereditary information regarding predisposition to preventable diseases with family and 62% would share information concerning unpreventable diseases. The most frequent concerns about incidental findings were ability to obtain health (48%) or life (41%) insurance. Only 21% of patients were concerned about privacy of information. CONCLUSIONS: Patients with cancer appear to prefer to receive information regarding incidental germline variants, but there is substantial variability with regard to what information patients wish to learn. The authors recommend that personal preferences for the disclosure of different types of incidental findings be clarified before a tumor profiling test is ordered. Cancer 2016;122:1588-97. © 2016 American Cancer Society.

Prospective assessment of the decision-making impact of the Breast Cancer Index in recommending extended adjuvant endocrine therapy for patients with early-stage ER-positive breast cancer.

Extended adjuvant endocrine therapy (10 vs. 5 years) trials have demonstrated improved outcomes in early-stage estrogen receptor (ER)-positive breast cancer; however, the absolute benefit is modest, and toxicity and tolerability challenges remain. Predictive and prognostic information from genomic analysis may help inform this clinical decision. The purpose of this study was to assess the impact of the Breast Cancer Index (BCI) on physician recommendations for extended endocrine therapy and on patient anxiety and decision conflict. Patients with stage I-III, ER-positive breast cancer who completed at least 3.5 years of adjuvant endocrine therapy were offered participation. Genomic classification with BCI was performed on archived tumor tissues and the results were reported to the treating physician who discussed results with the patient. Patients and physicians completed pre- and post-test questionnaires regarding preferences for extended endocrine therapy. Patients also completed the validated traditional Decisional Conflict Scale (DCS) and State Trait Anxiety Inventory forms (STAI-Y1) pre- and post-test. 96 patients were enrolled at the Yale Cancer Center [median age 60.5 years (range 45-87), 79% postmenopausal, 60% stage I). BCI predicted a low risk of late recurrence in 59% of patients versus intermediate/high in 24 and 17%, respectively. Physician recommendations for extended endocrine therapy changed for 26% of patients after considering BCI results, with a net decrease in recommendations for extended endocrine therapy from 74 to 54%. After testing, fewer patients wanted to continue extended therapy and decision conflict and anxiety also decreased. Mean STAI and DCS scores were 31.3 versus 29.1 (p = 0.031) and 20.9 versus 10.8 (p < 0.001) pre- and post-test, respectively. Incorporation of BCI into risk/benefit discussions regarding extended endocrine therapy resulted in changes in treatment recommendations and improved patient satisfaction.

Increased epigenetic age in normal breast tissue from luminal breast cancer patients.

BACKGROUND: Age is one of the most important risk factors for developing breast cancer. However, age-related changes in normal breast tissue that potentially lead to breast cancer are incompletely understood. Quantifying tissue-level DNA methylation can contribute to understanding these processes. We hypothesized that occurrence of breast cancer should be associated with an acceleration of epigenetic aging in normal breast tissue. RESULTS: Ninety-six normal breast tissue samples were obtained from 88 subjects (breast cancer = 35 subjects/40 samples, unaffected = 53 subjects/53 samples). Normal tissue samples from breast cancer patients were obtained from distant non-tumor sites of primary mastectomy specimens, while samples from unaffected women were obtained from the Komen Tissue Bank (n = 25) and from non-cancer-related breast surgery specimens (n = 28). Patients were further stratified into four cohorts: age < 50 years with and without breast cancer and age ≥ 50 with and without breast cancer. The Illumina HumanMethylation450k BeadChip microarray was used to generate methylation profiles from extracted DNA samples. Data was analyzed using the "Epigenetic Clock," a published biomarker of aging based on a defined set of 353 CpGs in the human genome. The resulting age estimate, DNA methylation age, was related to chronological age and to breast cancer status. The DNAmAge of normal breast tissue was strongly correlated with chronological age (r = 0.712, p < 0.001). Compared to unaffected peers, breast cancer patients exhibited significant age acceleration in their normal breast tissue (p = 0.002). Multivariate analysis revealed that epigenetic age acceleration in the normal breast tissue of subjects with cancer remained significant after adjusting for clinical and demographic variables. Additionally, smoking was found to be positively correlated with epigenetic aging in normal breast tissue (p = 0.012). CONCLUSIONS: Women with luminal breast cancer exhibit significant epigenetic age acceleration in normal adjacent breast tissue, which is consistent with an analogous finding in malignant breast tissue. Smoking is also associated with epigenetic age acceleration in normal breast tissue. Further studies are needed to determine whether epigenetic age acceleration in normal breast tissue is predictive of incident breast cancer and whether this mediates the risk of chronological age on breast cancer risk.

Bidirectional Text Messaging to Monitor Endocrine Therapy Adherence and Patient-Reported Outcomes in Breast Cancer.

INTRODUCTION: Up to 40% of patients with breast cancer may not adhere to adjuvant endocrine therapy. Therapy-related adverse effects (AEs) are important contributors to nonadherence. We developed a bidirectional text-message application, BETA-Text, that simultaneously tracks adherence, records symptoms, and alerts the clinical team. PATIENTS AND METHODS: We piloted our intervention in 100 patients. The intervention consisted of text messages to which patients responded for 3 months: daily, evaluating adherence; weekly, evaluating medication-related AEs; and monthly, regarding barriers to adherence. Concerning responses prompted a telephone call from a clinic nurse. The primary objective was to assess patient acceptance of this intervention using self-reported surveys. To compare participants with the general population at our institution, we assessed 100 consecutively treated patients as historical controls using medical record review. RESULTS: We approached 141 consecutive patients, 100 (71%) of whom agreed to participate and 89 of whom completed the intervention. A majority of patients reported that the intervention was easy to use (98%) and helpful in taking their medication (96%). Four patients discontinued therapy before 3 months, and 93% of patients who continued therapy took ≥ 80% of their medication. The frequency of AEs reported by participants via text was higher than that reported in clinical trials: hot flashes (72%), arthralgias (53%), and vaginal symptoms (35%). Approximately 39% of patients reported one or more severe AE that prompted an alert to the provider team to call the patient. CONCLUSION: A daily bidirectional text-messaging system can monitor adherence and identify AEs and other barriers to adherence in real time without inconveniencing patients. AEs of endocrine therapy, as detected using this texting approach, are more prevalent than reported in clinical trials.

Mutation based treatment recommendations from next generation sequencing data: a comparison of web tools.

Interpretation of complex cancer genome data, generated by tumor target profiling platforms, is key for the success of personalized cancer therapy. How to draw therapeutic conclusions from tumor profiling results is not standardized and may vary among commercial and academically-affiliated recommendation tools. We performed targeted sequencing of 315 genes from 75 metastatic breast cancer biopsies using the FoundationOne assay. Results were run through 4 different web tools including the Drug-Gene Interaction Database (DGidb), My Cancer Genome (MCG), Personalized Cancer Therapy (PCT), and cBioPortal, for drug and clinical trial recommendations. These recommendations were compared amongst each other and to those provided by FoundationOne. The identification of a gene as targetable varied across the different recommendation sources. Only 33% of cases had 4 or more sources recommend the same drug for at least one of the usually several altered genes found in tumor biopsies. These results indicate further development and standardization of broadly applicable software tools that assist in our therapeutic interpretation of genomic data is needed. Existing algorithms for data acquisition, integration and interpretation will likely need to incorporate artificial intelligence tools to improve both content and real-time status.