multiscale omics for the development of a cohort database and study platform in breast cancer survivors

Conditions: Anatomic Stage 0 Breast Cancer AJCC v8; Anatomic Stage I Breast Cancer AJCC v8; Anatomic Stage IA Breast Cancer AJCC v8; Anatomic Stage IB Breast Cancer AJCC v8; Anatomic Stage II Breast Cancer AJCC v8; Anatomic Stage IIA Breast Cancer AJCC v8; Anatomic Stage IIB Breast Cancer AJCC v8; Anatomic Stage III Breast Cancer AJCC v8; Anatomic Stage IIIA Breast Cancer AJCC v8; Anatomic Stage IIIB Breast Cancer AJCC v8; Anatomic Stage IIIC Breast Cancer AJCC v8; Prognostic Stage 0 Breast Cancer AJCC v8; Prognostic Stage I Breast Cancer AJCC v8; Prognostic Stage IA Breast Cancer AJCC v8; Prognostic Stage IB Breast Cancer AJCC v8; Prognostic Stage II Breast Cancer AJCC v8; Prognostic Stage IIA Breast Cancer AJCC v8; Prognostic Stage IIB Breast Cancer AJCC v8; Prognostic Stage III Breast Cancer AJCC v8; Prognostic Stage IIIA Breast Cancer AJCC v8; Prognostic Stage IIIB Breast Cancer AJCC v8; Prognostic Stage IIIC Breast Cancer AJCC v8

Summary: this study gathers information to create a database to improve the ability to diagnose cancer, predict long term health of breast cancer patients, and help develop future treatment products. this study will provide a foundational platform for therapeutic development and intervention studies in the future and may for therapeutic development and intervention studies in the future, and may advance researchers understanding of the contribution gut bacteria to altered circulating estrogens in breast cancer survivors.

primary objective: i. to use multiscale omics to build a cohort database that can be used as a reference population in support of multivariate analysis, predictive modeling, and development of natural product therapeutics and precision medicine applications for breast cancer survivors. secondary objective: i. to detect unique patterns of variance between 1) targeted serum metabolites, 2) plasma metabolome, 3) gut microbiome community structure, 4) gut microbiome metabolome, 5) urine metabolome, 6) quality of life measures, and 7) breast cancer survivors (bcs) symptoms by using multivariate analysis, machine learning tools, and artificial intelligence applied to the large data sets developed in this trial. outline: participants complete questionnaires over 10 minutes and undergo blood, urine, saliva, and fecal samples collection.

Eligibility criteria:
inclusion criteria: * bcs group * female patients diagnosed with breast cancer age 18 - 75, stages 0 through 3 at time of diagnosis * who have completed active therapy (including surgery, radiation, and/or chemotherapy) * able to speak english and complete surveys and provide the specimen (willing to follow the sample collection instructions) * able to read, understand and sign inform consent * control group * healthy volunteers age 18 - 75 * able to speak and read english, complete consent, surveys, and provide specimens exclusion criteria: * unable to give written consent * unable to fast before providing blood and urine * pregnant women (per participant report) and males * unwilling to travel to mayo clinic rochester to provide bio specimens