PRECISE is a study to discover new detection, prognosis and treatment biomarkers for cancer. This is a prospective, multi-center, observational study designed to collect de-identified biospecimens and clinical data from a large cohort of participants from clinical research networks in the United States. In this study, the investigators propose creating a large-scale normalized panomics dataset specifically designed for deep learning-based in silico analysis for biomarker discovery.
This study will enroll all subjects who are eligible and willing to participate with a goal of enrolling at least 10,000 in several categories: (i) Patients with Family History of Cancer, (ii) Patients with Clinical and Environmental Risk Factors for Cancer, and (iii) Patients with a Suspected or Confirmed Diagnosis of Cancer.
Study Type
OBSERVATIONAL
Patients with Family History of Cancer, (ii) Patients with Clinical and Environmental Risk Factors for Cancer, (iii) Patients with a Suspected or Confirmed Diagnosis of Cancer.
Greater Baltimore Medical Center
Baltimore, Maryland, United States
Panomics Relationships in the Epidemiology of Cancer through In Silico Expression (PRECISE)
* Establish and maintain a unique repository of blood, tissue, other biological samples and their associated data (survey data, medical records data, cancer registry data, and other related data) collected from thousands of patients 18 years of age or older who have cancer or are at risk of developing cancer. * Discover and validate new detection, prognosis and treatment biomarkers for cancer
Time frame: 5 years
Panomics Relationships in the Epidemiology of Cancer through In Silico Expression (PRECISE)
● Determine candidate genes and markers underlying cancer and response to treatment.
Time frame: 5 years
Panomics Relationships in the Epidemiology of Cancer through In Silico Expression (PRECISE)
● Discover and validate new detection, prognosis and treatment biomarkers for cancer
Time frame: 5 years
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