Targeted Genomic Analysis for Cancer
This study is looking at how analyzing your blood and tissue samples can help doctors understand your cancer better. Researchers will use a method called genomic sequencing to look at the genetic makeup of your cancer cells. This can help find changes in your genes that might be important for cancer development. The goal is to improve how doctors diagnose and treat rare cancers, especially those that are hard to treat with standard therapies. This study will follow participants for up to 15 years to see how these genetic findings relate to treatment outcomes.
- Study design
- This is an observational study, meaning researchers will collect and analyze samples without giving new treatments. It aims to enroll 1100 participants.
- What's involved
- You would provide previously collected tissue samples and may also have blood samples taken. You will be followed up every 3 months for 2 years, then every 6 months for 15 years.
- Compensation
- Not stated in the trial record.
- Follow-up
- Participants will be followed up every 3 months for 2 years, and then every 6 months for up to 15 years.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
Targeted Genomic Analysis of Blood and Tissue Samples From Patients With Cancer
At a glance
Conditions
Where it's being run
11 sites across 2 statesStudy leadership
- Shridar Ganesan · PRINCIPAL_INVESTIGATOR · Rutgers Cancer Institute of New Jersey
Who to contact
Do you actually qualify for this trial?
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Inclusion
Exclusion
What this trial measures
- Frequencies of individual specific mutations and combinations of mutations of related pathway genesUp to 15 years
Descriptive analysis will be used to determine frequencies of specific mutations and to determine the pathways that can be targeted most frequently in patients with rare/poor prognosis cancer.
- Rate of actionable mutations in rare and/or poor prognosis cancersUp to 15 years
The actual rate of mutations found in this study will be determined to estimate the true underlying mutation rate.