What Is Molecular Profiling?
Precision medicine tools, such as molecular profiling, are still often regarded as the second line of defense, to be used, when standard therapies have not produced results. Biomarker analysis may help you identify potential treatment options, but only your doctor can advise you on which treatment paths to consider.
Molecular Profiling of Bladder Cancer
The genetic mutations in some chromosomal genes, such as FGFR3, RB1, HRAS, TP53, TSC1, and others, occur which form tumors in the urinary bladder. These genes play an important role in the regulation of cell division which prevents cells from dividing too quickly.
Information provided by the U.S. National Library of Medicine
Your Doctor May Choose Molecular Profiling:
1. If typical first line (standard) therapies have failed
2. If there has been a recurrence (return) of your cancer
3. If your doctor is choosing from among several recommended treatments
4. If your cancer is particularly aggressive or rare, or if few treatment options are available for other reasons
If you are interested in learning about whether you may benefit from molecular profiling, you can start by speaking with your oncologist. Patients cannot order molecular profiling tests for themselves, but you can be proactive about this topic with your doctor.
To run molecular profiling tests, your oncologist will need a sample from a biopsy of your tumor or blood sample. Your oncologist may already have a sample that is ready and available for profiling. If not, then you will need to speak with your oncologist about having another biopsy done.
The financial toxicity of cancer care can be overwhelming. Speak to your care providers about financial hardship discounts and payments plans that may available to you.
Research Publications on Bladder Cancer Genetic and Biomarkers
Recent Developments in the Search for Urinary Biomarkers in Bladder Cancer
Purpose of Review
This review aims to evaluate research surrounding the utility of urinary biomarkers to detect bladder cancer and predict recurrence. Read