Current and Emerging Strategies to Treat Urothelial Carcinoma.
Berkha RaniJames J Ignatz-HooverPriyanka S RanaJames J DriscollPublished in: Cancers (2023)
Urothelial cell carcinoma (UCC, bladder cancer, BC) remains a difficult-to-treat malignancy with a rising incidence worldwide. In the U.S., UCC is the sixth most incident neoplasm and ~90% of diagnoses are made in those >55 years of age; it is ~four times more commonly observed in men than women. The most important risk factor for developing BC is tobacco smoking, which accounts for ~50% of cases, followed by occupational exposure to aromatic amines and ionizing radiation. The standard of care for advanced UCC includes platinum-based chemotherapy and programmed cell death (PD-1) or programmed cell death ligand 1 (PD-L1) inhibitors, administered as frontline, second-line, or maintenance therapy. UCC remains generally incurable and is associated with intrinsic and acquired drug and immune resistance. UCC is lethal in the metastatic state and characterized by genomic instability, high PD-L1 expression, DNA damage-response mutations, and a high tumor mutational burden. Although immune checkpoint inhibitors (ICIs) achieve long-term durable responses in other cancers, their ability to achieve similar results with metastatic UCC (mUCC) is not as well-defined. Here, we discuss therapies to improve UCC management and how comprehensive tumor profiling can identify actionable biomarkers and eventually fulfill the promise of precision medicine for UCC patients.
Keyphrases
- dna damage response
- squamous cell carcinoma
- small cell lung cancer
- end stage renal disease
- healthcare
- risk factors
- cardiovascular disease
- ejection fraction
- palliative care
- newly diagnosed
- type diabetes
- peritoneal dialysis
- adipose tissue
- high grade
- pregnant women
- polycystic ovary syndrome
- mesenchymal stem cells
- skeletal muscle
- radiation therapy
- bone marrow
- big data
- machine learning
- metabolic syndrome
- smoking cessation
- insulin resistance
- dna damage
- cell therapy
- deep learning
- patient reported
- single cell
- locally advanced
- artificial intelligence
- pain management
- middle aged
- genome wide
- rectal cancer