The genome algorithm is meritorious! Discover new targets for bladder cancer

July 13, 2018 Source: WuXi PharmaTech

Bladder cancer is the sixth most common cancer in the United States. According to the American Cancer Society (ACS), about 79000 people were diagnosed with bladder cancer in 2017, and nearly 17,000 people died of this disease. In the past few years, there has been a trend toward classification of bladder cancer based on gene expression patterns. A gene expression pattern called p53-like bladder cancer is known to be associated with invasive muscle invasive disease, but it is unclear how this subtype affects patient prognosis. Now, researchers at the Mount Sinai Health System in New York have identified two biomarkers by algorithmic models that may help oncologists predict the prognosis of patients with p53-like bladder cancer. Targeted treatment. Related papers were published in the recent "Oncogene".

According to ACS, the 5-year survival rate of muscle invasive bladder cancer is 63%. Patients' responses to conventional treatments, such as chemotherapy, can vary widely, so new therapies are needed to treat the disease. In recent years, immunotherapy using immunological checkpoint inhibitors has become a major advance in the treatment of bladder cancer, but some patients have become resistant. Last year, Roche discovered that a protein called TGF-β is associated with a patient's response to the PD-L1 inhibitor Tecentriq. If Tecentriq is combined with an anti-TGF-β compound, its effectiveness can be improved.

This study from the Mount Sinai team identified two p53-like bladder cancer biomarkers based on microRNA activity. The nomenclature of p53-like bladder cancer comes from the characteristics of the active genes associated with it. It is usually particularly aggressive and resistant to standard chemotherapy, but individual prognosis may vary widely. MicroRNA is a genetic material that regulates gene expression. Researchers used their previously developed computational model "ActMiR" to study microRNA activity based on changes in gene expression. The researchers used ActMiR to analyze bladder cancer data in the Cancer Genomic Atlas, and found two microRNAs that have a tumor suppressor effect in p53-like bladder cancer, one of which has better survival rates than patients. Related. The Sinai team has validated data from multiple types of breast cancer before analyzing bladder cancer data with ActMiR.

Although still in its early stages, researchers at Mount Sinai believe that the results suggest that targeting microRNAs has the potential to become a new treatment for bladder cancer. Other researchers are also exploring strategies to regulate microRNAs. For example, researchers at Imperial College London are investigating microRNAs that control cell migration and growth in breast and lung cancer.

Researchers at Mount Sinai said that more research is needed to determine the significance of the two biomarkers found this time for individualized treatment of patients with p53-like bladder cancer. "Our algorithm not only gives us insight into the underlying cellular mechanisms of this elusive bladder cancer, but also reveals the potential of microRNAs as therapeutic targets," commented Dr. Zhu Jun, Professor of Genetics and Genomics at Mount Sinai.

Reference material

[1] One step closer to personalized treatments for bladder cancer

[2] Discovery of New Biomarker Could Provide Personalized Treatment Options for Bladder Cancer

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