Splice Variant Biomarkers in Clear Cell Renal Cell Carcinoma Identified
Posted by Ellen Burns on August 2nd, 2022
Kidney cancer accounts for only 4% of all cancers in the United States; however, its incidence has more than doubled since 1975, and the most common type is clear cell renal cell carcinoma. Although the prognosis of patients has been improving due to new treatment options, the 5-year survival rate is 50% to 69% and even lower for patients with metastatic disease.
Scientists are trying to improve their understanding of clear cell renal cell carcinoma development to develop new targeted therapies. In a new study published in the European Journal of Urology, researchers at the Murphy Cancer Center identified biomarkers for this disease type and developed a tool to indicate which patients are at higher risk of poor prognosis based on the expression of biomarkers.
Clear cell renal cell carcinoma is a complex disease that develops from mutations in different types of genes, including hereditary and incidental changes. Despite this knowledge, none of these mutations can be used to develop effective treatments. To help better understand the key molecular processes involved in the development of clear cell renal cell carcinoma, Moffett's researchers began investigating alternative messenger RNA (mRNA) splice variants to determine whether they were altered in this disease and whether these variants could be used as biomarkers of patient prognosis.
MRNA is a key intermediate molecule in the conversion of DNA into protein. DNA is converted to mRNA in the nucleus. mRNA is then used as a template to form proteins that control all cellular and physiological processes; however, RNA molecules are spliced into different products before mRNA is converted into protein. This allows a gene to encode many different proteins. Alternative splicing is a natural process, but cancer cells can hijack this process, create splice variants, and promote cancer development and progression.
Moffett's researchers used a novel screening process that started with cancer cell line data and then confirmed with clear cell renal cell carcinoma patient data to identify splice variants enriched in patients. They identified 16 key splice variants altered in patients with clear cell renal cell carcinoma, several of which were associated with disease biology and outcome. The researchers also identified some splicing variants associated with altered DNA modification patterns.
The researchers used this information to create a survival risk tool based on the combined expression levels of five splice variants. Expression of RNASET2 and FGD1 was associated with worse prognosis, whereas expression of PDZD2, COBLL1 and PTPN14 was associated with better prognosis. This tool enables patients to be stratified according to overall survival and low, intermediate, and high risk of cancer-specific survival. The researchers further analyzed protein expression patterns in clear cell renal cell carcinoma tumor samples and found that some proteins responsible for gene splicing altered expression and protein modification patterns in high-risk patient populations.
Brandon Manley, MD, study author and assistant member of the Department of Genitourinary Oncology, explained: "These results suggest that altered splicing variants may play an important role in the development of clear cell renal cell carcinoma and represent biomarkers of patient prognosis.” “Future studies need to clarify the mechanistic role of aberrant splicing variants, their significance in predicting response to systemic therapy, and their use as biomarkers for disease detection, recurrence, or metastasis.”
"The discovery of renal cancer-specific splice variants may facilitate the development of blood-based liquid biopsy tests to better manage patients' disease. We are testing whether these RNA splicing variants are also detectable in the blood of patients with clear cell renal cell carcinoma. If successful, we will develop a highly sensitive blood-based method to diagnose this disease early. This non-invasive approach can also be used to monitor disease progression or even predict response to treatment," said study author Dr. Wang Liang, a senior member of the Department of Genitourinary Oncology.
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About the AuthorEllen Burns
Joined: November 1st, 2019
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