Researchers at The University of Texas MD Anderson Cancer Center have developed a new model of aggressive renal cell carcinoma (RCC), providing new insights into the genomic events and molecular targets that drive chromosomal instability and metastatic progression.
The Power of Gene Editing
The study, published in Nature Cancer, utilized CRISPR/Cas9 gene editing to create a model that accurately represents RCC in humans.
The team was able to identify that the loss of a cluster of interferon receptor (IFNR) genes plays a crucial role in allowing cancer cells to tolerate chromosomal instability – a feature that may be used to predict a tumor’s potential to become metastatic and resistant to treatment.
“We introduced specific mutations that closely mimic the early stages of human cancers to see how tumors evolve and metastasize,” said Professor Giannicola Genovese.
“These insights can help clinicians identify tumors that have the genomic potential to become aggressive.”
Targeting Renal Cell Carcinoma
Renal cell carcinoma, the most common type of kidney cancer, is usually treatable with a combination of surgery, targeted therapy, and immunotherapy.
However, up to one-third of patients will have aggressive disease progression, emphasizing the need for more effective therapeutic strategies and predictive tools for treatment responses.
One characteristic of cancer is chromosomal instability, which is associated with resistance to many types of therapy and a poor prognosis.
The team used CRISPR/Cas 9-based genome editing to create RCC models lacking common tumor suppressor genes, identifying specific chromosomal abnormalities involved in driving metastasis and how tumors are able to tolerate them.
Looking into the Future
Through genome sequencing and single-cell RNA sequencing, the researchers were able to further explore the molecular drivers of RCC and gain a new understanding of chromosomal instability.
They identified that a cluster of highly conserved IFNR genes, usually involved in the immune response, were suppressed in the model.
The team found an inverse correlation between the loss of these IFNR genes and aneuploidy, a condition marked by having an abnormal number of chromosomes.
This suggests that the tumors adapt to high levels of chromosomal instability through the disruption of the IFNR pathway, indicating a potential biomarker of metastatic potential.
In the future, the team plans to test drug combinations in these newly generated models to determine how the tumors adapt to various therapies.
This could lead to clinical trials that may help predict treatment response in patients with RCC, improving outcomes for those with this aggressive disease.
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The study was published in Nature Cancer. Follow us on Twitter for more articles about this topic.
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