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CU researchers awarded grant to develop genetic risk score for thyroid cancer

Researchers in the University of Colorado Department of Biomedical Informatics and the Department of Medicine want to better understand the genetic architecture behind thyroid cancer to prevent unnecessary — and sometimes invasive — treatments.

2024-04-01
(Press-News.org) Researchers at the University of Colorado School of Medicine are hopeful new research could prevent up to 130,000 unneeded fine-needle aspiration (FNA) biopsies of thyroid nodules and subsequent surgeries each year in the United States by better understanding the genetic risk associated with thyroid cancer.

Through an R21 grant from the National Institutes of Health, Nikita Pozdeyev, MD, assistant professor of biomedical informatics, Chris Gignoux, PhD, professor of biomedical informatics, and Bryan Haugen, MD, professor of medicine and head of the Division of Endocrinology, Metabolism, and Diabetes, will study new strategies that could pave the way for personalized management of thyroid nodules, inform future mechanistic studies of thyroid cancer, and lead to a clinical trial of an ultrasound and genetic thyroid nodule classifier. This work aims to create a clearer diagnosis and better standard of care for thousands of patients who experience a thyroid nodule that currently requires biopsy.

“Our ultimate goal is to diagnose thyroid cancer better,” says Pozdeyev, a trained endocrinologist in the Department of Biomedical Informatics who utilizes data to tackle clinical challenges. 

Thyroid cancer is the most common endocrine malignancy, representing about 44,000 new cases and 1% of new cancer diagnoses each year. When a thyroid nodule is detected in a patient, it can be difficult to know whether it’s benign or cancerous.

A FNA biopsy can help determine a diagnosis, but, ultimately, around 20% of biopsies return an inconclusive result, Pozdeyev says.

“We then order additional testing and frequently have to perform diagnostic surgery, basically removing a person’s thyroid,” he explains. “And in some cases, we find that we went through all of this trouble to learn that it wasn’t necessary and a thyroid nodule is benign. With this grant, we will incorporate genetics to better quantify the risk that a particular person has thyroid cancer.”

The power of data The researchers will leverage biobanks across the world, including the biobank at the Colorado Center for Personalized Medicine, to create a dataset that wouldn’t be possible otherwise.

“We have a lot of buy-in from institutions all over the world that want to help us solve this problem,” Gignoux says. “Studying human genetics is extremely collaborative because we benefit from scenarios where we can look at hundreds and thousands to millions of people. This helps us to have thorough studies.”

The data will help the team to create a polygenic risk score (PRS), which Gignoux explains as a mechanism to measure risk of disease based on complex traits. Unlike some forms of cancers where one gene can determine risk — like the BRCA gene in hereditary breast cancer — thyroid cancer risk is dependent on a slate of genes interacting with each other.

To analyze the genetics behind thyroid cancer, the researchers will test genetic associations directly using a GWAS meta-analysis with 12,091 thyroid cancer cases, 56,949, patients with benign nodules and nearly 1.8 million individuals without thyroid nodular disease as controls. They’ll also use a computational method to disentangle the signals driving thyroid cancer from other common thyroid nodule traits, such as goiter.

In the end, the research might inform more than cancerous tumors.

“Our grant is centered on the ultimate outcome of being able to say something about thyroid cancer, but in order to do that, we have to have lots of data across a range of thyroid traits. For example, we have collected the largest dataset to date on hypothyroid genetics,” Gignoux says. “This allows us to tease out the specific signal that predisposes people to thyroid cancer itself.”

“This is the future of personalized medicine research,” he continues. “We want to be able to benefit from what the data world can collectively tell us, then bring it back into a setting with domain experts to derive the maximal benefit and ensure our results translate into clinical and medical impact.”

The future of patient care The course of treatment for a person with a thyroid nodule has evolved greatly over the last five decades.

“Before the 1980s, if a physician felt a lump on a patient’s neck, they pretty much went straight to surgery,” says Haugen, who works in the Department of Medicine and has been seeing patients with thyroid tumors for more than 30 years.

The introduction of FNA biopsies then allowed pathologists to know whether a tumor was benign. It was a real improvement, Haugen says, and cut unnecessary surgeries by about half, but there’s still more work to do to create better outcomes for patients, especially the 20% of people who receive inconclusive biopsy results.

“The next level of innovation was better ultrasounds,” he says. “There are still many people who go to surgery who don't need it. You don't want to miss a cancer, but at the same time, you don't want to send a bunch of people with benign nodules to surgery if they don't need it.”

Having thyroid surgery can come with risks of complication – while low, they still happen, Haugen says – and the potential to need medication for the rest of a patient’s life.

The study’s success means that in the future, a doctor could see a patient with a nodule, use an ultrasound, look at the history of the patient, and use the polygenic risk score to determine whether a biopsy or surgery is necessary.

“This could reduce tens of thousands of unnecessary biopsies and subsequent surgeries,” he says. “It will be so beneficial to physicians and their patients to have another tool to guide management.”

END


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[Press-News.org] CU researchers awarded grant to develop genetic risk score for thyroid cancer
Researchers in the University of Colorado Department of Biomedical Informatics and the Department of Medicine want to better understand the genetic architecture behind thyroid cancer to prevent unnecessary — and sometimes invasive — treatments.