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Thyroid Cancer Prognostic Signature Developed Using Microenvironment Profiles

NEW YORK – A team led by investigators at Vanderbilt University Medical Center has developed a signature for thyroid cancer aggressiveness that incorporates immune and other microenvironment features found with multiomic analyses.

"Continuing research on the stromal microenvironment of thyroid cancer has the potential to improve care of thyroid cancer patients, identify novel therapeutic targets for aggressive disease, and potentially help prevent [anaplastic thyroid cancer], one of the most aggressive forms of thyroid cancer," senior and corresponding author Vivian Weiss, associate vice chair for clinical and translational research at Vanderbilt's pathology, microbiology, and immunology department, and her colleagues wrote in Cell Genomics on Thursday.

In the past, the authors explained, thyroid cancer profiling has largely focused on features involved in malignancy and tumor development. For the current study, on the other hand, they incorporated stromal microenvironment features, tumor gene mutations, gene fusions, and more to assess instead potential contributors to thyroid cancer aggressiveness, treatment response, disease recurrence, and patient outcomes.

"Molecular testing is a major focus of the thyroid cancer field, and a key question is whether gene expression data can supplement high-risk mutations (e.g., TP53) for predicting which tumors are likely to recur, metastasize, or be resistant to therapy," Weiss said in an email.

Using a combination of tumor exome sequencing, RNA-seq, spatial transcriptomic profiling, and clinical data, the researchers searched for prognostic biomarkers in 312 formalin-fixed, paraffin-embedded resected thyroid lesions from 251 thyroid cancer patients with indolent or aggressive disease. The collection of tumors tested included 116 samples from the papillary subtype, they noted, along with 106 follicular tumors, 55 tumors from the transformed subtype, and 35 non-neoplastic thyroid tumors.

With these data, the team came up with a 549-gene "molecular aggression and prediction" (MAP) score for predicting thyroid cancer aggressiveness with insights from the tumor microenvironment — this set of genes included tumor microenvironment components such as immune infiltrate, collagen remodeling, and cancer-associated fibroblast genes as well as contributors to pathways involved in epithelial de-differentiation and cell division.

"The MAP score encompasses genes associated with key tumor microenvironment cell populations, highlighting the importance of fibroblasts and macrophages in disease progression and resistance to therapy in thyroid cancer," Weiss explained.

When the investigators applied the MAP scoring method to a particularly lethal form of thyroid cancer called anaplastic thyroid cancer (ATC), for example, they found that ATC tumors falling into the moderate MAP score group tended to have relatively robust responses to checkpoint immunotherapy treatment. In contrast, ATC tumors with high MAP scores had poorer immunotherapy response and were higher risk overall.

"We show that incorporation of a molecular signature including stromal genes with standard mutational analysis could improve risk-stratification and may even predict immunotherapy response in [anaplastic thyroid cancer] patients," the authors reported, adding that "[i]n the future, we envision a testing platform utilizing both mutational and stromal microenvironment data for outcome and [immune checkpoint blockade] response prediction."

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