Papillary thyroid cancer immune phenotypes via tumor-infiltrating lymphocyte spatial analysis

in Endocrine-Related Cancer
Authors:
Myungwoo Nam Department of Medicine, Lincoln Medical and Mental Health Center, Bronx, New York, USA

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Woojung Yang Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA

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Hye Sung Kim Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA

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Jewel Park Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA

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Gahee Park Lunit Inc, Oncology group, Seoul, Republic of Korea

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Sukjun Kim Lunit Inc, Oncology group, Seoul, Republic of Korea

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Sanghoon Song Lunit Inc, Oncology group, Seoul, Republic of Korea

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Chan-Young Ock Lunit Inc, Oncology group, Seoul, Republic of Korea

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Victor G Wang Department of Genetics and Genome Sciences, UConn Health, Farmington, Connecticut, USA
The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA

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Jeffrey H Chuang Department of Genetics and Genome Sciences, UConn Health, Farmington, Connecticut, USA
The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA

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Young Kwang Chae Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, Illinois, USA

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https://orcid.org/0000-0003-1557-7235

Correspondence should be addressed to Y K Chae: ychae@nm.org
DOI:
https://doi.org/10.1530/ERC-23-0110
Volume/Issue:
Volume 30: Issue 9
Article Type:
Research Article
Article ID:
e230110
Online Publication Date:
28 Jul 2023
Copyright:
© the author(s) 2023
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Standard-of-care treatment options provide an excellent prognosis for papillary thyroid cancers (PTCs); however, approximately 10% of cases are advanced PTCs, resulting in less than 50% 5-year survival rates. Understanding the tumor microenvironment is essential for understanding cancer progression and investigating potential biomarkers for treatment, such as immunotherapy. Our study focused on tumor-infiltrating lymphocytes (TILs), which are the main effectors of antitumor immunity and related to the mechanism of immunotherapy. Using an artificial intelligence model, we analyzed the density of intratumoral and peritumoral TILs in the pathologic slides of The Cancer Genome Atlas PTC cohort. Tumors were classified into three immune phenotypes (IPs) based on the spatial distribution of TILs: immune-desert (48%), immune-excluded (34%), and inflamed (18%). Immune-desert IP was mostly characterized by RAS mutations, high thyroid differentiation score, and low antitumor immune response. Immune-excluded IP predominantly consisted of BRAF V600E-mutated tumors and had a higher rate of lymph node metastasis. Inflamed IP was characterized by a high antitumor immune response, as demonstrated by a high cytolytic score, immune-related cell infiltrations, expression of immunomodulatory molecules (including immunotherapy target molecules), and enrichment of immune-related pathways. This study is the first to investigate IP classification using TILs in PTC through a tissue-based approach. Each IP had unique immune and genomic profiles. Further studies are warranted to assess the predictive value of IP classification in advanced PTC patients treated with immunotherapy.

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Print ISSN:
1351-0088
Online ISSN:
1479-6821
Copyright:
© the author(s) 2023
Article ID:
e230110
Received Date:
31 May 2023
Accepted Date:
06 Jun 2023
Print Publication Date:
01 Sep 2023
Online Publication Date:
28 Jul 2023
Keywords:
papillary thyroid cancer; immune phenotypes; tumor-infiltrating lymphocytes; spatial distribution; artificial intelligence powered analyzer

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