Next Article in Journal
Mechanisms of Matrix-Induced Chemoresistance of Breast Cancer Cells—Deciphering Novel Potential Targets for a Cell Sensitization
Next Article in Special Issue
Long-Term Outcome after Hemithyroidectomy for Papillary Thyroid Cancer: A Comparative Study and Review of the Literature
Previous Article in Journal
The Role of MicroRNAs in the Metastatic Process of High-Risk HPV-Induced Cancers
Previous Article in Special Issue
CCND1 Splice Variant as A Novel Diagnostic and Predictive Biomarker for Thyroid Cancer
Open AccessFeature PaperArticle

Immune Gene Signature Delineates a Subclass of Papillary Thyroid Cancer with Unfavorable Clinical Outcomes

by Kyuryung Kim 1,2,3, Sora Jeon 1,3, Tae-Min Kim 1,2,3,* and Chan Kwon Jung 1,3,4,*
1
Cancer Research Institute, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
2
Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
3
Department of Biomedicine & Health Sciences, Graduate School, The Catholic University of Korea, Seoul 06591, Korea
4
Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea
*
Authors to whom correspondence should be addressed.
Cancers 2018, 10(12), 494; https://doi.org/10.3390/cancers10120494
Received: 17 November 2018 / Revised: 2 December 2018 / Accepted: 3 December 2018 / Published: 5 December 2018
(This article belongs to the Special Issue Thyroid Cancer)
Papillary thyroid carcinoma (PTC) represents a heterogeneous disease with diverse clinical outcomes highlighting a need to identify robust biomarkers with clinical relevance. We applied non-negative matrix factorization-based deconvolution to publicly available gene expression profiles of thyroid cancers in the Cancer Genome Atlas (TCGA) consortium. Among three metagene signatures identified, two signatures were enriched in canonical BRAF-like and RAS-like thyroid cancers with up-regulation of genes involved in oxidative phosphorylation and cell adhesions, respectively. The third metagene signature representing up-regulation of immune-related genes further segregated BRAF-like and RAS-like PTCs into their respective subgroups of immunoreactive (IR) and immunodeficient (ID), respectively. BRAF-IR PTCs showed enrichment of tumor infiltrating immune cells, tall cell variant PTC, and shorter recurrence-free survival compared to BRAF-ID PTCs. RAS-IR and RAS-ID PTC subtypes included majority of normal thyroid tissues and follicular variant PTC, respectively. Immunopathological features of PTC subtypes such as immune cell fraction, repertoire of T cell receptors, cytolytic activity, and expression level of immune checkpoints such as and PD-L1 and CTLA-4 were consistently observed in two different cohorts. Taken together, an immune-related metagene signature can classify PTCs into four molecular subtypes, featuring the distinct histologic type, genetic and transcriptional alterations, and potential clinical significance. View Full-Text
Keywords: papillary thyroid carcinoma; immunity; molecular taxonomy; non-negative matrix factorization; survival papillary thyroid carcinoma; immunity; molecular taxonomy; non-negative matrix factorization; survival
Show Figures

Graphical abstract

MDPI and ACS Style

Kim, K.; Jeon, S.; Kim, T.-M.; Jung, C.K. Immune Gene Signature Delineates a Subclass of Papillary Thyroid Cancer with Unfavorable Clinical Outcomes. Cancers 2018, 10, 494.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
  • Supplementary File 1:

    ZIP-Document (ZIP, 1852 KB)

  • Externally hosted supplementary file 1
    Link: http://no
    Description: The following are available online at www.mdpi.com/xxx/s1, Table S1: GSEA of three metagene signatures. Top 20 Gene Ontology terms significantly enriched with gene-level weights of 3 metagene signatures are shown. ES and NES are enrichment score and normalized ES as the output of GSEA, respectively, Table S2: Gene-level weights and metagene factors for GSEA of 3 metagene signatures. For 3 metagene signatures, weights for GSEA and metagene factors for metagene projection are shown. The genes in each metagene signature are sorted in order of the weight values, Table S3: Sequencing information of RNAseq (CMC cohort).
Back to TopTop