Pparγ targets‐derived diagnostic and prognostic index for papillary thyroid cancer

Jaehyung Kim, Soo Young Kim, Shi Xun Ma, Seok Mo Kim, Su Jin Shin, Yong Sang Lee, Hojin Chang, Hang Seok Chang, Cheong Soo Park, Su Bin Lim

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In most cases, papillary thyroid cancer (PTC) is highly curable and associated with an excellent prognosis. Yet, there are several clinicopathological features that lead to a poor prognosis, underscoring the need for a better genomic strategy to refine prognostication and patient manage-ment. We hypothesized that PPARγ targets could be potential markers for better diagnosis and prognosis due to the variants found in PPARG in three pairs of monozygotic twins with PTC. Here, we developed a 10‐gene personalized prognostic index, designated PPARGi, based on gene expression of 10 PPARγ targets. Through scRNA‐seq data analysis of PTC tissues derived from patients, we found that PPARGi genes were predominantly expressed in macrophages and epithelial cells. Machine learning algorithms showed a near‐perfect performance of PPARGi in deciding the pres-ence of the disease and in selecting a small subset of patients with poor disease‐specific survival in TCGA‐THCA and newly developed merged microarray data (MMD) consisting exclusively of thyroid cancers and normal tissues.

Original languageEnglish
Article number5110
JournalCancers
Volume13
Issue number20
DOIs
Publication statusPublished - 2021 Oct 2

Bibliographical note

Publisher Copyright:
© 2021 by the authors. Li-censee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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