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Stem cell index-based RiskScore model for predicting prognosis in thyroid cancer and experimental verification.

Ruoran Chen1, Wei Gao1, Linlang Liang1

  • 1Department of Endocrinology, General Hospital of Northern Theater Command, Shenyang, 110016, China.

Heliyon
|June 13, 2024
PubMed
Summary

This study developed an mRNA expression-based stemness index (mRNAsi) signature to predict therapeutic resistance and immunotherapy response in thyroid cancer (THCA). The findings offer potential for improved patient prognosis and treatment strategies.

Keywords:
ImmunotherapyMolecular subtypesPrognostic modelStem cellThyroid cancermRNAsi

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Cancer stemness is characterized by an mRNA expression-based stemness index (mRNAsi).
  • The predictive value of mRNAsi in thyroid cancer (THCA) for therapeutic resistance and immunotherapy remains unclear.

Purpose of the Study:

  • To evaluate and validate the role of mRNAsi in drug sensitivity in THCA.
  • To explore the relationship between mRNAsi, THCA clinical features, and tumor immunity using bioinformatics.

Main Methods:

  • Calculated mRNAsi using transcriptome data from TCGA and PCBC databases.
  • Identified THCA molecular subtypes using mRNAsi-related genes and ConsensusClusterPlus.
  • Developed a prognostic model with 5 mRNAsi-related genes using Lasso cox regression.

Main Results:

  • THCA was classified into 3 subtypes based on mRNAsi; subtype C2 showed the poorest prognosis and highest immune score.
  • Subtype C2 exhibited increased sensitivity to Cisplatin, Erlotinib, Paclitaxel, and Lapatinib.
  • The 5-gene prognostic signature accurately predicted THCA prognosis and was validated across datasets.

Conclusions:

  • Identification of three THCA subtypes based on mRNAsi.
  • Development of a prognostic model utilizing mRNAsi-related genes with potential for predicting prognosis and immunotherapy response.