Bioinformatics-driven dissection of PANoptosis-related molecular subtypes and tumor immune microenvironment

Wen-Ting Pei1, Chun-Lei Liu2, Xiao-Ling Li3

  • 1Department of Pediatrics, Children's Hospital Affiliated to Shandong University (Jinan Children's Hospital), No. 23976 Jingshi Road, Huaiyin District, Jinan, 250000, Shandong Province, China.

Insights

This study defines PANoptosis subtypes in pediatric acute myeloid leukemia (AML), revealing distinct immune microenvironments and patient outcomes. Findings identify potential therapeutic targets for AML treatment.

Area of Science:

  • Immunology
  • Oncology
  • Genetics

Background:

  • PANoptosis, a programmed cell death pathway, influences tumor immunity but its role in pediatric acute myeloid leukemia (AML) is unclear.
  • Understanding PANoptosis mechanisms is crucial for developing novel pediatric AML therapies.

Purpose of the Study:

  • To define PANoptosis-associated molecular subtypes in pediatric AML.
  • To characterize tumor immune microenvironment (TIME) heterogeneity.
  • To identify potential regulatory genes and small-molecule drug targets.

Main Methods:

  • Bioinformatic analysis of pediatric AML bone marrow transcriptomic data (TARGET database).
  • Unsupervised clustering to identify molecular subtypes based on 68 PANoptosis-related genes.
  • In silico molecular docking for drug target identification.

Main Results:

  • Four distinct PANoptosis-associated molecular subtypes (C1-C4) were identified.
  • Subtype C2 showed high CD8+ T-cell and NK cell activity, correlating with better prognosis.
  • Subtype C1 exhibited immune suppression and poor survival.
  • An IGF1-CCL2-CCL4 gene set linked to PANoptosis and Toll-like receptor signaling was identified.

Conclusions:

  • PANoptosis contributes to significant molecular and immune heterogeneity in pediatric AML.
  • Identified subtypes offer a framework for stratifying patients for targeted therapies.
  • Further research and experimental validation are needed for identified gene sets and drug candidates.

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