Computational gene expression analysis reveals distinct molecular subgroups of T-cell prolymphocytic leukemia

PLoS One. 2022 Sep 21;17(9):e0274463. doi: 10.1371/journal.pone.0274463. eCollection 2022.

Abstract

T-cell prolymphocytic leukemia (T-PLL) is a rare blood cancer with poor prognosis. Overexpression of the proto-oncogene TCL1A and missense mutations of the tumor suppressor ATM are putative main drivers of T-PLL development, but so far only little is known about the existence of T-PLL gene expression subtypes. We performed an in-depth computational reanalysis of 68 gene expression profiles of one of the largest currently existing T-PLL patient cohorts. Hierarchical clustering combined with bootstrapping revealed three robust T-PLL gene expression subgroups. Additional comparative analyses revealed similarities and differences of these subgroups at the level of individual genes, signaling and metabolic pathways, and associated gene regulatory networks. Differences were mainly reflected at the transcriptomic level, whereas gene copy number profiles of the three subgroups were much more similar to each other, except for few characteristic differences like duplications of parts of the chromosomes 7, 8, 14, and 22. At the network level, most of the 41 predicted potential major regulators showed subgroup-specific expression levels that differed at least in comparison to one other subgroup. Functional annotations suggest that these regulators contribute to differences between the subgroups by altering processes like immune responses, angiogenesis, cellular respiration, cell proliferation, apoptosis, or migration. Most of these regulators are known from other cancers and several of them have been reported in relation to leukemia (e.g. AHSP, CXCL8, CXCR2, ELANE, FFAR2, G0S2, GIMAP2, IL1RN, LCN2, MBTD1, PPP1R15A). The existence of the three revealed T-PLL subgroups was further validated by a classification of T-PLL patients from two other smaller cohorts. Overall, our study contributes to an improved stratification of T-PLL and the observed subgroup-specific molecular characteristics could help to develop urgently needed targeted treatment strategies.

MeSH terms

  • Blood Proteins / genetics
  • Chromosomal Proteins, Non-Histone / genetics
  • GTP Phosphohydrolases / genetics
  • Gene Expression Regulation, Neoplastic
  • Genes, Tumor Suppressor
  • Humans
  • Leukemia, Prolymphocytic* / genetics
  • Leukemia, Prolymphocytic, T-Cell* / genetics
  • Leukemia, Prolymphocytic, T-Cell* / pathology
  • Membrane Proteins / genetics
  • Molecular Chaperones / genetics
  • Proteins / genetics
  • Signal Transduction
  • Transcriptome

Substances

  • AHSP protein, human
  • Blood Proteins
  • Chromosomal Proteins, Non-Histone
  • MBTD1 protein, human
  • Membrane Proteins
  • Molecular Chaperones
  • Proteins
  • GIMAP2 protein, human
  • GTP Phosphohydrolases

Grants and funding

This work was done within the Transcan-2 ERA-NET consortium ‘ERANET-PLL’ funded by the EU Horizon 2020 program (grant numbers: 01KT1906A/B). We also acknowledge support by the German Research Foundation and the Open Access Publication Funds of the SLUB/TU Dresden to cover the article processing charge. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.