Translational Medicine Communications (Sep 2018)

Notch pathway connections in primary leukaemia samples of limited size

  • Luka Horvat,
  • Josipa Skelin,
  • Biljana Jelić Puškarić,
  • Isidoro Feliciello,
  • Darko Heckel,
  • Josip Madunić,
  • Ika Kardum-Skelin,
  • Maja Matulić,
  • Delfa Radić-Krišto,
  • Mariastefania Antica

DOI
https://doi.org/10.1186/s41231-018-0026-z
Journal volume & issue
Vol. 3, no. 1
pp. 1 – 9

Abstract

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Abstract Background The Notch pathway combined with other signalling molecules acts specifically for the development of each blood cell type and differentiation stage. A causative role of Notch dysfunction in leukaemia development has been found in many studies so, initially only for T- acute lymphoblastic leukaemia (T-ALL) but more recently also for B cell and myeloid leukaemia. The aim of our study is to introduce a method for multiple direct analysis of the Notch pathway partners in a population of only 500 or fewer cells. The notion of this method consists in gaining insight into gene expression at the level of the malignant clone population. A small number of cells is a significant limitation when working on primary cells either when freshly isolated or when analysed after several days in cocultures. Methods The primers were designed to avoid genomic amplification through the selection of 3′ and 5′ primers that hybridise with different exons. Cell lines and primary cells were collected and multiplex quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) performed on a descending number of cells, ranging from 2,500 cells up to 50 cells per sample, for the Notch pathway genes and other transcription factors important for cell differentiation. ImageJ program, STATISTICA 13.1 software package and Student’s t-test were used for statistical evaluation. We checked protein expression by western blot. Results We characterised the gene expression levels of Notch, Ikaros and Parp genes in leukaemia cell lines of B and T origin and in primary leukaemia samples of limited size. We further compared our results to the cDNA analysis obtained by total RNA isolation from a large number of cells as routinely performed in clinical laboratories, and finally tested the method described on primary cells from leukaemia patients. Conclusions This rapid multiple gene expression analysis of a small population of cells provides efficient cell classification determining malignant changes as an important additional information for clinical leukaemia diagnostics as well as for in vitro studies of primary cells.

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