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Poster display session

134P - Optimization of RNA-Seq analysis in uterine sarcomas

Date

15 Oct 2022

Session

Poster display session

Presenters

Nikola Hajkova

Citation

Annals of Oncology (2022) 33 (suppl_8): S1383-S1430. 10.1016/annonc/annonc1095

Authors

N. Hajkova1, E. Krkavcová1, R. Michalkova1, J. Dvorák2, J. Hojný1, M. Bártu1, I. Stružinská1, K. Nemejcova1, P. Dundr1

Author affiliations

  • 1 General Teaching Hospital and The First Faculty of Medicine of Charles University in Prague, Prague/CZ
  • 2 Institute of Pathology - First Faculty of Medicine, Charles University and General University Hospital, Prague/CZ

Resources

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Abstract 134P

Background

Pure uterine sarcomas are rare tumours which account for less than 3 % of all uterine malignancies. Knowledge about their molecular background is limited. Identification of new molecular pattern and new molecular markers could help to better stratify these tumours in terms of their diagnostic or therapeutic options. Whole transcriptome RNA-Seq is a robust tool which could reveal novel gene fusions, aberrant splicing events, or gene expression. However, optimization of library preparation from archive specimens (FFPE) is crucial for a retrospective study, which is necessary due to the rarity of these tumours.

Methods

Total RNA was isolated from 6 samples from different tumour types with confirmed gene fusion from FFPE or fresh frozen (FF) tissue. 500 ng of total RNA was used for the rRNA depletion protocol using the NEBNext Globin & rRNA Depletion Kit (NEB). rRNA removal was confirmed by qPCR. Fold change in the levels of rRNA genes (28S, 18S, 16S, 12S) and reference gene POLR2A in the depleted and non-depleted group was calculated (ΔΔ Ct method). Transcriptome libraries were constructed from depleted RNA using KAPA RNA HyperPrep kit (Roche) and sequenced on NextSeq. Biostatistical analysis was performed using constructed pipeline in CLC Genomics Workbench (Qiagen).

Results

Depletion of rRNA (>10,000x rRNA decrease) was comparable for FFPE and FF samples, and had no significant effect on the mRNA levels, the Ct values of POLR2A were stable in both depleted and untreated groups. The proportions of different RNA types after rRNA depletion were calculated during the bioinformatical RNA-Seq analysis: < 0.5 % of rRNA, 70-82 % mRNA, 13-27 % ncRNA, and miscRNA 3-5 % for the six tested samples. Whole transcriptome RNA-Seq analyses revealed all fusions previously detected by panel RNA-Seq approach. According to the preliminary results, the target of 60 million reads is sufficient to detect even low-expressed fusions and aberrant transcripts.

Conclusions

Whole transcriptome RNA-Seq is a complex tool for analysis of molecular patterns and for exploring novel diagnostic markers or therapy targets. Optimization of the library preparation including effective rRNA depletion was a necessary step to get high quality data for downstream analyses in a set of uterine sarcomas.

Legal entity responsible for the study

The authors.

Funding

Supported by MZCR (NU21-03-00122).

Disclosure

All authors have declared no conflicts of interest.

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