PhD Scientific Days 2020

Pathology and Oncology III. Lectures

Improving Molecular Diagnostics in Pediatric Acute Lymphoblastic Leukemia with Comprehensive Biostatistical Analysis of RNA Based Panel Sequencing

Előadó neve

Dr. Bedics, Gábor

Előadó munkahelye

Semmelweis University, 1st Department of Pathology and Experimental Cancer Research

Előadó telefonszáma

+36304371071

Előadó e-mail címe

bedics.gabor@med.semmelweis-univ.hu

Az előadás címe

Improving Molecular Diagnostics in Pediatric Acute Lymphoblastic Leukemia with Comprehensive Biostatistical Analysis of RNA Based Panel Sequencing

Szerző(k) neve és munkahelye

Gábor Bedics1, Szilvia Krizsán1, Lili Kotmayer1, Tibor Nagy2, Endre Sebestyén1
1 1st Department of Pathology and Experimental Cancer Research, Semmelweis University, Budapest
2 Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Debrecen

Szekció

Pathology and Oncology III. Lectures

Language of the presentation

Hungarian

Section, first choice

Pathology and Oncology

Section, second choice

Molecular Sciences

Összefoglaló szövege

Introduction
Acute Lymphoblastic Leukemia (ALL) is the most frequent malignancy during childhood. It affects 60-70 children in Hungary annually. Although the overall survival increased dramatically during the last century, novel diagnostic-, and personalized therapeutic methods could increase the survival rate even more. Additionally, these methods could reduce the side-effects caused by the usually applied chemotherapy.
Aims
Our long term aim is to develop an integrated next-generation sequencing (NGS) and bioinformatic analysis pipeline, in order to provide clinically relevant diagnostic information based on transcriptome panel sequencing. Using this information, personalized therapy can be administered to patients. The aim of this study was to analyze NGS results from a bioinformatical and statistical point of view and provide initial recommendations in interpreting them for medical reports and clinical diagnosis.
Methods
We performed RNA-based QuiaSeq PanCancer panel sequencing on 77 ALL patients and 11 control samples, using an Illumina MiSeq device. We analyzed raw sequencing data using the FusionCatcher, STAR Fusion, and Pizzly tools, besides integrating the data with the FusionHub database. Fusion transcript results were further analyzed with R and R-Studio. We evaluated the distribution of fusion transcript spanning and paired reads, besides their expression, in order to optimize sensitivity and specificity of medical diagnosis presented in reports.
Results
We detected numerous well-known fusion transcripts occurring in pediatric ALL including: ETV6-RUNX1 fusion transcripts in 9 patients, P2RY8-CRLF2 in 4 patients, and KMT2A-AFDN, DDX5-LEF1, NFATC1-RNPS1 each of them in 2 patients. Moreover, we found several hundred fusion transcripts with a known pathogenicity in other diseases, or unknown clinical significance.
Conclusions
Here we present a comprehensive bioinformatics and biostatistics analysis of 11 RNA-based QiaSeq PanCancer NGS runs. This dataset may serve as the basis of optimization for the downstream bioinformatic analysis of NGS data of the Hungarian pediatric ALL patient population in order to improve the quality of the personalized molecular diagnosis.

Additional Information

Endre Sebestyén
sebestyen.endre@med.semmelweis-univ.hu

Bemutatás módja

Szóbeli

Kind

Szabad

Status

elfogadva

Accepted presentation method

szóbeli

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

4694

Start

17:30

End

17:45

Authors (legacy)

Gábor Bedics1, Szilvia Krizsán1, Lili Kotmayer1, Tibor Nagy2, Endre Sebestyén1
1 1st Department of Pathology and Experimental Cancer Research, Semmelweis University, Budapest
2 Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Debrecen