Integrated genomic and transcriptomic analysis improves disease classification and risk stratification of MDS with ring sideroblasts

SND-ID: 2023-148. Version: 1. DOI: https://doi.org/10.48723/zt59-8x04

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Associated documentation

readme.txt (1.58 KB)

Variable_list_metadata_RS.csv (5.51 KB)

Citation

Creator/Principal investigator(s)

Gabriele Todisco - Karolinska Institutet, Department of Medicine, Huddinge / Center for Hematology and Regenerative Medicine (HERM)

Eva Hellström-Lindberg - Karolinska Institutet, Department of Medicine, Huddinge / Center for Hematology and Regenerative Medicine (HERM)

Research principal

Karolinska Institutet - Department of Medicine, Huddinge / Center for Hematology and Regenerative Medicine (HERM)

Description

Full transcriptome (RNA-sequencing) from bulk CD34+ bone marrow mononuclear cells from MDS patients with ring sideroblasts. CD34+ cells were isolated from the MNC using AUTO-MACS with double-separation option (Miltenyi Biotec, Germany) and submitted for RNA extraction. RNA was extracted with RNeasy Microkit (Qiagen, Hilden, Germany) and treated with DNase, according to manufacturer instruction. RNA integrity number was estimated using Agilent RNA 6000 Pico (Agilent Technologies, Palo Alto, CA) and was greater than 6.5 for all the samples (median 8.2). The RNA-sequencing (RNA-seq) libraries were prepared from total RNA using SMARTer Stranded Total RNA-Seq Kit v2 Pico Input Mammalian with enzymatic ribosomal depletion (Takara Bio, Japan). Libraries were sequenced using the Novaseq 6000 with paired-end 150bp configuration. The molecular data were integrated with clinical information aiming to improve prognosis prediction in this hematologic malignancy.

The dataset consists of 2 files:
- FASTQ_RS.tar.gz: compressed folder that includes 258 fastq files
- metadata_RS.xlsx

The total size of the dat

Data contains personal data

Yes

Sensitive personal data

Yes

Type of personal data

Genetic and health information

Code key exists

Yes

Language

English

Method and outcome

Population

Patients with Myelodysplastic neoplasms with ring sideroblasts (MDS-RS)

Study design

Observational study

Sampling procedure

We studied 129 MDS patients with ring sideroblasts within a population of 834 myeloid neoplasms evaluated at Karolinska University Hospital in Stockholm between February 2004 and August 2020.

CD34+ cells were isolated from the MNC using AUTO-MACS with double-separation option (Miltenyi Biotec, Germany) and submitted for RNA extraction for all cases and controls. The RNA-sequencing (RNA-seq) libraries were prepared from total RNA using SMARTer Stranded Total RNA-Seq Kit v2 Pico Input Mammalian with enzymatic ribosomal depletion (Takara Bio, Japan). Libraries were sequenced using the Novaseq 6000 with paired-end 150bp configuration.

Time period(s) investigated

2002 – 2022

Biobank is connected to the study

This study has used existing samples from a scientific collection or biobank

Scientific collection or biobank name: Karolinska MDS Biobank

Type(s) of sample: Bone marrow cells; Human sample; RNA

Number of individuals/objects

129

Data format / data structure

Text

Other

Data collection

Geographic coverage

Geographic spread

Geographic location: Sweden

Administrative information

Responsible department/unit

Department of Medicine, Huddinge / Center for Hematology and Regenerative Medicine (HERM)

Ethics Review

Stockholm - Ref. 2017/1090-31/4

Topic and keywords

Research area

Cancer and oncology (Standard för svensk indelning av forskningsämnen 2011)

Keywords

Hematologic diseases, Myelodysplastic syndromes, Myelodysplastic-myeloproliferative diseases, Human health and safety, Cancer, Neoplasms, Tumors

Publications

Todisco G, Creignou M, Bernard E, Björklund AC, Moura PL, Tesi B, Mortera Blanco T, Sander B, Jansson M, Walldin G, Barbosa I, Reinsbach SE, Hofman IJ, Nilsson C, Yoshizato T, Dimitriou M, Chang D, Olafsdottir S, Venckute Larsson S, Tobiasson M, Malcovati L, Woll P, Jacobsen SW, Papaemmanuil E, Hellström-Lindberg E. Integrated genomic and transcriptomic analysis improves disease classification and risk stratification of MDS with ring sideroblasts. Clin Cancer Res. 2023 Jul 27:CCR-23-0538. doi: 10.1158/1078-0432.CCR-23-0538.
DOI: https://doi.org/10.1158/1078-0432.CCR-23-0538

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