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Article ; Online: Development and Validation of a Novel RNA Sequencing-Based Prognostic Score for Acute Myeloid Leukemia.

Wang, Mei / Lindberg, Johan / Klevebring, Daniel / Nilsson, Christer / Lehmann, Sören / Grönberg, Henrik / Rantalainen, Mattias

Journal of the National Cancer Institute

2018 Volume 110, Issue 10, Page(s) 1094–1101

Abstract: Background: Recent progress in sequencing technologies allows us to explore comprehensive genomic and transcriptomic information to improve the current European LeukemiaNet (ELN) system of acute myeloid leukemia (AML).: Methods: We compared the ... ...

Abstract	Background: Recent progress in sequencing technologies allows us to explore comprehensive genomic and transcriptomic information to improve the current European LeukemiaNet (ELN) system of acute myeloid leukemia (AML). Methods: We compared the prognostic value of traditional demographic and cytogenetic risk factors, genomic data in the form of somatic aberrations of 25 AML-relevant genes, and whole-transcriptome expression profiling (RNA sequencing) in 267 intensively treated AML patients (Clinseq-AML). Multivariable penalized Cox models (overall survival [OS]) were developed for each data modality (clinical, genomic, transcriptomic), together with an associated prognostic risk score. Results: Of the three data modalities, transcriptomic data provided the best prognostic value, with an integrated area under the curve (iAUC) of a time-dependent receiver operating characteristic (ROC) curve of 0.73. We developed a prognostic risk score (Clinseq-G) from transcriptomic data, which was validated in the independent The Cancer Genome Atlas AML cohort (RNA sequencing, n = 142, iAUC = 0.73, comparing the high-risk group with the low-risk group, hazard ratio [HR]OS = 2.42, 95% confidence interval [CI] = 1.51 to 3.88). Comparison between Clinseq-G and ELN score iAUC estimates indicated strong evidence in favor of the Clinseq-G model (Bayes factor = 26.78). The proposed model remained statistically significant in multivariable analysis including the ELN and other well-known risk factors (HRos = 2.34, 95% CI = 1.30 to 4.22). We further validated the Clinseq-G model in a second independent data set (n = 458, iAUC = 0.66, adjusted HROS = 2.02, 95% CI = 1.33 to 3.08; adjusted HREFS = 2.10, 95% CI = 1.42 to 3.12). Conclusions: Our results indicate that the Clinseq-G prediction model, based on transcriptomic data from RNA sequencing, outperforms traditional clinical parameters and previously reported models based on genomic biomarkers.
MeSH term(s)	Biomarkers, Tumor ; Gene Expression Profiling ; Humans ; Kaplan-Meier Estimate ; Leukemia, Myeloid, Acute/diagnosis ; Leukemia, Myeloid, Acute/genetics ; Leukemia, Myeloid, Acute/mortality ; Prognosis ; Proportional Hazards Models ; ROC Curve ; Reproducibility of Results ; Sequence Analysis, RNA ; Transcriptome
Chemical Substances	Biomarkers, Tumor
Language	English
Publishing date	2018-03-02
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2992-0
ISSN	1460-2105 ; 0027-8874 ; 0198-0157
ISSN (online)	1460-2105
ISSN	0027-8874 ; 0198-0157
DOI	10.1093/jnci/djy021
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Article ; Online: Study design requirements for RNA sequencing-based breast cancer diagnostics.

Mer, Arvind Singh / Klevebring, Daniel / Grönberg, Henrik / Rantalainen, Mattias

Scientific reports

2016 Volume 6, Page(s) 20200

Abstract: Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. ... ...

Abstract	Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.
MeSH term(s)	Breast Neoplasms/classification ; Breast Neoplasms/diagnosis ; Breast Neoplasms/genetics ; Databases, Genetic ; Female ; Humans ; Receptors, Cell Surface/metabolism ; Research Design ; Sample Size ; Sequence Analysis, RNA/methods
Chemical Substances	Receptors, Cell Surface
Language	English
Publishing date	2016-02-01
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/srep20200
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Article ; Online: Determining breast cancer histological grade from RNA-sequencing data.

Wang, Mei / Klevebring, Daniel / Lindberg, Johan / Czene, Kamila / Grönberg, Henrik / Rantalainen, Mattias

Breast cancer research : BCR

2016 Volume 18, Issue 1, Page(s) 48

Abstract: Background: The histologic grade (HG) of breast cancer is an established prognostic factor. The grade is usually reported on a scale ranging from 1 to 3, where grade 3 tumours are the most aggressive. However, grade 2 is associated with an intermediate ... ...

Abstract	Background: The histologic grade (HG) of breast cancer is an established prognostic factor. The grade is usually reported on a scale ranging from 1 to 3, where grade 3 tumours are the most aggressive. However, grade 2 is associated with an intermediate risk of recurrence, and carries limited information for clinical decision-making. Patients classified as grade 2 are at risk of both under- and over-treatment. Methods: RNA-sequencing analysis was conducted in a cohort of 275 women diagnosed with invasive breast cancer. Multivariate prediction models were developed to classify tumours into high and low transcriptomic grade (TG) based on gene- and isoform-level expression data from RNA-sequencing. HG2 tumours were reclassified according to the prediction model and a recurrence-free survival analysis was performed by the multivariate Cox proportional hazards regression model to assess to what extent the TG model could be used to stratify patients. The prediction model was validated in N=487 breast cancer cases from the The Cancer Genome Atlas (TCGA) data set. Differentially expressed genes and isoforms associated with HGs were analysed using linear models. Results: The classification of grade 1 and grade 3 tumours based on RNA-sequencing data achieved high accuracy (area under the receiver operating characteristic curve = 0.97). The association between recurrence-free survival rate and HGs was confirmed in the study population (hazard ratio of grade 3 versus 1 was 2.62 with 95 % confidence interval = 1.04-6.61). The TG model enabled us to reclassify grade 2 tumours as high TG and low TG gene or isoform grade. The risk of recurrence in the high TG group of grade 2 tumours was higher than in low TG group (hazard ratio = 2.43, 95 % confidence interval = 1.13-5.20). We found 8200 genes and 13,809 isoforms that were differentially expressed between HG1 and HG3 breast cancer tumours. Conclusions: Gene- and isoform-level expression data from RNA-sequencing could be utilised to differentiate HG1 and HG3 tumours with high accuracy. We identified a large number of novel genes and isoforms associated with HG. Grade 2 tumours could be reclassified as high and low TG, which has the potential to reduce over- and under-treatment if implemented clinically.
MeSH term(s)	Adult ; Aged ; Aged, 80 and over ; Biomarkers, Tumor ; Breast Neoplasms/genetics ; Breast Neoplasms/mortality ; Breast Neoplasms/pathology ; Computational Biology/methods ; Databases, Nucleic Acid ; Female ; Gene Expression Profiling ; Genetic Association Studies ; Humans ; Kaplan-Meier Estimate ; Middle Aged ; Neoplasm Grading ; Neoplasm Metastasis ; Neoplasm Staging ; Prognosis ; ROC Curve ; Reproducibility of Results ; Sequence Analysis, RNA ; Sweden ; Transcriptome ; Tumor Burden
Chemical Substances	Biomarkers, Tumor
Language	English
Publishing date	2016-05-10
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2015059-3
ISSN	1465-542X ; 1465-5411
ISSN (online)	1465-542X
ISSN	1465-5411
DOI	10.1186/s13058-016-0710-8
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Zs.A 5494: Show issues

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Article ; Online: Expression levels of long non-coding RNAs are prognostic for AML outcome.

Mer, Arvind Singh / Lindberg, Johan / Nilsson, Christer / Klevebring, Daniel / Wang, Mei / Grönberg, Henrik / Lehmann, Soren / Rantalainen, Mattias

Journal of hematology & oncology

2018 Volume 11, Issue 1, Page(s) 52

Abstract: Background: Long non-coding RNA (lncRNA) expression has been implicated in a range of molecular mechanisms that are central in cancer. However, lncRNA expression has not yet been comprehensively characterized in acute myeloid leukemia (AML). Here, we ... ...

Abstract	Background: Long non-coding RNA (lncRNA) expression has been implicated in a range of molecular mechanisms that are central in cancer. However, lncRNA expression has not yet been comprehensively characterized in acute myeloid leukemia (AML). Here, we assess to what extent lncRNA expression is prognostic of AML patient overall survival (OS) and determine if there are indications of lncRNA-based molecular subtypes of AML. Methods: We performed RNA sequencing of 274 intensively treated AML patients in a Swedish cohort and quantified lncRNA expression. Univariate and multivariate time-to-event analysis was applied to determine association between individual lncRNAs with OS. Unsupervised statistical learning was applied to ascertain if lncRNA-based molecular subtypes exist and are prognostic. Results: Thirty-three individual lncRNAs were found to be associated with OS (adjusted p value < 0.05). We established four distinct molecular subtypes based on lncRNA expression using a consensus clustering approach. LncRNA-based subtypes were found to stratify patients into groups with prognostic information (p value < 0.05). Subsequently, lncRNA expression-based subtypes were validated in an independent patient cohort (TCGA-AML). LncRNA subtypes could not be directly explained by any of the recurrent cytogenetic or mutational aberrations, although associations with some of the established genetic and clinical factors were found, including mutations in NPM1, TP53, and FLT3. Conclusion: LncRNA expression-based four subtypes, discovered in this study, are reproducible and can effectively stratify AML patients. LncRNA expression profiling can provide valuable information for improved risk stratification of AML patients.
MeSH term(s)	Female ; Humans ; Leukemia, Myeloid, Acute/genetics ; Male ; Prognosis ; RNA, Long Noncoding/metabolism ; Treatment Outcome
Chemical Substances	RNA, Long Noncoding
Language	English
Publishing date	2018-04-07
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2429631-4
ISSN	1756-8722 ; 1756-8722
ISSN (online)	1756-8722
ISSN	1756-8722
DOI	10.1186/s13045-018-0596-2
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Article ; Online: Exome sequencing of contralateral breast cancer identifies metastatic disease.

Klevebring, Daniel / Lindberg, Johan / Rockberg, Julia / Hilliges, Camilla / Hall, Per / Sandberg, Maria / Czene, Kamila

Breast cancer research and treatment

2015 Volume 151, Issue 2, Page(s) 319–324

Abstract: Women with contralateral breast cancer (CBC) have significantly worse prognosis compared to women with unilateral cancer. A possible explanation of the poor prognosis of patients with CBC is that in a subset of patients, the second cancer is not a new ... ...

Abstract	Women with contralateral breast cancer (CBC) have significantly worse prognosis compared to women with unilateral cancer. A possible explanation of the poor prognosis of patients with CBC is that in a subset of patients, the second cancer is not a new primary tumor but a metastasis of the first cancer that has potentially obtained aggressive characteristics through selection of treatment. Exome and whole-genome sequencing of solid tumors has previously been used to investigate the clonal relationship between primary tumors and metastases in several diseases. In order to assess the relationship between the first and the second cancer, we performed exome sequencing to identify somatic mutations in both first and second cancers, and compared paired normal tissue of 25 patients with metachronous CBC. For three patients, we identified shared somatic mutations indicating a common clonal origin thereby demonstrating that the second tumor is a metastasis of the first cancer, rather than a new primary cancer. Accordingly, these patients all developed distant metastasis within 3 years of the second diagnosis, compared with 7 out of 22 patients with non-shared somatic profiles. Genomic profiling of both tumors help the clinicians distinguish between true CBCs and subsequent metastases.
MeSH term(s)	Alleles ; Breast Neoplasms/genetics ; Breast Neoplasms/metabolism ; Breast Neoplasms/mortality ; Breast Neoplasms/pathology ; Exome ; Female ; High-Throughput Nucleotide Sequencing ; Humans ; Mutation ; Neoplasm Metastasis ; Prognosis ; Registries
Language	English
Publishing date	2015-06
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	604563-7
ISSN	1573-7217 ; 0167-6806
ISSN (online)	1573-7217
ISSN	0167-6806
DOI	10.1007/s10549-015-3403-6
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Article ; Online: In-depth transcriptome analysis reveals novel TARs and prevalent antisense transcription in human cell lines.

Klevebring, Daniel / Bjursell, Magnus / Emanuelsson, Olof / Lundeberg, Joakim

PloS one

2010 Volume 5, Issue 3, Page(s) e9762

Abstract: Several recent studies have indicated that transcription is pervasive in regions outside of protein coding genes and that short antisense transcripts can originate from the promoter and terminator regions of genes. Here we investigate transcription of ... ...

Abstract	Several recent studies have indicated that transcription is pervasive in regions outside of protein coding genes and that short antisense transcripts can originate from the promoter and terminator regions of genes. Here we investigate transcription of fragments longer than 200 nucleotides, focusing on antisense transcription for known protein coding genes and intergenic transcription. We find that roughly 12% to 16% of all reads that originate from promoter and terminator regions, respectively, map antisense to the gene in question. Furthermore, we detect a high number of novel transcriptionally active regions (TARs) that are generally expressed at a lower level than protein coding genes. We find that the correlation between RNA-seq data and microarray data is dependent on the gene length, with longer genes showing a better correlation. We detect high antisense transcriptional activity from promoter, terminator and intron regions of protein-coding genes and identify a vast number of previously unidentified TARs, including putative novel EGFR transcripts. This shows that in-depth analysis of the transcriptome using RNA-seq is a valuable tool for understanding complex transcriptional events. Furthermore, the development of new algorithms for estimation of gene expression from RNA-seq data is necessary to minimize length bias.
MeSH term(s)	Cell Line, Tumor ; ErbB Receptors/genetics ; Gene Expression Regulation, Neoplastic ; Genome, Human ; Humans ; Introns ; Models, Genetic ; Nucleotides/chemistry ; Oligonucleotide Array Sequence Analysis ; Oligonucleotides, Antisense/chemistry ; Oligonucleotides, Antisense/genetics ; Transcription, Genetic
Chemical Substances	Nucleotides ; Oligonucleotides, Antisense ; ErbB Receptors (EC 2.7.10.1)
Language	English
Publishing date	2010-03-25
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0009762
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Article ; Online: Increased throughput by parallelization of library preparation for massive sequencing.

Lundin, Sverker / Stranneheim, Henrik / Pettersson, Erik / Klevebring, Daniel / Lundeberg, Joakim

PloS one

2010 Volume 5, Issue 4, Page(s) e10029

Abstract: Background: Massively parallel sequencing systems continue to improve on data output, while leaving labor-intensive library preparations a potential bottleneck. Efforts are currently under way to relieve the crucial and time-consuming work to prepare ... ...

Abstract	Background: Massively parallel sequencing systems continue to improve on data output, while leaving labor-intensive library preparations a potential bottleneck. Efforts are currently under way to relieve the crucial and time-consuming work to prepare DNA for high-throughput sequencing. Methodology/principal findings: In this study, we demonstrate an automated parallel library preparation protocol using generic carboxylic acid-coated superparamagnetic beads and polyethylene glycol precipitation as a reproducible and flexible method for DNA fragment length separation. With this approach the library preparation for DNA sequencing can easily be adjusted to a desired fragment length. The automated protocol, here demonstrated using the GS FLX Titanium instrument, was compared to the standard manual library preparation, showing higher yield, throughput and great reproducibility. In addition, 12 libraries were prepared and uniquely tagged in parallel, and the distribution of sequence reads between these indexed samples could be improved using quantitative PCR-assisted pooling. Conclusions/significance: We present a novel automated procedure that makes it possible to prepare 36 indexed libraries per person and day, which can be increased to up to 96 libraries processed simultaneously. The yield, speed and robust performance of the protocol constitute a substantial improvement to present manual methods, without the need of extensive equipment investments. The described procedure enables a considerable efficiency increase for small to midsize sequencing centers.
MeSH term(s)	Automation ; Carboxylic Acids ; Chemical Precipitation ; Gene Library ; Polyethylene Glycols ; Sequence Analysis, DNA/instrumentation ; Sequence Analysis, DNA/methods
Chemical Substances	Carboxylic Acids ; Polyethylene Glycols (3WJQ0SDW1A)
Language	English
Publishing date	2010-04-06
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0010029
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Article ; Online: Library preparation and multiplex capture for massive parallel sequencing applications made efficient and easy.

Neiman, Mårten / Sundling, Simon / Grönberg, Henrik / Hall, Per / Czene, Kamila / Lindberg, Johan / Klevebring, Daniel

PloS one

2012 Volume 7, Issue 11, Page(s) e48616

Abstract: During the recent years, rapid development of sequencing technologies and a competitive market has enabled researchers to perform massive sequencing projects at a reasonable cost. As the price for the actual sequencing reactions drops, enabling more ... ...

Abstract	During the recent years, rapid development of sequencing technologies and a competitive market has enabled researchers to perform massive sequencing projects at a reasonable cost. As the price for the actual sequencing reactions drops, enabling more samples to be sequenced, the relative price for preparing libraries gets larger and the practical laboratory work becomes complex and tedious. We present a cost-effective strategy for simplified library preparation compatible with both whole genome- and targeted sequencing experiments. An optimized enzyme composition and reaction buffer reduces the number of required clean-up steps and allows for usage of bulk enzymes which makes the whole process cheap, efficient and simple. We also present a two-tagging strategy, which allows for multiplex sequencing of targeted regions. To prove our concept, we have prepared libraries for low-pass sequencing from 100 ng DNA, performed 2-, 4- and 8-plex exome capture and a 96-plex capture of a 500 kb region. In all samples we see a high concordance (>99.4%) of SNP calls when comparing to commercially available SNP-chip platforms.
MeSH term(s)	Exome/genetics ; Gene Library ; Genome, Human/genetics ; Heterozygote ; High-Throughput Nucleotide Sequencing/methods ; Humans ; Phosphorylation ; Polymorphism, Single Nucleotide/genetics
Language	English
Publishing date	2012-11-05
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0048616
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Article ; Online: Analysis of transcript and protein overlap in a human osteosarcoma cell line

Emanuelsson Olof / Lundberg Emma / Fagerberg Linn / Klevebring Daniel / Uhlén Mathias / Lundeberg Joakim

BMC Genomics, Vol 11, Iss 1, p

2010 Volume 684

Abstract: Abstract Background An interesting field of research in genomics and proteomics is to compare the overlap between the transcriptome and the proteome. Recently, the tools to analyse gene and protein expression on a whole-genome scale have been improved, ... ...

Abstract	Abstract Background An interesting field of research in genomics and proteomics is to compare the overlap between the transcriptome and the proteome. Recently, the tools to analyse gene and protein expression on a whole-genome scale have been improved, including the availability of the new generation sequencing instruments and high-throughput antibody-based methods to analyze the presence and localization of proteins. In this study, we used massive transcriptome sequencing (RNA-seq) to investigate the transcriptome of a human osteosarcoma cell line and compared the expression levels with in situ protein data obtained in-situ from antibody-based immunohistochemistry (IHC) and immunofluorescence microscopy (IF). Results A large-scale analysis based on 2749 genes was performed, corresponding to approximately 13% of the protein coding genes in the human genome. We found the presence of both RNA and proteins to a large fraction of the analyzed genes with 60% of the analyzed human genes detected by all three methods. Only 34 genes (1.2%) were not detected on the transcriptional or protein level with any method. Our data suggest that the majority of the human genes are expressed at detectable transcript or protein levels in this cell line. Since the reliability of antibodies depends on possible cross-reactivity, we compared the RNA and protein data using antibodies with different reliability scores based on various criteria, including Western blot analysis. Gene products detected in all three platforms generally have good antibody validation scores, while those detected only by antibodies, but not by RNA sequencing, generally consist of more low-scoring antibodies. Conclusion This suggests that some antibodies are staining the cells in an unspecific manner, and that assessment of transcript presence by RNA-seq can provide guidance for validation of the corresponding antibodies.
Keywords	Genetics ; QH426-470 ; Biology (General) ; QH301-705.5 ; Science ; Q ; DOAJ:Genetics ; DOAJ:Biology ; DOAJ:Biology and Life Sciences
Subject code	612
Language	English
Publishing date	2010-12-01T00:00:00Z
Publisher	BioMed Central
Document type	Article ; Online
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Article ; Online: Automation of cDNA synthesis and labelling improves reproducibility.

Klevebring, Daniel / Gry, Marcus / Lindberg, Johan / Eidefors, Anna / Lundeberg, Joakim

Journal of biomedicine & biotechnology

2009 Volume 2009, Page(s) 396808

Abstract: Background: Several technologies, such as in-depth sequencing and microarrays, enable large-scale interrogation of genomes and transcriptomes. In this study, we asses reproducibility and throughput by moving all laboratory procedures to a robotic ... ...

Abstract	Background: Several technologies, such as in-depth sequencing and microarrays, enable large-scale interrogation of genomes and transcriptomes. In this study, we asses reproducibility and throughput by moving all laboratory procedures to a robotic workstation, capable of handling superparamagnetic beads. Here, we describe a fully automated procedure for cDNA synthesis and labelling for microarrays, where the purification steps prior to and after labelling are based on precipitation of DNA on carboxylic acid-coated paramagnetic beads. Results: The fully automated procedure allows for samples arrayed on a microtiter plate to be processed in parallel without manual intervention and ensuring high reproducibility. We compare our results to a manual sample preparation procedure and, in addition, use a comprehensive reference dataset to show that the protocol described performs better than similar manual procedures. Conclusions: We demonstrate, in an automated gene expression microarray experiment, a reduced variance between replicates, resulting in an increase in the statistical power to detect differentially expressed genes, thus allowing smaller differences between samples to be identified. This protocol can with minor modifications be used to create cDNA libraries for other applications such as in-depth analysis using next-generation sequencing technologies.
MeSH term(s)	Automation/methods ; DNA, Complementary/biosynthesis ; Fluorescent Dyes/metabolism ; Humans ; Microspheres ; Reproducibility of Results ; Staining and Labeling/methods
Chemical Substances	DNA, Complementary ; Fluorescent Dyes
Language	English
Publishing date	2009-10-15
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2052552-7
ISSN	1110-7251 ; 1110-7243
ISSN (online)	1110-7251
ISSN	1110-7243
DOI	10.1155/2009/396808
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