1. |
- Danielsson, Frida, et al.
(author)
-
Majority of differentially expressed genes are down-regulated during malignant transformation in a four-stage model
- 2013
-
In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 110:17, s. 6853-6858
-
Journal article (peer-reviewed)abstract
- The transformation of normal cells to malignant, metastatic tumor cells is a multistep process caused by the sequential acquirement of genetic changes. To identify these changes, we compared the transcriptomes and levels and distribution of proteins in a four-stage cell model of isogenically matched normal, immortalized, transformed, and metastatic human cells, using deep transcriptome sequencing and immunofluorescence microscopy. The data show that similar to 6% (n = 1,357) of the human protein-coding genes are differentially expressed across the stages in the model. Interestingly, the majority of these genes are down-regulated, linking malignant transformation to dedifferentiation. The up-regulated genes are mainly components that control cellular proliferation, whereas the down-regulated genes consist of proteins exposed on or secreted from the cell surface. As many of the identified gene products control basic cellular functions that are defective in cancers, the data provide candidates for follow-up studies to investigate their functional roles in tumor formation. When we further compared the expression levels of four of the identified proteins in clinical cancer cohorts, similar differences were observed between benign and cancer cells, as in the cell model. This shows that this comprehensive demonstration of the molecular changes underlying malignant transformation is a relevant model to study the process of tumor formation.
|
|
2. |
- Fagerberg, Linn, et al.
(author)
-
Contribution of antibody-based protein profiling to the human chromosome-centric proteome project (C-HPP)
- 2013
-
In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 12:6, s. 2439-2448
-
Journal article (peer-reviewed)abstract
- A gene-centric Human Proteome Project has been proposed to characterize the human protein-coding genes in a chromosome-centered manner to understand human biology and disease. Here, we report on the protein evidence for all genes predicted from the genome sequence based on manual annotation from literature (UniProt), antibody-based profiling in cells, tissues and organs and analysis of the transcript profiles using next generation sequencing in human cell lines of different origins. We estimate that there is good evidence for protein existence for 69% (n = 13985) of the human protein-coding genes, while 23% have only evidence on the RNA level and 7% still lack experimental evidence. Analysis of the expression patterns shows few tissue-specific proteins and approximately half of the genes expressed in all the analyzed cells. The status for each gene with regards to protein evidence is visualized in a chromosome-centric manner as part of a new version of the Human Protein Atlas (www.proteinatlas.org).
|
|
3. |
- Georgoudaki, Anna-Maria, et al.
(author)
-
Reprogramming Tumor-Associated Macrophages by Antibody Targeting Inhibits Cancer Progression and Metastasis
- 2016
-
In: Cell Reports. - : Elsevier BV. - 2211-1247. ; 15:9, s. 2000-2011
-
Journal article (peer-reviewed)abstract
- Tumors are composed of multiple cell types besides the tumor cells themselves, including innate immune cells such as macrophages. Tumor-associated macrophages (TAMs) are a heterogeneous population of myeloid cells present in the tumor microenvironment (TME). Here, they contribute to immunosuppression, enabling the establishment and persistence of solid tumors as well as metastatic dissemination. We have found that the pattern recognition scavenger receptor MARCO defines a subtype of suppressive TAMs and is linked to clinical outcome. An anti-MARCO monoclonal antibody was developed, which induces anti-tumor activity in breast and colon carcinoma, as well as in melanoma models through reprogramming-TAM-populations to a pro-inflammatory phenotype and increasing tumor immunogenicity. This anti-tumor activity is dependent on the inhibitory Fc-receptor, Fc gamma RIIB, and also enhances the efficacy of checkpoint therapy. These results demonstrate that immunotherapies using antibodies designed to modify myeloid cells of the TME represent a promising mode of cancer treatment.
|
|
4. |
- Klevebring, Daniel, 1981-, et al.
(author)
-
Analysis of transcript and protein overlap in a human osteosarcoma cell line
- 2010
-
In: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 11:1, s. 684-
-
Journal article (peer-reviewed)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.
|
|
5. |
- Klevebring, Daniel, 1981-, et al.
(author)
-
Automation of cDNA Synthesis and Labelling Improves Reproducibility
- 2009
-
In: Journal of Biomedicine and Biotechnology. - : Hindawi Limited. - 1110-7243 .- 1110-7251. ; 2009, s. 396808-
-
Journal article (peer-reviewed)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.
|
|
6. |
- Klevebring, Daniel, et al.
(author)
-
Exome sequencing of contralateral breast cancer identifies metastatic disease
- 2015
-
In: Breast Cancer Research and Treatment. - Stockholm : Karolinska Institutet, Dept of Medical Epidemiology and Biostatistics. - 0167-6806 .- 1573-7217.
-
Journal article (peer-reviewed)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.
|
|
7. |
- Klevebring, Daniel, 1981-, et al.
(author)
-
Genome-wide profiling of Populus small RNAs
- 2009
-
In: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 10, s. Article number 620-
-
Journal article (peer-reviewed)abstract
- Background: Short RNAs, and in particular microRNAs, are important regulators of gene expression both within defined regulatory pathways and at the epigenetic scale. We investigated the short RNA (sRNA) population (18-24 nt) of the transcriptome of green leaves from the sequenced Populus trichocarpa using a concatenation strategy in combination with 454 sequencing. Results: The most abundant size class of sRNAs were 24 nt and these were generally associated with a number of classes of retrotransposons and repetitive elements. Some repetitive elements were also associated with 22 nt RNAs. We identified an sRNA hot-spot on chromosome 19, overlapping a region containing both the sex-determining loci and a major cluster of NBS-LRR genes. A number of phased siRNA loci were identified, a subset of which are predicted to target PPR and NBS-LRR disease resistance genes, classes of genes that have been significantly expanded in Populus. Additional loci enriched for sRNA production were identified. We identified 15 novel predicted microRNAs (miRNAs), including miRNA∗ sequences, and identified a novel locus that may encode a dual miRNA or a miRNA and short interfering RNAs (siRNAs). Conclusions: The short RNA population of P. trichocarpa is at least as complex as that of Arabidopsis. We provide a first genome-wide view of short RNA production for P. trichocarpa and identify new, non-conserved miRNAs.
|
|
8. |
- Klevebring, Daniel, 1981-, et al.
(author)
-
In-depth transcriptome analysis reveals novel TARs and prevalent antisense transcription in human cell lines.
-
Other publication (other academic/artistic)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 also investigate the correlation between RNA-seq data and microarray data and conclude that the correlation is dependant on gene length such that longer genes show a better correlation.
|
|
9. |
- Klevebring, Daniel, et al.
(author)
-
In-Depth Transcriptome Analysis Reveals Novel TARs and Prevalent Antisense Transcription in Human Cell Lines
- 2010
-
In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 5:3, s. e9762-
-
Journal article (peer-reviewed)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.
|
|
10. |
- Klevebring, Daniel, 1981-
(author)
-
On Transcriptome Sequencing
- 2009
-
Doctoral thesis (other academic/artistic)abstract
- This thesis is about the use of massive DNA sequencing to investigate the transcriptome. During recent decades, several studies have made it clear that the transcriptome comprises a more complex set of biochemical machinery than was previously believed. The majority of the genome can be expressed as transcripts; and overlapping and antisense transcription is widespread. New technologies for the interroga- tion of nucleic acids have made it possible to investigate such cellular phenomena in much greater detail than ever before. For each application, special requirements need to be met. The work presented in this thesis focuses on the transcrip- tome and the development of technology for its analysis. In paper I, we report our development of an automated approach for sample preparation. The procedure was benchmarked against a publicly available reference data set, and we note that our approach outperformed similar manual procedures in terms of reproducibility. In the work reported in papers II-IV, we used different massive sequencing technologies to investigate the transcriptome. In paper II we describe a concatemerization approach that increased throughput by 65% using 454 sequencing,and we identify classes of transcripts not previously described in Populus. Papers III and IV both report studies based on SOLiD sequencing. In the former, we investigated transcripts and proteins for 13% of the human gene and detected a massive overlap for the upper 50% transcriptional levels. In the work described in paper IV, we investigated transcription in non-genic regions of the genome and detected expression from a high number of previ- ously unknown loci.
|
|
11. |
- Lindberg, Johan, et al.
(author)
-
The Mitochondrial and Autosomal Mutation Landscapes of Prostate Cancer
- 2013
-
In: European Urology. - : Elsevier BV. - 0302-2838 .- 1873-7560. ; 63:4, s. 702-708
-
Journal article (peer-reviewed)abstract
- Background: Prostate cancer (PCa) is the most common cancer in men. PCa is strongly age associated; low death rates in surveillance cohorts call into question the widespread use of surgery, which leads to overtreatment and a reduction in quality of life. There is a great need to increase the understanding of tumor characteristics in the context of disease progression. Objective: To perform the first multigenome investigation of PCa through analysis of both autosomal and mitochondrial DNA, and to integrate exome sequencing data, and RNA sequencing and copy-number alteration (CNA) data to investigate how various different tumor characteristics, commonly analyzed separately, are interconnected. Design, setting, and participants: Exome sequencing was applied to 64 tumor samples from 55 PCa patients with varying stage and grade. Integrated analysis was performed on a core set of 50 tumors from which exome sequencing, CNA, and RNA sequencing data were available. Outcome measurements and statistical analysis: Genes, mutated at a significantly higher rate relative to a genomic background, were identified. In addition, mitochondrial and autosomal mutation rates were correlated to CNAs and proliferation, assessed as a cell cycle gene expression signature. Results and limitations: Genes not previously reported to be significantly mutated in PCa, such as cell division cycle 27 homolog (Saccharomyces cerevisiae) (CDC27), myeloid/lymphoid or mixed-lineage leukemia 3 (MLL3), lysine (K)-specific demethylase 6A (KDM6A), and kinesin family member 5A (KIF5A) were identified. The mutation rate in the mitochondrial genome was 55 times higher than that of the autosomes. Multilevel analysis demonstrated a tight correlation between high reactive-oxygen exposure, chromosomal damage, high proliferation, and in parallel, a transition from multiclonal indolent primary PCa to monoclonal aggressive disease. As we only performed targeted sequence analysis; copy-number neutral rearrangements recently described for PCa were not accounted for. Conclusions: The mitochondrial genome displays an elevated mutation rate compared to the autosomal chromosomes. By integrated analysis, we demonstrated that different tumor characteristics are interconnected, providing an increased understanding of PCa etiology. (C) 2012 European Association of Urology. Published by Elsevier B. V. All rights reserved.
|
|
12. |
- Lundberg, Emma, et al.
(author)
-
Defining the transcriptome and proteome in three functionally different human cell lines
- 2010
-
In: Molecular Systems Biology. - : EMBO. - 1744-4292 .- 1744-4292. ; 6, s. 450-
-
Journal article (peer-reviewed)abstract
- An essential question in human biology is how cells and tissues differ in gene and protein expression and how these differences delineate specific biological function. Here, we have performed a global analysis of both mRNA and protein levels based on sequence-based transcriptome analysis (RNA-seq), SILAC-based mass spectrometry analysis and antibody-based confocal microscopy. The study was performed in three functionally different human cell lines and based on the global analysis, we estimated the fractions of mRNA and protein that are cell specific or expressed at similar/different levels in the cell lines. A highly ubiquitous RNA expression was found with > 60% of the gene products detected in all cells. The changes of mRNA and protein levels in the cell lines using SILAC and RNA ratios show high correlations, even though the genome-wide dynamic range is substantially higher for the proteins as compared with the transcripts. Large general differences in abundance for proteins from various functional classes are observed and, in general, the cell-type specific proteins are low abundant and highly enriched for cell-surface proteins. Thus, this study shows a path to characterize the transcriptome and proteome in human cells from different origins.
|
|
13. |
- Lundin, Sverker, et al.
(author)
-
Increased Throughput by Parallelization of Library Preparation for Massive Sequencing
- 2010
-
In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 5:3, s. e10029-
-
Journal article (peer-reviewed)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.
|
|
14. |
- Mer, Arvind Singh, et al.
(author)
-
Expression levels of long non-coding RNAs are prognostic for AML outcome
- 2018
-
In: Journal of Hematology & Oncology. - : BIOMED CENTRAL LTD. - 1756-8722. ; 11
-
Journal article (peer-reviewed)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.
|
|
15. |
- Mer, Arvind Singh, et al.
(author)
-
Study design requirements for RNA sequencing-based breast cancer diagnostics
- 2016
-
In: Scientific Reports. - Stockholm : Karolinska Institutet, Dept of Medical Epidemiology and Biostatistics. - 2045-2322.
-
Journal article (peer-reviewed)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.
|
|
16. |
- Rantalainen, Mattias, et al.
(author)
-
Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers
- 2016
-
In: Scientific Reports. - Stockholm : Karolinska Institutet, Dept of Medical Epidemiology and Biostatistics. - 2045-2322.
-
Journal article (peer-reviewed)abstract
- Sequencing-based breast cancer diagnostics have the potential to replace routine biomarkers and provide molecular characterization that enable personalized precision medicine. Here we investigate the concordance between sequencing-based and routine diagnostic biomarkers and to what extent tumor sequencing contributes clinically actionable information. We applied DNA- and RNA-sequencing to characterize tumors from 307 breast cancer patients with replication in up to 739 patients. We developed models to predict status of routine biomarkers (ER, HER2,Ki-67, histological grade) from sequencing data. Non-routine biomarkers, including mutations in BRCA1, BRCA2 and ERBB2(HER2), and additional clinically actionable somatic alterations were also investigated. Concordance with routine diagnostic biomarkers was high for ER status (AUC = 0.95;AUC(replication) = 0.97) and HER2 status (AUC = 0.97;AUC(replication) = 0.92). The transcriptomic grade model enabled classification of histological grade 1 and histological grade 3 tumors with high accuracy (AUC = 0.98;AUC(replication) = 0.94). Clinically actionable mutations in BRCA1, BRCA2 and ERBB2(HER2) were detected in 5.5% of patients, while 53% had genomic alterations matching ongoing or concluded breast cancer studies. Sequencing-based molecular profiling can be applied as an alternative to histopathology to determine ER and HER2 status, in addition to providing improved tumor grading and clinically actionable mutations and molecular subtypes. Our results suggest that sequencing-based breast cancer diagnostics in a near future can replace routine biomarkers
|
|
17. |
- Rimini, Rebecca, et al.
(author)
-
Validation of serum protein profiles by a dual antibody array approach
- 2009
-
In: Journal of Proteomics. - : Elsevier BV. - 1874-3919 .- 1876-7737. ; 73:2, s. 252-266
-
Journal article (peer-reviewed)abstract
- In recent years, affinity-based technologies have become important tools for serum profiling to uncover protein expression patterns linked to disease state or therapeutic effects. In this study, we describe a path towards the production of an antibody microarray to allow protein profiling of biotinylated human serum samples with reproducible sensitivity in the picomolar range. With the availability of growing numbers of affinity reagents, protein profiles are to be validated in efficient manners and we describe a cross-platform strategy based on data concordance with a suspension bead array to interrogate the identical set of antibodies with the same cohort of serum samples. Comparative analysis enabled to screen for high-performing antibodies, which were displaying consistent results across the two platforms and targeting known serum components. Moreover, data processing methods such as sample referencing and normalization were evaluated for their effects on inter-platform agreement. Our work suggests that mutual validation of protein expression profiles using alternative microarray platforms holds great potential in becoming an important and valuable component in affinity-based high-throughput proteomic screenings as it allows to narrow down the number of discovered targets prior to orthogonal, uniplexed validation approaches.
|
|
18. |
- Uhlén, Mathias, et al.
(author)
-
Antibody-based Protein Profiling of the Human Chromosome 21
- 2012
-
In: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 11:3
-
Journal article (peer-reviewed)abstract
- The Human Proteome Project has been proposed to create a knowledge-based resource based on a systematical mapping of all human proteins, chromosome by chromosome, in a gene-centric manner. With this background, we here describe the systematic analysis of chromosome 21 using an antibody-based approach for protein profiling using both confocal microscopy and immunohistochemistry, complemented with transcript profiling using next generation sequencing data. We also describe a new approach for protein isoform analysis using a combination of antibody-based probing and isoelectric focusing. The analysis has identified several genes on chromosome 21 with no previous evidence on the protein level, and the isoform analysis indicates that a large fraction of human proteins have multiple isoforms. A chromosome-wide matrix is presented with status for all chromosome 21 genes regarding subcellular localization, tissue distribution, and molecular characterization of the corresponding proteins. The path to generate a chromosome-specific resource, including integrated data from complementary assay platforms, such as mass spectrometry and gene tagging analysis, is discussed.
|
|
19. |
- Wang, Mei, et al.
(author)
-
Determining breast cancer histological grade from RNA-sequencing data
- 2016
-
In: Breast Cancer Research. - Stockholm : Karolinska Institutet, Dept of Medical Epidemiology and Biostatistics. - 1465-542X.
-
Journal article (peer-reviewed)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.
|
|
20. |
- Wang, Mei, et al.
(author)
-
Development and Validation of a Novel RNA Sequencing-Based Prognostic Score for Acute Myeloid Leukemia
- 2018
-
In: Journal of the National Cancer Institute. - : OXFORD UNIV PRESS INC. - 0027-8874 .- 1460-2105. ; 110:10, s. 1094-1101
-
Journal article (peer-reviewed)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.
|
|