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Edlund, Karolina
Publications (10 of 12) Show all publications
Fagerberg, L., Hallström, B. M., Oksvold, P., Kampf, C., Djureinovic, D., Odeberg, J., . . . Uhlén, M. (2014). Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics. Molecular & Cellular Proteomics, 13(2), 397-406
Open this publication in new window or tab >>Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics
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2014 (English)In: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 13, no 2, p. 397-406Article in journal (Refereed) Published
Abstract [en]

Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease. Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody-based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to ∼80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-221324 (URN)10.1074/mcp.M113.035600 (DOI)000331369000002 ()24309898 (PubMedID)
Available from: 2014-03-28 Created: 2014-03-28 Last updated: 2017-12-05Bibliographically approved
Kampf, C., Mardinoglu, A., Fagerberg, L., Hallstrom, B. M., Edlund, K., Lundberg, E., . . . Uhlen, M. (2014). The human liver-specific proteome defined by transcriptomics and antibody-based profiling. The FASEB Journal, 28(7), 2901-2914
Open this publication in new window or tab >>The human liver-specific proteome defined by transcriptomics and antibody-based profiling
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2014 (English)In: The FASEB Journal, ISSN 0892-6638, E-ISSN 1530-6860, Vol. 28, no 7, p. 2901-2914Article in journal (Refereed) Published
Abstract [en]

Human liver physiology and the genetic etiology of the liver diseases can potentially be elucidated through the identification of proteins with enriched expression in the liver. Here, we combined data from RNA sequencing (RNA-Seq) and antibody-based immunohistochemistry across all major human tissues to explore the human liver proteome with enriched expression, as well as the cell type-enriched expression in hepatocyte and bile duct cells. We identified in total 477 protein-coding genes with elevated expression in the liver: 179 genes have higher expression as compared to all the other analyzed tissues; 164 genes have elevated transcript levels in the liver shared with at least one other tissue type; and an additional 134 genes have a mild level of increased expression in the liver. We identified the precise localization of these proteins through antibody-based protein profiling and the subcellular localization of these proteins through immunofluorescent-based profiling. We also identified the biological processes and metabolic functions associated with these proteins, investigated their contribution in the occurrence of liver diseases, and identified potential targets for their treatment. Our study demonstrates the use of RNA-Seq and antibody-based immunohistochemistry for characterizing the human liver proteome, as well as the use of tissue-specific proteins in identification of novel drug targets and discovery of biomarkers.

Keywords
immunohistochemistry, RNA sequencing, metabolism
National Category
Cell and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-228968 (URN)10.1096/fj.14-250555 (DOI)000337949400015 ()
Available from: 2014-07-25 Created: 2014-07-24 Last updated: 2018-01-11Bibliographically approved
Botling, J., Edlund, K., Lohr, M., Hellwig, B., Holmberg, L., Lambe, M., . . . Micke, P. (2013). Biomarker discovery in non-small cell lung cancer: integrating gene expression profiling, meta-analysis and tissue microarray validation. Clinical Cancer Research, 19(1), 194-204
Open this publication in new window or tab >>Biomarker discovery in non-small cell lung cancer: integrating gene expression profiling, meta-analysis and tissue microarray validation
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2013 (English)In: Clinical Cancer Research, ISSN 1078-0432, E-ISSN 1557-3265, Vol. 19, no 1, p. 194-204Article in journal (Refereed) Published
Abstract [en]

Background:

Global gene expression profiling has been widely used in lung cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis and therapy response. So far, the value of these multi-gene signatures in clinical practice is unclear and the biological importance of individual genes is difficult to assess as the published signatures virtually do not overlap

Methods:

Here we describe a novel single institute cohort, including 196 non-small lung cancers (NSCLC) with clinical information and long-term follow-up. Gene expression array data was used as a training set to screen for single genes with prognostic impact. The top 450 probe sets identified using a univariate Cox regression model (significance level p<0.01) were tested in a meta-analysis including five publicly available independent lung cancer cohorts (n=860).

RESULTS:

The meta-analysis revealed 14 genes that were significantly associated with survival (p<0.001) with a false discovery rate <1%. The prognostic impact of one of these genes, the cell adhesion molecule 1 (CADM1), was confirmed by use of immunohistochemistry on tissue microarrays from two independent NSCLC cohorts, altogether including 617 NSCLC samples. Low CADM1 protein expression was significantly associated with shorter survival, with particular influence in the adenocarcinoma patient subgroup.

CONCLUSIONS:

Using a novel NSCLC cohort together with a meta-analysis validation approach, we have identified a set of single genes with independent prognostic impact. One of these genes, CADM1, was further established as an immunohistochemical marker with a potential application in clinical diagnostics.

National Category
Clinical Laboratory Medicine
Research subject
Pathology
Identifiers
urn:nbn:se:uu:diva-183399 (URN)10.1158/1078-0432.CCR-12-1139 (DOI)000313051100021 ()23032747 (PubMedID)
Available from: 2012-10-25 Created: 2012-10-25 Last updated: 2018-02-01Bibliographically approved
Planck, M., Edlund, K., Botling, J., Micke, P., Isaksson, S. & Staaf, J. (2013). Genomic and Transcriptional Alterations in Lung Adenocarcinoma in Relation to EGFR and KRAS Mutation Status. PLoS ONE, 8(10), e78614
Open this publication in new window or tab >>Genomic and Transcriptional Alterations in Lung Adenocarcinoma in Relation to EGFR and KRAS Mutation Status
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2013 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, no 10, p. e78614-Article in journal (Refereed) Published
Abstract [en]

Introduction: In lung adenocarcinoma, the mutational spectrum is dominated by EGFR and KRAS mutations. Improved knowledge about genomic and transcriptional alterations in and between mutation-defined subgroups may identify genes involved in disease development or progression. Methods: Genomic profiles from 457 adenocarcinomas, including 113 EGFR-mutated, 134 KRAS-mutated and 210 EGFR and KRAS-wild type tumors (EGFRwt/KRASwt), and gene expression profiles from 914 adenocarcinomas, including 309 EGFR-mutated, 192 KRAS-mutated, and 413 EGFRwt/KRASwt tumors, were assembled from different repositories. Genomic and transcriptional differences between the three mutational groups were analyzed by both supervised and unsupervised methods. Results: EGFR-mutated adenocarcinomas displayed a larger number of copy number alterations and recurrent amplifications, a higher fraction of total loss-of-heterozygosity, higher genomic complexity, and a more distinct expression pattern than EGFR-wild type adenocarcinomas. Several of these differences were also consistent when the three mutational groups were stratified by stage, gender and smoking status. Specific copy number alterations were associated with mutation status, predominantly including regions of gain with the highest frequency in EGFR-mutated tumors. Differential regions included both large and small regions of gain on 1p, 5q34-q35.3, 7p, 7q11.21, 12p12.1, 16p, and 21q, and losses on 6q16.3-q21, 8p, and 9p, with 20-40% frequency differences between the mutational groups. Supervised gene expression analyses identified 96 consistently differentially expressed genes between the mutational groups, and together with unsupervised analyses these analyses highlighted the difficulty in broadly resolving the three mutational groups into distinct transcriptional entities. Conclusions: We provide a comprehensive overview of the genomic and transcriptional landscape in lung adenocarcinoma stratified by EGFR and KRAS mutations. Our analyses suggest that the overall genomic and transcriptional landscape of lung adenocarcinoma is affected, but only to a minor extent, by EGFR and KRAS mutation status.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-211447 (URN)10.1371/journal.pone.0078614 (DOI)000326152300073 ()
Available from: 2013-11-27 Created: 2013-11-25 Last updated: 2018-02-01Bibliographically approved
Grundberg, I., Kiflemariam, S., Mignardi, M., Imgenberg-Kreuz, J., Edlund, K., Micke, P., . . . Nilsson, M. (2013). In situ mutation detection and visualization of intratumor heterogeneity for cancer research and diagnostics. Oncotarget, 4(12), 2407-2418
Open this publication in new window or tab >>In situ mutation detection and visualization of intratumor heterogeneity for cancer research and diagnostics
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2013 (English)In: Oncotarget, ISSN 1949-2553, Vol. 4, no 12, p. 2407-2418Article in journal (Refereed) Published
Abstract [en]

Current assays for somatic mutation analysis are based on extracts from tissue sections that often contain morphologically heterogeneous neoplastic regions with variable contents of normal stromal and inflammatory cells, obscuring the results of the assays. We have developed an RNA-based in situ mutation assay that targets oncogenic mutations in a multiplex fashion that resolves the heterogeneity of the tissue sample. Activating oncogenic mutations are targets for a new generation of cancer drugs. For anti-EGFR therapy prediction, we demonstrate reliable in situ detection of KRAS mutations in codon 12 and 13 in colon and lung cancers in three different types of routinely processed tissue materials. High-throughput screening of KRAS mutation status was successfully performed on a tissue microarray. Moreover, we show how the patterns of expressed mutated and wild-type alleles can be studied in situ in tumors with complex combinations of mutated EGFR, KRAS and TP53. This in situ method holds great promise as a tool to investigate the role of somatic mutations during tumor progression and for prediction of response to targeted therapy.

National Category
Basic Medicine
Research subject
Pathology
Identifiers
urn:nbn:se:uu:diva-222138 (URN)24280411 (PubMedID)
Note

Botling och Nilsson har delat sista författarskap.

Available from: 2014-04-08 Created: 2014-04-08 Last updated: 2018-02-01Bibliographically approved
Lohr, M., Edlund, K., Botling, J., Hammad, S., Hellwig, B., Othman, A., . . . Micke, P. (2013). The prognostic relevance of tumour-infiltrating plasma cells and immunoglobulin kappa C indicates an important role of the humoral immune response in non-small cell lung cancer. Cancer Letters, 333(2), 222-228
Open this publication in new window or tab >>The prognostic relevance of tumour-infiltrating plasma cells and immunoglobulin kappa C indicates an important role of the humoral immune response in non-small cell lung cancer
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2013 (English)In: Cancer Letters, ISSN 0304-3835, E-ISSN 1872-7980, Vol. 333, no 2, p. 222-228Article in journal (Refereed) Published
Abstract [en]

A prognostic impact of immunoglobulin kappa C (IGKC) expression has been described in cancer. We analysed the influence of B-cell and plasma cell markers, as well as IGKC expression, in non-small lung cancer (NSCLC) using immunohistochemistry on a tissue microarray. IGKC protein expression was independently associated with longer survival, with particular impact in the adenocarcinoma subgroup. Moreover, a correlation was seen with CD138+ cells, but not with CD20. CD138 expression revealed a comparable association with survival. In conclusion, IGKC expression in stroma–infiltrating plasma cells is a prognostic marker in NSCLC, supporting emerging treatment concepts that exploit the humoral immune response.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-181908 (URN)10.1016/j.canlet.2013.01.036 (DOI)000318838700011 ()
Available from: 2012-10-01 Created: 2012-10-01 Last updated: 2018-02-01Bibliographically approved
Schmidt, M., Hellwig, B., Hammad, S., Othman, A., Lohr, M., Chen, Z., . . . Hengstler, J. G. (2012). A comprehensive analysis of human gene expression profiles identifies stromal immunoglobulin kappa C as a compatible prognostic marker in human solid tumors. Clinical Cancer Research, 18(9), 2695-2703
Open this publication in new window or tab >>A comprehensive analysis of human gene expression profiles identifies stromal immunoglobulin kappa C as a compatible prognostic marker in human solid tumors
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2012 (English)In: Clinical Cancer Research, ISSN 1078-0432, E-ISSN 1557-3265, Vol. 18, no 9, p. 2695-2703Article in journal (Refereed) Published
Abstract [en]

PURPOSE:

Although the central role of the immune system for tumor prognosis is generally accepted a single robust marker is not yet available.

EXPERIMENTAL DESIGN:

Based on ROC (receiver operating characteristic) analyses robust markers were identified from a 60 gene B-cell derived metagene and analyzed in gene expression profiles of 1810 breast cancer, 1056 non-small cell lung cancer, 513 colorectal and 426 ovarian cancer patients. Protein and RNA levels were examined in paraffin embedded tissue of 330 breast cancer patients. The cell types were identified using immunohistochemical co-staining and confocal fluorescence microscopy.

RESULTS:

We identified immunoglobulin kappa C (IGKC) which as a single marker is similarly predictive and prognostic as the entire B-cell metagene. IGKC was consistently associated with metastasis free survival across different molecular subtypes in node-negative breast cancer (n=965) and predicted response to anthracycline-based neoadjuvant chemotherapy (n=845) [P less than 0.001]. In addition, IGKC gene expression was prognostic in non-small cell lung cancer and colorectal cancer. No association was observed in ovarian cancer. IGKC protein expression was significantly associated with survival in paraffin embedded tissues of 330 breast cancer patients. Tumor infiltrating plasma cells were identified as the source of IGKC expression

CONCLUSION:

Our findings provide IGKC as a novel diagnostic marker for risk stratification in human cancer and support concepts to exploit the humoral immune response for anti-cancer therapy. It could be validated in several independent cohorts and performed similarly well in RNA from fresh frozen as well as from paraffin tissue and on protein level by immunostaining.

National Category
Clinical Laboratory Medicine
Research subject
Pathology
Identifiers
urn:nbn:se:uu:diva-169734 (URN)10.1158/1078-0432.CCR-11-2210 (DOI)000304249200030 ()22351685 (PubMedID)
Available from: 2012-03-05 Created: 2012-03-05 Last updated: 2018-02-01Bibliographically approved
Edlund, K., Lindskog, C., Saito, A., Berglund, A., Pontén, F., Göransson-Kultima, H., . . . Micke, P. (2012). CD99 is a novel prognostic stromal marker in non-small cell lung cancer. International Journal of Cancer, 131(10), 2264-2273
Open this publication in new window or tab >>CD99 is a novel prognostic stromal marker in non-small cell lung cancer
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2012 (English)In: International Journal of Cancer, ISSN 0020-7136, E-ISSN 1097-0215, Vol. 131, no 10, p. 2264-2273Article in journal (Refereed) Published
Abstract [en]

The complex interaction between cancer cells and the microenvironment plays an essential role in all stages of tumourigenesis. Despite the significance of this interplay, alterations in protein composition underlying tumour-stroma interactions are largely unknown. The aim of this study was to identify stromal proteins with clinical relevance in non-small cell lung cancer (NSCLC). A list encompassing 203 stromal candidate genes was compiled based on gene expression array data and available literature. The protein expression of these genes in human NSCLC was screened using the Human Protein Atlas. Twelve proteins were selected that showed a differential stromal staining pattern (BGN, CD99, DCN, EMILIN1, FBN1, PDGFRB, PDLIM5, POSTN, SPARC, TAGLN, TNC, VCAN). The corresponding antibodies were applied on tissue microarrays, including 190 NSCLC samples, and stromal staining was correlated with clinical parameters. Higher stromal expression of CD99 was associated with better prognosis in the univariate (p=0.037) and multivariate (p=0.039) analysis. The association was independent from the proportion of tumour stroma, the fraction of inflammatory cells, and clinical and pathological parameters like stage, performance status and tumour histology. The prognostic impact of stromal CD99 protein expression was confirmed in an independent cohort of 240 NSCLC patients (p=0.008). Furthermore, double-staining confocal fluorescence microscopy showed that CD99 was expressed in stromal lymphocytes as well as in cancer associated fibroblasts. Based on a comprehensive screening strategy the membrane protein CD99 was identified as a novel stromal factor with clinical relevance. The results support the concept that stromal properties have an important impact on tumour progression.

National Category
Clinical Laboratory Medicine
Research subject
Pathology
Identifiers
urn:nbn:se:uu:diva-170991 (URN)10.1002/ijc.27518 (DOI)000309185300007 ()22392539 (PubMedID)
Note

Karolina Edlund and Cecilia Lindskog are shared first authors.

Available from: 2012-03-14 Created: 2012-03-14 Last updated: 2018-02-01
Mattsson, J. S., Imgenberg-Kreuz, J., Edlund, K., Botling, J. & Micke, P. (2012). Consistent mutation status within histologically heterogeneous lung cancer lesions. Histopathology, 61(4), 744-748
Open this publication in new window or tab >>Consistent mutation status within histologically heterogeneous lung cancer lesions
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2012 (English)In: Histopathology, ISSN 0309-0167, E-ISSN 1365-2559, Vol. 61, no 4, p. 744-748Article in journal (Refereed) Published
Abstract [en]

Aims: Activating epidermal growth factor receptor (EGFR) and KRAS mutations characterize molecular subgroups of non-small-cell lung cancer (NSCLC) with a strong predictive value for response to EGFR inhibitor therapy. However, the temporal occurrence and clonal stability of these mutations during the course of cancer progression are debated. The aim of this study was to characterize the presence of EGFR and KRAS mutations in histologically different areas of primary NSCLC lesions. Methods and results: Formalin-fixed paraffin-embedded cancer specimens from six cases with EGFR mutations and five cases with KRAS mutations were selected from a pool of primary resected NSCLC patients. From each tumour, three morphologically distinct areas were manually microdissected and analysed for the presence of mutations. The results demonstrated consistent EGFR and KRAS mutation status in the different histological areas of all primary tumours. Conclusions: The results support the concept that activating EGFR and KRAS mutations are oncogenic events that are consistently present throughout the primary tumour independently of histological heterogeneity. Thus, for molecular diagnostics, any part of the tumour is likely to be representative for EGFR and KRAS mutation testing.

Keywords
EGFR, heterogeneity, KRAS, lung cancer, molecular testing, mutation analysis
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-187099 (URN)10.1111/j.1365-2559.2012.04245.x (DOI)000310481800022 ()
Available from: 2012-12-04 Created: 2012-12-03 Last updated: 2019-10-07
Edlund, K., Larsson, O., Ameur, A., Bunikis, I., Gyllensten, U., Leroy, B., . . . Soussi, T. (2012). Data-driven unbiased curation of the TP53 tumor suppressor gene mutation database and validation by ultradeep sequencing of human tumors. Proceedings of the National Academy of Sciences of the United States of America, 109(24), 9551-9556
Open this publication in new window or tab >>Data-driven unbiased curation of the TP53 tumor suppressor gene mutation database and validation by ultradeep sequencing of human tumors
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2012 (English)In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 109, no 24, p. 9551-9556Article in journal (Refereed) Published
Abstract [en]

Cancer mutation databases are expected to play central roles in personalized medicine by providing targets for drug development and biomarkers to tailor treatments to each patient. The accuracy of reported mutations is a critical issue that is commonly overlooked, which leads to mutation databases that include a sizable number of spurious mutations, either sequencing errors or passenger mutations. Here we report an analysis of the latest version of the TP53 mutation database, including 34,453 mutations. By using several data-driven methods on multiple independent quality criteria, we obtained a quality score for each report contributing to the database. This score can now be used to filter for high-confidence mutations and reports within the database. Sequencing the entire TP53 gene from various types of cancer using next-generation sequencing with ultradeep coverage validated our approach for curation. In summary, 9.7% of all collected studies, mostly comprising numerous tumors with multiple infrequent TP53 mutations, should be excluded when analyzing TP53 mutations. Thus, by combining statistical and experimental analyses, we provide a curated mutation database for TP53 mutations and a framework for mutation database analysis.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-175985 (URN)10.1073/pnas.1200019109 (DOI)000305511300070 ()22628563 (PubMedID)
Available from: 2012-06-14 Created: 2012-06-14 Last updated: 2018-02-01Bibliographically approved
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