oposSOM
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Analysis of large-scale molecular biological data using self-organizing maps

Comprehensive analysis of genome-wide molecular data challenges bioinformatics methodology in terms of intuitive visualization with single-sample resolution, biomarker selection, functional information mining and highly granular stratification of sample classes. oposSOM combines those functionalities making use of a comprehensive analysis and visualization strategy based on self-organizing maps (SOM) machine learning which we call 'high-dimensional data portraying'. The method was successfully applied in a series of studies using mostly transcriptome data but also data of other OMICs realms.

LHA ID: 7Q0CTG2MJJ-6

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Created: 6th May 2019 at 12:36

Last updated: 15th May 2019 at 12:56

Last used: 3rd Dec 2024 at 17:01

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Version 2 (latest) Created 6th May 2019 at 12:37 by Henry Löffler-Wirth

replaced static file with link to Bioconductor

Related items

HNPCC-Sys - Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome
No description specified

Programme: This Project is not associated with a Programme

Public web page: Not specified

e:Med

e:Med has the objective of establishing systems medicine in Germany. e:Med promotes system-oriented research into diseases in order to facilitate improved prevention, more comprehensive diagnostics and individually adjusted therapy schemes in individualized medicine. The program brings together scientists with molecular-genetic, clinical, mathematical and information technology expertise, with the objective of ensuring that research results quickly benefit patients.

Programme: Default Programme

Public web page: https://www.sys-med.de/en/

Transcriptional states of CAR-T infusion relate to neurotoxicity - lessons from high-resolution single-cell SOM expression portraying.
imSAVAR - Immune safety avatar: nonclinical mimicking of the immune system effects of immunomodulatory therapies

Abstract (Expand)

Anti-CD19 CAR-T cell immunotherapy is a hopeful treatment option for patients with B cell lymphomas, however it copes with partly severe adverse effects like neurotoxicity. Single-cell resolved molecular … data sets in combination with clinical parametrization allow for comprehensive characterization of cellular subpopulations, their transcriptomic states, and their relation to the adverse effects. We here present a re-analysis of single-cell RNA sequencing data of 24 patients comprising more than 130,000 cells with focus on cellular states and their association to immune cell related neurotoxicity. For this, we developed a single-cell data portraying workflow to disentangle the transcriptional state space with single-cell resolution and its analysis in terms of modularly-composed cellular programs. We demonstrated capabilities of single-cell data portraying to disentangle transcriptional states using intuitive visualization, functional mining, molecular cell stratification, and variability analyses. Our analysis revealed that the T cell composition of the patient's infusion product as well as the spectrum of their transcriptional states of cells derived from patients with low ICANS grade do not markedly differ from those of cells from high ICANS patients, while the relative abundancies, particularly that of cycling cells, of LAG3-mediated exhaustion and of CAR positive cells, vary. Our study provides molecular details of the transcriptomic landscape with possible impact to overcome neurotoxicity.

Authors: H. Loeffler-Wirth, M. Rade, A. Arakelyan, M. Kreuz, M. Loeffler, U. Koehl, K. Reiche, H. Binder

Date Published: 17th Oct 2022

Publication Type: Journal article

A modular transcriptome map of mature B cell lymphomas.
GLA - German Lymphoma Alliance, MMML-MYC-SYS, oBIG - omics Bioinformatics for Health

Abstract (Expand)

BACKGROUND: Germinal center-derived B cell lymphomas are tumors of the lymphoid tissues representing one of the most heterogeneous malignancies. Here we characterize the variety of transcriptomic … phenotypes of this disease based on 873 biopsy specimens collected in the German Cancer Aid MMML (Molecular Mechanisms in Malignant Lymphoma) consortium. They include diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt's lymphoma, mixed FL/DLBCL lymphomas, primary mediastinal large B cell lymphoma, multiple myeloma, IRF4-rearranged large cell lymphoma, MYC-negative Burkitt-like lymphoma with chr. 11q aberration and mantle cell lymphoma. METHODS: We apply self-organizing map (SOM) machine learning to microarray-derived expression data to generate a holistic view on the transcriptome landscape of lymphomas, to describe the multidimensional nature of gene regulation and to pursue a modular view on co-expression. Expression data were complemented by pathological, genetic and clinical characteristics. RESULTS: We present a transcriptome map of B cell lymphomas that allows visual comparison between the SOM portraits of different lymphoma strata and individual cases. It decomposes into one dozen modules of co-expressed genes related to different functional categories, to genetic defects and to the pathogenesis of lymphomas. On a molecular level, this disease rather forms a continuum of expression states than clearly separated phenotypes. We introduced the concept of combinatorial pattern types (PATs) that stratifies the lymphomas into nine PAT groups and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma signatures. Inflammation signatures in combination with healthy B cell and tonsil characteristics associate with better overall survival rates, while proliferation in combination with inflammation and plasma cell characteristics worsens it. A phenotypic similarity tree is presented that reveals possible progression paths along the transcriptional dimensions. Our analysis provided a novel look on the transition range between FL and DLBCL, on DLBCL with poor prognosis showing expression patterns resembling that of Burkitt's lymphoma and particularly on 'double-hit' MYC and BCL2 transformed lymphomas. CONCLUSIONS: The transcriptome map provides a tool that aggregates, refines and visualizes the data collected in the MMML study and interprets them in the light of previous knowledge to provide orientation and support in current and future studies on lymphomas and on other cancer entities.

Authors: H. Loeffler-Wirth, M. Kreuz, L. Hopp, A. Arakelyan, A. Haake, S. B. Cogliatti, A. C. Feller, M. L. Hansmann, D. Lenze, P. Moller, H. K. Muller-Hermelink, E. Fortenbacher, E. Willscher, G. Ott, A. Rosenwald, C. Pott, C. Schwaenen, H. Trautmann, S. Wessendorf, H. Stein, M. Szczepanowski, L. Trumper, M. Hummel, W. Klapper, R. Siebert, M. Loeffler, H. Binder

Date Published: 30th Apr 2019

Publication Type: Not specified

Human Diseases: B-cell lymphoma, diffuse large B-cell lymphoma, follicular lymphoma, Burkitt lymphoma

Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome.
CAPSys - Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome, oBIG - omics Bioinformatics for Health

Abstract (Expand)

We analyzed the blood transcriptome of sepsis framed within community-acquired pneumonia (CAP) and characterized its molecular and cellular heterogeneity in terms of functional modules of co-regulated … genes with impact for the underlying pathophysiological mechanisms. Our results showed that CAP severity is associated with immune suppression owing to T-cell exhaustion and HLA and chemokine receptor deactivation, endotoxin tolerance, macrophage polarization, and metabolic conversion from oxidative phosphorylation to glycolysis. We also found footprints of host's response to viruses and bacteria, altered levels of mRNA from erythrocytes and platelets indicating coagulopathy that parallel severity of sepsis and survival. Finally, our data demonstrated chromatin re-modeling associated with extensive transcriptional deregulation of chromatin modifying enzymes, which suggests the extensive changes of DNA methylation with potential impact for marker selection and functional characterization. Based on the molecular footprints identified, we propose a novel stratification of CAP cases into six groups differing in the transcriptomic scores of CAP severity, interferon response, and erythrocyte mRNA expression with impact for prognosis. Our analysis increases the resolution of transcriptomic footprints of CAP and reveals opportunities for selecting sets of transcriptomic markers with impact for translation of omics research in terms of patient stratification schemes and sets of signature genes.

Authors: L. Hopp, H. Loeffler-Wirth, L. Nersisyan, A. Arakelyan, H. Binder

Date Published: 2nd Aug 2018

Publication Type: Not specified

Human Diseases: disease by infectious agent, pneumonia

RNA-seq analysis identifies different transcriptomic types and developmental trajectories of primary melanomas.
Leipzig Melanoma Studies

Abstract (Expand)

Recent studies revealed trajectories of mutational events in early melanomagenesis, but the accompanying changes in gene expression are far less understood. Therefore, we performed a comprehensive … RNA-seq analysis of laser-microdissected melanocytic nevi (n = 23) and primary melanoma samples (n = 57) and characterized the molecular mechanisms of early melanoma development. Using self-organizing maps, unsupervised clustering, and analysis of pseudotime (PT) dynamics to identify evolutionary trajectories, we describe here two transcriptomic types of melanocytic nevi (N1 and N2) and primary melanomas (M1 and M2). N1/M1 lesions are characterized by pigmentation-type and MITF gene signatures, and a high prevalence of NRAS mutations in M1 melanomas. N2/M2 lesions are characterized by inflammatory-type and AXL gene signatures with an equal distribution of wild-type and mutated BRAF and low prevalence of NRAS mutations in M2 melanomas. Interestingly, N1 nevi and M1 melanomas and N2 nevi and M2 melanomas, respectively, cluster together, but there is no clustering in a stage-dependent manner. Transcriptional signatures of M1 melanomas harbor signatures of BRAF/MEK inhibitor resistance and M2 melanomas harbor signatures of anti-PD-1 antibody treatment resistance. Pseudotime dynamics of nevus and melanoma samples are suggestive for a switch-like immune-escape mechanism in melanoma development with downregulation of immune genes paralleled by an increasing expression of a cell cycle signature in late-stage melanomas. Taken together, the transcriptome analysis identifies gene signatures and mechanisms underlying development of melanoma in early and late stages with relevance for diagnostics and therapy.

Authors: M. Kunz, H. Loffler-Wirth, M. Dannemann, E. Willscher, G. Doose, J. Kelso, T. Kottek, B. Nickel, L. Hopp, J. Landsberg, S. Hoffmann, T. Tuting, P. Zigrino, C. Mauch, J. Utikal, M. Ziemer, H. J. Schulze, M. Holzel, A. Roesch, S. Kneitz, S. Meierjohann, A. Bosserhoff, H. Binder, M. Schartl

Date Published: 12th Jul 2018

Publication Type: Not specified

Human Diseases: melanoma

Dysregulated Signal Propagation in a MYC-associated Boolean Gene Network in B-cell Lymphoma
MMML-MYC-SYS

Abstract (Expand)

By the modern molecular biological approaches that exploit the availability of high quality gene expression data, it is made clear that flexible and robust responses of cellular programs are encoded … in the relations between gene expression values. These relations naturally define a network where they stand for edges between the nodes that stand for the genes. The wiring of these networks often found to be dysregulated in cancer. Different system biological approaches that rely on correlations, differential equations and logical analysis are used to probe these relations in gene expression data especially. In our work we investigated selected biological functions in aggressive germinal center B-cell lymphoma in terms of a logical analysis of gene-regulation in Boolean space and a signal propagation algorithm considering network topology based on gene expression data. We especially aimed at studying the activity of the MYC gene as a key player. It is shown that the functional output of a gene network is affected by the states of the genes and also by the wirings between them. Our results support the key function of MYC in lymphoma biology. In addition, we showed that genes can alter functional output of the network by alternative mechanisms like reducing the variance in propagating signal and locking it to a certain level.

Authors: V. Cakir, H. Loeffler-Wirth, A. Arakelyan, H. Binder

Date Published: 17th May 2017

Publication Type: Not specified

Human Diseases: B-cell lymphoma

Mapping heterogeneity in patient-derived melanoma cultures by single-cell RNA-seq.
Leipzig Melanoma Studies

Abstract (Expand)

Recent technological advances in single-cell genomics make it possible to analyze cellular heterogeneity of tumor samples. Here, we applied single-cell RNA-seq to measure the transcriptomes of 307 … single cells cultured from three biopsies of three different patients with a BRAF/NRAS wild type, BRAF mutant/NRAS wild type and BRAF wild type/NRAS mutant melanoma metastasis, respectively. Analysis based on self-organizing maps identified sub-populations defined by multiple gene expression modules involved in proliferation, oxidative phosphorylation, pigmentation and cellular stroma. Gene expression modules had prognostic relevance when compared with gene expression data from published melanoma samples and patient survival data. We surveyed kinome expression patterns across sub-populations of the BRAF/NRAS wild type sample and found that CDK4 and CDK2 were consistently highly expressed in the majority of cells, suggesting that these kinases might be involved in melanoma progression. Treatment of cells with the CDK4 inhibitor palbociclib restricted cell proliferation to a similar, and in some cases greater, extent than MAPK inhibitors. Finally, we identified a low abundant sub-population in this sample that highly expressed a module containing ABC transporter ABCB5, surface markers CD271 and CD133, and multiple aldehyde dehydrogenases (ALDHs). Patient-derived cultures of the BRAF mutant/NRAS wild type and BRAF wild type/NRAS mutant metastases showed more homogeneous single-cell gene expression patterns with gene expression modules for proliferation and ABC transporters. Taken together, our results describe an intertumor and intratumor heterogeneity in melanoma short-term cultures which might be relevant for patient survival, and suggest promising targets for new treatment approaches in melanoma therapy.

Authors: T. Gerber, E. Willscher, H. Loeffler-Wirth, L. Hopp, D. Schadendorf, M. Schartl, U. Anderegg, G. Camp, B. Treutlein, H. Binder, M. Kunz

Date Published: 3rd Jan 2017

Publication Type: Not specified

Human Diseases: melanoma

oposSOM: R-package for high-dimensional portraying of genome-wide expression landscapes on bioconductor.
HNPCC-Sys - Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome

Abstract (Expand)

MOTIVATION: Comprehensive analysis of genome-wide molecular data challenges bioinformatics methodology in terms of intuitive visualization with single-sample resolution, biomarker selection, functional … information mining and highly granular stratification of sample classes. oposSOM combines those functionalities making use of a comprehensive analysis and visualization strategy based on self-organizing maps (SOM) machine learning which we call 'high-dimensional data portraying'. The method was successfully applied in a series of studies using mostly transcriptome data but also data of other OMICs realms. AVAILABILITY AND IMPLEMENTATION: oposSOM is now publicly available as Bioconductor R package. CONTACT: wirth@izbi.uni-leipzig.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Authors: H. Loffler-Wirth, M. Kalcher, H. Binder

Date Published: 1st Oct 2015

Publication Type: Not specified

Portraying the Expression Landscapes of B-CellLymphoma-Intuitive Detection of Outlier Samples and of Molecular Subtypes.
MMML-MYC-SYS

Abstract (Expand)

We present an analytic framework based on Self-Organizing Map (SOM) machine learning to study large scale patient data sets. The potency of the approach is demonstrated in a case study using gene … expression data of more than 200 mature aggressive B-cell lymphoma patients. The method portrays each sample with individual resolution, characterizes the subtypes, disentangles the expression patterns into distinct modules, extracts their functional context using enrichment techniques and enables investigation of the similarity relations between the samples. The method also allows to detect and to correct outliers caused by contaminations. Based on our analysis, we propose a refined classification of B-cell Lymphoma into four molecular subtypes which are characterized by differential functional and clinical characteristics.

Authors: L. Hopp, K. Lembcke, H. Binder, H. Wirth

Date Published: 2nd Dec 2013

Publication Type: Not specified

Human Diseases: non-Hodgkin lymphoma, B-cell lymphoma

SOM portrayal of the peripheral blood transcriptome
LIFE - Leipzig Research Center for Civilization Diseases

Abstract (Expand)

Background: The transcriptome of healthy blood offers an option to characterize the physiological state of an individual with diagnostic impact. As a prerequisite such application requires the understanding … of the variability of the expression landscape of healthy individual’s as a function of factors such as age, gender, and aspects of the human constitution and lifestyle. Previous studies mostly were limited to only small population sizes and thus lack representativeness in many respects. Methods and data: The present thesis provides an extensive and detailed study on the gene expression landscape of peripheral blood of healthy individuals based on transcriptome data of 3,388 individuals screened in the population study LIFE between 2011 and 2014. For analysis we applied a neural network technique using self-organizing maps (SOM). Our home-made R-program ‘oposSOM’ enables to reduce the dimension of expression data from tens of thousands of genes to a few thousand ‘meta-genes’ and generates portraits of transcriptional activity that allowed us the sample-to-sample comparison of expression patterns. Results: We disentangled the expression patterns of the portraits into 15 well separated modules of co-expressed genes. Their activation patterns allowed us to aggregate the participants into three types (‘1’, ‘M’, ‘2’). Enrichment techniques extracts the functional context of the modules and revealed that corresponding cellular processes are selectively activated and de-activated in a type-specific fashion: For example, ‘Inflammation’ and ‘Blood coagulation’ are activated in type ‘1’ and ‘Metabolic activity’ and ‘Translation’ in Type ‘2’ samples. We map clinical parameters (complete blood count, lifestyle status, medication and the anthropometric body and BMI type) into the expression landscape in order to study the association between them and the transcriptome landscape. We found that red blood cell components, drug consumption of several drug classes affecting the cardio-vascular system or blood forming organs, tobacco and alcohol consumption, and the BMI types of obese participants highly correlate with meta-genes in the type ‘1’ area, whereas type ‘2’ meta-genes maximal correlate with the lymphocyte count and pre-obese characteristics of the participants. For blood count parameters and medication we found a gender-specific bias. Conclusion: Our analysis provides a comprehensive description of the human blood transcriptome in terms of a series of characteristic expression modules and of health-relevant factors. It provides a healthy reference system for blood transcriptome profiling studies in healthcare to extract potential associations between emerging diseases and the gene expression patterns in clinical research.

Author: M. Schmidt

Date Published: 9th Jul 2005

Publication Type: Not specified

Multi-omics cartography of glioma heterogeneity
GGN - German Glioma Network

Abstract (Expand)

Molecular mechanisms of lower grade (II- III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendro-glioma-like … (IDH-O) tumors both carrying mutations(s) at the Isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma-resemblance. We generated de-tailed maps of the transcriptomes and DNA-methylomes revealing that cell functions divide into three major archeotypic hallmarks: (i) increased proliferation in IDH-wt and, to a less degree, IDH-O, (ii) increased inflammation in IDH-A and IDH-wt, and (iii) the loss of synaptic transmis-sion in all subtypes. Immunogenic properties of IDH-A are diverse partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We ana-lyzed details of coregulation between gene expression and DNA-methylation and of the immu-nogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby molecular cartography provides a graphical coordinate system, which links gene-level information with glioma sub-types, their phenotypes and clinical context.

Authors: Hans Binder, Maria Schmidt, Lydia Hopp, Arsen Arakelyan, Henry Löffler-Wirth

Date Published: No date defined

Publication Type: Journal article

Human Diseases: brain glioma

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