Spheromics

Kontiolahti, Finland

Spheromics

Kontiolahti, Finland
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Luo J.,Systems Analytics Inc. | Schumacher M.,Novartis | Scherer A.,Spheromics | Sanoudou D.,National and Kapodistrian University of Athens | And 21 more authors.
Pharmacogenomics Journal | Year: 2010

Batch effects are the systematic non-biological differences between batches (groups) of samples in microarray experiments due to various causes such as differences in sample preparation and hybridization protocols. Previous work focused mainly on the development of methods for effective batch effects removal. However, their impact on cross-batch prediction performance, which is one of the most important goals in microarray-based applications, has not been addressed. This paper uses a broad selection of data sets from the Microarray Quality Control Phase II (MAQC-II) effort, generated on three microarray platforms with different causes of batch effects to assess the efficacy of their removal. Two data sets from cross-tissue and cross-platform experiments are also included. Of the 120 cases studied using Support vector machines (SVM) and K nearest neighbors (KNN) as classifiers and Matthews correlation coefficient (MCC) as performance metric, we find that Ratio-G, Ratio-A, EJLR, mean-centering and standardization methods perform better or equivalent to no batch effect removal in 89, 85, 83, 79 and 75% of the cases, respectively, suggesting that the application of these methods is generally advisable and ratio-based methods are preferred. © 2010 Macmillan Publishers Limited. All rights reserved.


Vethe H.,University of Bergen | Finne K.,University of Bergen | Skogstrand T.,University of Bergen | Vaudel M.,University of Bergen | And 8 more authors.
Journal of Hypertension | Year: 2015

Background: Hypertensive nephrosclerosis is one of the most frequent causes of chronic kidney failure. Proteome analysis potentially improves the pathophysiological understanding and diagnostic precision of this disorder. In the present exploratory study, we investigated experimental nephrosclerosis in the two-kidney, one-clip (2K1C) hypertensive rat model.Methods: The renal cortex proteome from juxtamedullary cortex and outer cortex of 2K1C male Wistar-Hannover rats (n=4) was compared with the sham-operated controls (n=6), using mass spectrometry-based quantitative proteomics. We combined a high abundant plasma protein depletion strategy with an extended liquid chromatographic gradient to improve peptide and protein identification. Immunohistology was used for independent confirmation of abundance.Results: We identified 1724 proteins, of which 1434 were quantified with at least two unique peptides. Comparative proteomics revealed 608 proteins, including the plateletderived growth factor receptor-b signalling pathway, with different abundances between the non-clipped kidney of hypertensive 2K1C rats and the corresponding kidney of the normotensive controls (P<0.05, absolute fold change ≥1.5). Among the most significantly altered proteins in the whole cortex were periostin, transgelin, and creatine kinase B-type. Relative abundance of periostin alone allowed clear classification of 2K1C and controls. Enrichment of periostin in 2K1C rats was verified by immunohistology, showing positivity especially around the fibrotic vessels.Conclusion: The proteome is altered in hypertensioninduced kidney damage. We propose periostin, especially in combination with transgelin and creatine kinase B-type, as possible proteomic classifier to distinguish hypertensive nephrosclerosis from the normal tissue. This classifier needs to be further validated with respect to early diagnosis of fibrosis, prognosis, and its potential as a novel molecular target for pharmacological interventions. © 2014 Wolters Kluwer Health.


Eikrem O.,University of Bergen | Beisland C.,University of Bergen | Hjelle K.,University of Bergen | Flatberg A.,Norwegian University of Science and Technology | And 6 more authors.
PLoS ONE | Year: 2016

Formalin-fixed, paraffin-embedded (FFPE) tissues are an underused resource for molecular analyses. This proof of concept study aimed to compare RNAseq results from FFPE biopsies with the corresponding RNAlater1 (Qiagen, Germany) stored samples from clear cell renal cell carcinoma (ccRCC) patients to investigate feasibility of RNAseq in archival tissue. From each of 16 patients undergoing partial or full nephrectomy, four core biopsies, such as two specimens with ccRCC and two specimens of adjacent normal tissue, were obtained with a 16g needle. One normal and one ccRCC tissue specimen per patient was stored either in FFPE or RNAlater1. RNA sequencing libraries were generated applying the new Illumina TruSeq1 Access library preparation protocol. Comparative analysis was done using voom/Limma R-package. The analysis of the FFPE and RNAlater1 datasets yielded similar numbers of detected genes, differentially expressed transcripts and affected pathways. The FFPE and RNAlater datasets shared 80% (n = 1106) differentially expressed genes. The average expression and the log2 fold changes of these transcripts correlated with R2 = 0.97, and R2 = 0.96, respectively. Among transcripts with the highest fold changes in both datasets were carbonic anhydrase 9 (CA9), neuronal pentraxin-2 (NPTX2) and uromodulin (UMOD) that were confirmed by immunohistochemistry. IPA revealed the presence of gene signatures of cancer and nephrotoxicity, renal damage and immune response. To simulate the feasibility of clinical biomarker studies with FFPE samples, a classifier model was developed for the FFPE dataset: expression data for CA9 alone had an accuracy, specificity and sensitivity of 94%, respectively, and achieved similar performance in the RNAlater dataset. Transforming growth factor-β1 (TGFB1)-regulated genes, epithelial to mesenchymal transition (EMT) and NOTCH signaling cascade may support novel therapeutic strategies. In conclusion, in this proof of concept study, RNAseq data obtained from FFPE kidney biopsies are comparable to data obtained from fresh stored material, thereby expanding the utility of archival tissue specimens. © 2016 Eikrem et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Rodder S.,University of Bern | Scherer A.,Spheromics | Korner M.,University of Bern | Eisenberger U.,University of Bern | And 7 more authors.
American Journal of Transplantation | Year: 2010

Definition of acute renal allograft rejection (AR) markers remains clinically relevant. Features of T-cell-mediated AR are tubulointerstitial and vascular inflammation associated with excessive extracellular matrix (ECM) remodeling, regulated by metzincins, including matrix metalloproteases (MMP). Our study focused on expression of metzincins (METS), and metzincins and related genes (MARGS) in renal allograft biopsies using four independent microarray data sets. Our own cases included normal histology (N, n = 20), borderline changes (BL, n = 4), AR (n = 10) and AR + IF/TA (n = 7). MARGS enriched in all data sets were further examined on mRNA and/or protein level in additional patients. METS and MARGS differentiated AR from BL, AR + IF/TA and N in a principal component analysis. Their expression changes correlated to Banff t- and i-scores. Two AR classifiers, based on METS (including MMP7, TIMP1), or on MARGS were established in our own and validated in the three additional data sets. Thirteen MARGS were significantly enriched in AR patients of all data sets comprising MMP7, -9, TIMP1, -2, thrombospondin2 (THBS2) and fibrillin1. RT-PCR using microdissected glomeruli/tubuli confirmed MMP7, -9 and THBS2 microarray results; immunohistochemistry showed augmentation of MMP2, -9 and TIMP1 in AR. TIMP1 and THBS2 were enriched in AR patient serum. Therefore, differentially expressed METS and MARGS especially TIMP1, MMP7/-9 represent potential molecular AR markers. © 2009 The American Society of Transplantation and the American Society of Transplant Surgeons.


Rodder S.,University of Bern | Scherer A.,Spheromics | Korner M.,University of Bern | Marti H.-P.,University of Bern
Virchows Archiv | Year: 2011

Metzincins and functionally related genes play important roles in extracellular matrix remodeling both in healthy and fibrotic conditions. We recently presented a transcriptomic classifier consisting of 19 metzincins and related genes (MARGS) discriminating biopsies from renal transplant patients with or without interstitial fibrosis/tubular atrophy (IF/TA) by virtue of gene expression measurement (Roedder et al., Am J Transplant 9:517-526, 2009). Here we demonstrate that the same algorithm has diagnostic value in non-transplant solid organ fibrosis. We used publically available microarray datasets of 325 human heart, liver, lung, kidney cortex, and pancreas microarray samples (265 with fibrosis, 60 healthy controls). Expression of nine commonly differentially expressed genes was confirmed by TaqMan low-density arrays (Applied Biosystems, USA) in 50 independent archival tissue specimens with matched histological diagnoses to microarray patients. In separate and in combined, integrated microarray data analyses of five datasets with 325 samples, the previously published MARGS classifier for renal post-transplant IF/TA had a mean AUC of 87% and 82%, respectively. These data demonstrate that the MARGS gene panel classifier not only discriminates IF/TA from normal renal transplant tissue, but also classifies solid organ fibrotic conditions of human pancreas, liver, heart, kidney, and lung tissue samples with high specificity and accuracy, suggesting that the MARGS classifier is a cross-platform, cross-organ classifier of fibrotic conditions of different etiologies when compared to normal tissue. © Springer-Verlag 2011.


Staedtler F.,Novartis | Hartmann N.,Novartis | Letzkus M.,Novartis | Bongiovanni S.,Novartis | And 4 more authors.
Biomarkers | Year: 2013

Context: Correct gender assignment in humans at the molecular level is crucial in many scientific disciplines and applied areas. Materials and methods: Candidate gender markers were identified through supervised statistical analysis of genome wide microarray expression data from human blood samples (N=123, 58 female, 65 male) as a training set. The potential of the markers to predict undisclosed tissue donor gender was tested on microarray data from 13 healthy and 11 cancerous human tissue collections (internal) and external datasets from samples of varying tissue origin. The abundance of some genes in the marker panel was quantified by RT-PCR as alternative analytical technology. Results: We identified and qualified predictive, gender-specific transcript markers based on a set of five genes (RPS4Y1, EIF1AY, DDX3Y, KDM5D and XIST). Conclusion: Gene expression marker panels can be used as a robust tissue- and platform-independent predictive approach for gender determination. © 2013 Informa UK Ltd. All rights reserved: reproduction in whole or part not permitted.


Marti H.-P.,University of Bergen | Fuscoe J.C.,National Center for Toxicological Research (NCTR) | Kwekel J.C.,National Center for Toxicological Research (NCTR) | Anagnostopoulou A.,University of Bern | Scherer A.,Spheromics
Nephrology Dialysis Transplantation | Year: 2014

Background. We have previously described a transcriptomic classifier consisting of metzincins and related genes (MARGS) discriminating kidneys and other organs with or without fibrosis from human biopsies. We now apply our MARGS-based algorithm to a rat model of age-associated interstitial renal fibrosis. Methods. Untreated Fisher 344 rats (n = 76) were sacrificed between 2 to 104 weeks of age. For gene expression studies, we used single colour (Cy3) Agilent Whole Rat Genome 4 × 44k microarrays; 4-5 animals of each sex were profiled at each of the following ages: 2, 5, 6, 8, 15, 21, 78 and 104 weeks. Intensity data were subjected to variance stabilization (www.Partek.com). Data were analysed with ANOVA and other statistical methods. Results. Sixty MARGS were differentially expressed across age groups. More MARGS were differentially expressed in older males than in older females. Principal component analysis showed gene expression induced segregation of age groups by sex from 6 to 104 weeks of age. The expression level of MMP7 correlated best with fibrosis grade. Severity of fibrosis was determined in 20 animals at 78 and 104 weeks of age. Expression values of 15 of 19 genes of the original classifier present on the Agilent array, in conjunction with linear discriminant analysis, was sufficient to correctly classify these 20 samples into non-fibrosis and fibrosis. Overrepresentation of MMP2 protein and CD44 protein in fibrosis was confirmed by immunofluorescence. Conclusions. Based on these results and our previous work, the MARGS classifier represents a cross-organ and crossspecies classifier of fibrosis irrespective of aetiology. This finding provides evidence for a common pathway leading to fibrosis and will help to design a PCR-based clinical test. © 2014 The Author 2014. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.


PubMed | Novartis and Spheromics
Type: | Journal: Biomarker research | Year: 2014

Exact sample annotation in expression microarray datasets is essential for any type of pharmacogenomics research.Candidate markers were explored through the application of Hartigans dip test statistics to a publically available human whole genome microarray dataset. The marker performance was tested on 188 serial samples from 53 donors and of variable tissue origin from five public microarray datasets. A qualified transcript marker panel consisting of three probe sets for human leukocyte antigens HLA-DQA1 (2 probe sets) and HLA-DRB4 identified sample donor identifier inconsistencies in six of the 188 test samples. About 3% of the test samples require root-cause analysis due to unresolvable inaccuracies.The transcript marker panel consisting of HLA-DQA1 and HLA-DRB4 represents a robust, tissue-independent composite marker to assist control donor annotation concordance at the transcript level. Allele-selectivity of HLA genes renders them good candidates for fingerprinting with donor specific expression pattern.


PubMed | University of Bergen, Spheromics, University of Bern and National Center for Toxicological Research (NCTR)
Type: Journal Article | Journal: Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association | Year: 2014

We have previously described a transcriptomic classifier consisting of metzincins and related genes (MARGS) discriminating kidneys and other organs with or without fibrosis from human biopsies. We now apply our MARGS-based algorithm to a rat model of age-associated interstitial renal fibrosis.Untreated Fisher 344 rats (n = 76) were sacrificed between 2 to 104 weeks of age. For gene expression studies, we used single colour (Cy3) Agilent Whole Rat Genome 4 44k microarrays; 4-5 animals of each sex were profiled at each of the following ages: 2, 5, 6, 8, 15, 21, 78 and 104 weeks. Intensity data were subjected to variance stabilization (www.Partek.com). Data were analysed with ANOVA and other statistical methods.Sixty MARGS were differentially expressed across age groups. More MARGS were differentially expressed in older males than in older females. Principal component analysis showed gene expression induced segregation of age groups by sex from 6 to 104 weeks of age. The expression level of MMP7 correlated best with fibrosis grade. Severity of fibrosis was determined in 20 animals at 78 and 104 weeks of age. Expression values of 15 of 19 genes of the original classifier present on the Agilent array, in conjunction with linear discriminant analysis, was sufficient to correctly classify these 20 samples into non-fibrosis and fibrosis. Overrepresentation of MMP2 protein and CD44 protein in fibrosis was confirmed by immunofluorescence.Based on these results and our previous work, the MARGS classifier represents a cross-organ and cross-species classifier of fibrosis irrespective of aetiology. This finding provides evidence for a common pathway leading to fibrosis and will help to design a PCR-based clinical test.


PubMed | University of Bergen, Spheromics and Norwegian University of Science and Technology
Type: Journal Article | Journal: PloS one | Year: 2016

Formalin-fixed, paraffin-embedded (FFPE) tissues are an underused resource for molecular analyses. This proof of concept study aimed to compare RNAseq results from FFPE biopsies with the corresponding RNAlater (Qiagen, Germany) stored samples from clear cell renal cell carcinoma (ccRCC) patients to investigate feasibility of RNAseq in archival tissue. From each of 16 patients undergoing partial or full nephrectomy, four core biopsies, such as two specimens with ccRCC and two specimens of adjacent normal tissue, were obtained with a 16g needle. One normal and one ccRCC tissue specimen per patient was stored either in FFPE or RNAlater. RNA sequencing libraries were generated applying the new Illumina TruSeq Access library preparation protocol. Comparative analysis was done using voom/Limma R-package. The analysis of the FFPE and RNAlater datasets yielded similar numbers of detected genes, differentially expressed transcripts and affected pathways. The FFPE and RNAlater datasets shared 80% (n = 1106) differentially expressed genes. The average expression and the log2 fold changes of these transcripts correlated with R2 = 0.97, and R2 = 0.96, respectively. Among transcripts with the highest fold changes in both datasets were carbonic anhydrase 9 (CA9), neuronal pentraxin-2 (NPTX2) and uromodulin (UMOD) that were confirmed by immunohistochemistry. IPA revealed the presence of gene signatures of cancer and nephrotoxicity, renal damage and immune response. To simulate the feasibility of clinical biomarker studies with FFPE samples, a classifier model was developed for the FFPE dataset: expression data for CA9 alone had an accuracy, specificity and sensitivity of 94%, respectively, and achieved similar performance in the RNAlater dataset. Transforming growth factor-1 (TGFB1)-regulated genes, epithelial to mesenchymal transition (EMT) and NOTCH signaling cascade may support novel therapeutic strategies. In conclusion, in this proof of concept study, RNAseq data obtained from FFPE kidney biopsies are comparable to data obtained from fresh stored material, thereby expanding the utility of archival tissue specimens.

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