Intermediate filament dynamics and breast cancer: Aberrant promoter methylation of the Synemin gene is associated with early tumor relapse

Noetzel, Erik; Rose, Michael; Sevinc, Elif Demirdogen; Hilgers, Ralf-Dieter; Hartmann, Arndt; Naami, Amjad; Knüchel, Ruth; Dahl, Edgar

doi:10.1038/onc.2010.229

Cited by 46 publications

(42 citation statements)

References 42 publications

(55 reference statements)

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“…The differentially expressed proteins were more comprehensive and subtype-specific in the former data set, because of its larger the sample size and higher sequence coverage. Particularly, for the triple-negative subtype, which has been characterized by the high abundances of basal-like cytokeratins (56), SMOC1, S100B, GSTA1, SFRP1, S100A1, PTX3, SOX10, ANGPT2, COCH, as well as many other known markers such as SYNM1 (57), MFI2 (58), NDRG2 (59), CRYAB (60), and PLA2G4A (61) were found on top of the list of differential regulated proteins in the CPTAC data (supplemental Table S3). Markers are located on the scatter plot based on the fold changes relative to the three subtypes (axes) in log-scale.…”

Section: Resultsmentioning

confidence: 99%

Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences

Zhang

Pirmoradian

Zubarev

et al. 2017

Molecular & Cellular Proteomics

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Most implementations of mass spectrometry-based proteomics involve enzymatic digestion of proteins, expanding the analysis to multiple proteolytic peptides for each protein. Currently, there is no consensus of how to summarize peptides' abundances to protein concentrations, and such efforts are complicated by the fact that error control normally is applied to the identification process, and do not directly control errors linking peptide abundance measures to protein concentration. Peptides resulting from suboptimal digestion or being partially modified are not representative of the protein concentration. Without a mechanism to remove such unrepresentative peptides, their abundance adversely impacts the estimation of their protein's concentration. Here, we present a relative quantification approach, Diffacto, that applies factor analysis to extract the covariation of peptides' abundances. The method enables a weighted geometrical average summarization and automatic elimination of incoherent peptides. We demonstrate, based on a set of controlled label-free experiments using standard mixtures of proteins, that the covariation structure extracted by the factor analysis accurately reflects protein concentrations. In the 1% peptide-spectrum match-level FDR data set, as many as 11% of the peptides have abundance differences incoherent with the other peptides attributed to the same protein. If not controlled, such contradicting peptide abundance have a severe impact on protein quantifications. When adding the quantities of each protein's three most abundant peptides, we note as many as 14% of the proteins being estimated as having a negative correlation with their actual concentration differences between samples. Diffacto reduced the amount of such obviously incorrectly quantified proteins to 1.6%. Furthermore, by analyzing clinical data sets from two breast cancer studies, our method revealed the persistent proteomic signatures linked to three subtypes of breast cancer. We conclude that Diffacto can facilitate the interpretation and enhance the utility of most types of proteomics data.

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Section: Resultsmentioning

confidence: 99%

Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences

Zhang

Pirmoradian

Zubarev

et al. 2017

Molecular & Cellular Proteomics

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“…There are several biological functions that can be used to functionally categorize these biomarker genes. First, there is a set of genes associated with the cytoskeleton, extracellular matrix, angiogenesis, and hypoxia that includes SYNM (32), COL15A1, COL3A1, PTN (33), IFT57 (34), and MXI1 (35). Next, there is a set of cell cycle-related genes that includes CDC37L1, BTG2 (24), and SACM1L.…”

Section: Discussionmentioning

confidence: 99%

Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

et al. 2014

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Prostate cancer remains the second leading cause of cancer death in American men and there is an unmet need for biomarkers to identify patients with aggressive disease. In an effort to identify biomarkers of recurrence, we performed global RNA sequencing on 106 formalin-fixed, paraffin-embedded (FFPE) prostatectomy samples from 100 patients at three independent sites, defining a 24-gene signature panel. The 24 genes in this panel function in cell cycle progression, angiogenesis, hypoxia, apoptosis, PI3K signaling, steroid metabolism, translation, chromatin modification and transcription. Sixteen genes have been associated with cancer with five specifically associated with prostate cancer (BTG2, IGFBP3, SIRT1, MXI1 and FDPS). Validation was performed on an independent publicly available dataset of 140 patients, where the new signature panel outperformed markers published previously in terms of predicting biochemical recurrence (BCR). Our work also identified differences in gene expression between Gleason Pattern 4+3 and 3+4 tumors, including several genes involved in the epithelial to mesenchymal transition and developmental pathways. Overall, this study defines a novel biomarker panel that has the potential to improve the clinical management of prostate cancer.

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“…Pathologic conditions can induce synemin expression in diverse cell types, including reactive astrocytes, liver fibrotic cells (55,82,84), and glioblastomas (45,70). Synemin expression is also altered in myoepithelial cells of breast carcinomas due to changes in the methylation of the synemin gene (61). It is abundant in glioblastoma tumors (45) and in reactive astrocytes after neurotrauma and in Alexander disease (69).…”

Section: C455mentioning

confidence: 99%

Myopathic changes in murine skeletal muscle lacking synemin

García‐Pelagio

Muriel

O’Neill

et al. 2015

American Journal of Physiology-Cell Physiology

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(IF) proteins are associated with defects in the organization of the contractile apparatus and its links to costameres, which connect the sarcomeres to the cell membrane. Here we study the role in skeletal muscle of synemin, a type IV IF protein, by examining mice null for synemin (synm-null). Synm-null mice have a mild skeletal muscle phenotype. Tibialis anterior (TA) muscles show a significant decrease in mean fiber diameter, a decrease in twitch and tetanic force, and an increase in susceptibility to injury caused by lengthening contractions. Organization of proteins associated with the contractile apparatus and costameres is not significantly altered in the synm-null. Elastimetry of the sarcolemma and associated contractile apparatus in extensor digitorum longus myofibers reveals a reduction in tension consistent with an increase in sarcolemmal deformability. Although fatigue after repeated isometric contractions is more marked in TA muscles of synm-null mice, the ability of the mice to run uphill on a treadmill is similar to controls. Our results suggest that synemin contributes to linkage between costameres and the contractile apparatus and that the absence of synemin results in decreased fiber size and increased sarcolemmal deformability and susceptibility to injury. Thus synemin plays a moderate but distinct role in fast twitch skeletal muscle. cytoskeleton; costameres; elastimetry; biomechanical properties; desmin A LARGE NUMBER OF HUMAN DISEASES, ranging from skin disorders (51), to premature aging (34, 64), to skeletal and cardiac myopathies (19,37), are linked to mutations in genes encoding intermediate filament (IF) proteins (25). Since the discovery of desmin, the major IF protein of striated muscle (49), its role and that of other IF proteins in muscle have been of keen interest to many laboratories (reviewed in 16). Our research on muscle IF proteins has addressed their role in force transmission and in organizing the sarcoplasm and stabilizing it against injury during force generation.Force generated in muscle can be transmitted radially, from the myofibrils, across the sarcolemma to the extracellular matrix and neighboring cells (11, 67). As a result, a significant amount of force is exerted on the sarcolemma and the structures that link it to the underlying contractile apparatus and the extracellular matrix. The ability of the sarcolemma with the underlying contractile apparatus to withstand the distortions caused during isotonic contractions (2, 11, 12) depends on specialized structures, termed "costameres" (66), that mediate the radial transmission of force across the sarcolemma (11). Costameres are structures at the sarcolemma of striated muscle fibers that align circumferentially around the Z disks and the M bands of the nearest myofibrils, and longitudinally, to form a rectilinear sarcolemmal network comprised of integral membrane proteins (such as dystroglycan, the sarcoglycans, and Na-K-ATPase), proteins of the extracellular matrix (such as laminin and collagen IV), and proteins of t...

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Intermediate filament dynamics and breast cancer: Aberrant promoter methylation of the Synemin gene is associated with early tumor relapse

Cited by 46 publications

References 42 publications

Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences

Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences

Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Myopathic changes in murine skeletal muscle lacking synemin

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